Overview

Brought to you by YData

Dataset statistics

Number of variables93
Number of observations604720
Missing cells35800281
Missing cells (%)63.7%
Total size in memory429.1 MiB
Average record size in memory744.0 B

Variable types

Text93

Dataset

DescriptionEntomology NMNH Extant Extant Specimen Records 0052484-241126133413365
URLhttps://doi.org/10.15468/hnhrg3

Alerts

institutionID has constant value "urn:lsid:biocol.org:col:34871" Constant
collectionID has constant value "urn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad" Constant
institutionCode has constant value "USNM" Constant
collectionCode has constant value "ENT" Constant
datasetName has constant value "NMNH Extant Biology" Constant
organismID has constant value "70 21'9"W" Constant
eventType has constant value "-11.7815" Constant
waterBody has constant value "DeMarmels" Constant
verbatimDepth has constant value "220m inside cave entrance" Constant
locationRemarks has constant value "Garrison, Rosser W." Constant
verbatimSRS has constant value "Argia" Constant
footprintSpatialFit has constant value "Gynacantha membranalis" Constant
georeferencedBy has constant value "orichalcea" Constant
earliestEonOrLowestEonothem has constant value "Animalia, Arthropoda, Insecta, Odonata, Anisoptera, Aeshnidae" Constant
latestEonOrHighestEonothem has constant value "Animalia" Constant
earliestEraOrLowestErathem has constant value "Arthropoda" Constant
latestEraOrHighestErathem has constant value "Insecta" Constant
latestEpochOrHighestSeries has constant value "Pinellas" Constant
lowestBiostratigraphicZone has constant value "Gynacantha" Constant
formation has constant value "membranalis" Constant
identificationReferences has constant value "WGS 84 (EPSG:4326)" Constant
originalNameUsage has constant value "Google Earth" Constant
kingdom has constant value "Animalia" Constant
vernacularName has constant value "Type" Constant
catalogNumber has 233452 (38.6%) missing values Missing
recordNumber has 604683 (> 99.9%) missing values Missing
recordedBy has 203369 (33.6%) missing values Missing
sex has 339511 (56.1%) missing values Missing
lifeStage has 174155 (28.8%) missing values Missing
preparations has 42056 (7.0%) missing values Missing
associatedMedia has 390092 (64.5%) missing values Missing
occurrenceRemarks has 459346 (76.0%) missing values Missing
organismID has 604719 (> 99.9%) missing values Missing
eventType has 604719 (> 99.9%) missing values Missing
fieldNumber has 600468 (99.3%) missing values Missing
eventDate has 239420 (39.6%) missing values Missing
startDayOfYear has 244789 (40.5%) missing values Missing
endDayOfYear has 244303 (40.4%) missing values Missing
year has 239420 (39.6%) missing values Missing
month has 246636 (40.8%) missing values Missing
day has 270887 (44.8%) missing values Missing
verbatimEventDate has 396366 (65.5%) missing values Missing
habitat has 604521 (> 99.9%) missing values Missing
locationID has 603675 (99.8%) missing values Missing
higherGeography has 156093 (25.8%) missing values Missing
continent has 604592 (> 99.9%) missing values Missing
waterBody has 604719 (> 99.9%) missing values Missing
islandGroup has 602200 (99.6%) missing values Missing
island has 595353 (98.5%) missing values Missing
country has 156115 (25.8%) missing values Missing
stateProvince has 173239 (28.6%) missing values Missing
county has 254867 (42.1%) missing values Missing
locality has 158363 (26.2%) missing values Missing
minimumElevationInMeters has 558058 (92.3%) missing values Missing
maximumElevationInMeters has 573266 (94.8%) missing values Missing
verbatimElevation has 594785 (98.4%) missing values Missing
minimumDepthInMeters has 604685 (> 99.9%) missing values Missing
maximumDepthInMeters has 604709 (> 99.9%) missing values Missing
verbatimDepth has 604714 (> 99.9%) missing values Missing
locationRemarks has 604719 (> 99.9%) missing values Missing
decimalLatitude has 285696 (47.2%) missing values Missing
decimalLongitude has 285696 (47.2%) missing values Missing
geodeticDatum has 578337 (95.6%) missing values Missing
coordinateUncertaintyInMeters has 592766 (98.0%) missing values Missing
coordinatePrecision has 604717 (> 99.9%) missing values Missing
pointRadiusSpatialFit has 604718 (> 99.9%) missing values Missing
verbatimCoordinates has 604718 (> 99.9%) missing values Missing
verbatimLatitude has 523062 (86.5%) missing values Missing
verbatimLongitude has 523032 (86.5%) missing values Missing
verbatimCoordinateSystem has 604717 (> 99.9%) missing values Missing
verbatimSRS has 604719 (> 99.9%) missing values Missing
footprintSpatialFit has 604719 (> 99.9%) missing values Missing
georeferencedBy has 604719 (> 99.9%) missing values Missing
georeferenceProtocol has 366819 (60.7%) missing values Missing
georeferenceRemarks has 596270 (98.6%) missing values Missing
geologicalContextID has 604716 (> 99.9%) missing values Missing
earliestEonOrLowestEonothem has 604719 (> 99.9%) missing values Missing
latestEonOrHighestEonothem has 604719 (> 99.9%) missing values Missing
earliestEraOrLowestErathem has 604719 (> 99.9%) missing values Missing
latestEraOrHighestErathem has 604719 (> 99.9%) missing values Missing
earliestPeriodOrLowestSystem has 604716 (> 99.9%) missing values Missing
earliestEpochOrLowestSeries has 604717 (> 99.9%) missing values Missing
latestEpochOrHighestSeries has 604719 (> 99.9%) missing values Missing
latestAgeOrHighestStage has 604717 (> 99.9%) missing values Missing
lowestBiostratigraphicZone has 604719 (> 99.9%) missing values Missing
formation has 604719 (> 99.9%) missing values Missing
identificationQualifier has 603282 (99.8%) missing values Missing
typeStatus has 486142 (80.4%) missing values Missing
identifiedBy has 455024 (75.2%) missing values Missing
identifiedByID has 604718 (> 99.9%) missing values Missing
dateIdentified has 604718 (> 99.9%) missing values Missing
identificationReferences has 604719 (> 99.9%) missing values Missing
originalNameUsage has 604719 (> 99.9%) missing values Missing
kingdom has 6300 (1.0%) missing values Missing
subgenus has 512525 (84.8%) missing values Missing
specificEpithet has 8751 (1.4%) missing values Missing
infraspecificEpithet has 571231 (94.5%) missing values Missing
taxonRank has 571236 (94.5%) missing values Missing
scientificNameAuthorship has 90502 (15.0%) missing values Missing
vernacularName has 604718 (> 99.9%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique

Reproduction

Analysis started2025-02-10 18:47:58.209295
Analysis finished2025-02-10 18:48:15.023621
Duration16.81 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct604720
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:15.371952image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6047200
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique604720 ?
Unique (%)100.0%

Sample

1st row1321729650
2nd row1320180785
3rd row4403931423
4th row1320185860
5th row1320185980
ValueCountFrequency (%)
1321729650 1
 
< 0.1%
1321751610 1
 
< 0.1%
1828939237 1
 
< 0.1%
1321753851 1
 
< 0.1%
4403917418 1
 
< 0.1%
1321742115 1
 
< 0.1%
4403931423 1
 
< 0.1%
1320185860 1
 
< 0.1%
1320185980 1
 
< 0.1%
2236094411 1
 
< 0.1%
Other values (604710) 604710
> 99.9%
2025-02-10T13:48:15.877206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1132979
18.7%
3 860538
14.2%
2 781913
12.9%
0 530707
8.8%
8 513756
8.5%
9 488229
8.1%
7 474017
7.8%
4 451821
 
7.5%
5 410705
 
6.8%
6 402535
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6047200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1132979
18.7%
3 860538
14.2%
2 781913
12.9%
0 530707
8.8%
8 513756
8.5%
9 488229
8.1%
7 474017
7.8%
4 451821
 
7.5%
5 410705
 
6.8%
6 402535
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6047200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1132979
18.7%
3 860538
14.2%
2 781913
12.9%
0 530707
8.8%
8 513756
8.5%
9 488229
8.1%
7 474017
7.8%
4 451821
 
7.5%
5 410705
 
6.8%
6 402535
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6047200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1132979
18.7%
3 860538
14.2%
2 781913
12.9%
0 530707
8.8%
8 513756
8.5%
9 488229
8.1%
7 474017
7.8%
4 451821
 
7.5%
5 410705
 
6.8%
6 402535
 
6.7%
Distinct56593
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:16.052537image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11489680
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30780 ?
Unique (%)5.1%

Sample

1st row2013-09-16 11:56:00
2nd row2016-06-09 14:33:00
3rd row2023-08-23 09:36:00
4th row2023-05-19 10:32:00
5th row2015-10-05 15:58:00
ValueCountFrequency (%)
2023-05-13 60773
 
5.0%
2017-04-17 42518
 
3.5%
2014-01-09 31212
 
2.6%
2023-05-15 20528
 
1.7%
2023-05-12 16800
 
1.4%
2015-10-06 15979
 
1.3%
2018-02-08 14193
 
1.2%
2015-10-05 10265
 
0.8%
2017-09-29 10242
 
0.8%
11:48:00 10115
 
0.8%
Other values (3141) 976815
80.8%
2025-02-10T13:48:16.270097image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2928318
25.5%
1 1566388
13.6%
2 1372552
11.9%
- 1209440
10.5%
: 1209440
10.5%
604720
 
5.3%
3 593130
 
5.2%
5 494673
 
4.3%
4 456568
 
4.0%
9 314335
 
2.7%
Other values (3) 740116
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11489680
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2928318
25.5%
1 1566388
13.6%
2 1372552
11.9%
- 1209440
10.5%
: 1209440
10.5%
604720
 
5.3%
3 593130
 
5.2%
5 494673
 
4.3%
4 456568
 
4.0%
9 314335
 
2.7%
Other values (3) 740116
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11489680
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2928318
25.5%
1 1566388
13.6%
2 1372552
11.9%
- 1209440
10.5%
: 1209440
10.5%
604720
 
5.3%
3 593130
 
5.2%
5 494673
 
4.3%
4 456568
 
4.0%
9 314335
 
2.7%
Other values (3) 740116
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11489680
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2928318
25.5%
1 1566388
13.6%
2 1372552
11.9%
- 1209440
10.5%
: 1209440
10.5%
604720
 
5.3%
3 593130
 
5.2%
5 494673
 
4.3%
4 456568
 
4.0%
9 314335
 
2.7%
Other values (3) 740116
 
6.4%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:16.305539image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters17536880
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 604720
100.0%
2025-02-10T13:48:16.388277image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2418880
13.8%
: 2418880
13.8%
l 1814160
 
10.3%
i 1209440
 
6.9%
r 1209440
 
6.9%
c 1209440
 
6.9%
g 604720
 
3.4%
7 604720
 
3.4%
8 604720
 
3.4%
4 604720
 
3.4%
Other values (8) 4837760
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17536880
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2418880
13.8%
: 2418880
13.8%
l 1814160
 
10.3%
i 1209440
 
6.9%
r 1209440
 
6.9%
c 1209440
 
6.9%
g 604720
 
3.4%
7 604720
 
3.4%
8 604720
 
3.4%
4 604720
 
3.4%
Other values (8) 4837760
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17536880
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2418880
13.8%
: 2418880
13.8%
l 1814160
 
10.3%
i 1209440
 
6.9%
r 1209440
 
6.9%
c 1209440
 
6.9%
g 604720
 
3.4%
7 604720
 
3.4%
8 604720
 
3.4%
4 604720
 
3.4%
Other values (8) 4837760
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17536880
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2418880
13.8%
: 2418880
13.8%
l 1814160
 
10.3%
i 1209440
 
6.9%
r 1209440
 
6.9%
c 1209440
 
6.9%
g 604720
 
3.4%
7 604720
 
3.4%
8 604720
 
3.4%
4 604720
 
3.4%
Other values (8) 4837760
27.6%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:16.418362image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters27212400
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
2nd rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
3rd rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
4th rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
5th rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
ValueCountFrequency (%)
urn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad 604720
100.0%
2025-02-10T13:48:16.502259image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3023600
 
11.1%
a 2418880
 
8.9%
- 2418880
 
8.9%
d 1814160
 
6.7%
c 1814160
 
6.7%
u 1814160
 
6.7%
8 1209440
 
4.4%
3 1209440
 
4.4%
: 1209440
 
4.4%
9 1209440
 
4.4%
Other values (12) 9070800
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27212400
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3023600
 
11.1%
a 2418880
 
8.9%
- 2418880
 
8.9%
d 1814160
 
6.7%
c 1814160
 
6.7%
u 1814160
 
6.7%
8 1209440
 
4.4%
3 1209440
 
4.4%
: 1209440
 
4.4%
9 1209440
 
4.4%
Other values (12) 9070800
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27212400
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3023600
 
11.1%
a 2418880
 
8.9%
- 2418880
 
8.9%
d 1814160
 
6.7%
c 1814160
 
6.7%
u 1814160
 
6.7%
8 1209440
 
4.4%
3 1209440
 
4.4%
: 1209440
 
4.4%
9 1209440
 
4.4%
Other values (12) 9070800
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27212400
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3023600
 
11.1%
a 2418880
 
8.9%
- 2418880
 
8.9%
d 1814160
 
6.7%
c 1814160
 
6.7%
u 1814160
 
6.7%
8 1209440
 
4.4%
3 1209440
 
4.4%
: 1209440
 
4.4%
9 1209440
 
4.4%
Other values (12) 9070800
33.3%

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:16.531710image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2418880
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 604720
100.0%
2025-02-10T13:48:16.614214image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 604720
25.0%
S 604720
25.0%
N 604720
25.0%
M 604720
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2418880
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 604720
25.0%
S 604720
25.0%
N 604720
25.0%
M 604720
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2418880
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 604720
25.0%
S 604720
25.0%
N 604720
25.0%
M 604720
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2418880
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 604720
25.0%
S 604720
25.0%
N 604720
25.0%
M 604720
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:16.643275image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1814160
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENT
2nd rowENT
3rd rowENT
4th rowENT
5th rowENT
ValueCountFrequency (%)
ent 604720
100.0%
2025-02-10T13:48:16.726855image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 604720
33.3%
N 604720
33.3%
T 604720
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1814160
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 604720
33.3%
N 604720
33.3%
T 604720
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1814160
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 604720
33.3%
N 604720
33.3%
T 604720
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1814160
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 604720
33.3%
N 604720
33.3%
T 604720
33.3%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:16.757825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11489680
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 604720
33.3%
extant 604720
33.3%
biology 604720
33.3%
2025-02-10T13:48:16.844206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1209440
 
10.5%
1209440
 
10.5%
t 1209440
 
10.5%
o 1209440
 
10.5%
M 604720
 
5.3%
H 604720
 
5.3%
E 604720
 
5.3%
x 604720
 
5.3%
a 604720
 
5.3%
n 604720
 
5.3%
Other values (5) 3023600
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11489680
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1209440
 
10.5%
1209440
 
10.5%
t 1209440
 
10.5%
o 1209440
 
10.5%
M 604720
 
5.3%
H 604720
 
5.3%
E 604720
 
5.3%
x 604720
 
5.3%
a 604720
 
5.3%
n 604720
 
5.3%
Other values (5) 3023600
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11489680
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1209440
 
10.5%
1209440
 
10.5%
t 1209440
 
10.5%
o 1209440
 
10.5%
M 604720
 
5.3%
H 604720
 
5.3%
E 604720
 
5.3%
x 604720
 
5.3%
a 604720
 
5.3%
n 604720
 
5.3%
Other values (5) 3023600
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11489680
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1209440
 
10.5%
1209440
 
10.5%
t 1209440
 
10.5%
o 1209440
 
10.5%
M 604720
 
5.3%
H 604720
 
5.3%
E 604720
 
5.3%
x 604720
 
5.3%
a 604720
 
5.3%
n 604720
 
5.3%
Other values (5) 3023600
26.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:16.874279image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length16.99375083
Min length16

Characters and Unicode

Total characters10276461
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 600941
99.4%
humanobservation 3779
 
0.6%
2025-02-10T13:48:16.960602image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3008484
29.3%
r 1205661
11.7%
n 608499
 
5.9%
i 604720
 
5.9%
s 604720
 
5.9%
v 604720
 
5.9%
m 604720
 
5.9%
c 600941
 
5.8%
P 600941
 
5.8%
p 600941
 
5.8%
Other values (9) 1232114
12.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10276461
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3008484
29.3%
r 1205661
11.7%
n 608499
 
5.9%
i 604720
 
5.9%
s 604720
 
5.9%
v 604720
 
5.9%
m 604720
 
5.9%
c 600941
 
5.8%
P 600941
 
5.8%
p 600941
 
5.8%
Other values (9) 1232114
12.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10276461
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3008484
29.3%
r 1205661
11.7%
n 608499
 
5.9%
i 604720
 
5.9%
s 604720
 
5.9%
v 604720
 
5.9%
m 604720
 
5.9%
c 600941
 
5.8%
P 600941
 
5.8%
p 600941
 
5.8%
Other values (9) 1232114
12.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10276461
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3008484
29.3%
r 1205661
11.7%
n 608499
 
5.9%
i 604720
 
5.9%
s 604720
 
5.9%
v 604720
 
5.9%
m 604720
 
5.9%
c 600941
 
5.8%
P 600941
 
5.8%
p 600941
 
5.8%
Other values (9) 1232114
12.0%

occurrenceID
Text

Unique 

Distinct604720
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:48:17.228218image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters38097360
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique604720 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/3c83a10d1-1e59-4b08-af5b-28d12d2d0c80
2nd rowhttp://n2t.net/ark:/65665/383bb510d-d5ce-4c09-b4c4-bc1482fbaf28
3rd rowhttp://n2t.net/ark:/65665/383f13aa6-a5b6-40bc-bddc-b42c557aebfc
4th rowhttp://n2t.net/ark:/65665/383f4d560-c2d2-485c-906c-b6dad303fd7a
5th rowhttp://n2t.net/ark:/65665/383f634da-bb58-423c-85f4-a267b04c5ee5
ValueCountFrequency (%)
http://n2t.net/ark:/65665/3c83a10d1-1e59-4b08-af5b-28d12d2d0c80 1
 
< 0.1%
http://n2t.net/ark:/65665/3c932a059-56b2-4846-9e97-741d7bdde29c 1
 
< 0.1%
http://n2t.net/ark:/65665/384cb9f0c-76d8-41b2-9a2e-351c10a4ab3f 1
 
< 0.1%
http://n2t.net/ark:/65665/3c94d744a-d127-4564-9b0c-5d349a138dd0 1
 
< 0.1%
http://n2t.net/ark:/65665/384c3715b-7768-468a-b76b-a68ff7a554d0 1
 
< 0.1%
http://n2t.net/ark:/65665/3c8c6462b-a9e9-4efa-9205-6fb4e5ef4e65 1
 
< 0.1%
http://n2t.net/ark:/65665/383f13aa6-a5b6-40bc-bddc-b42c557aebfc 1
 
< 0.1%
http://n2t.net/ark:/65665/383f4d560-c2d2-485c-906c-b6dad303fd7a 1
 
< 0.1%
http://n2t.net/ark:/65665/383f634da-bb58-423c-85f4-a267b04c5ee5 1
 
< 0.1%
http://n2t.net/ark:/65665/3c898aee2-d463-49d7-ad9c-6fd423e170e1 1
 
< 0.1%
Other values (604710) 604710
> 99.9%
2025-02-10T13:48:17.566658image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 3023600
 
7.9%
6 2949751
 
7.7%
- 2418880
 
6.3%
t 2418880
 
6.3%
5 2343491
 
6.2%
a 1889528
 
5.0%
2 1739197
 
4.6%
e 1738583
 
4.6%
3 1737642
 
4.6%
4 1737535
 
4.6%
Other values (16) 16100273
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38097360
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 3023600
 
7.9%
6 2949751
 
7.7%
- 2418880
 
6.3%
t 2418880
 
6.3%
5 2343491
 
6.2%
a 1889528
 
5.0%
2 1739197
 
4.6%
e 1738583
 
4.6%
3 1737642
 
4.6%
4 1737535
 
4.6%
Other values (16) 16100273
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38097360
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 3023600
 
7.9%
6 2949751
 
7.7%
- 2418880
 
6.3%
t 2418880
 
6.3%
5 2343491
 
6.2%
a 1889528
 
5.0%
2 1739197
 
4.6%
e 1738583
 
4.6%
3 1737642
 
4.6%
4 1737535
 
4.6%
Other values (16) 16100273
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38097360
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 3023600
 
7.9%
6 2949751
 
7.7%
- 2418880
 
6.3%
t 2418880
 
6.3%
5 2343491
 
6.2%
a 1889528
 
5.0%
2 1739197
 
4.6%
e 1738583
 
4.6%
3 1737642
 
4.6%
4 1737535
 
4.6%
Other values (16) 16100273
42.3%

catalogNumber
Text

Missing 

Distinct371254
Distinct (%)> 99.9%
Missing233452
Missing (%)38.6%
Memory size4.6 MiB
2025-02-10T13:48:17.875575image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length15
Mean length15.03873482
Min length12

Characters and Unicode

Total characters5583401
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique371240 ?
Unique (%)> 99.9%

Sample

1st rowUSNMENT00831303
2nd rowUSNMENT00356408
3rd rowUSNMENT01436172
4th rowUSNMENT00357025
5th rowUSNMENT00314717
ValueCountFrequency (%)
usnment00377587 2
 
< 0.1%
usnment00381323 2
 
< 0.1%
usnment00937212 2
 
< 0.1%
usnment00377617 2
 
< 0.1%
usnment00536541 2
 
< 0.1%
usnment00533165 2
 
< 0.1%
usnment00385557 2
 
< 0.1%
usnment01200936 2
 
< 0.1%
usnment00385731 2
 
< 0.1%
usnment00937214 2
 
< 0.1%
Other values (371244) 371248
> 99.9%
2025-02-10T13:48:18.277991image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 804733
14.4%
N 741878
13.3%
1 377023
 
6.8%
S 371268
 
6.6%
U 371224
 
6.6%
M 371224
 
6.6%
E 370648
 
6.6%
T 370648
 
6.6%
3 302855
 
5.4%
4 225937
 
4.0%
Other values (11) 1275963
22.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5583401
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 804733
14.4%
N 741878
13.3%
1 377023
 
6.8%
S 371268
 
6.6%
U 371224
 
6.6%
M 371224
 
6.6%
E 370648
 
6.6%
T 370648
 
6.6%
3 302855
 
5.4%
4 225937
 
4.0%
Other values (11) 1275963
22.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5583401
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 804733
14.4%
N 741878
13.3%
1 377023
 
6.8%
S 371268
 
6.6%
U 371224
 
6.6%
M 371224
 
6.6%
E 370648
 
6.6%
T 370648
 
6.6%
3 302855
 
5.4%
4 225937
 
4.0%
Other values (11) 1275963
22.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5583401
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 804733
14.4%
N 741878
13.3%
1 377023
 
6.8%
S 371268
 
6.6%
U 371224
 
6.6%
M 371224
 
6.6%
E 370648
 
6.6%
T 370648
 
6.6%
3 302855
 
5.4%
4 225937
 
4.0%
Other values (11) 1275963
22.9%

recordNumber
Text

Missing 

Distinct33
Distinct (%)89.2%
Missing604683
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:18.365616image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length43
Median length26
Mean length17.13513514
Min length4

Characters and Unicode

Total characters634
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)86.5%

Sample

1st rowCollection number "14,957"
2nd rowLot 607, Sub 182
3rd row4012
4th rowDognin Collection
5th row12.097
ValueCountFrequency (%)
collection 10
 
10.0%
no 9
 
9.0%
walsingham 7
 
7.0%
dognin 5
 
5.0%
hopkins 3
 
3.0%
quaintance 2
 
2.0%
wlsm 2
 
2.0%
townes 2
 
2.0%
number 2
 
2.0%
from 2
 
2.0%
Other values (56) 56
56.0%
2025-02-10T13:48:18.503978image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
9.9%
o 52
 
8.2%
n 47
 
7.4%
l 39
 
6.2%
i 33
 
5.2%
. 26
 
4.1%
e 25
 
3.9%
a 22
 
3.5%
t 19
 
3.0%
1 19
 
3.0%
Other values (47) 289
45.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 634
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
63
 
9.9%
o 52
 
8.2%
n 47
 
7.4%
l 39
 
6.2%
i 33
 
5.2%
. 26
 
4.1%
e 25
 
3.9%
a 22
 
3.5%
t 19
 
3.0%
1 19
 
3.0%
Other values (47) 289
45.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 634
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
63
 
9.9%
o 52
 
8.2%
n 47
 
7.4%
l 39
 
6.2%
i 33
 
5.2%
. 26
 
4.1%
e 25
 
3.9%
a 22
 
3.5%
t 19
 
3.0%
1 19
 
3.0%
Other values (47) 289
45.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 634
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
63
 
9.9%
o 52
 
8.2%
n 47
 
7.4%
l 39
 
6.2%
i 33
 
5.2%
. 26
 
4.1%
e 25
 
3.9%
a 22
 
3.5%
t 19
 
3.0%
1 19
 
3.0%
Other values (47) 289
45.6%

recordedBy
Text

Missing 

Distinct18727
Distinct (%)4.7%
Missing203369
Missing (%)33.6%
Memory size4.6 MiB
2025-02-10T13:48:18.657906image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length90
Median length84
Mean length11.25701693
Min length1

Characters and Unicode

Total characters4518015
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9104 ?
Unique (%)2.3%

Sample

1st rowM. Ortiz B.
2nd row[Not Stated]
3rd rowS. Roble
4th row[Not Stated]
5th rowC. Flint
ValueCountFrequency (%)
not 65723
 
7.2%
stated 65707
 
7.2%
l 40187
 
4.4%
39883
 
4.4%
j 36893
 
4.0%
macior 31234
 
3.4%
d 28472
 
3.1%
c 27158
 
3.0%
r 25638
 
2.8%
b 22051
 
2.4%
Other values (10691) 530867
58.1%
2025-02-10T13:48:18.885497image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
512462
 
11.3%
. 355587
 
7.9%
t 305186
 
6.8%
a 299390
 
6.6%
e 290122
 
6.4%
o 240216
 
5.3%
r 229316
 
5.1%
i 173792
 
3.8%
n 169878
 
3.8%
l 136877
 
3.0%
Other values (73) 1805189
40.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4518015
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
512462
 
11.3%
. 355587
 
7.9%
t 305186
 
6.8%
a 299390
 
6.6%
e 290122
 
6.4%
o 240216
 
5.3%
r 229316
 
5.1%
i 173792
 
3.8%
n 169878
 
3.8%
l 136877
 
3.0%
Other values (73) 1805189
40.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4518015
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
512462
 
11.3%
. 355587
 
7.9%
t 305186
 
6.8%
a 299390
 
6.6%
e 290122
 
6.4%
o 240216
 
5.3%
r 229316
 
5.1%
i 173792
 
3.8%
n 169878
 
3.8%
l 136877
 
3.0%
Other values (73) 1805189
40.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4518015
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
512462
 
11.3%
. 355587
 
7.9%
t 305186
 
6.8%
a 299390
 
6.6%
e 290122
 
6.4%
o 240216
 
5.3%
r 229316
 
5.1%
i 173792
 
3.8%
n 169878
 
3.8%
l 136877
 
3.0%
Other values (73) 1805189
40.0%
Distinct941
Distinct (%)0.2%
Missing3136
Missing (%)0.5%
Memory size4.6 MiB
2025-02-10T13:48:18.918904image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.044863228
Min length1

Characters and Unicode

Total characters628573
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique393 ?
Unique (%)0.1%

Sample

1st row7
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 548305
91.1%
2 10273
 
1.7%
3 6619
 
1.1%
4 4295
 
0.7%
5 2621
 
0.4%
6 2340
 
0.4%
7 1822
 
0.3%
8 1527
 
0.3%
10 1306
 
0.2%
9 1254
 
0.2%
Other values (931) 21222
 
3.5%
2025-02-10T13:48:19.011552image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 560888
89.2%
2 17645
 
2.8%
3 11801
 
1.9%
4 8337
 
1.3%
5 6511
 
1.0%
0 6142
 
1.0%
6 5349
 
0.9%
7 4420
 
0.7%
8 3992
 
0.6%
9 3488
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 628573
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 560888
89.2%
2 17645
 
2.8%
3 11801
 
1.9%
4 8337
 
1.3%
5 6511
 
1.0%
0 6142
 
1.0%
6 5349
 
0.9%
7 4420
 
0.7%
8 3992
 
0.6%
9 3488
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 628573
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 560888
89.2%
2 17645
 
2.8%
3 11801
 
1.9%
4 8337
 
1.3%
5 6511
 
1.0%
0 6142
 
1.0%
6 5349
 
0.9%
7 4420
 
0.7%
8 3992
 
0.6%
9 3488
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 628573
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 560888
89.2%
2 17645
 
2.8%
3 11801
 
1.9%
4 8337
 
1.3%
5 6511
 
1.0%
0 6142
 
1.0%
6 5349
 
0.9%
7 4420
 
0.7%
8 3992
 
0.6%
9 3488
 
0.6%

sex
Text

Missing 

Distinct95
Distinct (%)< 0.1%
Missing339511
Missing (%)56.1%
Memory size4.6 MiB
2025-02-10T13:48:19.040300image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length34
Mean length5.351737686
Min length4

Characters and Unicode

Total characters1419329
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)< 0.1%

Sample

1st rowWorker
2nd rowMale
3rd rowMale
4th rowMale
5th rowMale
ValueCountFrequency (%)
male 137835
50.2%
female 93225
34.0%
unknown 34039
 
12.4%
worker 7022
 
2.6%
1487
 
0.5%
unable 240
 
0.1%
to 240
 
0.1%
determine 240
 
0.1%
2025-02-10T13:48:19.224236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 332267
23.4%
l 231300
16.3%
a 231300
16.3%
M 120716
 
8.5%
m 110584
 
7.8%
n 102597
 
7.2%
F 80595
 
5.7%
o 41301
 
2.9%
k 41061
 
2.9%
U 34224
 
2.4%
Other values (13) 93384
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1419329
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 332267
23.4%
l 231300
16.3%
a 231300
16.3%
M 120716
 
8.5%
m 110584
 
7.8%
n 102597
 
7.2%
F 80595
 
5.7%
o 41301
 
2.9%
k 41061
 
2.9%
U 34224
 
2.4%
Other values (13) 93384
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1419329
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 332267
23.4%
l 231300
16.3%
a 231300
16.3%
M 120716
 
8.5%
m 110584
 
7.8%
n 102597
 
7.2%
F 80595
 
5.7%
o 41301
 
2.9%
k 41061
 
2.9%
U 34224
 
2.4%
Other values (13) 93384
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1419329
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 332267
23.4%
l 231300
16.3%
a 231300
16.3%
M 120716
 
8.5%
m 110584
 
7.8%
n 102597
 
7.2%
F 80595
 
5.7%
o 41301
 
2.9%
k 41061
 
2.9%
U 34224
 
2.4%
Other values (13) 93384
 
6.6%

lifeStage
Text

Missing 

Distinct178
Distinct (%)< 0.1%
Missing174155
Missing (%)28.8%
Memory size4.6 MiB
2025-02-10T13:48:19.255060image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length5
Mean length5.285092843
Min length1

Characters and Unicode

Total characters2275576
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)< 0.1%

Sample

1st rowAdult
2nd rowAdult
3rd rowAdult
4th rowAdult
5th rowAdult
ValueCountFrequency (%)
adult 425078
95.7%
immature 4871
 
1.1%
wings 3368
 
0.8%
alate 1659
 
0.4%
apterous 1572
 
0.4%
pupa 1198
 
0.3%
soldier 1080
 
0.2%
worker 1007
 
0.2%
larva 943
 
0.2%
reproductive 667
 
0.2%
Other values (46) 2928
 
0.7%
2025-02-10T13:48:19.356287image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 434662
19.1%
u 434253
19.1%
l 428547
18.8%
d 426929
18.8%
A 392238
17.2%
a 47160
 
2.1%
13806
 
0.6%
e 13577
 
0.6%
r 11681
 
0.5%
m 10485
 
0.5%
Other values (35) 62238
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2275576
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 434662
19.1%
u 434253
19.1%
l 428547
18.8%
d 426929
18.8%
A 392238
17.2%
a 47160
 
2.1%
13806
 
0.6%
e 13577
 
0.6%
r 11681
 
0.5%
m 10485
 
0.5%
Other values (35) 62238
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2275576
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 434662
19.1%
u 434253
19.1%
l 428547
18.8%
d 426929
18.8%
A 392238
17.2%
a 47160
 
2.1%
13806
 
0.6%
e 13577
 
0.6%
r 11681
 
0.5%
m 10485
 
0.5%
Other values (35) 62238
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2275576
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 434662
19.1%
u 434253
19.1%
l 428547
18.8%
d 426929
18.8%
A 392238
17.2%
a 47160
 
2.1%
13806
 
0.6%
e 13577
 
0.6%
r 11681
 
0.5%
m 10485
 
0.5%
Other values (35) 62238
 
2.7%

preparations
Text

Missing 

Distinct272
Distinct (%)< 0.1%
Missing42056
Missing (%)7.0%
Memory size4.6 MiB
2025-02-10T13:48:19.387230image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length93
Median length6
Mean length6.839828032
Min length1

Characters and Unicode

Total characters3848525
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)< 0.1%

Sample

1st rowPinned
2nd rowPinned
3rd rowPinned
4th rowEnvelope
5th rowPinned
ValueCountFrequency (%)
pinned 389792
63.9%
envelope 114691
 
18.8%
slide 65067
 
10.7%
vial 9498
 
1.6%
ethanol 6482
 
1.1%
section 3747
 
0.6%
on 3653
 
0.6%
3195
 
0.5%
ink 3151
 
0.5%
pen 3072
 
0.5%
Other values (93) 7800
 
1.3%
2025-02-10T13:48:19.485658image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 916570
23.8%
e 701224
18.2%
i 472718
12.3%
d 455956
11.8%
P 366246
 
9.5%
l 199786
 
5.2%
p 142808
 
3.7%
o 133897
 
3.5%
v 114853
 
3.0%
E 112904
 
2.9%
Other values (48) 231563
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3848525
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 916570
23.8%
e 701224
18.2%
i 472718
12.3%
d 455956
11.8%
P 366246
 
9.5%
l 199786
 
5.2%
p 142808
 
3.7%
o 133897
 
3.5%
v 114853
 
3.0%
E 112904
 
2.9%
Other values (48) 231563
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3848525
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 916570
23.8%
e 701224
18.2%
i 472718
12.3%
d 455956
11.8%
P 366246
 
9.5%
l 199786
 
5.2%
p 142808
 
3.7%
o 133897
 
3.5%
v 114853
 
3.0%
E 112904
 
2.9%
Other values (48) 231563
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3848525
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 916570
23.8%
e 701224
18.2%
i 472718
12.3%
d 455956
11.8%
P 366246
 
9.5%
l 199786
 
5.2%
p 142808
 
3.7%
o 133897
 
3.5%
v 114853
 
3.0%
E 112904
 
2.9%
Other values (48) 231563
 
6.0%

associatedMedia
Text

Missing 

Distinct214407
Distinct (%)99.9%
Missing390092
Missing (%)64.5%
Memory size4.6 MiB
2025-02-10T13:48:19.615689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length259
Median length49
Mean length52.23455467
Min length48

Characters and Unicode

Total characters11210998
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214268 ?
Unique (%)99.8%

Sample

1st rowhttps://collections.nmnh.si.edu/media/?i=16421668
2nd rowhttps://collections.nmnh.si.edu/media/?i=16411146
3rd rowhttps://collections.nmnh.si.edu/media/?i=16342640
4th rowhttps://collections.nmnh.si.edu/media/?i=16365128
5th rowhttps://collections.nmnh.si.edu/media/?i=16326001
ValueCountFrequency (%)
https://collections.nmnh.si.edu/media/?i=16612365 38
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16556913 19
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16558066 14
 
< 0.1%
16556913 12
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16623013 10
 
< 0.1%
16574611 9
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16945972 7
 
< 0.1%
16561531 7
 
< 0.1%
16556901 7
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16947492 5
 
< 0.1%
Other values (284058) 287167
> 99.9%
2025-02-10T13:48:19.823883image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 858512
 
7.7%
/ 858512
 
7.7%
e 643884
 
5.7%
t 643884
 
5.7%
s 643884
 
5.7%
. 643884
 
5.7%
n 643884
 
5.7%
1 468009
 
4.2%
l 429256
 
3.8%
o 429256
 
3.8%
Other values (21) 4948033
44.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11210998
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 858512
 
7.7%
/ 858512
 
7.7%
e 643884
 
5.7%
t 643884
 
5.7%
s 643884
 
5.7%
. 643884
 
5.7%
n 643884
 
5.7%
1 468009
 
4.2%
l 429256
 
3.8%
o 429256
 
3.8%
Other values (21) 4948033
44.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11210998
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 858512
 
7.7%
/ 858512
 
7.7%
e 643884
 
5.7%
t 643884
 
5.7%
s 643884
 
5.7%
. 643884
 
5.7%
n 643884
 
5.7%
1 468009
 
4.2%
l 429256
 
3.8%
o 429256
 
3.8%
Other values (21) 4948033
44.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11210998
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 858512
 
7.7%
/ 858512
 
7.7%
e 643884
 
5.7%
t 643884
 
5.7%
s 643884
 
5.7%
. 643884
 
5.7%
n 643884
 
5.7%
1 468009
 
4.2%
l 429256
 
3.8%
o 429256
 
3.8%
Other values (21) 4948033
44.1%

occurrenceRemarks
Text

Missing 

Distinct31235
Distinct (%)21.5%
Missing459346
Missing (%)76.0%
Memory size4.6 MiB
2025-02-10T13:48:19.992978image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length151446
Median length89176
Mean length77.46756641
Min length1

Characters and Unicode

Total characters11261770
Distinct characters120
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27503 ?
Unique (%)18.9%

Sample

1st rowOne leg removed for genetic sampling while on loan to GUELPH.
2nd rowLindroth, 1975:125: (the loc. is no doubt wrong).
3rd rowF. Monros Coll. 1959 G.M. Greene Coll. C. Schaeffer Coll. Shoemaker Coll. 1956 A. Nicolay Coll. 1950 L.W. Saylor Coll.
4th rowSpecimen data is incomplete. Phase 1 of data capture inlcluded USNMENT#s and general locality.
5th rowOne leg removed for genetic sampling while on loan to GUELPH.
ValueCountFrequency (%)
digitization 56218
 
3.4%
by 48162
 
2.9%
digital 44075
 
2.7%
transcribed 44039
 
2.7%
volunteers 44039
 
2.7%
of 42600
 
2.6%
on 41034
 
2.5%
to 36795
 
2.2%
loan 36495
 
2.2%
for 36258
 
2.2%
Other values (46961) 1230406
74.1%
2025-02-10T13:48:20.244414image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1496225
 
13.3%
e 833183
 
7.4%
i 803329
 
7.1%
a 671754
 
6.0%
t 666687
 
5.9%
o 651617
 
5.8%
n 613739
 
5.4%
r 553298
 
4.9%
s 447996
 
4.0%
l 427415
 
3.8%
Other values (110) 4096527
36.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11261770
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1496225
 
13.3%
e 833183
 
7.4%
i 803329
 
7.1%
a 671754
 
6.0%
t 666687
 
5.9%
o 651617
 
5.8%
n 613739
 
5.4%
r 553298
 
4.9%
s 447996
 
4.0%
l 427415
 
3.8%
Other values (110) 4096527
36.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11261770
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1496225
 
13.3%
e 833183
 
7.4%
i 803329
 
7.1%
a 671754
 
6.0%
t 666687
 
5.9%
o 651617
 
5.8%
n 613739
 
5.4%
r 553298
 
4.9%
s 447996
 
4.0%
l 427415
 
3.8%
Other values (110) 4096527
36.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11261770
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1496225
 
13.3%
e 833183
 
7.4%
i 803329
 
7.1%
a 671754
 
6.0%
t 666687
 
5.9%
o 651617
 
5.8%
n 613739
 
5.4%
r 553298
 
4.9%
s 447996
 
4.0%
l 427415
 
3.8%
Other values (110) 4096527
36.4%

organismID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:20.281014image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row70 21'9"W
ValueCountFrequency (%)
70 1
50.0%
21'9"w 1
50.0%
2025-02-10T13:48:20.361961image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1
11.1%
0 1
11.1%
1
11.1%
2 1
11.1%
1 1
11.1%
' 1
11.1%
9 1
11.1%
" 1
11.1%
W 1
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7 1
11.1%
0 1
11.1%
1
11.1%
2 1
11.1%
1 1
11.1%
' 1
11.1%
9 1
11.1%
" 1
11.1%
W 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7 1
11.1%
0 1
11.1%
1
11.1%
2 1
11.1%
1 1
11.1%
' 1
11.1%
9 1
11.1%
" 1
11.1%
W 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7 1
11.1%
0 1
11.1%
1
11.1%
2 1
11.1%
1 1
11.1%
' 1
11.1%
9 1
11.1%
" 1
11.1%
W 1
11.1%

eventType
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:20.392948image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row-11.7815
ValueCountFrequency (%)
11.7815 1
100.0%
2025-02-10T13:48:20.472652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
37.5%
- 1
 
12.5%
. 1
 
12.5%
7 1
 
12.5%
8 1
 
12.5%
5 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 3
37.5%
- 1
 
12.5%
. 1
 
12.5%
7 1
 
12.5%
8 1
 
12.5%
5 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 3
37.5%
- 1
 
12.5%
. 1
 
12.5%
7 1
 
12.5%
8 1
 
12.5%
5 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 3
37.5%
- 1
 
12.5%
. 1
 
12.5%
7 1
 
12.5%
8 1
 
12.5%
5 1
 
12.5%

fieldNumber
Text

Missing 

Distinct3093
Distinct (%)72.7%
Missing600468
Missing (%)99.3%
Memory size4.6 MiB
2025-02-10T13:48:20.602945image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length29
Mean length9.591251176
Min length1

Characters and Unicode

Total characters40782
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2648 ?
Unique (%)62.3%

Sample

1st rowBBB991
2nd rowBBB642-DERM
3rd row1653
4th rowJSL021109-18
5th rowCOL-8-101
ValueCountFrequency (%)
1653 128
 
2.8%
2 46
 
1.0%
bbb899-hym 34
 
0.7%
1 32
 
0.7%
bbb791-hym 26
 
0.6%
bbb749-hym 23
 
0.5%
759-8 22
 
0.5%
tub 20
 
0.4%
tank 18
 
0.4%
9 18
 
0.4%
Other values (3089) 4227
92.0%
2025-02-10T13:48:20.804670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 4784
 
11.7%
0 3997
 
9.8%
- 3980
 
9.8%
1 3402
 
8.3%
2 2239
 
5.5%
3 1558
 
3.8%
6 1542
 
3.8%
7 1514
 
3.7%
4 1498
 
3.7%
9 1482
 
3.6%
Other values (60) 14786
36.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 40782
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 4784
 
11.7%
0 3997
 
9.8%
- 3980
 
9.8%
1 3402
 
8.3%
2 2239
 
5.5%
3 1558
 
3.8%
6 1542
 
3.8%
7 1514
 
3.7%
4 1498
 
3.7%
9 1482
 
3.6%
Other values (60) 14786
36.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 40782
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 4784
 
11.7%
0 3997
 
9.8%
- 3980
 
9.8%
1 3402
 
8.3%
2 2239
 
5.5%
3 1558
 
3.8%
6 1542
 
3.8%
7 1514
 
3.7%
4 1498
 
3.7%
9 1482
 
3.6%
Other values (60) 14786
36.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 40782
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 4784
 
11.7%
0 3997
 
9.8%
- 3980
 
9.8%
1 3402
 
8.3%
2 2239
 
5.5%
3 1558
 
3.8%
6 1542
 
3.8%
7 1514
 
3.7%
4 1498
 
3.7%
9 1482
 
3.6%
Other values (60) 14786
36.3%

eventDate
Text

Missing 

Distinct46148
Distinct (%)12.6%
Missing239420
Missing (%)39.6%
Memory size4.6 MiB
2025-02-10T13:48:20.981022image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length10
Mean length11.06884752
Min length4

Characters and Unicode

Total characters4043450
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13232 ?
Unique (%)3.6%

Sample

1st row1967-06-20
2nd row1914-07
3rd row2005-08-02
4th row1964-04-25
5th row1971-08-22
ValueCountFrequency (%)
1998-07-26 709
 
0.2%
1938 574
 
0.2%
2006-06-24 544
 
0.1%
1933 524
 
0.1%
1960-06-30 506
 
0.1%
1936 472
 
0.1%
1927-07-10 469
 
0.1%
1964-08-01/1964-08-31 449
 
0.1%
1930 435
 
0.1%
1966-06-23 407
 
0.1%
Other values (46130) 360245
98.6%
2025-02-10T13:48:21.234100image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 782638
19.4%
1 702348
17.4%
0 653087
16.2%
9 492965
12.2%
2 288127
 
7.1%
6 225522
 
5.6%
7 216691
 
5.4%
8 183523
 
4.5%
5 159737
 
4.0%
3 155914
 
3.9%
Other values (6) 182898
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4043450
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 782638
19.4%
1 702348
17.4%
0 653087
16.2%
9 492965
12.2%
2 288127
 
7.1%
6 225522
 
5.6%
7 216691
 
5.4%
8 183523
 
4.5%
5 159737
 
4.0%
3 155914
 
3.9%
Other values (6) 182898
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4043450
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 782638
19.4%
1 702348
17.4%
0 653087
16.2%
9 492965
12.2%
2 288127
 
7.1%
6 225522
 
5.6%
7 216691
 
5.4%
8 183523
 
4.5%
5 159737
 
4.0%
3 155914
 
3.9%
Other values (6) 182898
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4043450
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 782638
19.4%
1 702348
17.4%
0 653087
16.2%
9 492965
12.2%
2 288127
 
7.1%
6 225522
 
5.6%
7 216691
 
5.4%
8 183523
 
4.5%
5 159737
 
4.0%
3 155914
 
3.9%
Other values (6) 182898
 
4.5%

startDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing244789
Missing (%)40.5%
Memory size4.6 MiB
2025-02-10T13:48:21.400047image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.849043289
Min length1

Characters and Unicode

Total characters1025459
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row171
2nd row212
3rd row214
4th row116
5th row234
ValueCountFrequency (%)
212 4210
 
1.2%
213 4014
 
1.1%
182 3947
 
1.1%
181 3445
 
1.0%
151 3112
 
0.9%
152 2941
 
0.8%
183 2913
 
0.8%
191 2887
 
0.8%
207 2741
 
0.8%
178 2632
 
0.7%
Other values (356) 327089
90.9%
2025-02-10T13:48:21.627743image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 238127
23.2%
2 202525
19.7%
3 100701
9.8%
9 70985
 
6.9%
0 70947
 
6.9%
4 70160
 
6.8%
5 69390
 
6.8%
8 68439
 
6.7%
6 67900
 
6.6%
7 66285
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1025459
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 238127
23.2%
2 202525
19.7%
3 100701
9.8%
9 70985
 
6.9%
0 70947
 
6.9%
4 70160
 
6.8%
5 69390
 
6.8%
8 68439
 
6.7%
6 67900
 
6.6%
7 66285
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1025459
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 238127
23.2%
2 202525
19.7%
3 100701
9.8%
9 70985
 
6.9%
0 70947
 
6.9%
4 70160
 
6.8%
5 69390
 
6.8%
8 68439
 
6.7%
6 67900
 
6.6%
7 66285
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1025459
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 238127
23.2%
2 202525
19.7%
3 100701
9.8%
9 70985
 
6.9%
0 70947
 
6.9%
4 70160
 
6.8%
5 69390
 
6.8%
8 68439
 
6.7%
6 67900
 
6.6%
7 66285
 
6.5%

endDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing244303
Missing (%)40.4%
Memory size4.6 MiB
2025-02-10T13:48:21.781444image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.857215392
Min length1

Characters and Unicode

Total characters1029789
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row171
2nd row212
3rd row214
4th row116
5th row234
ValueCountFrequency (%)
212 4994
 
1.4%
181 4276
 
1.2%
213 3666
 
1.0%
151 3533
 
1.0%
182 3365
 
0.9%
243 3191
 
0.9%
207 2999
 
0.8%
191 2952
 
0.8%
197 2774
 
0.8%
120 2623
 
0.7%
Other values (356) 326044
90.5%
2025-02-10T13:48:21.994263image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 236813
23.0%
2 202617
19.7%
3 102147
9.9%
0 72053
 
7.0%
9 71767
 
7.0%
4 70263
 
6.8%
5 69867
 
6.8%
6 68660
 
6.7%
7 67928
 
6.6%
8 67674
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1029789
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 236813
23.0%
2 202617
19.7%
3 102147
9.9%
0 72053
 
7.0%
9 71767
 
7.0%
4 70263
 
6.8%
5 69867
 
6.8%
6 68660
 
6.7%
7 67928
 
6.6%
8 67674
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1029789
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 236813
23.0%
2 202617
19.7%
3 102147
9.9%
0 72053
 
7.0%
9 71767
 
7.0%
4 70263
 
6.8%
5 69867
 
6.8%
6 68660
 
6.7%
7 67928
 
6.6%
8 67674
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1029789
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 236813
23.0%
2 202617
19.7%
3 102147
9.9%
0 72053
 
7.0%
9 71767
 
7.0%
4 70263
 
6.8%
5 69867
 
6.8%
6 68660
 
6.7%
7 67928
 
6.6%
8 67674
 
6.6%

year
Text

Missing 

Distinct191
Distinct (%)0.1%
Missing239420
Missing (%)39.6%
Memory size4.6 MiB
2025-02-10T13:48:22.118661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1461200
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)< 0.1%

Sample

1st row1967
2nd row1914
3rd row2005
4th row1964
5th row1971
ValueCountFrequency (%)
1966 12313
 
3.4%
1968 9194
 
2.5%
1971 8970
 
2.5%
1967 8361
 
2.3%
1965 7882
 
2.2%
1972 6275
 
1.7%
1964 6152
 
1.7%
1974 6096
 
1.7%
1973 6078
 
1.7%
1963 5563
 
1.5%
Other values (181) 288416
79.0%
2025-02-10T13:48:22.298960image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 398215
27.3%
9 381833
26.1%
6 108781
 
7.4%
0 108045
 
7.4%
2 92925
 
6.4%
7 89271
 
6.1%
8 74906
 
5.1%
5 72462
 
5.0%
3 69682
 
4.8%
4 65080
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1461200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 398215
27.3%
9 381833
26.1%
6 108781
 
7.4%
0 108045
 
7.4%
2 92925
 
6.4%
7 89271
 
6.1%
8 74906
 
5.1%
5 72462
 
5.0%
3 69682
 
4.8%
4 65080
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1461200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 398215
27.3%
9 381833
26.1%
6 108781
 
7.4%
0 108045
 
7.4%
2 92925
 
6.4%
7 89271
 
6.1%
8 74906
 
5.1%
5 72462
 
5.0%
3 69682
 
4.8%
4 65080
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1461200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 398215
27.3%
9 381833
26.1%
6 108781
 
7.4%
0 108045
 
7.4%
2 92925
 
6.4%
7 89271
 
6.1%
8 74906
 
5.1%
5 72462
 
5.0%
3 69682
 
4.8%
4 65080
 
4.5%

month
Text

Missing 

Distinct13
Distinct (%)< 0.1%
Missing246636
Missing (%)40.8%
Memory size4.6 MiB
2025-02-10T13:48:22.340640image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length1
Mean length1.113249964
Min length1

Characters and Unicode

Total characters398637
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row6
2nd row7
3rd row8
4th row4
5th row8
ValueCountFrequency (%)
7 74085
20.7%
6 58953
16.5%
8 51938
14.5%
5 36241
10.1%
9 26043
 
7.3%
4 25759
 
7.2%
3 16892
 
4.7%
10 16541
 
4.6%
2 14421
 
4.0%
11 13740
 
3.8%
Other values (4) 23473
 
6.6%
2025-02-10T13:48:22.431920image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 74085
18.6%
1 67492
16.9%
6 58954
14.8%
8 51939
13.0%
5 36241
9.1%
9 26044
 
6.5%
4 25760
 
6.5%
2 24685
 
6.2%
3 16892
 
4.2%
0 16541
 
4.1%
Other values (3) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 398637
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7 74085
18.6%
1 67492
16.9%
6 58954
14.8%
8 51939
13.0%
5 36241
9.1%
9 26044
 
6.5%
4 25760
 
6.5%
2 24685
 
6.2%
3 16892
 
4.2%
0 16541
 
4.1%
Other values (3) 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 398637
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7 74085
18.6%
1 67492
16.9%
6 58954
14.8%
8 51939
13.0%
5 36241
9.1%
9 26044
 
6.5%
4 25760
 
6.5%
2 24685
 
6.2%
3 16892
 
4.2%
0 16541
 
4.1%
Other values (3) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 398637
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7 74085
18.6%
1 67492
16.9%
6 58954
14.8%
8 51939
13.0%
5 36241
9.1%
9 26044
 
6.5%
4 25760
 
6.5%
2 24685
 
6.2%
3 16892
 
4.2%
0 16541
 
4.1%
Other values (3) 4
 
< 0.1%

day
Text

Missing 

Distinct32
Distinct (%)< 0.1%
Missing270887
Missing (%)44.8%
Memory size4.6 MiB
2025-02-10T13:48:22.478971image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length2
Mean length1.683176918
Min length1

Characters and Unicode

Total characters561900
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row20
2nd row2
3rd row25
4th row22
5th row6
ValueCountFrequency (%)
1 20555
 
6.2%
8 13029
 
3.9%
20 12179
 
3.6%
10 11989
 
3.6%
15 11884
 
3.6%
12 11876
 
3.6%
25 11249
 
3.4%
6 11148
 
3.3%
16 11145
 
3.3%
23 10866
 
3.3%
Other values (24) 207915
62.3%
2025-02-10T13:48:22.581613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 155576
27.7%
2 137768
24.5%
3 45163
 
8.0%
8 33226
 
5.9%
0 33162
 
5.9%
5 33152
 
5.9%
6 32821
 
5.8%
4 31502
 
5.6%
7 30851
 
5.5%
9 28675
 
5.1%
Other values (3) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 561900
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 155576
27.7%
2 137768
24.5%
3 45163
 
8.0%
8 33226
 
5.9%
0 33162
 
5.9%
5 33152
 
5.9%
6 32821
 
5.8%
4 31502
 
5.6%
7 30851
 
5.5%
9 28675
 
5.1%
Other values (3) 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 561900
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 155576
27.7%
2 137768
24.5%
3 45163
 
8.0%
8 33226
 
5.9%
0 33162
 
5.9%
5 33152
 
5.9%
6 32821
 
5.8%
4 31502
 
5.6%
7 30851
 
5.5%
9 28675
 
5.1%
Other values (3) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 561900
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 155576
27.7%
2 137768
24.5%
3 45163
 
8.0%
8 33226
 
5.9%
0 33162
 
5.9%
5 33152
 
5.9%
6 32821
 
5.8%
4 31502
 
5.6%
7 30851
 
5.5%
9 28675
 
5.1%
Other values (3) 4
 
< 0.1%

verbatimEventDate
Text

Missing 

Distinct67999
Distinct (%)32.6%
Missing396366
Missing (%)65.5%
Memory size4.6 MiB
2025-02-10T13:48:22.627174image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length79
Median length71
Mean length10.59664321
Min length1

Characters and Unicode

Total characters2207853
Distinct characters92
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51583 ?
Unique (%)24.8%

Sample

1st row[Not Stated]
2nd row2-Aug-2005
3rd row[Not Stated]
4th row[Not Stated]
5th row9-IX-78
ValueCountFrequency (%)
not 32203
 
8.2%
stated 32171
 
8.2%
july 8707
 
2.2%
aug 7740
 
2.0%
june 7233
 
1.8%
may 5958
 
1.5%
1968 5763
 
1.5%
1971 5706
 
1.5%
1966 4507
 
1.1%
1972 2978
 
0.8%
Other values (37321) 279788
71.2%
2025-02-10T13:48:22.828262image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 217348
 
9.8%
184400
 
8.4%
9 146706
 
6.6%
- 127710
 
5.8%
2 112946
 
5.1%
t 105546
 
4.8%
I 88881
 
4.0%
6 79326
 
3.6%
0 76313
 
3.5%
. 64867
 
2.9%
Other values (82) 1003810
45.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2207853
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 217348
 
9.8%
184400
 
8.4%
9 146706
 
6.6%
- 127710
 
5.8%
2 112946
 
5.1%
t 105546
 
4.8%
I 88881
 
4.0%
6 79326
 
3.6%
0 76313
 
3.5%
. 64867
 
2.9%
Other values (82) 1003810
45.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2207853
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 217348
 
9.8%
184400
 
8.4%
9 146706
 
6.6%
- 127710
 
5.8%
2 112946
 
5.1%
t 105546
 
4.8%
I 88881
 
4.0%
6 79326
 
3.6%
0 76313
 
3.5%
. 64867
 
2.9%
Other values (82) 1003810
45.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2207853
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 217348
 
9.8%
184400
 
8.4%
9 146706
 
6.6%
- 127710
 
5.8%
2 112946
 
5.1%
t 105546
 
4.8%
I 88881
 
4.0%
6 79326
 
3.6%
0 76313
 
3.5%
. 64867
 
2.9%
Other values (82) 1003810
45.5%

habitat
Text

Missing 

Distinct89
Distinct (%)44.7%
Missing604521
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:22.892380image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length103
Median length43
Mean length19.28643216
Min length5

Characters and Unicode

Total characters3838
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)32.2%

Sample

1st rowRoadside in coniferous forest
2nd rowOn a figleaf gourd
3rd rowcultivated garden
4th rowhammocks-dense hardwood & Palmetto forests
5th rowvisiting mango flowers
ValueCountFrequency (%)
garden 45
 
7.4%
cultivated 44
 
7.3%
stream 26
 
4.3%
on 26
 
4.3%
forest 23
 
3.8%
in 19
 
3.1%
of 13
 
2.1%
collected 12
 
2.0%
at 9
 
1.5%
terre 8
 
1.3%
Other values (183) 381
62.9%
2025-02-10T13:48:23.024350image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.7%
i 190
 
5.0%
l 185
 
4.8%
Other values (52) 1188
31.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3838
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.7%
i 190
 
5.0%
l 185
 
4.8%
Other values (52) 1188
31.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3838
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.7%
i 190
 
5.0%
l 185
 
4.8%
Other values (52) 1188
31.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3838
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.7%
i 190
 
5.0%
l 185
 
4.8%
Other values (52) 1188
31.0%

locationID
Text

Missing 

Distinct185
Distinct (%)17.7%
Missing603675
Missing (%)99.8%
Memory size4.6 MiB
2025-02-10T13:48:23.058385image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length14
Mean length10.78947368
Min length1

Characters and Unicode

Total characters11275
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)9.0%

Sample

1st rowMEI Site 97-81
2nd rowRD-044
3rd rowMEI Site 97-81
4th rowMEI Site 97-81
5th rowMEI Site 97-81
ValueCountFrequency (%)
mei 652
27.5%
site 610
25.7%
97-81 301
12.7%
97-92 132
 
5.6%
97-90 52
 
2.2%
97-58 46
 
1.9%
97-74 31
 
1.3%
97-88 26
 
1.1%
97-93 24
 
1.0%
k-m1 19
 
0.8%
Other values (195) 479
20.2%
2025-02-10T13:48:23.161064image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1327
 
11.8%
- 986
 
8.7%
9 904
 
8.0%
7 770
 
6.8%
M 698
 
6.2%
I 659
 
5.8%
E 656
 
5.8%
t 638
 
5.7%
e 637
 
5.6%
i 624
 
5.5%
Other values (46) 3376
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11275
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1327
 
11.8%
- 986
 
8.7%
9 904
 
8.0%
7 770
 
6.8%
M 698
 
6.2%
I 659
 
5.8%
E 656
 
5.8%
t 638
 
5.7%
e 637
 
5.6%
i 624
 
5.5%
Other values (46) 3376
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11275
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1327
 
11.8%
- 986
 
8.7%
9 904
 
8.0%
7 770
 
6.8%
M 698
 
6.2%
I 659
 
5.8%
E 656
 
5.8%
t 638
 
5.7%
e 637
 
5.6%
i 624
 
5.5%
Other values (46) 3376
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11275
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1327
 
11.8%
- 986
 
8.7%
9 904
 
8.0%
7 770
 
6.8%
M 698
 
6.2%
I 659
 
5.8%
E 656
 
5.8%
t 638
 
5.7%
e 637
 
5.6%
i 624
 
5.5%
Other values (46) 3376
29.9%

higherGeography
Text

Missing 

Distinct10596
Distinct (%)2.4%
Missing156093
Missing (%)25.8%
Memory size4.6 MiB
2025-02-10T13:48:23.313879image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length101
Median length91
Mean length30.38929222
Min length4

Characters and Unicode

Total characters13633457
Distinct characters132
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3142 ?
Unique (%)0.7%

Sample

1st rowUnited States, [Not Stated], [Not Stated]
2nd rowCosta Rica, Cartago, [Not Stated]
3rd rowUnited States, Alaska, Aleutians West
4th rowUnited States, Virginia, Virginia Beach
5th rowUnited States, New York, [Not Stated]
ValueCountFrequency (%)
united 222849
 
12.1%
states 221117
 
12.1%
not 168021
 
9.2%
stated 168019
 
9.2%
california 23411
 
1.3%
virginia 23321
 
1.3%
new 22503
 
1.2%
colorado 21080
 
1.1%
mexico 21004
 
1.1%
canada 16233
 
0.9%
Other values (6796) 927210
50.5%
2025-02-10T13:48:23.544408image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1386867
 
10.2%
t 1386839
 
10.2%
1386141
 
10.2%
e 1091011
 
8.0%
i 816099
 
6.0%
n 814243
 
6.0%
, 798935
 
5.9%
o 692570
 
5.1%
d 580440
 
4.3%
s 501693
 
3.7%
Other values (122) 4178619
30.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13633457
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1386867
 
10.2%
t 1386839
 
10.2%
1386141
 
10.2%
e 1091011
 
8.0%
i 816099
 
6.0%
n 814243
 
6.0%
, 798935
 
5.9%
o 692570
 
5.1%
d 580440
 
4.3%
s 501693
 
3.7%
Other values (122) 4178619
30.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13633457
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1386867
 
10.2%
t 1386839
 
10.2%
1386141
 
10.2%
e 1091011
 
8.0%
i 816099
 
6.0%
n 814243
 
6.0%
, 798935
 
5.9%
o 692570
 
5.1%
d 580440
 
4.3%
s 501693
 
3.7%
Other values (122) 4178619
30.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13633457
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1386867
 
10.2%
t 1386839
 
10.2%
1386141
 
10.2%
e 1091011
 
8.0%
i 816099
 
6.0%
n 814243
 
6.0%
, 798935
 
5.9%
o 692570
 
5.1%
d 580440
 
4.3%
s 501693
 
3.7%
Other values (122) 4178619
30.6%

continent
Text

Missing 

Distinct6
Distinct (%)4.7%
Missing604592
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:23.580841image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length4
Mean length7.15625
Min length4

Characters and Unicode

Total characters916
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st rowSouth America
2nd rowAsia
3rd rowSouth America
4th rowEurope
5th rowAsia
ValueCountFrequency (%)
asia 69
40.8%
america 40
23.7%
north 21
 
12.4%
south 19
 
11.2%
europe 9
 
5.3%
africa 9
 
5.3%
not 1
 
0.6%
stated 1
 
0.6%
2025-02-10T13:48:23.661840image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 916
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 916
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 916
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

waterBody
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:23.692855image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDeMarmels
ValueCountFrequency (%)
demarmels 1
100.0%
2025-02-10T13:48:23.773786image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2
22.2%
D 1
11.1%
M 1
11.1%
a 1
11.1%
r 1
11.1%
m 1
11.1%
l 1
11.1%
s 1
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2
22.2%
D 1
11.1%
M 1
11.1%
a 1
11.1%
r 1
11.1%
m 1
11.1%
l 1
11.1%
s 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2
22.2%
D 1
11.1%
M 1
11.1%
a 1
11.1%
r 1
11.1%
m 1
11.1%
l 1
11.1%
s 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2
22.2%
D 1
11.1%
M 1
11.1%
a 1
11.1%
r 1
11.1%
m 1
11.1%
l 1
11.1%
s 1
11.1%

islandGroup
Text

Missing 

Distinct72
Distinct (%)2.9%
Missing602200
Missing (%)99.6%
Memory size4.6 MiB
2025-02-10T13:48:23.809693image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length13
Mean length13.7202381
Min length5

Characters and Unicode

Total characters34575
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.8%

Sample

1st rowSunda Islands
2nd rowInner Islands
3rd rowViti Levu Group
4th rowChuuk Lagoon
5th rowSunda Islands
ValueCountFrequency (%)
islands 2160
42.2%
sunda 956
18.7%
marquesas 249
 
4.9%
solomon 226
 
4.4%
bass 171
 
3.3%
chuuk 149
 
2.9%
lagoon 149
 
2.9%
outer 149
 
2.9%
inner 140
 
2.7%
group 100
 
2.0%
Other values (78) 673
 
13.1%
2025-02-10T13:48:23.911070image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 5365
15.5%
a 4395
12.7%
n 3948
11.4%
d 3266
9.4%
2602
7.5%
l 2568
7.4%
I 2313
6.7%
u 1953
 
5.6%
S 1250
 
3.6%
o 1226
 
3.5%
Other values (39) 5689
16.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 34575
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 5365
15.5%
a 4395
12.7%
n 3948
11.4%
d 3266
9.4%
2602
7.5%
l 2568
7.4%
I 2313
6.7%
u 1953
 
5.6%
S 1250
 
3.6%
o 1226
 
3.5%
Other values (39) 5689
16.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 34575
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 5365
15.5%
a 4395
12.7%
n 3948
11.4%
d 3266
9.4%
2602
7.5%
l 2568
7.4%
I 2313
6.7%
u 1953
 
5.6%
S 1250
 
3.6%
o 1226
 
3.5%
Other values (39) 5689
16.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 34575
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 5365
15.5%
a 4395
12.7%
n 3948
11.4%
d 3266
9.4%
2602
7.5%
l 2568
7.4%
I 2313
6.7%
u 1953
 
5.6%
S 1250
 
3.6%
o 1226
 
3.5%
Other values (39) 5689
16.5%

island
Text

Missing 

Distinct436
Distinct (%)4.7%
Missing595353
Missing (%)98.5%
Memory size4.6 MiB
2025-02-10T13:48:24.060703image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length21
Mean length9.324436853
Min length3

Characters and Unicode

Total characters87342
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique168 ?
Unique (%)1.8%

Sample

1st rowSouth Island
2nd rowPohnpei
3rd rowSouth Island
4th rowOahu
5th rowGuadalcanal
ValueCountFrequency (%)
island 3167
21.5%
south 1636
 
11.1%
java 884
 
6.0%
levu 565
 
3.8%
viti 541
 
3.7%
north 519
 
3.5%
guadalcanal 327
 
2.2%
borneo 253
 
1.7%
hiva 247
 
1.7%
key 246
 
1.7%
Other values (438) 6372
43.2%
2025-02-10T13:48:24.271404image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 12933
14.8%
n 6143
 
7.0%
l 5485
 
6.3%
o 5446
 
6.2%
5390
 
6.2%
u 4466
 
5.1%
d 4450
 
5.1%
s 4126
 
4.7%
e 3908
 
4.5%
t 3745
 
4.3%
Other values (52) 31250
35.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 87342
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 12933
14.8%
n 6143
 
7.0%
l 5485
 
6.3%
o 5446
 
6.2%
5390
 
6.2%
u 4466
 
5.1%
d 4450
 
5.1%
s 4126
 
4.7%
e 3908
 
4.5%
t 3745
 
4.3%
Other values (52) 31250
35.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 87342
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 12933
14.8%
n 6143
 
7.0%
l 5485
 
6.3%
o 5446
 
6.2%
5390
 
6.2%
u 4466
 
5.1%
d 4450
 
5.1%
s 4126
 
4.7%
e 3908
 
4.5%
t 3745
 
4.3%
Other values (52) 31250
35.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 87342
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 12933
14.8%
n 6143
 
7.0%
l 5485
 
6.3%
o 5446
 
6.2%
5390
 
6.2%
u 4466
 
5.1%
d 4450
 
5.1%
s 4126
 
4.7%
e 3908
 
4.5%
t 3745
 
4.3%
Other values (52) 31250
35.8%

country
Text

Missing 

Distinct361
Distinct (%)0.1%
Missing156115
Missing (%)25.8%
Memory size4.6 MiB
2025-02-10T13:48:24.428419image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length57
Median length44
Mean length10.35667681
Min length4

Characters and Unicode

Total characters4646057
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowCosta Rica
3rd rowUnited States
4th rowUnited States
5th rowUnited States
ValueCountFrequency (%)
united 222629
30.9%
states 220899
30.7%
canada 16232
 
2.3%
mexico 15811
 
2.2%
china 14526
 
2.0%
brazil 12973
 
1.8%
costa 8910
 
1.2%
rica 8910
 
1.2%
peru 7637
 
1.1%
india 7029
 
1.0%
Other values (376) 184674
25.6%
2025-02-10T13:48:24.644609image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 718259
15.5%
e 560772
12.1%
a 528526
11.4%
i 389761
8.4%
n 365385
7.9%
d 287382
 
6.2%
271625
 
5.8%
s 261111
 
5.6%
S 244256
 
5.3%
U 223931
 
4.8%
Other values (56) 795049
17.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4646057
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 718259
15.5%
e 560772
12.1%
a 528526
11.4%
i 389761
8.4%
n 365385
7.9%
d 287382
 
6.2%
271625
 
5.8%
s 261111
 
5.6%
S 244256
 
5.3%
U 223931
 
4.8%
Other values (56) 795049
17.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4646057
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 718259
15.5%
e 560772
12.1%
a 528526
11.4%
i 389761
8.4%
n 365385
7.9%
d 287382
 
6.2%
271625
 
5.8%
s 261111
 
5.6%
S 244256
 
5.3%
U 223931
 
4.8%
Other values (56) 795049
17.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4646057
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 718259
15.5%
e 560772
12.1%
a 528526
11.4%
i 389761
8.4%
n 365385
7.9%
d 287382
 
6.2%
271625
 
5.8%
s 261111
 
5.6%
S 244256
 
5.3%
U 223931
 
4.8%
Other values (56) 795049
17.1%

stateProvince
Text

Missing 

Distinct3068
Distinct (%)0.7%
Missing173239
Missing (%)28.6%
Memory size4.6 MiB
2025-02-10T13:48:24.802074image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length57
Median length44
Mean length9.044942883
Min length2

Characters and Unicode

Total characters3902721
Distinct characters116
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique808 ?
Unique (%)0.2%

Sample

1st row[Not Stated]
2nd rowCartago
3rd rowAlaska
4th rowVirginia
5th rowNew York
ValueCountFrequency (%)
not 29440
 
5.2%
stated 29440
 
5.2%
california 23322
 
4.1%
virginia 22013
 
3.9%
colorado 20952
 
3.7%
new 16651
 
2.9%
texas 12341
 
2.2%
arizona 12146
 
2.1%
florida 9884
 
1.7%
maryland 9608
 
1.7%
Other values (2915) 379877
67.2%
2025-02-10T13:48:25.031838image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 524357
 
13.4%
o 333196
 
8.5%
i 321786
 
8.2%
n 299093
 
7.7%
r 250082
 
6.4%
e 216703
 
5.6%
t 208658
 
5.3%
s 151919
 
3.9%
l 138292
 
3.5%
134193
 
3.4%
Other values (106) 1324442
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3902721
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 524357
 
13.4%
o 333196
 
8.5%
i 321786
 
8.2%
n 299093
 
7.7%
r 250082
 
6.4%
e 216703
 
5.6%
t 208658
 
5.3%
s 151919
 
3.9%
l 138292
 
3.5%
134193
 
3.4%
Other values (106) 1324442
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3902721
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 524357
 
13.4%
o 333196
 
8.5%
i 321786
 
8.2%
n 299093
 
7.7%
r 250082
 
6.4%
e 216703
 
5.6%
t 208658
 
5.3%
s 151919
 
3.9%
l 138292
 
3.5%
134193
 
3.4%
Other values (106) 1324442
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3902721
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 524357
 
13.4%
o 333196
 
8.5%
i 321786
 
8.2%
n 299093
 
7.7%
r 250082
 
6.4%
e 216703
 
5.6%
t 208658
 
5.3%
s 151919
 
3.9%
l 138292
 
3.5%
134193
 
3.4%
Other values (106) 1324442
33.9%

county
Text

Missing 

Distinct4068
Distinct (%)1.2%
Missing254867
Missing (%)42.1%
Memory size4.6 MiB
2025-02-10T13:48:25.187145image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length51
Median length45
Mean length9.456280209
Min length1

Characters and Unicode

Total characters3308308
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1157 ?
Unique (%)0.3%

Sample

1st row[Not Stated]
2nd row[Not Stated]
3rd rowAleutians West
4th rowVirginia Beach
5th row[Not Stated]
ValueCountFrequency (%)
not 132062
25.3%
stated 132060
25.3%
boulder 6789
 
1.3%
creek 6760
 
1.3%
clear 6751
 
1.3%
san 5405
 
1.0%
montgomery 4939
 
0.9%
cochise 4320
 
0.8%
prince 3492
 
0.7%
tuolumne 3206
 
0.6%
Other values (4079) 215282
41.3%
2025-02-10T13:48:25.417041image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 455467
13.8%
a 309900
 
9.4%
e 305731
 
9.2%
o 264738
 
8.0%
171213
 
5.2%
d 169224
 
5.1%
S 152130
 
4.6%
N 137690
 
4.2%
n 133853
 
4.0%
[ 132080
 
4.0%
Other values (88) 1076282
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3308308
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 455467
13.8%
a 309900
 
9.4%
e 305731
 
9.2%
o 264738
 
8.0%
171213
 
5.2%
d 169224
 
5.1%
S 152130
 
4.6%
N 137690
 
4.2%
n 133853
 
4.0%
[ 132080
 
4.0%
Other values (88) 1076282
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3308308
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 455467
13.8%
a 309900
 
9.4%
e 305731
 
9.2%
o 264738
 
8.0%
171213
 
5.2%
d 169224
 
5.1%
S 152130
 
4.6%
N 137690
 
4.2%
n 133853
 
4.0%
[ 132080
 
4.0%
Other values (88) 1076282
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3308308
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 455467
13.8%
a 309900
 
9.4%
e 305731
 
9.2%
o 264738
 
8.0%
171213
 
5.2%
d 169224
 
5.1%
S 152130
 
4.6%
N 137690
 
4.2%
n 133853
 
4.0%
[ 132080
 
4.0%
Other values (88) 1076282
32.5%

locality
Text

Missing 

Distinct76621
Distinct (%)17.2%
Missing158363
Missing (%)26.2%
Memory size4.6 MiB
2025-02-10T13:48:25.589358image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length550043
Median length182
Mean length24.13015367
Min length1

Characters and Unicode

Total characters10770663
Distinct characters148
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44463 ?
Unique (%)10.0%

Sample

1st row[Not Stated]
2nd rowRio Aquiares, Turrialba
3rd rowSaint Paul Island, Bering Sea
4th rowFalse Cape State Park, Wash Woods, 100 meters east of Interpreter's residence
5th row[Not Stated]
ValueCountFrequency (%)
not 66601
 
4.1%
stated 66524
 
4.1%
of 42103
 
2.6%
miles 21225
 
1.3%
kilometers 15789
 
1.0%
park 15479
 
1.0%
river 15374
 
1.0%
lake 14864
 
0.9%
near 12865
 
0.8%
creek 12692
 
0.8%
Other values (59148) 1327951
82.4%
2025-02-10T13:48:25.835756image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1113923
 
10.3%
a 970976
 
9.0%
e 784777
 
7.3%
o 677654
 
6.3%
t 644226
 
6.0%
n 525770
 
4.9%
i 505577
 
4.7%
r 496321
 
4.6%
l 397845
 
3.7%
s 367559
 
3.4%
Other values (138) 4286035
39.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10770663
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1113923
 
10.3%
a 970976
 
9.0%
e 784777
 
7.3%
o 677654
 
6.3%
t 644226
 
6.0%
n 525770
 
4.9%
i 505577
 
4.7%
r 496321
 
4.6%
l 397845
 
3.7%
s 367559
 
3.4%
Other values (138) 4286035
39.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10770663
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1113923
 
10.3%
a 970976
 
9.0%
e 784777
 
7.3%
o 677654
 
6.3%
t 644226
 
6.0%
n 525770
 
4.9%
i 505577
 
4.7%
r 496321
 
4.6%
l 397845
 
3.7%
s 367559
 
3.4%
Other values (138) 4286035
39.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10770663
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1113923
 
10.3%
a 970976
 
9.0%
e 784777
 
7.3%
o 677654
 
6.3%
t 644226
 
6.0%
n 525770
 
4.9%
i 505577
 
4.7%
r 496321
 
4.6%
l 397845
 
3.7%
s 367559
 
3.4%
Other values (138) 4286035
39.8%
Distinct1812
Distinct (%)3.9%
Missing558058
Missing (%)92.3%
Memory size4.6 MiB
2025-02-10T13:48:25.989644image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.369958424
Min length3

Characters and Unicode

Total characters250573
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique454 ?
Unique (%)1.0%

Sample

1st row2040.0
2nd row240.0
3rd row165.0
4th row400.0
5th row1300.0
ValueCountFrequency (%)
2743.0 1183
 
2.5%
3353.0 909
 
1.9%
1829.0 812
 
1.7%
610.0 652
 
1.4%
1524.0 627
 
1.3%
914.0 612
 
1.3%
427.0 567
 
1.2%
1100.0 562
 
1.2%
200.0 531
 
1.1%
1372.0 519
 
1.1%
Other values (1798) 39688
85.1%
2025-02-10T13:48:26.274782image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 75959
30.3%
. 46662
18.6%
1 25391
 
10.1%
2 21165
 
8.4%
3 15751
 
6.3%
5 14062
 
5.6%
4 13695
 
5.5%
7 11236
 
4.5%
9 9362
 
3.7%
6 9353
 
3.7%
Other values (2) 7937
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 250573
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 75959
30.3%
. 46662
18.6%
1 25391
 
10.1%
2 21165
 
8.4%
3 15751
 
6.3%
5 14062
 
5.6%
4 13695
 
5.5%
7 11236
 
4.5%
9 9362
 
3.7%
6 9353
 
3.7%
Other values (2) 7937
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 250573
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 75959
30.3%
. 46662
18.6%
1 25391
 
10.1%
2 21165
 
8.4%
3 15751
 
6.3%
5 14062
 
5.6%
4 13695
 
5.5%
7 11236
 
4.5%
9 9362
 
3.7%
6 9353
 
3.7%
Other values (2) 7937
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 250573
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 75959
30.3%
. 46662
18.6%
1 25391
 
10.1%
2 21165
 
8.4%
3 15751
 
6.3%
5 14062
 
5.6%
4 13695
 
5.5%
7 11236
 
4.5%
9 9362
 
3.7%
6 9353
 
3.7%
Other values (2) 7937
 
3.2%
Distinct1534
Distinct (%)4.9%
Missing573266
Missing (%)94.8%
Memory size4.6 MiB
2025-02-10T13:48:26.432473image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.472658485
Min length3

Characters and Unicode

Total characters172137
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)1.3%

Sample

1st row2040.0
2nd row240.0
3rd row165.0
4th row400.0
5th row1300.0
ValueCountFrequency (%)
3353.0 850
 
2.7%
2438.0 719
 
2.3%
1829.0 717
 
2.3%
1524.0 582
 
1.9%
2743.0 553
 
1.8%
427.0 467
 
1.5%
1200.0 465
 
1.5%
1372.0 453
 
1.4%
2134.0 424
 
1.3%
2499.0 416
 
1.3%
Other values (1523) 25808
82.0%
2025-02-10T13:48:26.652765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51748
30.1%
. 31454
18.3%
1 16786
 
9.8%
2 15345
 
8.9%
3 10880
 
6.3%
4 9719
 
5.6%
5 9555
 
5.6%
7 7998
 
4.6%
9 6255
 
3.6%
8 6241
 
3.6%
Other values (2) 6156
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 172137
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 51748
30.1%
. 31454
18.3%
1 16786
 
9.8%
2 15345
 
8.9%
3 10880
 
6.3%
4 9719
 
5.6%
5 9555
 
5.6%
7 7998
 
4.6%
9 6255
 
3.6%
8 6241
 
3.6%
Other values (2) 6156
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 172137
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 51748
30.1%
. 31454
18.3%
1 16786
 
9.8%
2 15345
 
8.9%
3 10880
 
6.3%
4 9719
 
5.6%
5 9555
 
5.6%
7 7998
 
4.6%
9 6255
 
3.6%
8 6241
 
3.6%
Other values (2) 6156
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 172137
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 51748
30.1%
. 31454
18.3%
1 16786
 
9.8%
2 15345
 
8.9%
3 10880
 
6.3%
4 9719
 
5.6%
5 9555
 
5.6%
7 7998
 
4.6%
9 6255
 
3.6%
8 6241
 
3.6%
Other values (2) 6156
 
3.6%

verbatimElevation
Text

Missing 

Distinct1024
Distinct (%)10.3%
Missing594785
Missing (%)98.4%
Memory size4.6 MiB
2025-02-10T13:48:26.809291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length94
Median length31
Mean length8.088173125
Min length1

Characters and Unicode

Total characters80356
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique334 ?
Unique (%)3.4%

Sample

1st row140 meters
2nd row3900 feet
3rd row5940 feet
4th row180 meters
5th row3000 feet
ValueCountFrequency (%)
m 2783
 
14.5%
feet 2472
 
12.9%
meters 1521
 
7.9%
ft 1465
 
7.6%
1000 347
 
1.8%
level 318
 
1.7%
sea 318
 
1.7%
300 305
 
1.6%
near 276
 
1.4%
3200 236
 
1.2%
Other values (619) 9193
47.8%
2025-02-10T13:48:27.018452image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16890
21.0%
e 9358
11.6%
9299
11.6%
t 5738
 
7.1%
m 5103
 
6.4%
f 4103
 
5.1%
1 4089
 
5.1%
5 3791
 
4.7%
2 2913
 
3.6%
. 2459
 
3.1%
Other values (44) 16613
20.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 80356
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 16890
21.0%
e 9358
11.6%
9299
11.6%
t 5738
 
7.1%
m 5103
 
6.4%
f 4103
 
5.1%
1 4089
 
5.1%
5 3791
 
4.7%
2 2913
 
3.6%
. 2459
 
3.1%
Other values (44) 16613
20.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 80356
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 16890
21.0%
e 9358
11.6%
9299
11.6%
t 5738
 
7.1%
m 5103
 
6.4%
f 4103
 
5.1%
1 4089
 
5.1%
5 3791
 
4.7%
2 2913
 
3.6%
. 2459
 
3.1%
Other values (44) 16613
20.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 80356
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 16890
21.0%
e 9358
11.6%
9299
11.6%
t 5738
 
7.1%
m 5103
 
6.4%
f 4103
 
5.1%
1 4089
 
5.1%
5 3791
 
4.7%
2 2913
 
3.6%
. 2459
 
3.1%
Other values (44) 16613
20.7%

minimumDepthInMeters
Text

Missing 

Distinct13
Distinct (%)37.1%
Missing604685
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:27.059305image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length5
Mean length5.114285714
Min length3

Characters and Unicode

Total characters179
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)20.0%

Sample

1st row0.0
2nd row250.0
3rd row0.0
4th rowArgia orichalcea
5th row370.0
ValueCountFrequency (%)
250.0 9
25.0%
0.0 6
16.7%
880.0 6
16.7%
370.0 3
 
8.3%
1707.0 2
 
5.6%
775.0 2
 
5.6%
argia 1
 
2.8%
orichalcea 1
 
2.8%
359.0 1
 
2.8%
1400.0 1
 
2.8%
Other values (4) 4
11.1%
2025-02-10T13:48:27.158360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 68
38.0%
. 34
19.0%
5 13
 
7.3%
7 13
 
7.3%
8 12
 
6.7%
2 9
 
5.0%
3 6
 
3.4%
1 4
 
2.2%
a 3
 
1.7%
4 2
 
1.1%
Other values (12) 15
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 179
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 68
38.0%
. 34
19.0%
5 13
 
7.3%
7 13
 
7.3%
8 12
 
6.7%
2 9
 
5.0%
3 6
 
3.4%
1 4
 
2.2%
a 3
 
1.7%
4 2
 
1.1%
Other values (12) 15
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 179
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 68
38.0%
. 34
19.0%
5 13
 
7.3%
7 13
 
7.3%
8 12
 
6.7%
2 9
 
5.0%
3 6
 
3.4%
1 4
 
2.2%
a 3
 
1.7%
4 2
 
1.1%
Other values (12) 15
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 179
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 68
38.0%
. 34
19.0%
5 13
 
7.3%
7 13
 
7.3%
8 12
 
6.7%
2 9
 
5.0%
3 6
 
3.4%
1 4
 
2.2%
a 3
 
1.7%
4 2
 
1.1%
Other values (12) 15
 
8.4%

maximumDepthInMeters
Text

Missing 

Distinct4
Distinct (%)36.4%
Missing604709
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:27.189824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.090909091
Min length5

Characters and Unicode

Total characters56
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st row220.0
2nd row220.0
3rd row370.0
4th row220.0
5th row1400.0
ValueCountFrequency (%)
220.0 6
54.5%
370.0 3
27.3%
1400.0 1
 
9.1%
500.0 1
 
9.1%
2025-02-10T13:48:27.276406image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

verbatimDepth
Text

Constant  Missing 

Distinct1
Distinct (%)16.7%
Missing604714
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:27.308360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters150
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row220m inside cave entrance
2nd row220m inside cave entrance
3rd row220m inside cave entrance
4th row220m inside cave entrance
5th row220m inside cave entrance
ValueCountFrequency (%)
220m 6
25.0%
inside 6
25.0%
cave 6
25.0%
entrance 6
25.0%
2025-02-10T13:48:27.390288image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 150
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 150
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 150
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

locationRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:27.422873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters19
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowGarrison, Rosser W.
ValueCountFrequency (%)
garrison 1
33.3%
rosser 1
33.3%
w 1
33.3%
2025-02-10T13:48:27.504001image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 3
15.8%
s 3
15.8%
o 2
10.5%
2
10.5%
G 1
 
5.3%
a 1
 
5.3%
i 1
 
5.3%
n 1
 
5.3%
, 1
 
5.3%
R 1
 
5.3%
Other values (3) 3
15.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 3
15.8%
s 3
15.8%
o 2
10.5%
2
10.5%
G 1
 
5.3%
a 1
 
5.3%
i 1
 
5.3%
n 1
 
5.3%
, 1
 
5.3%
R 1
 
5.3%
Other values (3) 3
15.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 3
15.8%
s 3
15.8%
o 2
10.5%
2
10.5%
G 1
 
5.3%
a 1
 
5.3%
i 1
 
5.3%
n 1
 
5.3%
, 1
 
5.3%
R 1
 
5.3%
Other values (3) 3
15.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 3
15.8%
s 3
15.8%
o 2
10.5%
2
10.5%
G 1
 
5.3%
a 1
 
5.3%
i 1
 
5.3%
n 1
 
5.3%
, 1
 
5.3%
R 1
 
5.3%
Other values (3) 3
15.8%

decimalLatitude
Text

Missing 

Distinct38000
Distinct (%)11.9%
Missing285696
Missing (%)47.2%
Memory size4.6 MiB
2025-02-10T13:48:27.660280image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length65
Median length7
Mean length6.690020187
Min length3

Characters and Unicode

Total characters2134277
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15792 ?
Unique (%)5.0%

Sample

1st row9.91378
2nd row57.18
3rd row36.5787
4th row15.5864
5th row45.4838
ValueCountFrequency (%)
39.6891 5053
 
1.6%
60.75 3840
 
1.2%
60.7493 2462
 
0.8%
40.0925 2379
 
0.7%
38.02 2014
 
0.6%
42.7299 1697
 
0.5%
37.23 1343
 
0.4%
40.015 1287
 
0.4%
42.78 1170
 
0.4%
38.9559 1141
 
0.4%
Other values (37318) 296643
93.0%
2025-02-10T13:48:27.885194image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 319023
14.9%
3 273800
12.8%
4 209113
9.8%
1 188958
8.9%
2 172350
8.1%
9 169602
7.9%
7 165610
7.8%
8 159004
7.5%
5 153218
7.2%
6 152394
7.1%
Other values (26) 171205
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2134277
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 319023
14.9%
3 273800
12.8%
4 209113
9.8%
1 188958
8.9%
2 172350
8.1%
9 169602
7.9%
7 165610
7.8%
8 159004
7.5%
5 153218
7.2%
6 152394
7.1%
Other values (26) 171205
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2134277
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 319023
14.9%
3 273800
12.8%
4 209113
9.8%
1 188958
8.9%
2 172350
8.1%
9 169602
7.9%
7 165610
7.8%
8 159004
7.5%
5 153218
7.2%
6 152394
7.1%
Other values (26) 171205
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2134277
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 319023
14.9%
3 273800
12.8%
4 209113
9.8%
1 188958
8.9%
2 172350
8.1%
9 169602
7.9%
7 165610
7.8%
8 159004
7.5%
5 153218
7.2%
6 152394
7.1%
Other values (26) 171205
8.0%

decimalLongitude
Text

Missing 

Distinct36959
Distinct (%)11.6%
Missing285696
Missing (%)47.2%
Memory size4.6 MiB
2025-02-10T13:48:28.047241image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.477506395
Min length3

Characters and Unicode

Total characters2385504
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15086 ?
Unique (%)4.7%

Sample

1st row-83.6744
2nd row-170.27
3rd row-75.8881
4th row-61.4739
5th row-75.9727
ValueCountFrequency (%)
105.644 5103
 
1.6%
139.5 3838
 
1.2%
139.504 2462
 
0.8%
105.358 2379
 
0.7%
87.8123 1697
 
0.5%
119.93 1404
 
0.4%
105.27 1361
 
0.4%
80.4178 1322
 
0.4%
0.365 1301
 
0.4%
87.76 1163
 
0.4%
Other values (36449) 296994
93.1%
2025-02-10T13:48:28.268697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 319023
13.4%
1 292933
12.3%
- 270766
11.4%
7 217532
9.1%
8 193895
8.1%
6 165418
6.9%
5 162723
6.8%
3 158480
6.6%
2 156818
6.6%
9 154493
6.5%
Other values (8) 293423
12.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2385504
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 319023
13.4%
1 292933
12.3%
- 270766
11.4%
7 217532
9.1%
8 193895
8.1%
6 165418
6.9%
5 162723
6.8%
3 158480
6.6%
2 156818
6.6%
9 154493
6.5%
Other values (8) 293423
12.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2385504
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 319023
13.4%
1 292933
12.3%
- 270766
11.4%
7 217532
9.1%
8 193895
8.1%
6 165418
6.9%
5 162723
6.8%
3 158480
6.6%
2 156818
6.6%
9 154493
6.5%
Other values (8) 293423
12.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2385504
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 319023
13.4%
1 292933
12.3%
- 270766
11.4%
7 217532
9.1%
8 193895
8.1%
6 165418
6.9%
5 162723
6.8%
3 158480
6.6%
2 156818
6.6%
9 154493
6.5%
Other values (8) 293423
12.3%

geodeticDatum
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing578337
Missing (%)95.6%
Memory size4.6 MiB
2025-02-10T13:48:28.306617image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length17.50456734
Min length5

Characters and Unicode

Total characters461823
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowWGS 84 (EPSG:4326)
2nd rowWGS 84 (EPSG:4326)
3rd rowWGS 84 (EPSG:4326)
4th rowWGS 84 (EPSG:4326)
5th rowWGS 84 (EPSG:4326)
ValueCountFrequency (%)
wgs 25014
32.6%
84 25014
32.6%
epsg:4326 25008
32.6%
wgs84 754
 
1.0%
nad83 399
 
0.5%
epsg:4269 399
 
0.5%
wgs40 214
 
0.3%
arthropoda 1
 
< 0.1%
1973-05-08 1
 
< 0.1%
2025-02-10T13:48:28.397662image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 51389
11.1%
S 51389
11.1%
4 51389
11.1%
50421
10.9%
8 26168
 
5.7%
W 25982
 
5.6%
3 25408
 
5.5%
( 25407
 
5.5%
E 25407
 
5.5%
P 25407
 
5.5%
Other values (20) 103456
22.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 461823
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 51389
11.1%
S 51389
11.1%
4 51389
11.1%
50421
10.9%
8 26168
 
5.7%
W 25982
 
5.6%
3 25408
 
5.5%
( 25407
 
5.5%
E 25407
 
5.5%
P 25407
 
5.5%
Other values (20) 103456
22.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 461823
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 51389
11.1%
S 51389
11.1%
4 51389
11.1%
50421
10.9%
8 26168
 
5.7%
W 25982
 
5.6%
3 25408
 
5.5%
( 25407
 
5.5%
E 25407
 
5.5%
P 25407
 
5.5%
Other values (20) 103456
22.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 461823
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 51389
11.1%
S 51389
11.1%
4 51389
11.1%
50421
10.9%
8 26168
 
5.7%
W 25982
 
5.6%
3 25408
 
5.5%
( 25407
 
5.5%
E 25407
 
5.5%
P 25407
 
5.5%
Other values (20) 103456
22.4%
Distinct1494
Distinct (%)12.5%
Missing592766
Missing (%)98.0%
Memory size4.6 MiB
2025-02-10T13:48:28.547375image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.138698344
Min length2

Characters and Unicode

Total characters49474
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique746 ?
Unique (%)6.2%

Sample

1st row931
2nd row10206
3rd row6642
4th row3036
5th row301
ValueCountFrequency (%)
3036 1744
 
14.6%
301 466
 
3.9%
34239 426
 
3.6%
1189 258
 
2.2%
20000 247
 
2.1%
3048 220
 
1.8%
15000 199
 
1.7%
52150 194
 
1.6%
14563 162
 
1.4%
9346 135
 
1.1%
Other values (1484) 7903
66.1%
2025-02-10T13:48:28.755633image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9238
18.7%
3 8252
16.7%
1 6353
12.8%
2 4894
9.9%
6 4647
9.4%
4 3910
7.9%
5 3501
 
7.1%
9 3065
 
6.2%
8 2862
 
5.8%
7 2745
 
5.5%
Other values (7) 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49474
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 9238
18.7%
3 8252
16.7%
1 6353
12.8%
2 4894
9.9%
6 4647
9.4%
4 3910
7.9%
5 3501
 
7.1%
9 3065
 
6.2%
8 2862
 
5.8%
7 2745
 
5.5%
Other values (7) 7
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49474
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 9238
18.7%
3 8252
16.7%
1 6353
12.8%
2 4894
9.9%
6 4647
9.4%
4 3910
7.9%
5 3501
 
7.1%
9 3065
 
6.2%
8 2862
 
5.8%
7 2745
 
5.5%
Other values (7) 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49474
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 9238
18.7%
3 8252
16.7%
1 6353
12.8%
2 4894
9.9%
6 4647
9.4%
4 3910
7.9%
5 3501
 
7.1%
9 3065
 
6.2%
8 2862
 
5.8%
7 2745
 
5.5%
Other values (7) 7
 
< 0.1%

coordinatePrecision
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing604717
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:28.792460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4
Min length2

Characters and Unicode

Total characters12
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowOdonata
2nd row69
3rd row128
ValueCountFrequency (%)
odonata 1
33.3%
69 1
33.3%
128 1
33.3%
2025-02-10T13:48:28.877502image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
16.7%
O 1
8.3%
d 1
8.3%
o 1
8.3%
n 1
8.3%
t 1
8.3%
6 1
8.3%
9 1
8.3%
1 1
8.3%
2 1
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2
16.7%
O 1
8.3%
d 1
8.3%
o 1
8.3%
n 1
8.3%
t 1
8.3%
6 1
8.3%
9 1
8.3%
1 1
8.3%
2 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2
16.7%
O 1
8.3%
d 1
8.3%
o 1
8.3%
n 1
8.3%
t 1
8.3%
6 1
8.3%
9 1
8.3%
1 1
8.3%
2 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2
16.7%
O 1
8.3%
d 1
8.3%
o 1
8.3%
n 1
8.3%
t 1
8.3%
6 1
8.3%
9 1
8.3%
1 1
8.3%
2 1
8.3%

pointRadiusSpatialFit
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing604718
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:28.908562image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row69
2nd row128
ValueCountFrequency (%)
69 1
50.0%
128 1
50.0%
2025-02-10T13:48:28.993428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
20.0%
9 1
20.0%
1 1
20.0%
2 1
20.0%
8 1
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
6 1
20.0%
9 1
20.0%
1 1
20.0%
2 1
20.0%
8 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
6 1
20.0%
9 1
20.0%
1 1
20.0%
2 1
20.0%
8 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
6 1
20.0%
9 1
20.0%
1 1
20.0%
2 1
20.0%
8 1
20.0%

verbatimCoordinates
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing604718
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:29.023915image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9
Min length4

Characters and Unicode

Total characters18
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowCoenagrionidae
2nd row1973
ValueCountFrequency (%)
coenagrionidae 1
50.0%
1973 1
50.0%
2025-02-10T13:48:29.108495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2
11.1%
e 2
11.1%
n 2
11.1%
a 2
11.1%
i 2
11.1%
C 1
 
5.6%
g 1
 
5.6%
r 1
 
5.6%
d 1
 
5.6%
1 1
 
5.6%
Other values (3) 3
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2
11.1%
e 2
11.1%
n 2
11.1%
a 2
11.1%
i 2
11.1%
C 1
 
5.6%
g 1
 
5.6%
r 1
 
5.6%
d 1
 
5.6%
1 1
 
5.6%
Other values (3) 3
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2
11.1%
e 2
11.1%
n 2
11.1%
a 2
11.1%
i 2
11.1%
C 1
 
5.6%
g 1
 
5.6%
r 1
 
5.6%
d 1
 
5.6%
1 1
 
5.6%
Other values (3) 3
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2
11.1%
e 2
11.1%
n 2
11.1%
a 2
11.1%
i 2
11.1%
C 1
 
5.6%
g 1
 
5.6%
r 1
 
5.6%
d 1
 
5.6%
1 1
 
5.6%
Other values (3) 3
16.7%

verbatimLatitude
Text

Missing 

Distinct10290
Distinct (%)12.6%
Missing523062
Missing (%)86.5%
Memory size4.6 MiB
2025-02-10T13:48:29.260855image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length9
Mean length8.943949154
Min length1

Characters and Unicode

Total characters730345
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3874 ?
Unique (%)4.7%

Sample

1st rowN36.578717
2nd row0 deg 50' 00" N
3rd row3 deg. 21.1' N
4th row10 32' S
5th row39.079276
ValueCountFrequency (%)
n 12202
 
10.3%
deg 3779
 
3.2%
s 3061
 
2.6%
40.014986 1227
 
1.0%
38.955944 1139
 
1.0%
39 889
 
0.7%
10 854
 
0.7%
12 805
 
0.7%
40.001652 790
 
0.7%
38 783
 
0.7%
Other values (9199) 93254
78.5%
2025-02-10T13:48:29.480003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 79859
10.9%
. 76634
10.5%
4 74529
10.2%
1 56463
 
7.7%
2 53355
 
7.3%
8 51998
 
7.1%
0 49153
 
6.7%
9 48559
 
6.6%
5 48310
 
6.6%
6 41823
 
5.7%
Other values (44) 149662
20.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 730345
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 79859
10.9%
. 76634
10.5%
4 74529
10.2%
1 56463
 
7.7%
2 53355
 
7.3%
8 51998
 
7.1%
0 49153
 
6.7%
9 48559
 
6.6%
5 48310
 
6.6%
6 41823
 
5.7%
Other values (44) 149662
20.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 730345
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 79859
10.9%
. 76634
10.5%
4 74529
10.2%
1 56463
 
7.7%
2 53355
 
7.3%
8 51998
 
7.1%
0 49153
 
6.7%
9 48559
 
6.6%
5 48310
 
6.6%
6 41823
 
5.7%
Other values (44) 149662
20.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 730345
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 79859
10.9%
. 76634
10.5%
4 74529
10.2%
1 56463
 
7.7%
2 53355
 
7.3%
8 51998
 
7.1%
0 49153
 
6.7%
9 48559
 
6.6%
5 48310
 
6.6%
6 41823
 
5.7%
Other values (44) 149662
20.5%

verbatimLongitude
Text

Missing 

Distinct10183
Distinct (%)12.5%
Missing523032
Missing (%)86.5%
Memory size4.6 MiB
2025-02-10T13:48:29.634790image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length28
Mean length9.817243659
Min length1

Characters and Unicode

Total characters801951
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3804 ?
Unique (%)4.7%

Sample

1st rowW75.88805
2nd row66 deg 09' 44" W
3rd row59 deg. 40.5' W
4th row62 48' W
5th row-76.59802
ValueCountFrequency (%)
w 13038
 
11.0%
deg 3758
 
3.2%
e 2358
 
2.0%
105.270546 1260
 
1.1%
76.94553 1139
 
1.0%
76 1012
 
0.9%
59 834
 
0.7%
105.307491 790
 
0.7%
70 782
 
0.7%
77.254426 778
 
0.7%
Other values (9264) 92725
78.3%
2025-02-10T13:48:29.858933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 78854
 
9.8%
. 76662
 
9.6%
1 65451
 
8.2%
8 61925
 
7.7%
0 59445
 
7.4%
5 56396
 
7.0%
6 55542
 
6.9%
- 52771
 
6.6%
2 48852
 
6.1%
3 48668
 
6.1%
Other values (44) 197385
24.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 801951
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7 78854
 
9.8%
. 76662
 
9.6%
1 65451
 
8.2%
8 61925
 
7.7%
0 59445
 
7.4%
5 56396
 
7.0%
6 55542
 
6.9%
- 52771
 
6.6%
2 48852
 
6.1%
3 48668
 
6.1%
Other values (44) 197385
24.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 801951
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7 78854
 
9.8%
. 76662
 
9.6%
1 65451
 
8.2%
8 61925
 
7.7%
0 59445
 
7.4%
5 56396
 
7.0%
6 55542
 
6.9%
- 52771
 
6.6%
2 48852
 
6.1%
3 48668
 
6.1%
Other values (44) 197385
24.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 801951
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7 78854
 
9.8%
. 76662
 
9.6%
1 65451
 
8.2%
8 61925
 
7.7%
0 59445
 
7.4%
5 56396
 
7.0%
6 55542
 
6.9%
- 52771
 
6.6%
2 48852
 
6.1%
3 48668
 
6.1%
Other values (44) 197385
24.6%
Distinct3
Distinct (%)100.0%
Missing604717
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:29.979295image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length8
Mean length12.66666667
Min length7

Characters and Unicode

Total characters38
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowDegrees Minutes Seconds
2nd row9 March
3rd row8.v.1973
ValueCountFrequency (%)
degrees 1
16.7%
minutes 1
16.7%
seconds 1
16.7%
9 1
16.7%
march 1
16.7%
8.v.1973 1
16.7%
2025-02-10T13:48:30.072390image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5
 
13.2%
s 3
 
7.9%
3
 
7.9%
c 2
 
5.3%
9 2
 
5.3%
r 2
 
5.3%
M 2
 
5.3%
n 2
 
5.3%
. 2
 
5.3%
7 1
 
2.6%
Other values (14) 14
36.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5
 
13.2%
s 3
 
7.9%
3
 
7.9%
c 2
 
5.3%
9 2
 
5.3%
r 2
 
5.3%
M 2
 
5.3%
n 2
 
5.3%
. 2
 
5.3%
7 1
 
2.6%
Other values (14) 14
36.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5
 
13.2%
s 3
 
7.9%
3
 
7.9%
c 2
 
5.3%
9 2
 
5.3%
r 2
 
5.3%
M 2
 
5.3%
n 2
 
5.3%
. 2
 
5.3%
7 1
 
2.6%
Other values (14) 14
36.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5
 
13.2%
s 3
 
7.9%
3
 
7.9%
c 2
 
5.3%
9 2
 
5.3%
r 2
 
5.3%
M 2
 
5.3%
n 2
 
5.3%
. 2
 
5.3%
7 1
 
2.6%
Other values (14) 14
36.8%

verbatimSRS
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:30.101550image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowArgia
ValueCountFrequency (%)
argia 1
100.0%
2025-02-10T13:48:30.182574image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1
20.0%
r 1
20.0%
g 1
20.0%
i 1
20.0%
a 1
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1
20.0%
r 1
20.0%
g 1
20.0%
i 1
20.0%
a 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1
20.0%
r 1
20.0%
g 1
20.0%
i 1
20.0%
a 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1
20.0%
r 1
20.0%
g 1
20.0%
i 1
20.0%
a 1
20.0%

footprintSpatialFit
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:30.212422image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowGynacantha membranalis
ValueCountFrequency (%)
gynacantha 1
50.0%
membranalis 1
50.0%
2025-02-10T13:48:30.295167image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5
22.7%
n 3
13.6%
m 2
 
9.1%
G 1
 
4.5%
y 1
 
4.5%
c 1
 
4.5%
t 1
 
4.5%
h 1
 
4.5%
1
 
4.5%
e 1
 
4.5%
Other values (5) 5
22.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5
22.7%
n 3
13.6%
m 2
 
9.1%
G 1
 
4.5%
y 1
 
4.5%
c 1
 
4.5%
t 1
 
4.5%
h 1
 
4.5%
1
 
4.5%
e 1
 
4.5%
Other values (5) 5
22.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5
22.7%
n 3
13.6%
m 2
 
9.1%
G 1
 
4.5%
y 1
 
4.5%
c 1
 
4.5%
t 1
 
4.5%
h 1
 
4.5%
1
 
4.5%
e 1
 
4.5%
Other values (5) 5
22.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5
22.7%
n 3
13.6%
m 2
 
9.1%
G 1
 
4.5%
y 1
 
4.5%
c 1
 
4.5%
t 1
 
4.5%
h 1
 
4.5%
1
 
4.5%
e 1
 
4.5%
Other values (5) 5
22.7%

georeferencedBy
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:30.324443image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st roworichalcea
ValueCountFrequency (%)
orichalcea 1
100.0%
2025-02-10T13:48:30.405589image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 2
20.0%
a 2
20.0%
o 1
10.0%
r 1
10.0%
i 1
10.0%
h 1
10.0%
l 1
10.0%
e 1
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 2
20.0%
a 2
20.0%
o 1
10.0%
r 1
10.0%
i 1
10.0%
h 1
10.0%
l 1
10.0%
e 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 2
20.0%
a 2
20.0%
o 1
10.0%
r 1
10.0%
i 1
10.0%
h 1
10.0%
l 1
10.0%
e 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 2
20.0%
a 2
20.0%
o 1
10.0%
r 1
10.0%
i 1
10.0%
h 1
10.0%
l 1
10.0%
e 1
10.0%

georeferenceProtocol
Text

Missing 

Distinct64
Distinct (%)< 0.1%
Missing366819
Missing (%)60.7%
Memory size4.6 MiB
2025-02-10T13:48:30.438534image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length72
Median length12
Mean length10.94749497
Min length3

Characters and Unicode

Total characters2604420
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)< 0.1%

Sample

1st rowGoogle Maps
2nd rowGoogle Earth
3rd rowGoogle Earth
4th rowGEOLocate
5th rowGoogle Earth
ValueCountFrequency (%)
google 163403
40.4%
earth 120779
29.8%
geolocate 70758
17.5%
maps 42650
 
10.5%
gps 1516
 
0.4%
coordinates 782
 
0.2%
centroid 781
 
0.2%
geonames 719
 
0.2%
from 711
 
0.2%
country 671
 
0.2%
Other values (105) 2061
 
0.5%
2025-02-10T13:48:30.540558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 402623
15.5%
e 238641
9.2%
a 237508
9.1%
G 236572
9.1%
t 194824
7.5%
E 191441
7.4%
l 169506
 
6.5%
166930
 
6.4%
g 163835
 
6.3%
r 124382
 
4.8%
Other values (51) 478158
18.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2604420
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 402623
15.5%
e 238641
9.2%
a 237508
9.1%
G 236572
9.1%
t 194824
7.5%
E 191441
7.4%
l 169506
 
6.5%
166930
 
6.4%
g 163835
 
6.3%
r 124382
 
4.8%
Other values (51) 478158
18.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2604420
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 402623
15.5%
e 238641
9.2%
a 237508
9.1%
G 236572
9.1%
t 194824
7.5%
E 191441
7.4%
l 169506
 
6.5%
166930
 
6.4%
g 163835
 
6.3%
r 124382
 
4.8%
Other values (51) 478158
18.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2604420
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 402623
15.5%
e 238641
9.2%
a 237508
9.1%
G 236572
9.1%
t 194824
7.5%
E 191441
7.4%
l 169506
 
6.5%
166930
 
6.4%
g 163835
 
6.3%
r 124382
 
4.8%
Other values (51) 478158
18.4%

georeferenceRemarks
Text

Missing 

Distinct1134
Distinct (%)13.4%
Missing596270
Missing (%)98.6%
Memory size4.6 MiB
2025-02-10T13:48:30.694036image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length200
Median length182
Mean length45.17183432
Min length10

Characters and Unicode

Total characters381702
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique400 ?
Unique (%)4.7%

Sample

1st rowCoordinate Uncertainty In Meters: 56182
2nd rowCoordinate Uncertainty In Meters: 49611
3rd rowCoordinate Uncertainty In Meters: 97700
4th rowCoordinate Uncertainty In Meters: 41787
5th rowCoordinate Uncertainty In Meters: 71236
ValueCountFrequency (%)
in 8280
17.4%
coordinate 8141
17.1%
meters 8141
17.1%
uncertainty 8141
17.1%
verbatim 1307
 
2.7%
coordinate-degrees 1307
 
2.7%
minutes 1307
 
2.7%
3792 274
 
0.6%
the 221
 
0.5%
6066 174
 
0.4%
Other values (1273) 10425
21.8%
2025-02-10T13:48:30.917741image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 42275
 
11.1%
39268
 
10.3%
t 37520
 
9.8%
n 36171
 
9.5%
r 29384
 
7.7%
i 21348
 
5.6%
o 20139
 
5.3%
a 19993
 
5.2%
s 11760
 
3.1%
d 9751
 
2.6%
Other values (59) 114093
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 381702
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 42275
 
11.1%
39268
 
10.3%
t 37520
 
9.8%
n 36171
 
9.5%
r 29384
 
7.7%
i 21348
 
5.6%
o 20139
 
5.3%
a 19993
 
5.2%
s 11760
 
3.1%
d 9751
 
2.6%
Other values (59) 114093
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 381702
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 42275
 
11.1%
39268
 
10.3%
t 37520
 
9.8%
n 36171
 
9.5%
r 29384
 
7.7%
i 21348
 
5.6%
o 20139
 
5.3%
a 19993
 
5.2%
s 11760
 
3.1%
d 9751
 
2.6%
Other values (59) 114093
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 381702
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 42275
 
11.1%
39268
 
10.3%
t 37520
 
9.8%
n 36171
 
9.5%
r 29384
 
7.7%
i 21348
 
5.6%
o 20139
 
5.3%
a 19993
 
5.2%
s 11760
 
3.1%
d 9751
 
2.6%
Other values (59) 114093
29.9%

geologicalContextID
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing604716
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:30.958680image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length17
Mean length17.5
Min length4

Characters and Unicode

Total characters70
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowHagen in Selys
2nd rowBrazil, [Not Stated]
3rd rowUnited States, Florida, Pinellas
4th rowPeru
ValueCountFrequency (%)
hagen 1
9.1%
in 1
9.1%
selys 1
9.1%
brazil 1
9.1%
not 1
9.1%
stated 1
9.1%
united 1
9.1%
states 1
9.1%
florida 1
9.1%
pinellas 1
9.1%
2025-02-10T13:48:31.049494image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
10.0%
e 7
 
10.0%
t 6
 
8.6%
a 6
 
8.6%
i 5
 
7.1%
l 5
 
7.1%
n 4
 
5.7%
S 3
 
4.3%
s 3
 
4.3%
, 3
 
4.3%
Other values (15) 21
30.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7
 
10.0%
e 7
 
10.0%
t 6
 
8.6%
a 6
 
8.6%
i 5
 
7.1%
l 5
 
7.1%
n 4
 
5.7%
S 3
 
4.3%
s 3
 
4.3%
, 3
 
4.3%
Other values (15) 21
30.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7
 
10.0%
e 7
 
10.0%
t 6
 
8.6%
a 6
 
8.6%
i 5
 
7.1%
l 5
 
7.1%
n 4
 
5.7%
S 3
 
4.3%
s 3
 
4.3%
, 3
 
4.3%
Other values (15) 21
30.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7
 
10.0%
e 7
 
10.0%
t 6
 
8.6%
a 6
 
8.6%
i 5
 
7.1%
l 5
 
7.1%
n 4
 
5.7%
S 3
 
4.3%
s 3
 
4.3%
, 3
 
4.3%
Other values (15) 21
30.0%

earliestEonOrLowestEonothem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.084109image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length61
Median length61
Mean length61
Min length61

Characters and Unicode

Total characters61
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAnimalia, Arthropoda, Insecta, Odonata, Anisoptera, Aeshnidae
ValueCountFrequency (%)
animalia 1
16.7%
arthropoda 1
16.7%
insecta 1
16.7%
odonata 1
16.7%
anisoptera 1
16.7%
aeshnidae 1
16.7%
2025-02-10T13:48:31.167817image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8
13.1%
5
 
8.2%
n 5
 
8.2%
, 5
 
8.2%
A 4
 
6.6%
e 4
 
6.6%
o 4
 
6.6%
t 4
 
6.6%
i 4
 
6.6%
r 3
 
4.9%
Other values (9) 15
24.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 61
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 8
13.1%
5
 
8.2%
n 5
 
8.2%
, 5
 
8.2%
A 4
 
6.6%
e 4
 
6.6%
o 4
 
6.6%
t 4
 
6.6%
i 4
 
6.6%
r 3
 
4.9%
Other values (9) 15
24.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 61
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 8
13.1%
5
 
8.2%
n 5
 
8.2%
, 5
 
8.2%
A 4
 
6.6%
e 4
 
6.6%
o 4
 
6.6%
t 4
 
6.6%
i 4
 
6.6%
r 3
 
4.9%
Other values (9) 15
24.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 61
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 8
13.1%
5
 
8.2%
n 5
 
8.2%
, 5
 
8.2%
A 4
 
6.6%
e 4
 
6.6%
o 4
 
6.6%
t 4
 
6.6%
i 4
 
6.6%
r 3
 
4.9%
Other values (9) 15
24.6%

latestEonOrHighestEonothem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.200114image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAnimalia
ValueCountFrequency (%)
animalia 1
100.0%
2025-02-10T13:48:31.285385image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2
25.0%
a 2
25.0%
A 1
12.5%
n 1
12.5%
m 1
12.5%
l 1
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 2
25.0%
a 2
25.0%
A 1
12.5%
n 1
12.5%
m 1
12.5%
l 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 2
25.0%
a 2
25.0%
A 1
12.5%
n 1
12.5%
m 1
12.5%
l 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 2
25.0%
a 2
25.0%
A 1
12.5%
n 1
12.5%
m 1
12.5%
l 1
12.5%

earliestEraOrLowestErathem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.314089image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowArthropoda
ValueCountFrequency (%)
arthropoda 1
100.0%
2025-02-10T13:48:31.394596image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 2
20.0%
o 2
20.0%
A 1
10.0%
t 1
10.0%
h 1
10.0%
p 1
10.0%
d 1
10.0%
a 1
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 2
20.0%
o 2
20.0%
A 1
10.0%
t 1
10.0%
h 1
10.0%
p 1
10.0%
d 1
10.0%
a 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 2
20.0%
o 2
20.0%
A 1
10.0%
t 1
10.0%
h 1
10.0%
p 1
10.0%
d 1
10.0%
a 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 2
20.0%
o 2
20.0%
A 1
10.0%
t 1
10.0%
h 1
10.0%
p 1
10.0%
d 1
10.0%
a 1
10.0%

latestEraOrHighestErathem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.423918image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowInsecta
ValueCountFrequency (%)
insecta 1
100.0%
2025-02-10T13:48:31.506183image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 1
14.3%
n 1
14.3%
s 1
14.3%
e 1
14.3%
c 1
14.3%
t 1
14.3%
a 1
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
I 1
14.3%
n 1
14.3%
s 1
14.3%
e 1
14.3%
c 1
14.3%
t 1
14.3%
a 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
I 1
14.3%
n 1
14.3%
s 1
14.3%
e 1
14.3%
c 1
14.3%
t 1
14.3%
a 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
I 1
14.3%
n 1
14.3%
s 1
14.3%
e 1
14.3%
c 1
14.3%
t 1
14.3%
a 1
14.3%
Distinct4
Distinct (%)100.0%
Missing604716
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.538434image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length6.5
Mean length7.5
Min length4

Characters and Unicode

Total characters30
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowBrazil
2nd rowUnited States
3rd rowOdonata
4th rowPeru
ValueCountFrequency (%)
brazil 1
20.0%
united 1
20.0%
states 1
20.0%
odonata 1
20.0%
peru 1
20.0%
2025-02-10T13:48:31.624266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
13.3%
t 4
13.3%
e 3
 
10.0%
i 2
 
6.7%
n 2
 
6.7%
r 2
 
6.7%
d 2
 
6.7%
S 1
 
3.3%
P 1
 
3.3%
o 1
 
3.3%
Other values (8) 8
26.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4
13.3%
t 4
13.3%
e 3
 
10.0%
i 2
 
6.7%
n 2
 
6.7%
r 2
 
6.7%
d 2
 
6.7%
S 1
 
3.3%
P 1
 
3.3%
o 1
 
3.3%
Other values (8) 8
26.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4
13.3%
t 4
13.3%
e 3
 
10.0%
i 2
 
6.7%
n 2
 
6.7%
r 2
 
6.7%
d 2
 
6.7%
S 1
 
3.3%
P 1
 
3.3%
o 1
 
3.3%
Other values (8) 8
26.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4
13.3%
t 4
13.3%
e 3
 
10.0%
i 2
 
6.7%
n 2
 
6.7%
r 2
 
6.7%
d 2
 
6.7%
S 1
 
3.3%
P 1
 
3.3%
o 1
 
3.3%
Other values (8) 8
26.7%
Distinct3
Distinct (%)100.0%
Missing604717
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.657659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.333333333
Min length7

Characters and Unicode

Total characters28
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row[Not Stated]
2nd rowFlorida
3rd rowAeshnidae
ValueCountFrequency (%)
not 1
25.0%
stated 1
25.0%
florida 1
25.0%
aeshnidae 1
25.0%
2025-02-10T13:48:31.746364image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 3
 
10.7%
a 3
 
10.7%
e 3
 
10.7%
d 3
 
10.7%
o 2
 
7.1%
i 2
 
7.1%
[ 1
 
3.6%
r 1
 
3.6%
h 1
 
3.6%
s 1
 
3.6%
Other values (8) 8
28.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 3
 
10.7%
a 3
 
10.7%
e 3
 
10.7%
d 3
 
10.7%
o 2
 
7.1%
i 2
 
7.1%
[ 1
 
3.6%
r 1
 
3.6%
h 1
 
3.6%
s 1
 
3.6%
Other values (8) 8
28.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 3
 
10.7%
a 3
 
10.7%
e 3
 
10.7%
d 3
 
10.7%
o 2
 
7.1%
i 2
 
7.1%
[ 1
 
3.6%
r 1
 
3.6%
h 1
 
3.6%
s 1
 
3.6%
Other values (8) 8
28.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 3
 
10.7%
a 3
 
10.7%
e 3
 
10.7%
d 3
 
10.7%
o 2
 
7.1%
i 2
 
7.1%
[ 1
 
3.6%
r 1
 
3.6%
h 1
 
3.6%
s 1
 
3.6%
Other values (8) 8
28.6%

latestEpochOrHighestSeries
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.775512image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPinellas
ValueCountFrequency (%)
pinellas 1
100.0%
2025-02-10T13:48:31.857884image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2
25.0%
P 1
12.5%
i 1
12.5%
n 1
12.5%
e 1
12.5%
a 1
12.5%
s 1
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 2
25.0%
P 1
12.5%
i 1
12.5%
n 1
12.5%
e 1
12.5%
a 1
12.5%
s 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 2
25.0%
P 1
12.5%
i 1
12.5%
n 1
12.5%
e 1
12.5%
a 1
12.5%
s 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 2
25.0%
P 1
12.5%
i 1
12.5%
n 1
12.5%
e 1
12.5%
a 1
12.5%
s 1
12.5%
Distinct3
Distinct (%)100.0%
Missing604717
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:31.895000image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length14
Mean length19
Min length12

Characters and Unicode

Total characters57
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row[Not Stated]
2nd rowSt. Petersburg
3rd rowHuaru Valley, 90 mi. N. of Lima
ValueCountFrequency (%)
not 1
9.1%
stated 1
9.1%
st 1
9.1%
petersburg 1
9.1%
huaru 1
9.1%
valley 1
9.1%
90 1
9.1%
mi 1
9.1%
n 1
9.1%
of 1
9.1%
2025-02-10T13:48:31.989810image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
14.0%
t 5
 
8.8%
a 4
 
7.0%
e 4
 
7.0%
u 3
 
5.3%
. 3
 
5.3%
r 3
 
5.3%
i 2
 
3.5%
o 2
 
3.5%
S 2
 
3.5%
Other values (18) 21
36.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 57
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8
 
14.0%
t 5
 
8.8%
a 4
 
7.0%
e 4
 
7.0%
u 3
 
5.3%
. 3
 
5.3%
r 3
 
5.3%
i 2
 
3.5%
o 2
 
3.5%
S 2
 
3.5%
Other values (18) 21
36.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 57
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8
 
14.0%
t 5
 
8.8%
a 4
 
7.0%
e 4
 
7.0%
u 3
 
5.3%
. 3
 
5.3%
r 3
 
5.3%
i 2
 
3.5%
o 2
 
3.5%
S 2
 
3.5%
Other values (18) 21
36.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 57
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8
 
14.0%
t 5
 
8.8%
a 4
 
7.0%
e 4
 
7.0%
u 3
 
5.3%
. 3
 
5.3%
r 3
 
5.3%
i 2
 
3.5%
o 2
 
3.5%
S 2
 
3.5%
Other values (18) 21
36.8%

lowestBiostratigraphicZone
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:32.021260image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowGynacantha
ValueCountFrequency (%)
gynacantha 1
100.0%
2025-02-10T13:48:32.102759image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3
30.0%
n 2
20.0%
G 1
 
10.0%
y 1
 
10.0%
c 1
 
10.0%
t 1
 
10.0%
h 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3
30.0%
n 2
20.0%
G 1
 
10.0%
y 1
 
10.0%
c 1
 
10.0%
t 1
 
10.0%
h 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3
30.0%
n 2
20.0%
G 1
 
10.0%
y 1
 
10.0%
c 1
 
10.0%
t 1
 
10.0%
h 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3
30.0%
n 2
20.0%
G 1
 
10.0%
y 1
 
10.0%
c 1
 
10.0%
t 1
 
10.0%
h 1
 
10.0%

formation
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:32.132991image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowmembranalis
ValueCountFrequency (%)
membranalis 1
100.0%
2025-02-10T13:48:32.214003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 2
18.2%
a 2
18.2%
e 1
9.1%
b 1
9.1%
r 1
9.1%
n 1
9.1%
l 1
9.1%
i 1
9.1%
s 1
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
m 2
18.2%
a 2
18.2%
e 1
9.1%
b 1
9.1%
r 1
9.1%
n 1
9.1%
l 1
9.1%
i 1
9.1%
s 1
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
m 2
18.2%
a 2
18.2%
e 1
9.1%
b 1
9.1%
r 1
9.1%
n 1
9.1%
l 1
9.1%
i 1
9.1%
s 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
m 2
18.2%
a 2
18.2%
e 1
9.1%
b 1
9.1%
r 1
9.1%
n 1
9.1%
l 1
9.1%
i 1
9.1%
s 1
9.1%
Distinct16
Distinct (%)1.1%
Missing603282
Missing (%)99.8%
Memory size4.6 MiB
2025-02-10T13:48:32.246118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length9
Mean length5.812934631
Min length2

Characters and Unicode

Total characters8359
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st rownear
2nd rowuncertain
3rd rownear
4th rownear
5th rowcf.
ValueCountFrequency (%)
near 466
31.6%
uncertain 459
31.1%
cf 238
16.1%
group 113
 
7.7%
subgroup 80
 
5.4%
complex 26
 
1.8%
aff 21
 
1.4%
sp 21
 
1.4%
n 15
 
1.0%
sensu 11
 
0.7%
Other values (6) 24
 
1.6%
2025-02-10T13:48:32.418503image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1418
17.0%
r 1132
13.5%
e 962
11.5%
a 948
11.3%
u 743
8.9%
c 733
8.8%
t 481
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (14) 951
11.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8359
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1418
17.0%
r 1132
13.5%
e 962
11.5%
a 948
11.3%
u 743
8.9%
c 733
8.8%
t 481
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (14) 951
11.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8359
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1418
17.0%
r 1132
13.5%
e 962
11.5%
a 948
11.3%
u 743
8.9%
c 733
8.8%
t 481
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (14) 951
11.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8359
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1418
17.0%
r 1132
13.5%
e 962
11.5%
a 948
11.3%
u 743
8.9%
c 733
8.8%
t 481
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (14) 951
11.4%

typeStatus
Text

Missing 

Distinct62
Distinct (%)0.1%
Missing486142
Missing (%)80.4%
Memory size4.6 MiB
2025-02-10T13:48:32.451730image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length8
Mean length7.058653376
Min length1

Characters and Unicode

Total characters837001
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)< 0.1%

Sample

1st rowParatype
2nd rowType
3rd rowHolotype
4th rowType
5th rowPrimary Syntype
ValueCountFrequency (%)
holotype 54132
44.3%
type 32982
27.0%
syntype 13149
 
10.8%
paratype 11029
 
9.0%
lectotype 5242
 
4.3%
primary 3223
 
2.6%
allotype 1092
 
0.9%
syntypes 429
 
0.4%
neotype 316
 
0.3%
cotype 298
 
0.2%
Other values (14) 175
 
0.1%
2025-02-10T13:48:32.551320image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y 135631
16.2%
e 124524
14.9%
p 118840
14.2%
o 115382
13.8%
t 91216
10.9%
l 56450
6.7%
H 54135
 
6.5%
T 32989
 
3.9%
a 25558
 
3.1%
r 17612
 
2.1%
Other values (16) 64664
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 837001
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
y 135631
16.2%
e 124524
14.9%
p 118840
14.2%
o 115382
13.8%
t 91216
10.9%
l 56450
6.7%
H 54135
 
6.5%
T 32989
 
3.9%
a 25558
 
3.1%
r 17612
 
2.1%
Other values (16) 64664
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 837001
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
y 135631
16.2%
e 124524
14.9%
p 118840
14.2%
o 115382
13.8%
t 91216
10.9%
l 56450
6.7%
H 54135
 
6.5%
T 32989
 
3.9%
a 25558
 
3.1%
r 17612
 
2.1%
Other values (16) 64664
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 837001
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
y 135631
16.2%
e 124524
14.9%
p 118840
14.2%
o 115382
13.8%
t 91216
10.9%
l 56450
6.7%
H 54135
 
6.5%
T 32989
 
3.9%
a 25558
 
3.1%
r 17612
 
2.1%
Other values (16) 64664
7.7%

identifiedBy
Text

Missing 

Distinct2736
Distinct (%)1.8%
Missing455024
Missing (%)75.2%
Memory size4.6 MiB
2025-02-10T13:48:32.703741image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length150
Median length106
Mean length27.7928268
Min length2

Characters and Unicode

Total characters4160475
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique933 ?
Unique (%)0.6%

Sample

1st rowWestfall, M. J., Jr.
2nd rowDonnelly, Thomas W.
3rd rowFlint, Oliver S., Jr., (ENT), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
4th rowKormann, K.
5th rowDeMarmels
ValueCountFrequency (%)
w 28134
 
4.4%
united 24412
 
3.8%
states 24411
 
3.8%
22738
 
3.5%
of 22001
 
3.4%
s 21919
 
3.4%
smithsonian 21911
 
3.4%
institution 21911
 
3.4%
museum 21368
 
3.3%
natural 21090
 
3.3%
Other values (2399) 413103
64.2%
2025-02-10T13:48:32.943678image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
493302
 
11.9%
i 251011
 
6.0%
o 231967
 
5.6%
t 230937
 
5.6%
n 230507
 
5.5%
a 200387
 
4.8%
, 193571
 
4.7%
r 182856
 
4.4%
. 170385
 
4.1%
s 166946
 
4.0%
Other values (61) 1808606
43.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4160475
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
493302
 
11.9%
i 251011
 
6.0%
o 231967
 
5.6%
t 230937
 
5.6%
n 230507
 
5.5%
a 200387
 
4.8%
, 193571
 
4.7%
r 182856
 
4.4%
. 170385
 
4.1%
s 166946
 
4.0%
Other values (61) 1808606
43.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4160475
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
493302
 
11.9%
i 251011
 
6.0%
o 231967
 
5.6%
t 230937
 
5.6%
n 230507
 
5.5%
a 200387
 
4.8%
, 193571
 
4.7%
r 182856
 
4.4%
. 170385
 
4.1%
s 166946
 
4.0%
Other values (61) 1808606
43.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4160475
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
493302
 
11.9%
i 251011
 
6.0%
o 231967
 
5.6%
t 230937
 
5.6%
n 230507
 
5.5%
a 200387
 
4.8%
, 193571
 
4.7%
r 182856
 
4.4%
. 170385
 
4.1%
s 166946
 
4.0%
Other values (61) 1808606
43.5%

identifiedByID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing604718
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:32.979931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7.5
Mean length7.5
Min length7

Characters and Unicode

Total characters15
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row27.7731
2nd row-4.55006
ValueCountFrequency (%)
27.7731 1
50.0%
4.55006 1
50.0%
2025-02-10T13:48:33.065557image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3
20.0%
. 2
13.3%
5 2
13.3%
0 2
13.3%
2 1
 
6.7%
3 1
 
6.7%
1 1
 
6.7%
- 1
 
6.7%
4 1
 
6.7%
6 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7 3
20.0%
. 2
13.3%
5 2
13.3%
0 2
13.3%
2 1
 
6.7%
3 1
 
6.7%
1 1
 
6.7%
- 1
 
6.7%
4 1
 
6.7%
6 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7 3
20.0%
. 2
13.3%
5 2
13.3%
0 2
13.3%
2 1
 
6.7%
3 1
 
6.7%
1 1
 
6.7%
- 1
 
6.7%
4 1
 
6.7%
6 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7 3
20.0%
. 2
13.3%
5 2
13.3%
0 2
13.3%
2 1
 
6.7%
3 1
 
6.7%
1 1
 
6.7%
- 1
 
6.7%
4 1
 
6.7%
6 1
 
6.7%

dateIdentified
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing604718
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:33.095392image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7
Min length6

Characters and Unicode

Total characters14
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row-82.64
2nd row-76.1874
ValueCountFrequency (%)
82.64 1
50.0%
76.1874 1
50.0%
2025-02-10T13:48:33.188634image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2
14.3%
8 2
14.3%
. 2
14.3%
6 2
14.3%
4 2
14.3%
7 2
14.3%
2 1
7.1%
1 1
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 2
14.3%
8 2
14.3%
. 2
14.3%
6 2
14.3%
4 2
14.3%
7 2
14.3%
2 1
7.1%
1 1
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 2
14.3%
8 2
14.3%
. 2
14.3%
6 2
14.3%
4 2
14.3%
7 2
14.3%
2 1
7.1%
1 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 2
14.3%
8 2
14.3%
. 2
14.3%
6 2
14.3%
4 2
14.3%
7 2
14.3%
2 1
7.1%
1 1
7.1%

identificationReferences
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:33.221507image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowWGS 84 (EPSG:4326)
ValueCountFrequency (%)
wgs 1
33.3%
84 1
33.3%
epsg:4326 1
33.3%
2025-02-10T13:48:33.306151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 2
11.1%
S 2
11.1%
2
11.1%
4 2
11.1%
W 1
 
5.6%
8 1
 
5.6%
( 1
 
5.6%
E 1
 
5.6%
P 1
 
5.6%
: 1
 
5.6%
Other values (4) 4
22.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 2
11.1%
S 2
11.1%
2
11.1%
4 2
11.1%
W 1
 
5.6%
8 1
 
5.6%
( 1
 
5.6%
E 1
 
5.6%
P 1
 
5.6%
: 1
 
5.6%
Other values (4) 4
22.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 2
11.1%
S 2
11.1%
2
11.1%
4 2
11.1%
W 1
 
5.6%
8 1
 
5.6%
( 1
 
5.6%
E 1
 
5.6%
P 1
 
5.6%
: 1
 
5.6%
Other values (4) 4
22.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 2
11.1%
S 2
11.1%
2
11.1%
4 2
11.1%
W 1
 
5.6%
8 1
 
5.6%
( 1
 
5.6%
E 1
 
5.6%
P 1
 
5.6%
: 1
 
5.6%
Other values (4) 4
22.2%
Distinct245072
Distinct (%)40.8%
Missing4631
Missing (%)0.8%
Memory size4.6 MiB
2025-02-10T13:48:33.389667image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length68
Median length61
Mean length20.77041739
Min length3

Characters and Unicode

Total characters12464099
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201386 ?
Unique (%)33.6%

Sample

1st rowCamponotus (Myrmosericus) rufoglaucus cinctella var. rufigenis
2nd rowAthrips mesoleuca
3rd rowParanthrene asilipennis
4th rowAcanthagrion trilobatum
5th rowCalathus nanulus
ValueCountFrequency (%)
bombus 69597
 
5.3%
sp 44400
 
3.4%
pyrobombus 21249
 
1.6%
xylocopa 12224
 
0.9%
unidentified 9030
 
0.7%
argia 8665
 
0.7%
apis 8603
 
0.6%
enallagma 7977
 
0.6%
crambus 7970
 
0.6%
ischnura 7458
 
0.6%
Other values (130820) 1127419
85.1%
2025-02-10T13:48:33.548747image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1254120
 
10.1%
i 1043361
 
8.4%
s 971373
 
7.8%
o 842893
 
6.8%
e 820899
 
6.6%
724503
 
5.8%
r 712805
 
5.7%
l 623128
 
5.0%
u 614998
 
4.9%
n 589887
 
4.7%
Other values (71) 4266132
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12464099
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1254120
 
10.1%
i 1043361
 
8.4%
s 971373
 
7.8%
o 842893
 
6.8%
e 820899
 
6.6%
724503
 
5.8%
r 712805
 
5.7%
l 623128
 
5.0%
u 614998
 
4.9%
n 589887
 
4.7%
Other values (71) 4266132
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12464099
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1254120
 
10.1%
i 1043361
 
8.4%
s 971373
 
7.8%
o 842893
 
6.8%
e 820899
 
6.6%
724503
 
5.8%
r 712805
 
5.7%
l 623128
 
5.0%
u 614998
 
4.9%
n 589887
 
4.7%
Other values (71) 4266132
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12464099
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1254120
 
10.1%
i 1043361
 
8.4%
s 971373
 
7.8%
o 842893
 
6.8%
e 820899
 
6.6%
724503
 
5.8%
r 712805
 
5.7%
l 623128
 
5.0%
u 614998
 
4.9%
n 589887
 
4.7%
Other values (71) 4266132
34.2%

originalNameUsage
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing604719
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:33.579291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowGoogle Earth
ValueCountFrequency (%)
google 1
50.0%
earth 1
50.0%
2025-02-10T13:48:33.659873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2
16.7%
G 1
8.3%
g 1
8.3%
l 1
8.3%
e 1
8.3%
1
8.3%
E 1
8.3%
a 1
8.3%
r 1
8.3%
t 1
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2
16.7%
G 1
8.3%
g 1
8.3%
l 1
8.3%
e 1
8.3%
1
8.3%
E 1
8.3%
a 1
8.3%
r 1
8.3%
t 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2
16.7%
G 1
8.3%
g 1
8.3%
l 1
8.3%
e 1
8.3%
1
8.3%
E 1
8.3%
a 1
8.3%
r 1
8.3%
t 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2
16.7%
G 1
8.3%
g 1
8.3%
l 1
8.3%
e 1
8.3%
1
8.3%
E 1
8.3%
a 1
8.3%
r 1
8.3%
t 1
8.3%
Distinct3454
Distinct (%)0.6%
Missing4650
Missing (%)0.8%
Memory size4.6 MiB
2025-02-10T13:48:33.699310image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length97
Median length91
Mean length62.39120769
Min length9

Characters and Unicode

Total characters37439092
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique574 ?
Unique (%)0.1%

Sample

1st rowAnimalia, Arthropoda, Insecta, Hymenoptera, Formicidae, Formicinae
2nd rowAnimalia, Arthropoda, Insecta, Lepidoptera, Gelechiidae, Gelechiinae
3rd rowAnimalia, Arthropoda, Insecta, Lepidoptera, Sesiidae, Sesiinae
4th rowAnimalia, Arthropoda, Insecta, Odonata, Zygoptera, Coenagrionidae
5th rowAnimalia, Arthropoda, Insecta, Coleoptera, Carabidae
ValueCountFrequency (%)
arthropoda 599790
17.3%
animalia 598420
17.3%
insecta 588007
17.0%
hymenoptera 146523
 
4.2%
odonata 117300
 
3.4%
lepidoptera 99955
 
2.9%
apidae 82945
 
2.4%
diptera 73546
 
2.1%
coleoptera 72087
 
2.1%
apinae 63529
 
1.8%
Other values (2936) 1026199
29.6%
2025-02-10T13:48:33.814286image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4571468
12.2%
e 2938748
 
7.8%
2868231
 
7.7%
, 2867865
 
7.7%
i 2865509
 
7.7%
o 2433279
 
6.5%
r 2317205
 
6.2%
t 2192393
 
5.9%
n 2160394
 
5.8%
p 1690401
 
4.5%
Other values (51) 10533599
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37439092
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4571468
12.2%
e 2938748
 
7.8%
2868231
 
7.7%
, 2867865
 
7.7%
i 2865509
 
7.7%
o 2433279
 
6.5%
r 2317205
 
6.2%
t 2192393
 
5.9%
n 2160394
 
5.8%
p 1690401
 
4.5%
Other values (51) 10533599
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37439092
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4571468
12.2%
e 2938748
 
7.8%
2868231
 
7.7%
, 2867865
 
7.7%
i 2865509
 
7.7%
o 2433279
 
6.5%
r 2317205
 
6.2%
t 2192393
 
5.9%
n 2160394
 
5.8%
p 1690401
 
4.5%
Other values (51) 10533599
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37439092
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4571468
12.2%
e 2938748
 
7.8%
2868231
 
7.7%
, 2867865
 
7.7%
i 2865509
 
7.7%
o 2433279
 
6.5%
r 2317205
 
6.2%
t 2192393
 
5.9%
n 2160394
 
5.8%
p 1690401
 
4.5%
Other values (51) 10533599
28.1%

kingdom
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing6300
Missing (%)1.0%
Memory size4.6 MiB
2025-02-10T13:48:33.844164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4787360
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 598420
100.0%
2025-02-10T13:48:33.924836image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1196840
25.0%
a 1196840
25.0%
A 598420
12.5%
n 598420
12.5%
m 598420
12.5%
l 598420
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4787360
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1196840
25.0%
a 1196840
25.0%
A 598420
12.5%
n 598420
12.5%
m 598420
12.5%
l 598420
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4787360
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1196840
25.0%
a 1196840
25.0%
A 598420
12.5%
n 598420
12.5%
m 598420
12.5%
l 598420
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4787360
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1196840
25.0%
a 1196840
25.0%
A 598420
12.5%
n 598420
12.5%
m 598420
12.5%
l 598420
12.5%

phylum
Text

Distinct2
Distinct (%)< 0.1%
Missing4930
Missing (%)0.8%
Memory size4.6 MiB
2025-02-10T13:48:33.955487image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5997900
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowArthropoda
2nd rowArthropoda
3rd rowArthropoda
4th rowArthropoda
5th rowArthropoda
ValueCountFrequency (%)
arthropoda 599790
100.0%
2025-02-10T13:48:34.038640image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1199580
20.0%
o 1199580
20.0%
a 599826
10.0%
t 599790
10.0%
h 599790
10.0%
p 599790
10.0%
d 599790
10.0%
A 599754
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5997900
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 1199580
20.0%
o 1199580
20.0%
a 599826
10.0%
t 599790
10.0%
h 599790
10.0%
p 599790
10.0%
d 599790
10.0%
A 599754
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5997900
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 1199580
20.0%
o 1199580
20.0%
a 599826
10.0%
t 599790
10.0%
h 599790
10.0%
p 599790
10.0%
d 599790
10.0%
A 599754
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5997900
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 1199580
20.0%
o 1199580
20.0%
a 599826
10.0%
t 599790
10.0%
h 599790
10.0%
p 599790
10.0%
d 599790
10.0%
A 599754
10.0%

class
Text

Distinct13
Distinct (%)< 0.1%
Missing5496
Missing (%)0.9%
Memory size4.6 MiB
2025-02-10T13:48:34.069524image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.038307878
Min length7

Characters and Unicode

Total characters4217523
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowInsecta
2nd rowInsecta
3rd rowInsecta
4th rowInsecta
5th rowInsecta
ValueCountFrequency (%)
insecta 588007
98.1%
arachnida 7908
 
1.3%
diplopoda 1604
 
0.3%
collembola 798
 
0.1%
chilopoda 740
 
0.1%
diplura 76
 
< 0.1%
protura 62
 
< 0.1%
symphyla 8
 
< 0.1%
myriapoda 6
 
< 0.1%
onychophora 6
 
< 0.1%
Other values (3) 9
 
< 0.1%
2025-02-10T13:48:34.159201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 607141
14.4%
n 595933
14.1%
c 595923
14.1%
e 588805
14.0%
t 588070
13.9%
s 588008
13.9%
I 588007
13.9%
i 10334
 
0.2%
d 10262
 
0.2%
h 8668
 
0.2%
Other values (18) 36372
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4217523
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 607141
14.4%
n 595933
14.1%
c 595923
14.1%
e 588805
14.0%
t 588070
13.9%
s 588008
13.9%
I 588007
13.9%
i 10334
 
0.2%
d 10262
 
0.2%
h 8668
 
0.2%
Other values (18) 36372
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4217523
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 607141
14.4%
n 595933
14.1%
c 595923
14.1%
e 588805
14.0%
t 588070
13.9%
s 588008
13.9%
I 588007
13.9%
i 10334
 
0.2%
d 10262
 
0.2%
h 8668
 
0.2%
Other values (18) 36372
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4217523
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 607141
14.4%
n 595933
14.1%
c 595923
14.1%
e 588805
14.0%
t 588070
13.9%
s 588008
13.9%
I 588007
13.9%
i 10334
 
0.2%
d 10262
 
0.2%
h 8668
 
0.2%
Other values (18) 36372
 
0.9%

order
Text

Distinct85
Distinct (%)< 0.1%
Missing4816
Missing (%)0.8%
Memory size4.6 MiB
2025-02-10T13:48:34.191960image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length16
Mean length9.460972089
Min length5

Characters and Unicode

Total characters5675675
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowHymenoptera
2nd rowLepidoptera
3rd rowLepidoptera
4th rowOdonata
5th rowColeoptera
ValueCountFrequency (%)
hymenoptera 146434
24.4%
odonata 117300
19.6%
lepidoptera 99929
16.7%
diptera 73541
12.3%
coleoptera 72075
12.0%
hemiptera 37773
 
6.3%
siphonaptera 10088
 
1.7%
trichoptera 9110
 
1.5%
araneae 4645
 
0.8%
thysanoptera 4630
 
0.8%
Other values (73) 24379
 
4.1%
2025-02-10T13:48:34.284017image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 849639
15.0%
a 747964
13.2%
t 600150
10.6%
p 583317
10.3%
o 554705
9.8%
r 496497
8.7%
n 284722
 
5.0%
i 241800
 
4.3%
d 223179
 
3.9%
m 190651
 
3.4%
Other values (33) 903051
15.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5675675
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 849639
15.0%
a 747964
13.2%
t 600150
10.6%
p 583317
10.3%
o 554705
9.8%
r 496497
8.7%
n 284722
 
5.0%
i 241800
 
4.3%
d 223179
 
3.9%
m 190651
 
3.4%
Other values (33) 903051
15.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5675675
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 849639
15.0%
a 747964
13.2%
t 600150
10.6%
p 583317
10.3%
o 554705
9.8%
r 496497
8.7%
n 284722
 
5.0%
i 241800
 
4.3%
d 223179
 
3.9%
m 190651
 
3.4%
Other values (33) 903051
15.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5675675
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 849639
15.0%
a 747964
13.2%
t 600150
10.6%
p 583317
10.3%
o 554705
9.8%
r 496497
8.7%
n 284722
 
5.0%
i 241800
 
4.3%
d 223179
 
3.9%
m 190651
 
3.4%
Other values (33) 903051
15.9%

family
Text

Distinct1481
Distinct (%)0.2%
Missing4937
Missing (%)0.8%
Memory size4.6 MiB
2025-02-10T13:48:34.440431image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length19
Mean length10.51244367
Min length3

Characters and Unicode

Total characters6305185
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)< 0.1%

Sample

1st rowFormicidae
2nd rowGelechiidae
3rd rowSesiidae
4th rowCoenagrionidae
5th rowCarabidae
ValueCountFrequency (%)
apidae 82945
 
13.8%
libellulidae 42510
 
7.1%
coenagrionidae 35189
 
5.9%
chrysomelidae 17542
 
2.9%
asilidae 13404
 
2.2%
geometridae 12783
 
2.1%
crambidae 12086
 
2.0%
curculionidae 12016
 
2.0%
psychodidae 11788
 
2.0%
formicidae 9927
 
1.7%
Other values (1470) 349958
58.3%
2025-02-10T13:48:34.668265image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 913350
14.5%
e 888633
14.1%
a 818158
13.0%
d 670599
10.6%
o 326213
 
5.2%
l 321141
 
5.1%
r 288681
 
4.6%
p 212863
 
3.4%
n 209521
 
3.3%
h 149416
 
2.4%
Other values (49) 1506610
23.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6305185
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 913350
14.5%
e 888633
14.1%
a 818158
13.0%
d 670599
10.6%
o 326213
 
5.2%
l 321141
 
5.1%
r 288681
 
4.6%
p 212863
 
3.4%
n 209521
 
3.3%
h 149416
 
2.4%
Other values (49) 1506610
23.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6305185
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 913350
14.5%
e 888633
14.1%
a 818158
13.0%
d 670599
10.6%
o 326213
 
5.2%
l 321141
 
5.1%
r 288681
 
4.6%
p 212863
 
3.4%
n 209521
 
3.3%
h 149416
 
2.4%
Other values (49) 1506610
23.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6305185
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 913350
14.5%
e 888633
14.1%
a 818158
13.0%
d 670599
10.6%
o 326213
 
5.2%
l 321141
 
5.1%
r 288681
 
4.6%
p 212863
 
3.4%
n 209521
 
3.3%
h 149416
 
2.4%
Other values (49) 1506610
23.9%

genus
Text

Distinct39740
Distinct (%)6.6%
Missing5432
Missing (%)0.9%
Memory size4.6 MiB
2025-02-10T13:48:34.835228image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length21
Mean length8.981117593
Min length1

Characters and Unicode

Total characters5382276
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14840 ?
Unique (%)2.5%

Sample

1st rowCamponotus
2nd rowAthrips
3rd rowParanthrene
4th rowAcanthagrion
5th rowCalathus
ValueCountFrequency (%)
bombus 62372
 
10.4%
xylocopa 12105
 
2.0%
unidentified 8808
 
1.5%
argia 8662
 
1.4%
enallagma 7977
 
1.3%
crambus 7970
 
1.3%
ischnura 7458
 
1.2%
sympetrum 6028
 
1.0%
apis 4969
 
0.8%
lestes 4236
 
0.7%
Other values (39686) 468802
78.2%
2025-02-10T13:48:35.148734image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 530794
 
9.9%
o 471993
 
8.8%
i 398632
 
7.4%
s 398294
 
7.4%
e 380922
 
7.1%
r 324165
 
6.0%
l 256048
 
4.8%
u 248374
 
4.6%
t 243058
 
4.5%
m 234489
 
4.4%
Other values (62) 1895507
35.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5382276
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 530794
 
9.9%
o 471993
 
8.8%
i 398632
 
7.4%
s 398294
 
7.4%
e 380922
 
7.1%
r 324165
 
6.0%
l 256048
 
4.8%
u 248374
 
4.6%
t 243058
 
4.5%
m 234489
 
4.4%
Other values (62) 1895507
35.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5382276
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 530794
 
9.9%
o 471993
 
8.8%
i 398632
 
7.4%
s 398294
 
7.4%
e 380922
 
7.1%
r 324165
 
6.0%
l 256048
 
4.8%
u 248374
 
4.6%
t 243058
 
4.5%
m 234489
 
4.4%
Other values (62) 1895507
35.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5382276
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 530794
 
9.9%
o 471993
 
8.8%
i 398632
 
7.4%
s 398294
 
7.4%
e 380922
 
7.1%
r 324165
 
6.0%
l 256048
 
4.8%
u 248374
 
4.6%
t 243058
 
4.5%
m 234489
 
4.4%
Other values (62) 1895507
35.2%

subgenus
Text

Missing 

Distinct3170
Distinct (%)3.4%
Missing512525
Missing (%)84.8%
Memory size4.6 MiB
2025-02-10T13:48:35.187037image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length18
Mean length9.945918976
Min length1

Characters and Unicode

Total characters916964
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1134 ?
Unique (%)1.2%

Sample

1st rowMyrmosericus
2nd rowAnomalagrion
3rd rowAnomalagrion
4th rowHypocaccus
5th rowBombus
ValueCountFrequency (%)
pyrobombus 21248
23.0%
bombus 7225
 
7.8%
apis 3633
 
3.9%
fervidobombus 3293
 
3.6%
neoxylocopa 2426
 
2.6%
alpinobombus 1554
 
1.7%
xylocopoides 1492
 
1.6%
schonnherria 1460
 
1.6%
separatobombus 1325
 
1.4%
chimarra 1296
 
1.4%
Other values (3159) 47264
51.3%
2025-02-10T13:48:35.289247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 129387
14.1%
s 73941
 
8.1%
b 73482
 
8.0%
r 63107
 
6.9%
m 58165
 
6.3%
u 57827
 
6.3%
a 57453
 
6.3%
i 52141
 
5.7%
y 39777
 
4.3%
e 39462
 
4.3%
Other values (47) 272222
29.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 916964
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 129387
14.1%
s 73941
 
8.1%
b 73482
 
8.0%
r 63107
 
6.9%
m 58165
 
6.3%
u 57827
 
6.3%
a 57453
 
6.3%
i 52141
 
5.7%
y 39777
 
4.3%
e 39462
 
4.3%
Other values (47) 272222
29.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 916964
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 129387
14.1%
s 73941
 
8.1%
b 73482
 
8.0%
r 63107
 
6.9%
m 58165
 
6.3%
u 57827
 
6.3%
a 57453
 
6.3%
i 52141
 
5.7%
y 39777
 
4.3%
e 39462
 
4.3%
Other values (47) 272222
29.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 916964
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 129387
14.1%
s 73941
 
8.1%
b 73482
 
8.0%
r 63107
 
6.9%
m 58165
 
6.3%
u 57827
 
6.3%
a 57453
 
6.3%
i 52141
 
5.7%
y 39777
 
4.3%
e 39462
 
4.3%
Other values (47) 272222
29.7%

specificEpithet
Text

Missing 

Distinct88940
Distinct (%)14.9%
Missing8751
Missing (%)1.4%
Memory size4.6 MiB
2025-02-10T13:48:35.465306image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length25
Mean length8.294070665
Min length1

Characters and Unicode

Total characters4943009
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50119 ?
Unique (%)8.4%

Sample

1st rowrufoglaucus
2nd rowmesoleuca
3rd rowasilipennis
4th rowtrilobatum
5th rownanulus
ValueCountFrequency (%)
sp 44400
 
7.4%
sylvicola 6285
 
1.1%
bifarius 4078
 
0.7%
kirbyellus 3621
 
0.6%
flavifrons 3483
 
0.6%
impatiens 3134
 
0.5%
undetermined 3047
 
0.5%
nevadensis 2529
 
0.4%
cerana 2431
 
0.4%
affinis 2295
 
0.4%
Other values (88797) 521298
87.4%
2025-02-10T13:48:35.712123image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 624165
12.6%
i 556726
11.3%
s 471813
 
9.5%
e 377708
 
7.6%
n 324342
 
6.6%
l 324007
 
6.6%
r 301739
 
6.1%
u 289537
 
5.9%
t 260984
 
5.3%
c 231687
 
4.7%
Other values (43) 1180301
23.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4943009
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 624165
12.6%
i 556726
11.3%
s 471813
 
9.5%
e 377708
 
7.6%
n 324342
 
6.6%
l 324007
 
6.6%
r 301739
 
6.1%
u 289537
 
5.9%
t 260984
 
5.3%
c 231687
 
4.7%
Other values (43) 1180301
23.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4943009
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 624165
12.6%
i 556726
11.3%
s 471813
 
9.5%
e 377708
 
7.6%
n 324342
 
6.6%
l 324007
 
6.6%
r 301739
 
6.1%
u 289537
 
5.9%
t 260984
 
5.3%
c 231687
 
4.7%
Other values (43) 1180301
23.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4943009
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 624165
12.6%
i 556726
11.3%
s 471813
 
9.5%
e 377708
 
7.6%
n 324342
 
6.6%
l 324007
 
6.6%
r 301739
 
6.1%
u 289537
 
5.9%
t 260984
 
5.3%
c 231687
 
4.7%
Other values (43) 1180301
23.9%

infraspecificEpithet
Text

Missing 

Distinct8352
Distinct (%)24.9%
Missing571231
Missing (%)94.5%
Memory size4.6 MiB
2025-02-10T13:48:35.755750image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length22
Mean length8.8483084
Min length1

Characters and Unicode

Total characters296321
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5802 ?
Unique (%)17.3%

Sample

1st rowrufigenis
2nd rowdecrescens
3rd rowmarianae
4th rowneglectum
5th rowlavatus
ValueCountFrequency (%)
nearcticus 2527
 
7.5%
fervidus 1188
 
3.5%
violacea 992
 
3.0%
pensylvanicus 904
 
2.7%
vagans 870
 
2.6%
portia 724
 
2.2%
virginica 593
 
1.8%
auricormus 587
 
1.8%
auripennis 578
 
1.7%
dorsata 440
 
1.3%
Other values (8332) 24136
72.0%
2025-02-10T13:48:35.866130image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 38963
13.1%
i 34627
11.7%
s 26724
9.0%
n 23021
 
7.8%
r 21553
 
7.3%
e 21399
 
7.2%
u 19000
 
6.4%
c 18314
 
6.2%
t 14569
 
4.9%
o 13863
 
4.7%
Other values (28) 64288
21.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 296321
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 38963
13.1%
i 34627
11.7%
s 26724
9.0%
n 23021
 
7.8%
r 21553
 
7.3%
e 21399
 
7.2%
u 19000
 
6.4%
c 18314
 
6.2%
t 14569
 
4.9%
o 13863
 
4.7%
Other values (28) 64288
21.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 296321
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 38963
13.1%
i 34627
11.7%
s 26724
9.0%
n 23021
 
7.8%
r 21553
 
7.3%
e 21399
 
7.2%
u 19000
 
6.4%
c 18314
 
6.2%
t 14569
 
4.9%
o 13863
 
4.7%
Other values (28) 64288
21.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 296321
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 38963
13.1%
i 34627
11.7%
s 26724
9.0%
n 23021
 
7.8%
r 21553
 
7.3%
e 21399
 
7.2%
u 19000
 
6.4%
c 18314
 
6.2%
t 14569
 
4.9%
o 13863
 
4.7%
Other values (28) 64288
21.7%

taxonRank
Text

Missing 

Distinct17
Distinct (%)0.1%
Missing571236
Missing (%)94.5%
Memory size4.6 MiB
2025-02-10T13:48:35.899207image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length10
Mean length9.835861904
Min length4

Characters and Unicode

Total characters329344
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowVariety
2nd rowsubspecies
3rd rowsubspecies
4th rowsubspecies
5th rowsubspecies
ValueCountFrequency (%)
subspecies 31600
94.3%
variety 1483
 
4.4%
aberration 168
 
0.5%
form 104
 
0.3%
race 69
 
0.2%
morphotype 28
 
0.1%
species 10
 
< 0.1%
group 10
 
< 0.1%
undet.cat 9
 
< 0.1%
var 5
 
< 0.1%
Other values (4) 10
 
< 0.1%
2025-02-10T13:48:35.994178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 94823
28.8%
e 64977
19.7%
i 33273
 
10.1%
b 31768
 
9.6%
p 31681
 
9.6%
c 31679
 
9.6%
u 31610
 
9.6%
r 1986
 
0.6%
a 1745
 
0.5%
t 1706
 
0.5%
Other values (20) 4096
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 329344
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 94823
28.8%
e 64977
19.7%
i 33273
 
10.1%
b 31768
 
9.6%
p 31681
 
9.6%
c 31679
 
9.6%
u 31610
 
9.6%
r 1986
 
0.6%
a 1745
 
0.5%
t 1706
 
0.5%
Other values (20) 4096
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 329344
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 94823
28.8%
e 64977
19.7%
i 33273
 
10.1%
b 31768
 
9.6%
p 31681
 
9.6%
c 31679
 
9.6%
u 31610
 
9.6%
r 1986
 
0.6%
a 1745
 
0.5%
t 1706
 
0.5%
Other values (20) 4096
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 329344
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 94823
28.8%
e 64977
19.7%
i 33273
 
10.1%
b 31768
 
9.6%
p 31681
 
9.6%
c 31679
 
9.6%
u 31610
 
9.6%
r 1986
 
0.6%
a 1745
 
0.5%
t 1706
 
0.5%
Other values (20) 4096
 
1.2%
Distinct10001
Distinct (%)1.9%
Missing90502
Missing (%)15.0%
Memory size4.6 MiB
2025-02-10T13:48:36.150708image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length43
Median length33
Mean length7.761809194
Min length2

Characters and Unicode

Total characters3991262
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3229 ?
Unique (%)0.6%

Sample

1st rowForel
2nd row(Lower)
3rd row(Guérin-Méneville)
4th rowLeonard
5th rowCasey
ValueCountFrequency (%)
25801
 
4.4%
hagen 24579
 
4.1%
cresson 22178
 
3.7%
selys 21328
 
3.6%
casey 19749
 
3.3%
say 14238
 
2.4%
fabricius 13983
 
2.4%
alexander 9897
 
1.7%
smith 9578
 
1.6%
kirby 8910
 
1.5%
Other values (6005) 422402
71.3%
2025-02-10T13:48:36.382824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 427913
 
10.7%
a 306441
 
7.7%
r 298135
 
7.5%
n 241900
 
6.1%
s 234839
 
5.9%
i 207245
 
5.2%
l 195525
 
4.9%
o 172511
 
4.3%
( 140296
 
3.5%
) 140296
 
3.5%
Other values (73) 1626161
40.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3991262
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 427913
 
10.7%
a 306441
 
7.7%
r 298135
 
7.5%
n 241900
 
6.1%
s 234839
 
5.9%
i 207245
 
5.2%
l 195525
 
4.9%
o 172511
 
4.3%
( 140296
 
3.5%
) 140296
 
3.5%
Other values (73) 1626161
40.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3991262
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 427913
 
10.7%
a 306441
 
7.7%
r 298135
 
7.5%
n 241900
 
6.1%
s 234839
 
5.9%
i 207245
 
5.2%
l 195525
 
4.9%
o 172511
 
4.3%
( 140296
 
3.5%
) 140296
 
3.5%
Other values (73) 1626161
40.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3991262
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 427913
 
10.7%
a 306441
 
7.7%
r 298135
 
7.5%
n 241900
 
6.1%
s 234839
 
5.9%
i 207245
 
5.2%
l 195525
 
4.9%
o 172511
 
4.3%
( 140296
 
3.5%
) 140296
 
3.5%
Other values (73) 1626161
40.7%

vernacularName
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing604718
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:48:36.419266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowType
2nd rowType
ValueCountFrequency (%)
type 2
100.0%
2025-02-10T13:48:36.498435image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
25.0%
y 2
25.0%
p 2
25.0%
e 2
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 2
25.0%
y 2
25.0%
p 2
25.0%
e 2
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 2
25.0%
y 2
25.0%
p 2
25.0%
e 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 2
25.0%
y 2
25.0%
p 2
25.0%
e 2
25.0%