Overview

Brought to you by YData

Dataset statistics

Number of variables66
Number of observations60042
Missing cells1532317
Missing cells (%)38.7%
Total size in memory30.2 MiB
Average record size in memory528.0 B

Variable types

Text66

Dataset

DescriptionField Museum of Natural History (Botany) Lichen Collection 0002582-250127130748423
URLhttps://doi.org/10.15468/dl.mn87bp

Alerts

accessRights has constant value "http://fieldmuseum.org/about/copyright-information" Constant
language has constant value "en" Constant
license has constant value "https://creativecommons.org/publicdomain/zero/1.0/" Constant
rightsHolder has constant value "The Field Museum of Natural History" Constant
type has constant value "PhysicalObject" Constant
collectionID has constant value "http://grbio.org/institution/field-museum-natural-history-botany-department" Constant
datasetID has constant value "lichen-21-dec-2022" Constant
institutionCode has constant value "F" Constant
collectionCode has constant value "Botany" Constant
ownerInstitutionCode has constant value "F" Constant
basisOfRecord has constant value "PreservedSpecimen" Constant
fieldNumber has constant value "818" Constant
nomenclaturalCode has constant value "ICBN" Constant
datasetName has 56342 (93.8%) missing values Missing
catalogNumber has 5562 (9.3%) missing values Missing
recordNumber has 8145 (13.6%) missing values Missing
recordedBy has 1775 (3.0%) missing values Missing
lifeStage has 60039 (> 99.9%) missing values Missing
associatedReferences has 55656 (92.7%) missing values Missing
occurrenceRemarks has 57970 (96.5%) missing values Missing
organismRemarks has 59950 (99.8%) missing values Missing
fieldNumber has 60041 (> 99.9%) missing values Missing
year has 7047 (11.7%) missing values Missing
month has 10869 (18.1%) missing values Missing
day has 16706 (27.8%) missing values Missing
verbatimEventDate has 59104 (98.4%) missing values Missing
habitat has 29062 (48.4%) missing values Missing
continent has 2334 (3.9%) missing values Missing
islandGroup has 56285 (93.7%) missing values Missing
island has 55634 (92.7%) missing values Missing
country has 2743 (4.6%) missing values Missing
stateProvince has 13152 (21.9%) missing values Missing
county has 33990 (56.6%) missing values Missing
municipality has 52197 (86.9%) missing values Missing
locality has 16084 (26.8%) missing values Missing
minimumElevationInMeters has 36294 (60.4%) missing values Missing
maximumElevationInMeters has 52179 (86.9%) missing values Missing
decimalLatitude has 10516 (17.5%) missing values Missing
decimalLongitude has 10516 (17.5%) missing values Missing
geodeticDatum has 59376 (98.9%) missing values Missing
coordinateUncertaintyInMeters has 39477 (65.7%) missing values Missing
georeferencedBy has 38000 (63.3%) missing values Missing
georeferencedDate has 51876 (86.4%) missing values Missing
georeferenceProtocol has 47686 (79.4%) missing values Missing
georeferenceSources has 24313 (40.5%) missing values Missing
georeferenceRemarks has 52148 (86.9%) missing values Missing
identificationQualifier has 59943 (99.8%) missing values Missing
typeStatus has 58591 (97.6%) missing values Missing
identifiedBy has 34027 (56.7%) missing values Missing
dateIdentified has 42731 (71.2%) missing values Missing
phylum has 1617 (2.7%) missing values Missing
class has 1919 (3.2%) missing values Missing
order has 2077 (3.5%) missing values Missing
family has 1848 (3.1%) missing values Missing
genus has 1559 (2.6%) missing values Missing
subgenus has 59985 (99.9%) missing values Missing
specificEpithet has 8744 (14.6%) missing values Missing
infraspecificEpithet has 57027 (95.0%) missing values Missing
taxonRank has 57027 (95.0%) missing values Missing
scientificNameAuthorship has 1308 (2.2%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique
organismID has unique values Unique

Reproduction

Analysis started2025-02-14 20:18:12.479473
Analysis finished2025-02-14 20:18:14.406749
Duration1.93 second
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct60042
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:14.511720image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters600420
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

Unique60042 ?
Unique (%)100.0%

Sample

1st row4002923125
2nd row4002923124
3rd row4002923123
4th row4002923122
5th row4002923121
ValueCountFrequency (%)
4002923125 1
 
< 0.1%
4002923116 1
 
< 0.1%
4002923069 1
 
< 0.1%
4002923095 1
 
< 0.1%
4002923096 1
 
< 0.1%
4002923097 1
 
< 0.1%
4002923098 1
 
< 0.1%
4002923123 1
 
< 0.1%
4002923122 1
 
< 0.1%
4002923121 1
 
< 0.1%
Other values (60032) 60032
> 99.9%
2025-02-14T15:18:14.710186image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 132488
22.1%
1 86842
14.5%
5 83891
14.0%
3 82981
13.8%
4 42318
 
7.0%
2 41676
 
6.9%
7 39952
 
6.7%
6 33862
 
5.6%
8 30933
 
5.2%
9 25477
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 600420
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 132488
22.1%
1 86842
14.5%
5 83891
14.0%
3 82981
13.8%
4 42318
 
7.0%
2 41676
 
6.9%
7 39952
 
6.7%
6 33862
 
5.6%
8 30933
 
5.2%
9 25477
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 600420
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 132488
22.1%
1 86842
14.5%
5 83891
14.0%
3 82981
13.8%
4 42318
 
7.0%
2 41676
 
6.9%
7 39952
 
6.7%
6 33862
 
5.6%
8 30933
 
5.2%
9 25477
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 600420
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 132488
22.1%
1 86842
14.5%
5 83891
14.0%
3 82981
13.8%
4 42318
 
7.0%
2 41676
 
6.9%
7 39952
 
6.7%
6 33862
 
5.6%
8 30933
 
5.2%
9 25477
 
4.2%

accessRights
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:14.765143image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length50
Median length50
Mean length50
Min length50

Characters and Unicode

Total characters3002100
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://fieldmuseum.org/about/copyright-information
2nd rowhttp://fieldmuseum.org/about/copyright-information
3rd rowhttp://fieldmuseum.org/about/copyright-information
4th rowhttp://fieldmuseum.org/about/copyright-information
5th rowhttp://fieldmuseum.org/about/copyright-information
ValueCountFrequency (%)
http://fieldmuseum.org/about/copyright-information 60042
100.0%
2025-02-14T15:18:14.849360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 300210
 
10.0%
t 300210
 
10.0%
/ 240168
 
8.0%
i 240168
 
8.0%
u 180126
 
6.0%
m 180126
 
6.0%
r 180126
 
6.0%
a 120084
 
4.0%
g 120084
 
4.0%
h 120084
 
4.0%
Other values (13) 1020714
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3002100
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 300210
 
10.0%
t 300210
 
10.0%
/ 240168
 
8.0%
i 240168
 
8.0%
u 180126
 
6.0%
m 180126
 
6.0%
r 180126
 
6.0%
a 120084
 
4.0%
g 120084
 
4.0%
h 120084
 
4.0%
Other values (13) 1020714
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3002100
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 300210
 
10.0%
t 300210
 
10.0%
/ 240168
 
8.0%
i 240168
 
8.0%
u 180126
 
6.0%
m 180126
 
6.0%
r 180126
 
6.0%
a 120084
 
4.0%
g 120084
 
4.0%
h 120084
 
4.0%
Other values (13) 1020714
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3002100
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 300210
 
10.0%
t 300210
 
10.0%
/ 240168
 
8.0%
i 240168
 
8.0%
u 180126
 
6.0%
m 180126
 
6.0%
r 180126
 
6.0%
a 120084
 
4.0%
g 120084
 
4.0%
h 120084
 
4.0%
Other values (13) 1020714
34.0%

language
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:14.879068image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters120084
Distinct characters2
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 rowen
2nd rowen
3rd rowen
4th rowen
5th rowen
ValueCountFrequency (%)
en 60042
100.0%
2025-02-14T15:18:14.967297image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 60042
50.0%
n 60042
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 120084
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 60042
50.0%
n 60042
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 120084
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 60042
50.0%
n 60042
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 120084
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 60042
50.0%
n 60042
50.0%

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:14.997886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length50
Median length50
Mean length50
Min length50

Characters and Unicode

Total characters3002100
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://creativecommons.org/publicdomain/zero/1.0/
2nd rowhttps://creativecommons.org/publicdomain/zero/1.0/
3rd rowhttps://creativecommons.org/publicdomain/zero/1.0/
4th rowhttps://creativecommons.org/publicdomain/zero/1.0/
5th rowhttps://creativecommons.org/publicdomain/zero/1.0/
ValueCountFrequency (%)
https://creativecommons.org/publicdomain/zero/1.0 60042
100.0%
2025-02-14T15:18:15.145006image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 360252
 
12.0%
o 300210
 
10.0%
i 180126
 
6.0%
m 180126
 
6.0%
c 180126
 
6.0%
r 180126
 
6.0%
e 180126
 
6.0%
t 180126
 
6.0%
. 120084
 
4.0%
n 120084
 
4.0%
Other values (14) 1020714
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3002100
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 360252
 
12.0%
o 300210
 
10.0%
i 180126
 
6.0%
m 180126
 
6.0%
c 180126
 
6.0%
r 180126
 
6.0%
e 180126
 
6.0%
t 180126
 
6.0%
. 120084
 
4.0%
n 120084
 
4.0%
Other values (14) 1020714
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3002100
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 360252
 
12.0%
o 300210
 
10.0%
i 180126
 
6.0%
m 180126
 
6.0%
c 180126
 
6.0%
r 180126
 
6.0%
e 180126
 
6.0%
t 180126
 
6.0%
. 120084
 
4.0%
n 120084
 
4.0%
Other values (14) 1020714
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3002100
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 360252
 
12.0%
o 300210
 
10.0%
i 180126
 
6.0%
m 180126
 
6.0%
c 180126
 
6.0%
r 180126
 
6.0%
e 180126
 
6.0%
t 180126
 
6.0%
. 120084
 
4.0%
n 120084
 
4.0%
Other values (14) 1020714
34.0%
Distinct5606
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:15.258783image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters1260882
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

Unique4138 ?
Unique (%)6.9%

Sample

1st row2021-10-11T12:13-0600
2nd row2022-01-26T06:31-0600
3rd row2021-10-11T12:13-0600
4th row2021-09-29T14:34-0600
5th row2021-10-14T17:04-0600
ValueCountFrequency (%)
2018-06-20t15:06-0600 1581
 
2.6%
2018-06-20t15:08-0600 1540
 
2.6%
2018-06-20t15:05-0600 1535
 
2.6%
2018-06-20t15:09-0600 1511
 
2.5%
2018-06-20t15:07-0600 1328
 
2.2%
2018-06-20t15:04-0600 968
 
1.6%
2018-06-20t15:11-0600 774
 
1.3%
2018-06-20t15:10-0600 753
 
1.3%
2018-06-20t15:12-0600 741
 
1.2%
2018-06-20t15:13-0600 688
 
1.1%
Other values (5596) 48623
81.0%
2025-02-14T15:18:15.413926image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 363869
28.9%
- 180126
14.3%
1 156054
12.4%
2 146879
11.6%
6 98161
 
7.8%
T 60042
 
4.8%
: 60042
 
4.8%
5 50821
 
4.0%
3 45646
 
3.6%
9 30698
 
2.4%
Other values (3) 68544
 
5.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1260882
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 363869
28.9%
- 180126
14.3%
1 156054
12.4%
2 146879
11.6%
6 98161
 
7.8%
T 60042
 
4.8%
: 60042
 
4.8%
5 50821
 
4.0%
3 45646
 
3.6%
9 30698
 
2.4%
Other values (3) 68544
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1260882
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 363869
28.9%
- 180126
14.3%
1 156054
12.4%
2 146879
11.6%
6 98161
 
7.8%
T 60042
 
4.8%
: 60042
 
4.8%
5 50821
 
4.0%
3 45646
 
3.6%
9 30698
 
2.4%
Other values (3) 68544
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1260882
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 363869
28.9%
- 180126
14.3%
1 156054
12.4%
2 146879
11.6%
6 98161
 
7.8%
T 60042
 
4.8%
: 60042
 
4.8%
5 50821
 
4.0%
3 45646
 
3.6%
9 30698
 
2.4%
Other values (3) 68544
 
5.4%

rightsHolder
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:15.467114image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length35
Mean length35
Min length35

Characters and Unicode

Total characters2101470
Distinct characters20
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 rowThe Field Museum of Natural History
2nd rowThe Field Museum of Natural History
3rd rowThe Field Museum of Natural History
4th rowThe Field Museum of Natural History
5th rowThe Field Museum of Natural History
ValueCountFrequency (%)
the 60042
16.7%
field 60042
16.7%
museum 60042
16.7%
of 60042
16.7%
natural 60042
16.7%
history 60042
16.7%
2025-02-14T15:18:15.551800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
300210
14.3%
e 180126
 
8.6%
u 180126
 
8.6%
s 120084
 
5.7%
i 120084
 
5.7%
l 120084
 
5.7%
r 120084
 
5.7%
t 120084
 
5.7%
a 120084
 
5.7%
o 120084
 
5.7%
Other values (10) 600420
28.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2101470
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
300210
14.3%
e 180126
 
8.6%
u 180126
 
8.6%
s 120084
 
5.7%
i 120084
 
5.7%
l 120084
 
5.7%
r 120084
 
5.7%
t 120084
 
5.7%
a 120084
 
5.7%
o 120084
 
5.7%
Other values (10) 600420
28.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2101470
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
300210
14.3%
e 180126
 
8.6%
u 180126
 
8.6%
s 120084
 
5.7%
i 120084
 
5.7%
l 120084
 
5.7%
r 120084
 
5.7%
t 120084
 
5.7%
a 120084
 
5.7%
o 120084
 
5.7%
Other values (10) 600420
28.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2101470
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
300210
14.3%
e 180126
 
8.6%
u 180126
 
8.6%
s 120084
 
5.7%
i 120084
 
5.7%
l 120084
 
5.7%
r 120084
 
5.7%
t 120084
 
5.7%
a 120084
 
5.7%
o 120084
 
5.7%
Other values (10) 600420
28.6%

type
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:15.581207image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters840588
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowPhysicalObject
2nd rowPhysicalObject
3rd rowPhysicalObject
4th rowPhysicalObject
5th rowPhysicalObject
ValueCountFrequency (%)
physicalobject 60042
100.0%
2025-02-14T15:18:15.663642image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 120084
14.3%
P 60042
 
7.1%
h 60042
 
7.1%
y 60042
 
7.1%
s 60042
 
7.1%
i 60042
 
7.1%
a 60042
 
7.1%
l 60042
 
7.1%
O 60042
 
7.1%
b 60042
 
7.1%
Other values (3) 180126
21.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 840588
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 120084
14.3%
P 60042
 
7.1%
h 60042
 
7.1%
y 60042
 
7.1%
s 60042
 
7.1%
i 60042
 
7.1%
a 60042
 
7.1%
l 60042
 
7.1%
O 60042
 
7.1%
b 60042
 
7.1%
Other values (3) 180126
21.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 840588
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 120084
14.3%
P 60042
 
7.1%
h 60042
 
7.1%
y 60042
 
7.1%
s 60042
 
7.1%
i 60042
 
7.1%
a 60042
 
7.1%
l 60042
 
7.1%
O 60042
 
7.1%
b 60042
 
7.1%
Other values (3) 180126
21.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 840588
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 120084
14.3%
P 60042
 
7.1%
h 60042
 
7.1%
y 60042
 
7.1%
s 60042
 
7.1%
i 60042
 
7.1%
a 60042
 
7.1%
l 60042
 
7.1%
O 60042
 
7.1%
b 60042
 
7.1%
Other values (3) 180126
21.4%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:15.691337image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters4503150
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 rowhttp://grbio.org/institution/field-museum-natural-history-botany-department
2nd rowhttp://grbio.org/institution/field-museum-natural-history-botany-department
3rd rowhttp://grbio.org/institution/field-museum-natural-history-botany-department
4th rowhttp://grbio.org/institution/field-museum-natural-history-botany-department
5th rowhttp://grbio.org/institution/field-museum-natural-history-botany-department
ValueCountFrequency (%)
http://grbio.org/institution/field-museum-natural-history-botany-department 60042
100.0%
2025-02-14T15:18:15.777663image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 600420
13.3%
i 360252
 
8.0%
n 300210
 
6.7%
- 300210
 
6.7%
r 300210
 
6.7%
o 300210
 
6.7%
e 240168
 
5.3%
a 240168
 
5.3%
/ 240168
 
5.3%
u 240168
 
5.3%
Other values (12) 1380966
30.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4503150
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 600420
13.3%
i 360252
 
8.0%
n 300210
 
6.7%
- 300210
 
6.7%
r 300210
 
6.7%
o 300210
 
6.7%
e 240168
 
5.3%
a 240168
 
5.3%
/ 240168
 
5.3%
u 240168
 
5.3%
Other values (12) 1380966
30.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4503150
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 600420
13.3%
i 360252
 
8.0%
n 300210
 
6.7%
- 300210
 
6.7%
r 300210
 
6.7%
o 300210
 
6.7%
e 240168
 
5.3%
a 240168
 
5.3%
/ 240168
 
5.3%
u 240168
 
5.3%
Other values (12) 1380966
30.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4503150
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 600420
13.3%
i 360252
 
8.0%
n 300210
 
6.7%
- 300210
 
6.7%
r 300210
 
6.7%
o 300210
 
6.7%
e 240168
 
5.3%
a 240168
 
5.3%
/ 240168
 
5.3%
u 240168
 
5.3%
Other values (12) 1380966
30.7%

datasetID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:15.807689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1080756
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowlichen-21-dec-2022
2nd rowlichen-21-dec-2022
3rd rowlichen-21-dec-2022
4th rowlichen-21-dec-2022
5th rowlichen-21-dec-2022
ValueCountFrequency (%)
lichen-21-dec-2022 60042
100.0%
2025-02-14T15:18:15.893732image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 240168
22.2%
- 180126
16.7%
c 120084
11.1%
e 120084
11.1%
l 60042
 
5.6%
i 60042
 
5.6%
h 60042
 
5.6%
n 60042
 
5.6%
1 60042
 
5.6%
d 60042
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1080756
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 240168
22.2%
- 180126
16.7%
c 120084
11.1%
e 120084
11.1%
l 60042
 
5.6%
i 60042
 
5.6%
h 60042
 
5.6%
n 60042
 
5.6%
1 60042
 
5.6%
d 60042
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1080756
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 240168
22.2%
- 180126
16.7%
c 120084
11.1%
e 120084
11.1%
l 60042
 
5.6%
i 60042
 
5.6%
h 60042
 
5.6%
n 60042
 
5.6%
1 60042
 
5.6%
d 60042
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1080756
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 240168
22.2%
- 180126
16.7%
c 120084
11.1%
e 120084
11.1%
l 60042
 
5.6%
i 60042
 
5.6%
h 60042
 
5.6%
n 60042
 
5.6%
1 60042
 
5.6%
d 60042
 
5.6%

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:15.921242image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters60042
Distinct characters1
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 rowF
2nd rowF
3rd rowF
4th rowF
5th rowF
ValueCountFrequency (%)
f 60042
100.0%
2025-02-14T15:18:16.004714image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
F 60042
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 60042
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
F 60042
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 60042
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
F 60042
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 60042
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
F 60042
100.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:16.033949image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters360252
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 rowBotany
2nd rowBotany
3rd rowBotany
4th rowBotany
5th rowBotany
ValueCountFrequency (%)
botany 60042
100.0%
2025-02-14T15:18:16.117176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 60042
16.7%
o 60042
16.7%
t 60042
16.7%
a 60042
16.7%
n 60042
16.7%
y 60042
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 360252
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 60042
16.7%
o 60042
16.7%
t 60042
16.7%
a 60042
16.7%
n 60042
16.7%
y 60042
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 360252
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 60042
16.7%
o 60042
16.7%
t 60042
16.7%
a 60042
16.7%
n 60042
16.7%
y 60042
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 360252
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 60042
16.7%
o 60042
16.7%
t 60042
16.7%
a 60042
16.7%
n 60042
16.7%
y 60042
16.7%

datasetName
Text

Missing 

Distinct9
Distinct (%)0.2%
Missing56342
Missing (%)93.8%
Memory size469.2 KiB
2025-02-14T15:18:16.148243image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length10
Mean length9.637837838
Min length6

Characters and Unicode

Total characters35660
Distinct characters50
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 rowNAMA Vouchers
2nd rowATM Graphidaceae Workshop, Puerto Rico, 2014
3rd rowNeotropical Epiphytic Microlichens Workshop, Puerto Rico, 2011
4th rowATM Graphidaceae Workshop, Puerto Rico, 2014
5th rowNAMA Vouchers
ValueCountFrequency (%)
ticolichen 2299
54.0%
vtypes 942
22.1%
nama 411
 
9.7%
vouchers 411
 
9.7%
lumbsch 20
 
0.5%
digitization 20
 
0.5%
neotropical 15
 
0.4%
epiphytic 15
 
0.4%
microlichens 15
 
0.4%
deb-0715660 10
 
0.2%
Other values (19) 96
 
2.3%
2025-02-14T15:18:16.264276image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 5104
14.3%
i 4795
13.4%
e 3720
10.4%
T 3255
9.1%
o 2813
7.9%
h 2784
7.8%
l 2338
 
6.6%
n 2338
 
6.6%
s 1434
 
4.0%
p 1000
 
2.8%
Other values (40) 6079
17.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 35660
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 5104
14.3%
i 4795
13.4%
e 3720
10.4%
T 3255
9.1%
o 2813
7.9%
h 2784
7.8%
l 2338
 
6.6%
n 2338
 
6.6%
s 1434
 
4.0%
p 1000
 
2.8%
Other values (40) 6079
17.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 35660
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 5104
14.3%
i 4795
13.4%
e 3720
10.4%
T 3255
9.1%
o 2813
7.9%
h 2784
7.8%
l 2338
 
6.6%
n 2338
 
6.6%
s 1434
 
4.0%
p 1000
 
2.8%
Other values (40) 6079
17.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 35660
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 5104
14.3%
i 4795
13.4%
e 3720
10.4%
T 3255
9.1%
o 2813
7.9%
h 2784
7.8%
l 2338
 
6.6%
n 2338
 
6.6%
s 1434
 
4.0%
p 1000
 
2.8%
Other values (40) 6079
17.0%

ownerInstitutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:16.292101image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters60042
Distinct characters1
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 rowF
2nd rowF
3rd rowF
4th rowF
5th rowF
ValueCountFrequency (%)
f 60042
100.0%
2025-02-14T15:18:16.375351image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
F 60042
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 60042
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
F 60042
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 60042
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
F 60042
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 60042
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
F 60042
100.0%

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:16.404269image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters1020714
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 60042
100.0%
2025-02-14T15:18:16.488878image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 300210
29.4%
r 120084
 
11.8%
P 60042
 
5.9%
s 60042
 
5.9%
v 60042
 
5.9%
d 60042
 
5.9%
S 60042
 
5.9%
p 60042
 
5.9%
c 60042
 
5.9%
i 60042
 
5.9%
Other values (2) 120084
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1020714
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 300210
29.4%
r 120084
 
11.8%
P 60042
 
5.9%
s 60042
 
5.9%
v 60042
 
5.9%
d 60042
 
5.9%
S 60042
 
5.9%
p 60042
 
5.9%
c 60042
 
5.9%
i 60042
 
5.9%
Other values (2) 120084
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1020714
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 300210
29.4%
r 120084
 
11.8%
P 60042
 
5.9%
s 60042
 
5.9%
v 60042
 
5.9%
d 60042
 
5.9%
S 60042
 
5.9%
p 60042
 
5.9%
c 60042
 
5.9%
i 60042
 
5.9%
Other values (2) 120084
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1020714
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 300210
29.4%
r 120084
 
11.8%
P 60042
 
5.9%
s 60042
 
5.9%
v 60042
 
5.9%
d 60042
 
5.9%
S 60042
 
5.9%
p 60042
 
5.9%
c 60042
 
5.9%
i 60042
 
5.9%
Other values (2) 120084
 
11.8%

occurrenceID
Text

Unique 

Distinct60042
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:16.551462image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters2161512
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

Unique60042 ?
Unique (%)100.0%

Sample

1st rowb103b2e6-ed9a-4e7a-981e-28bb14046615
2nd row34ae89c9-aff7-471c-a75c-40015f7b0487
3rd row279de73b-6651-4199-a2cb-0c440b09f00e
4th rowa72bf569-6677-4032-af8a-c81e343099e1
5th row6f1b0ef3-b71c-4e1e-848c-cfe2f2e014f1
ValueCountFrequency (%)
b103b2e6-ed9a-4e7a-981e-28bb14046615 1
 
< 0.1%
95a0891e-3975-43fb-b1e1-6269b9fc360d 1
 
< 0.1%
8f17eb63-f2c3-4f3e-aa3e-bdd07a2963b3 1
 
< 0.1%
1b9a6a43-1083-4a51-9330-cdce09fefed5 1
 
< 0.1%
9d584634-2a3d-4530-ba2e-81b61a706f95 1
 
< 0.1%
54381897-0d65-42f8-b1c6-8c9a31f6badc 1
 
< 0.1%
bb96d011-13b5-45c9-bae3-cbe82847960a 1
 
< 0.1%
279de73b-6651-4199-a2cb-0c440b09f00e 1
 
< 0.1%
a72bf569-6677-4032-af8a-c81e343099e1 1
 
< 0.1%
6f1b0ef3-b71c-4e1e-848c-cfe2f2e014f1 1
 
< 0.1%
Other values (60032) 60032
> 99.9%
2025-02-14T15:18:16.683154image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 240168
 
11.1%
4 172216
 
8.0%
8 128010
 
5.9%
a 127904
 
5.9%
b 127902
 
5.9%
9 127587
 
5.9%
c 113271
 
5.2%
2 112849
 
5.2%
0 112671
 
5.2%
5 112590
 
5.2%
Other values (7) 786344
36.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2161512
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 240168
 
11.1%
4 172216
 
8.0%
8 128010
 
5.9%
a 127904
 
5.9%
b 127902
 
5.9%
9 127587
 
5.9%
c 113271
 
5.2%
2 112849
 
5.2%
0 112671
 
5.2%
5 112590
 
5.2%
Other values (7) 786344
36.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2161512
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 240168
 
11.1%
4 172216
 
8.0%
8 128010
 
5.9%
a 127904
 
5.9%
b 127902
 
5.9%
9 127587
 
5.9%
c 113271
 
5.2%
2 112849
 
5.2%
0 112671
 
5.2%
5 112590
 
5.2%
Other values (7) 786344
36.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2161512
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 240168
 
11.1%
4 172216
 
8.0%
8 128010
 
5.9%
a 127904
 
5.9%
b 127902
 
5.9%
9 127587
 
5.9%
c 113271
 
5.2%
2 112849
 
5.2%
0 112671
 
5.2%
5 112590
 
5.2%
Other values (7) 786344
36.4%

catalogNumber
Text

Missing 

Distinct54478
Distinct (%)> 99.9%
Missing5562
Missing (%)9.3%
Memory size469.2 KiB
2025-02-14T15:18:16.839038image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length9
Mean length9.00023862
Min length8

Characters and Unicode

Total characters490333
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

Unique54476 ?
Unique (%)> 99.9%

Sample

1st rowC0398633F
2nd rowC0392902F
3rd rowC0398629F
4th rowC0396329F
5th rowC0397990F
ValueCountFrequency (%)
c0002658f 2
 
< 0.1%
c0301944f 2
 
< 0.1%
c0002638f 2
 
< 0.1%
c0061753f 1
 
< 0.1%
c0397861f 1
 
< 0.1%
c0392934f 1
 
< 0.1%
c0344343f 1
 
< 0.1%
c0396454f 1
 
< 0.1%
c0397684f 1
 
< 0.1%
c0398629f 1
 
< 0.1%
Other values (54469) 54469
> 99.9%
2025-02-14T15:18:17.053303image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 112732
23.0%
C 54477
11.1%
F 54476
11.1%
1 50134
10.2%
3 36060
 
7.4%
6 32062
 
6.5%
5 29828
 
6.1%
9 27726
 
5.7%
2 25058
 
5.1%
7 23738
 
4.8%
Other values (14) 44042
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 490333
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 112732
23.0%
C 54477
11.1%
F 54476
11.1%
1 50134
10.2%
3 36060
 
7.4%
6 32062
 
6.5%
5 29828
 
6.1%
9 27726
 
5.7%
2 25058
 
5.1%
7 23738
 
4.8%
Other values (14) 44042
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 490333
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 112732
23.0%
C 54477
11.1%
F 54476
11.1%
1 50134
10.2%
3 36060
 
7.4%
6 32062
 
6.5%
5 29828
 
6.1%
9 27726
 
5.7%
2 25058
 
5.1%
7 23738
 
4.8%
Other values (14) 44042
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 490333
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 112732
23.0%
C 54477
11.1%
F 54476
11.1%
1 50134
10.2%
3 36060
 
7.4%
6 32062
 
6.5%
5 29828
 
6.1%
9 27726
 
5.7%
2 25058
 
5.1%
7 23738
 
4.8%
Other values (14) 44042
 
9.0%

recordNumber
Text

Missing 

Distinct26762
Distinct (%)51.6%
Missing8145
Missing (%)13.6%
Memory size469.2 KiB
2025-02-14T15:18:17.206896image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length23
Mean length4.597086537
Min length1

Characters and Unicode

Total characters238575
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

Unique21134 ?
Unique (%)40.7%

Sample

1st row3599
2nd row2400
3rd row3543
4th row7105
5th rows.n.
ValueCountFrequency (%)
s.n 8895
 
15.9%
nama 411
 
0.7%
a 354
 
0.6%
b 345
 
0.6%
262
 
0.5%
c 246
 
0.4%
d 207
 
0.4%
e 176
 
0.3%
f 152
 
0.3%
g 143
 
0.3%
Other values (24066) 44806
80.0%
2025-02-14T15:18:17.437384image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 33099
13.9%
2 22742
9.5%
5 18435
 
7.7%
. 18352
 
7.7%
0 17638
 
7.4%
3 17199
 
7.2%
6 15405
 
6.5%
4 14710
 
6.2%
9 14675
 
6.2%
7 14095
 
5.9%
Other values (73) 52225
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 238575
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 33099
13.9%
2 22742
9.5%
5 18435
 
7.7%
. 18352
 
7.7%
0 17638
 
7.4%
3 17199
 
7.2%
6 15405
 
6.5%
4 14710
 
6.2%
9 14675
 
6.2%
7 14095
 
5.9%
Other values (73) 52225
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 238575
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 33099
13.9%
2 22742
9.5%
5 18435
 
7.7%
. 18352
 
7.7%
0 17638
 
7.4%
3 17199
 
7.2%
6 15405
 
6.5%
4 14710
 
6.2%
9 14675
 
6.2%
7 14095
 
5.9%
Other values (73) 52225
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 238575
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 33099
13.9%
2 22742
9.5%
5 18435
 
7.7%
. 18352
 
7.7%
0 17638
 
7.4%
3 17199
 
7.2%
6 15405
 
6.5%
4 14710
 
6.2%
9 14675
 
6.2%
7 14095
 
5.9%
Other values (73) 52225
21.9%

recordedBy
Text

Missing 

Distinct3139
Distinct (%)5.4%
Missing1775
Missing (%)3.0%
Memory size469.2 KiB
2025-02-14T15:18:17.581315image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length46
Median length38
Mean length14.24119999
Min length3

Characters and Unicode

Total characters829792
Distinct characters87
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

Unique1443 ?
Unique (%)2.5%

Sample

1st rowF. Grewe & T. J. Widhelm
2nd rowT. J. Widhelm & F. Grewe
3rd rowF. Grewe & T. J. Widhelm
4th rowA. Bárcenas-Peña
5th rowW. R. Dudley
ValueCountFrequency (%)
a 14134
 
7.4%
c 9846
 
5.2%
t 9444
 
5.0%
h 9291
 
4.9%
w 9140
 
4.8%
p 8195
 
4.3%
7369
 
3.9%
e 7057
 
3.7%
r 6542
 
3.4%
j 5336
 
2.8%
Other values (2333) 104341
54.7%
2025-02-14T15:18:17.800238image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132428
 
16.0%
. 113844
 
13.7%
e 46877
 
5.6%
a 38694
 
4.7%
r 37741
 
4.5%
l 31344
 
3.8%
n 25967
 
3.1%
o 23500
 
2.8%
t 23092
 
2.8%
s 22130
 
2.7%
Other values (77) 334175
40.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 829792
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
132428
 
16.0%
. 113844
 
13.7%
e 46877
 
5.6%
a 38694
 
4.7%
r 37741
 
4.5%
l 31344
 
3.8%
n 25967
 
3.1%
o 23500
 
2.8%
t 23092
 
2.8%
s 22130
 
2.7%
Other values (77) 334175
40.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 829792
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
132428
 
16.0%
. 113844
 
13.7%
e 46877
 
5.6%
a 38694
 
4.7%
r 37741
 
4.5%
l 31344
 
3.8%
n 25967
 
3.1%
o 23500
 
2.8%
t 23092
 
2.8%
s 22130
 
2.7%
Other values (77) 334175
40.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 829792
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
132428
 
16.0%
. 113844
 
13.7%
e 46877
 
5.6%
a 38694
 
4.7%
r 37741
 
4.5%
l 31344
 
3.8%
n 25967
 
3.1%
o 23500
 
2.8%
t 23092
 
2.8%
s 22130
 
2.7%
Other values (77) 334175
40.3%

lifeStage
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing60039
Missing (%)> 99.9%
Memory size469.2 KiB
2025-02-14T15:18:17.845690image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.333333333
Min length7

Characters and Unicode

Total characters22
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

Unique3 ?
Unique (%)100.0%

Sample

1st rowimmature
2nd rowfertile
3rd rowsterile
ValueCountFrequency (%)
immature 1
33.3%
fertile 1
33.3%
sterile 1
33.3%
2025-02-14T15:18:17.937366image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5
22.7%
i 3
13.6%
t 3
13.6%
r 3
13.6%
m 2
 
9.1%
l 2
 
9.1%
a 1
 
4.5%
u 1
 
4.5%
f 1
 
4.5%
s 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5
22.7%
i 3
13.6%
t 3
13.6%
r 3
13.6%
m 2
 
9.1%
l 2
 
9.1%
a 1
 
4.5%
u 1
 
4.5%
f 1
 
4.5%
s 1
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5
22.7%
i 3
13.6%
t 3
13.6%
r 3
13.6%
m 2
 
9.1%
l 2
 
9.1%
a 1
 
4.5%
u 1
 
4.5%
f 1
 
4.5%
s 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5
22.7%
i 3
13.6%
t 3
13.6%
r 3
13.6%
m 2
 
9.1%
l 2
 
9.1%
a 1
 
4.5%
u 1
 
4.5%
f 1
 
4.5%
s 1
 
4.5%

associatedReferences
Text

Missing 

Distinct3158
Distinct (%)72.0%
Missing55656
Missing (%)92.7%
Memory size469.2 KiB
2025-02-14T15:18:18.073487image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length195
Median length165
Mean length46.60579115
Min length17

Characters and Unicode

Total characters204413
Distinct characters78
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

Unique2866 ?
Unique (%)65.3%

Sample

1st rowLichenes Minus Cognitae Exsiccati|244
2nd rowLichenes Minus Cognitae Exsiccati|387
3rd rowLichenes Minus Cognitae Exsiccati|666
4th rowLichenes Minus Cognitae Exsiccati|560
5th rowLichenes Minus Cognitae Exsiccati|673
ValueCountFrequency (%)
lichenes 2996
 
12.0%
exsiccati 1034
 
4.1%
lichens 879
 
3.5%
a 868
 
3.5%
of 866
 
3.5%
north 756
 
3.0%
american 729
 
2.9%
by 612
 
2.5%
cognitae 504
 
2.0%
minus 504
 
2.0%
Other values (2821) 15220
61.0%
2025-02-14T15:18:18.301313image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20696
 
10.1%
i 19699
 
9.6%
e 18863
 
9.2%
c 13458
 
6.6%
s 11843
 
5.8%
a 10958
 
5.4%
n 10763
 
5.3%
o 7245
 
3.5%
t 7197
 
3.5%
r 7056
 
3.5%
Other values (68) 76635
37.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 204413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
20696
 
10.1%
i 19699
 
9.6%
e 18863
 
9.2%
c 13458
 
6.6%
s 11843
 
5.8%
a 10958
 
5.4%
n 10763
 
5.3%
o 7245
 
3.5%
t 7197
 
3.5%
r 7056
 
3.5%
Other values (68) 76635
37.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 204413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
20696
 
10.1%
i 19699
 
9.6%
e 18863
 
9.2%
c 13458
 
6.6%
s 11843
 
5.8%
a 10958
 
5.4%
n 10763
 
5.3%
o 7245
 
3.5%
t 7197
 
3.5%
r 7056
 
3.5%
Other values (68) 76635
37.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 204413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
20696
 
10.1%
i 19699
 
9.6%
e 18863
 
9.2%
c 13458
 
6.6%
s 11843
 
5.8%
a 10958
 
5.4%
n 10763
 
5.3%
o 7245
 
3.5%
t 7197
 
3.5%
r 7056
 
3.5%
Other values (68) 76635
37.5%

occurrenceRemarks
Text

Missing 

Distinct1569
Distinct (%)75.7%
Missing57970
Missing (%)96.5%
Memory size469.2 KiB
2025-02-14T15:18:18.449476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1200
Median length191
Mean length43.94111969
Min length2

Characters and Unicode

Total characters91046
Distinct characters96
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

Unique1427 ?
Unique (%)68.9%

Sample

1st rowBy side of trail from upper parking lot near lodge
2nd rowOriginally collected as part of the "Flore du Rwanda" from the Institut National de la Recherche Scientific Butare.
3rd rowExact coordinates from iNaturalist: 37.94850158, -90.93019867
4th rowExact coordinates from iNaturalist: 37.94881644, -90.9302269
5th rowVoucher, PdL CH2876 lodged in UNITEC (now UNITEC 7631).
ValueCountFrequency (%)
of 358
 
2.5%
the 350
 
2.5%
lichenes 346
 
2.5%
in 291
 
2.1%
exsiccati 245
 
1.7%
208
 
1.5%
by 192
 
1.4%
and 160
 
1.1%
on 158
 
1.1%
for 141
 
1.0%
Other values (3344) 11624
82.6%
2025-02-14T15:18:18.750364image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12122
 
13.3%
e 6757
 
7.4%
i 5904
 
6.5%
a 5388
 
5.9%
o 4682
 
5.1%
n 4668
 
5.1%
s 3992
 
4.4%
t 3962
 
4.4%
c 3623
 
4.0%
r 3473
 
3.8%
Other values (86) 36475
40.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 91046
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
12122
 
13.3%
e 6757
 
7.4%
i 5904
 
6.5%
a 5388
 
5.9%
o 4682
 
5.1%
n 4668
 
5.1%
s 3992
 
4.4%
t 3962
 
4.4%
c 3623
 
4.0%
r 3473
 
3.8%
Other values (86) 36475
40.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 91046
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
12122
 
13.3%
e 6757
 
7.4%
i 5904
 
6.5%
a 5388
 
5.9%
o 4682
 
5.1%
n 4668
 
5.1%
s 3992
 
4.4%
t 3962
 
4.4%
c 3623
 
4.0%
r 3473
 
3.8%
Other values (86) 36475
40.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 91046
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
12122
 
13.3%
e 6757
 
7.4%
i 5904
 
6.5%
a 5388
 
5.9%
o 4682
 
5.1%
n 4668
 
5.1%
s 3992
 
4.4%
t 3962
 
4.4%
c 3623
 
4.0%
r 3473
 
3.8%
Other values (86) 36475
40.1%

organismID
Text

Unique 

Distinct60042
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:18.909249image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.752273409
Min length4

Characters and Unicode

Total characters405420
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

Unique60042 ?
Unique (%)100.0%

Sample

1st row4422794
2nd row4441879
3rd row4422790
4th row4392296
5th row4423110
ValueCountFrequency (%)
4422794 1
 
< 0.1%
4422678 1
 
< 0.1%
4391387 1
 
< 0.1%
4391559 1
 
< 0.1%
4422786 1
 
< 0.1%
4444307 1
 
< 0.1%
4441911 1
 
< 0.1%
4422790 1
 
< 0.1%
4392296 1
 
< 0.1%
4423110 1
 
< 0.1%
Other values (60032) 60032
> 99.9%
2025-02-14T15:18:19.129374image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 107482
26.5%
1 49217
12.1%
4 44853
11.1%
5 34842
 
8.6%
0 31795
 
7.8%
2 28843
 
7.1%
9 28256
 
7.0%
8 27412
 
6.8%
6 27291
 
6.7%
7 25429
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 405420
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 107482
26.5%
1 49217
12.1%
4 44853
11.1%
5 34842
 
8.6%
0 31795
 
7.8%
2 28843
 
7.1%
9 28256
 
7.0%
8 27412
 
6.8%
6 27291
 
6.7%
7 25429
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 405420
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 107482
26.5%
1 49217
12.1%
4 44853
11.1%
5 34842
 
8.6%
0 31795
 
7.8%
2 28843
 
7.1%
9 28256
 
7.0%
8 27412
 
6.8%
6 27291
 
6.7%
7 25429
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 405420
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 107482
26.5%
1 49217
12.1%
4 44853
11.1%
5 34842
 
8.6%
0 31795
 
7.8%
2 28843
 
7.1%
9 28256
 
7.0%
8 27412
 
6.8%
6 27291
 
6.7%
7 25429
 
6.3%

organismRemarks
Text

Missing 

Distinct76
Distinct (%)82.6%
Missing59950
Missing (%)99.8%
Memory size469.2 KiB
2025-02-14T15:18:19.200698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length229
Median length60.5
Mean length33.09782609
Min length6

Characters and Unicode

Total characters3045
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

Unique69 ?
Unique (%)75.0%

Sample

1st rowParking area
2nd rowMost likely is this species, but need "C" reagent spot test to verify.
3rd rowMed UV-
4th rowParking area
5th rowParking area
ValueCountFrequency (%)
in 16
 
3.3%
green 13
 
2.7%
a 11
 
2.3%
thallus 10
 
2.1%
lichen 9
 
1.9%
with 8
 
1.6%
white 8
 
1.6%
to 8
 
1.6%
terrestrial 7
 
1.4%
on 7
 
1.4%
Other values (250) 389
80.0%
2025-02-14T15:18:19.317337image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
394
12.9%
e 288
 
9.5%
i 199
 
6.5%
a 192
 
6.3%
r 185
 
6.1%
l 176
 
5.8%
t 172
 
5.6%
n 159
 
5.2%
s 156
 
5.1%
o 149
 
4.9%
Other values (61) 975
32.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3045
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
394
12.9%
e 288
 
9.5%
i 199
 
6.5%
a 192
 
6.3%
r 185
 
6.1%
l 176
 
5.8%
t 172
 
5.6%
n 159
 
5.2%
s 156
 
5.1%
o 149
 
4.9%
Other values (61) 975
32.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3045
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
394
12.9%
e 288
 
9.5%
i 199
 
6.5%
a 192
 
6.3%
r 185
 
6.1%
l 176
 
5.8%
t 172
 
5.6%
n 159
 
5.2%
s 156
 
5.1%
o 149
 
4.9%
Other values (61) 975
32.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3045
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
394
12.9%
e 288
 
9.5%
i 199
 
6.5%
a 192
 
6.3%
r 185
 
6.1%
l 176
 
5.8%
t 172
 
5.6%
n 159
 
5.2%
s 156
 
5.1%
o 149
 
4.9%
Other values (61) 975
32.0%

fieldNumber
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing60041
Missing (%)> 99.9%
Memory size469.2 KiB
2025-02-14T15:18:19.347371image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
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 row818
ValueCountFrequency (%)
818 1
100.0%
2025-02-14T15:18:19.431897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 2
66.7%
1 1
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 2
66.7%
1 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 2
66.7%
1 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 2
66.7%
1 1
33.3%

year
Text

Missing 

Distinct228
Distinct (%)0.4%
Missing7047
Missing (%)11.7%
Memory size469.2 KiB
2025-02-14T15:18:19.560009image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters211980
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

Unique13 ?
Unique (%)< 0.1%

Sample

1st row2017
2nd row2016
3rd row2017
4th row2017
5th row1895
ValueCountFrequency (%)
2003 2125
 
4.0%
2004 1871
 
3.5%
2001 1811
 
3.4%
2002 1658
 
3.1%
1949 1566
 
3.0%
1939 1399
 
2.6%
1947 1301
 
2.5%
1948 1269
 
2.4%
1936 1195
 
2.3%
1945 981
 
1.9%
Other values (218) 37819
71.4%
2025-02-14T15:18:19.752630image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 50653
23.9%
9 43978
20.7%
0 31091
14.7%
2 22119
10.4%
4 15396
 
7.3%
8 13163
 
6.2%
3 12898
 
6.1%
7 8627
 
4.1%
5 7512
 
3.5%
6 6543
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 211980
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 50653
23.9%
9 43978
20.7%
0 31091
14.7%
2 22119
10.4%
4 15396
 
7.3%
8 13163
 
6.2%
3 12898
 
6.1%
7 8627
 
4.1%
5 7512
 
3.5%
6 6543
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 211980
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 50653
23.9%
9 43978
20.7%
0 31091
14.7%
2 22119
10.4%
4 15396
 
7.3%
8 13163
 
6.2%
3 12898
 
6.1%
7 8627
 
4.1%
5 7512
 
3.5%
6 6543
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 211980
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 50653
23.9%
9 43978
20.7%
0 31091
14.7%
2 22119
10.4%
4 15396
 
7.3%
8 13163
 
6.2%
3 12898
 
6.1%
7 8627
 
4.1%
5 7512
 
3.5%
6 6543
 
3.1%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing10869
Missing (%)18.1%
Memory size469.2 KiB
2025-02-14T15:18:19.798224image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.199682753
Min length1

Characters and Unicode

Total characters58992
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 row11
2nd row1
3rd row11
4th row8
5th row2
ValueCountFrequency (%)
7 6996
14.2%
8 6338
12.9%
10 5578
11.3%
6 5207
10.6%
3 4331
8.8%
5 3943
8.0%
9 3799
7.7%
4 3444
7.0%
1 2831
5.8%
11 2473
 
5.0%
Other values (2) 4233
8.6%
2025-02-14T15:18:19.887164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15123
25.6%
7 6996
11.9%
8 6338
10.7%
0 5578
 
9.5%
6 5207
 
8.8%
3 4331
 
7.3%
2 4233
 
7.2%
5 3943
 
6.7%
9 3799
 
6.4%
4 3444
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 58992
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 15123
25.6%
7 6996
11.9%
8 6338
10.7%
0 5578
 
9.5%
6 5207
 
8.8%
3 4331
 
7.3%
2 4233
 
7.2%
5 3943
 
6.7%
9 3799
 
6.4%
4 3444
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 58992
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 15123
25.6%
7 6996
11.9%
8 6338
10.7%
0 5578
 
9.5%
6 5207
 
8.8%
3 4331
 
7.3%
2 4233
 
7.2%
5 3943
 
6.7%
9 3799
 
6.4%
4 3444
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 58992
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 15123
25.6%
7 6996
11.9%
8 6338
10.7%
0 5578
 
9.5%
6 5207
 
8.8%
3 4331
 
7.3%
2 4233
 
7.2%
5 3943
 
6.7%
9 3799
 
6.4%
4 3444
 
5.8%

day
Text

Missing 

Distinct31
Distinct (%)0.1%
Missing16706
Missing (%)27.8%
Memory size469.2 KiB
2025-02-14T15:18:19.931418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.686842348
Min length1

Characters and Unicode

Total characters73101
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 row15
2nd row25
3rd row14
4th row17
5th row12
ValueCountFrequency (%)
1 2327
 
5.4%
15 1835
 
4.2%
8 1781
 
4.1%
20 1730
 
4.0%
7 1698
 
3.9%
12 1675
 
3.9%
10 1614
 
3.7%
11 1590
 
3.7%
9 1570
 
3.6%
13 1558
 
3.6%
Other values (21) 25958
59.9%
2025-02-14T15:18:20.034484image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20833
28.5%
2 16894
23.1%
3 6163
 
8.4%
0 4717
 
6.5%
7 4517
 
6.2%
8 4367
 
6.0%
6 4083
 
5.6%
5 4075
 
5.6%
9 3832
 
5.2%
4 3620
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 73101
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 20833
28.5%
2 16894
23.1%
3 6163
 
8.4%
0 4717
 
6.5%
7 4517
 
6.2%
8 4367
 
6.0%
6 4083
 
5.6%
5 4075
 
5.6%
9 3832
 
5.2%
4 3620
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 73101
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 20833
28.5%
2 16894
23.1%
3 6163
 
8.4%
0 4717
 
6.5%
7 4517
 
6.2%
8 4367
 
6.0%
6 4083
 
5.6%
5 4075
 
5.6%
9 3832
 
5.2%
4 3620
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 73101
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 20833
28.5%
2 16894
23.1%
3 6163
 
8.4%
0 4717
 
6.5%
7 4517
 
6.2%
8 4367
 
6.0%
6 4083
 
5.6%
5 4075
 
5.6%
9 3832
 
5.2%
4 3620
 
5.0%

verbatimEventDate
Text

Missing 

Distinct326
Distinct (%)34.8%
Missing59104
Missing (%)98.4%
Memory size469.2 KiB
2025-02-14T15:18:20.083655image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length76
Median length4
Mean length6.5
Min length3

Characters and Unicode

Total characters6097
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

Unique252 ?
Unique (%)26.9%

Sample

1st rows.d.
2nd rows.d.
3rd rows.d.
4th rows.d.
5th rows.d.
ValueCountFrequency (%)
s.d 499
47.7%
winter 19
 
1.8%
summer 8
 
0.8%
oct 6
 
0.6%
1976-07-00 5
 
0.5%
6/10/1976 5
 
0.5%
5/12/2007 5
 
0.5%
4
 
0.4%
spring 4
 
0.4%
1975-02-00 4
 
0.4%
Other values (364) 487
46.6%
2025-02-14T15:18:20.199284image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1040
17.1%
s 517
 
8.5%
d 509
 
8.3%
1 474
 
7.8%
/ 378
 
6.2%
9 362
 
5.9%
- 314
 
5.2%
0 299
 
4.9%
2 271
 
4.4%
8 219
 
3.6%
Other values (51) 1714
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6097
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 1040
17.1%
s 517
 
8.5%
d 509
 
8.3%
1 474
 
7.8%
/ 378
 
6.2%
9 362
 
5.9%
- 314
 
5.2%
0 299
 
4.9%
2 271
 
4.4%
8 219
 
3.6%
Other values (51) 1714
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6097
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 1040
17.1%
s 517
 
8.5%
d 509
 
8.3%
1 474
 
7.8%
/ 378
 
6.2%
9 362
 
5.9%
- 314
 
5.2%
0 299
 
4.9%
2 271
 
4.4%
8 219
 
3.6%
Other values (51) 1714
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6097
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 1040
17.1%
s 517
 
8.5%
d 509
 
8.3%
1 474
 
7.8%
/ 378
 
6.2%
9 362
 
5.9%
- 314
 
5.2%
0 299
 
4.9%
2 271
 
4.4%
8 219
 
3.6%
Other values (51) 1714
28.1%

habitat
Text

Missing 

Distinct11725
Distinct (%)37.8%
Missing29062
Missing (%)48.4%
Memory size469.2 KiB
2025-02-14T15:18:20.334149image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length254
Median length181
Mean length32.15823112
Min length3

Characters and Unicode

Total characters996262
Distinct characters97
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

Unique8662 ?
Unique (%)28.0%

Sample

1st rowOld growth Beech forest
2nd rowTemperate rain forest
3rd rowBeech Forest
4th rowXerophytic scrub
5th rowMixed scrub
ValueCountFrequency (%)
on 17689
 
11.1%
forest 6604
 
4.1%
and 4666
 
2.9%
bark 3979
 
2.5%
of 3612
 
2.3%
tree 2849
 
1.8%
trunk 2213
 
1.4%
with 2163
 
1.4%
trees 2055
 
1.3%
rocks 2051
 
1.3%
Other values (6399) 112189
70.1%
2025-02-14T15:18:20.543781image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
129156
13.0%
e 89428
 
9.0%
o 74882
 
7.5%
r 67436
 
6.8%
a 67273
 
6.8%
n 64315
 
6.5%
s 62261
 
6.2%
t 50246
 
5.0%
i 45334
 
4.6%
d 37658
 
3.8%
Other values (87) 308273
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 996262
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
129156
13.0%
e 89428
 
9.0%
o 74882
 
7.5%
r 67436
 
6.8%
a 67273
 
6.8%
n 64315
 
6.5%
s 62261
 
6.2%
t 50246
 
5.0%
i 45334
 
4.6%
d 37658
 
3.8%
Other values (87) 308273
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 996262
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
129156
13.0%
e 89428
 
9.0%
o 74882
 
7.5%
r 67436
 
6.8%
a 67273
 
6.8%
n 64315
 
6.5%
s 62261
 
6.2%
t 50246
 
5.0%
i 45334
 
4.6%
d 37658
 
3.8%
Other values (87) 308273
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 996262
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
129156
13.0%
e 89428
 
9.0%
o 74882
 
7.5%
r 67436
 
6.8%
a 67273
 
6.8%
n 64315
 
6.5%
s 62261
 
6.2%
t 50246
 
5.0%
i 45334
 
4.6%
d 37658
 
3.8%
Other values (87) 308273
30.9%

continent
Text

Missing 

Distinct11
Distinct (%)< 0.1%
Missing2334
Missing (%)3.9%
Memory size469.2 KiB
2025-02-14T15:18:20.584008image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.71582796
Min length4

Characters and Unicode

Total characters618389
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 rowNorth America
2nd rowEurope
3rd rowNorth America
4th rowNorth America
5th rowEurope
ValueCountFrequency (%)
america 39920
40.9%
north 36812
37.7%
europe 8823
 
9.0%
asia 5560
 
5.7%
south 3108
 
3.2%
oceania 2909
 
3.0%
africa 267
 
0.3%
antarctica 224
 
0.2%
unknown 6
 
< 0.1%
or 1
 
< 0.1%
2025-02-14T15:18:20.675028image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 86000
13.9%
a 51989
8.4%
e 51629
8.3%
i 48856
7.9%
o 48727
7.9%
A 45995
 
7.4%
c 43520
 
7.0%
t 40345
 
6.5%
39922
 
6.5%
h 39897
 
6.5%
Other values (20) 121509
19.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 618389
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 86000
13.9%
a 51989
8.4%
e 51629
8.3%
i 48856
7.9%
o 48727
7.9%
A 45995
 
7.4%
c 43520
 
7.0%
t 40345
 
6.5%
39922
 
6.5%
h 39897
 
6.5%
Other values (20) 121509
19.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 618389
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 86000
13.9%
a 51989
8.4%
e 51629
8.3%
i 48856
7.9%
o 48727
7.9%
A 45995
 
7.4%
c 43520
 
7.0%
t 40345
 
6.5%
39922
 
6.5%
h 39897
 
6.5%
Other values (20) 121509
19.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 618389
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 86000
13.9%
a 51989
8.4%
e 51629
8.3%
i 48856
7.9%
o 48727
7.9%
A 45995
 
7.4%
c 43520
 
7.0%
t 40345
 
6.5%
39922
 
6.5%
h 39897
 
6.5%
Other values (20) 121509
19.6%

islandGroup
Text

Missing 

Distinct79
Distinct (%)2.1%
Missing56285
Missing (%)93.7%
Memory size469.2 KiB
2025-02-14T15:18:20.721464image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length46
Median length34
Mean length13.62949162
Min length4

Characters and Unicode

Total characters51206
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

Unique22 ?
Unique (%)0.6%

Sample

1st rowAotearoa (New Zealand Archipelago)
2nd rowWest Indies
3rd rowWest Indies
4th rowJapanese Archipelago
5th rowJapanese Archipelago
ValueCountFrequency (%)
islands 1376
19.3%
azores 499
 
7.0%
indies 446
 
6.2%
west 446
 
6.2%
fiji 441
 
6.2%
phillipines 397
 
5.6%
archipelago 276
 
3.9%
south 270
 
3.8%
philippine 262
 
3.7%
shetland 241
 
3.4%
Other values (102) 2483
34.8%
2025-02-14T15:18:20.825610image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 5117
 
10.0%
i 4514
 
8.8%
a 4387
 
8.6%
n 4189
 
8.2%
e 4186
 
8.2%
l 3845
 
7.5%
3380
 
6.6%
d 2482
 
4.8%
h 1914
 
3.7%
I 1890
 
3.7%
Other values (48) 15302
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51206
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 5117
 
10.0%
i 4514
 
8.8%
a 4387
 
8.6%
n 4189
 
8.2%
e 4186
 
8.2%
l 3845
 
7.5%
3380
 
6.6%
d 2482
 
4.8%
h 1914
 
3.7%
I 1890
 
3.7%
Other values (48) 15302
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51206
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 5117
 
10.0%
i 4514
 
8.8%
a 4387
 
8.6%
n 4189
 
8.2%
e 4186
 
8.2%
l 3845
 
7.5%
3380
 
6.6%
d 2482
 
4.8%
h 1914
 
3.7%
I 1890
 
3.7%
Other values (48) 15302
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51206
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 5117
 
10.0%
i 4514
 
8.8%
a 4387
 
8.6%
n 4189
 
8.2%
e 4186
 
8.2%
l 3845
 
7.5%
3380
 
6.6%
d 2482
 
4.8%
h 1914
 
3.7%
I 1890
 
3.7%
Other values (48) 15302
29.9%

island
Text

Missing 

Distinct254
Distinct (%)5.8%
Missing55634
Missing (%)92.7%
Memory size469.2 KiB
2025-02-14T15:18:20.949826image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length27
Mean length9.987976407
Min length3

Characters and Unicode

Total characters44027
Distinct characters64
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

Unique90 ?
Unique (%)2.0%

Sample

1st rowIsla Chiloé
2nd rowNorth Island (Te Ika-a-Maui)
3rd rowHonshu
4th rowHonshu
5th rowHonshu
ValueCountFrequency (%)
island 1303
18.4%
luzon 605
 
8.5%
viti 441
 
6.2%
levu 441
 
6.2%
terceira 318
 
4.5%
livingston 226
 
3.2%
north 226
 
3.2%
taveuni 150
 
2.1%
kadavu 148
 
2.1%
honshu 114
 
1.6%
Other values (270) 3114
43.9%
2025-02-14T15:18:21.149015image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4890
 
11.1%
n 3997
 
9.1%
i 3042
 
6.9%
e 2749
 
6.2%
2678
 
6.1%
o 2580
 
5.9%
l 2371
 
5.4%
s 2294
 
5.2%
u 2030
 
4.6%
r 1833
 
4.2%
Other values (54) 15563
35.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 44027
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4890
 
11.1%
n 3997
 
9.1%
i 3042
 
6.9%
e 2749
 
6.2%
2678
 
6.1%
o 2580
 
5.9%
l 2371
 
5.4%
s 2294
 
5.2%
u 2030
 
4.6%
r 1833
 
4.2%
Other values (54) 15563
35.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 44027
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4890
 
11.1%
n 3997
 
9.1%
i 3042
 
6.9%
e 2749
 
6.2%
2678
 
6.1%
o 2580
 
5.9%
l 2371
 
5.4%
s 2294
 
5.2%
u 2030
 
4.6%
r 1833
 
4.2%
Other values (54) 15563
35.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 44027
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4890
 
11.1%
n 3997
 
9.1%
i 3042
 
6.9%
e 2749
 
6.2%
2678
 
6.1%
o 2580
 
5.9%
l 2371
 
5.4%
s 2294
 
5.2%
u 2030
 
4.6%
r 1833
 
4.2%
Other values (54) 15563
35.3%

country
Text

Missing 

Distinct157
Distinct (%)0.3%
Missing2743
Missing (%)4.6%
Memory size469.2 KiB
2025-02-14T15:18:21.201098image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length37
Median length35
Mean length14.52803714
Min length3

Characters and Unicode

Total characters832442
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

Unique27 ?
Unique (%)< 0.1%

Sample

1st rowUnited States of America
2nd rowNorway
3rd rowUnited States of America
4th rowUnited States of America
5th rowNorway
ValueCountFrequency (%)
united 24946
18.3%
of 24776
18.2%
states 24773
18.2%
america 24760
18.2%
canada 4530
 
3.3%
costa 2820
 
2.1%
rica 2820
 
2.1%
sweden 2738
 
2.0%
taiwan 1830
 
1.3%
honduras 1673
 
1.2%
Other values (171) 20423
15.0%
2025-02-14T15:18:21.319696image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 95374
11.5%
e 89152
 
10.7%
t 83372
 
10.0%
78790
 
9.5%
i 68598
 
8.2%
n 44135
 
5.3%
d 36876
 
4.4%
r 35430
 
4.3%
s 33043
 
4.0%
o 32567
 
3.9%
Other values (48) 235105
28.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 832442
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 95374
11.5%
e 89152
 
10.7%
t 83372
 
10.0%
78790
 
9.5%
i 68598
 
8.2%
n 44135
 
5.3%
d 36876
 
4.4%
r 35430
 
4.3%
s 33043
 
4.0%
o 32567
 
3.9%
Other values (48) 235105
28.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 832442
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 95374
11.5%
e 89152
 
10.7%
t 83372
 
10.0%
78790
 
9.5%
i 68598
 
8.2%
n 44135
 
5.3%
d 36876
 
4.4%
r 35430
 
4.3%
s 33043
 
4.0%
o 32567
 
3.9%
Other values (48) 235105
28.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 832442
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 95374
11.5%
e 89152
 
10.7%
t 83372
 
10.0%
78790
 
9.5%
i 68598
 
8.2%
n 44135
 
5.3%
d 36876
 
4.4%
r 35430
 
4.3%
s 33043
 
4.0%
o 32567
 
3.9%
Other values (48) 235105
28.2%

stateProvince
Text

Missing 

Distinct885
Distinct (%)1.9%
Missing13152
Missing (%)21.9%
Memory size469.2 KiB
2025-02-14T15:18:21.460200image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length34
Median length26
Mean length9.176796758
Min length3

Characters and Unicode

Total characters430300
Distinct characters86
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

Unique232 ?
Unique (%)0.5%

Sample

1st rowCalifornia
2nd rowSvalbard
3rd rowAlaska
4th rowCalifornia
5th rowSvalbard
ValueCountFrequency (%)
california 5091
 
9.0%
florida 2637
 
4.7%
ontario 2283
 
4.0%
new 1919
 
3.4%
washington 1708
 
3.0%
carolina 1394
 
2.5%
illinois 1303
 
2.3%
north 1292
 
2.3%
massachusetts 1168
 
2.1%
queensland 1090
 
1.9%
Other values (942) 36535
64.8%
2025-02-14T15:18:21.677013image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 59526
13.8%
i 40072
 
9.3%
n 39328
 
9.1%
o 34611
 
8.0%
r 28798
 
6.7%
s 23005
 
5.3%
e 22342
 
5.2%
l 20119
 
4.7%
t 17424
 
4.0%
u 11720
 
2.7%
Other values (76) 133355
31.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 430300
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 59526
13.8%
i 40072
 
9.3%
n 39328
 
9.1%
o 34611
 
8.0%
r 28798
 
6.7%
s 23005
 
5.3%
e 22342
 
5.2%
l 20119
 
4.7%
t 17424
 
4.0%
u 11720
 
2.7%
Other values (76) 133355
31.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 430300
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 59526
13.8%
i 40072
 
9.3%
n 39328
 
9.1%
o 34611
 
8.0%
r 28798
 
6.7%
s 23005
 
5.3%
e 22342
 
5.2%
l 20119
 
4.7%
t 17424
 
4.0%
u 11720
 
2.7%
Other values (76) 133355
31.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 430300
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 59526
13.8%
i 40072
 
9.3%
n 39328
 
9.1%
o 34611
 
8.0%
r 28798
 
6.7%
s 23005
 
5.3%
e 22342
 
5.2%
l 20119
 
4.7%
t 17424
 
4.0%
u 11720
 
2.7%
Other values (76) 133355
31.0%

county
Text

Missing 

Distinct1438
Distinct (%)5.5%
Missing33990
Missing (%)56.6%
Memory size469.2 KiB
2025-02-14T15:18:21.826206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length41
Median length26
Mean length7.846537694
Min length3

Characters and Unicode

Total characters204418
Distinct characters79
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

Unique500 ?
Unique (%)1.9%

Sample

1st rowSanta Cruz
2nd rowAleutians West
3rd rowMonterey
4th rowLake
5th rowSan Diego
ValueCountFrequency (%)
bay 1936
 
6.0%
thunder 1930
 
6.0%
san 977
 
3.0%
santa 883
 
2.7%
duval 634
 
2.0%
clara 559
 
1.7%
hualien 458
 
1.4%
marin 412
 
1.3%
nantou 407
 
1.3%
taichung 402
 
1.2%
Other values (1510) 23645
73.3%
2025-02-14T15:18:22.039370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 24595
 
12.0%
e 17228
 
8.4%
n 16716
 
8.2%
o 14217
 
7.0%
r 12891
 
6.3%
i 10626
 
5.2%
l 9799
 
4.8%
u 8817
 
4.3%
t 8300
 
4.1%
s 7463
 
3.7%
Other values (69) 73766
36.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 204418
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 24595
 
12.0%
e 17228
 
8.4%
n 16716
 
8.2%
o 14217
 
7.0%
r 12891
 
6.3%
i 10626
 
5.2%
l 9799
 
4.8%
u 8817
 
4.3%
t 8300
 
4.1%
s 7463
 
3.7%
Other values (69) 73766
36.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 204418
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 24595
 
12.0%
e 17228
 
8.4%
n 16716
 
8.2%
o 14217
 
7.0%
r 12891
 
6.3%
i 10626
 
5.2%
l 9799
 
4.8%
u 8817
 
4.3%
t 8300
 
4.1%
s 7463
 
3.7%
Other values (69) 73766
36.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 204418
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 24595
 
12.0%
e 17228
 
8.4%
n 16716
 
8.2%
o 14217
 
7.0%
r 12891
 
6.3%
i 10626
 
5.2%
l 9799
 
4.8%
u 8817
 
4.3%
t 8300
 
4.1%
s 7463
 
3.7%
Other values (69) 73766
36.1%

municipality
Text

Missing 

Distinct1139
Distinct (%)14.5%
Missing52197
Missing (%)86.9%
Memory size469.2 KiB
2025-02-14T15:18:22.186340image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length42
Median length25
Mean length9.070618228
Min length3

Characters and Unicode

Total characters71159
Distinct characters86
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

Unique554 ?
Unique (%)7.1%

Sample

1st rowPacific Grove
2nd rowSan Pedro
3rd rowNahant
4th rowGlenfield
5th rowSanta Barbara
ValueCountFrequency (%)
san 553
 
5.1%
jacksonville 447
 
4.1%
new 260
 
2.4%
bedford 256
 
2.3%
pilar 234
 
2.1%
athens 207
 
1.9%
irosin 167
 
1.5%
eustis 149
 
1.4%
la 134
 
1.2%
juan 130
 
1.2%
Other values (1253) 8401
76.8%
2025-02-14T15:18:22.471482image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 7195
 
10.1%
o 5865
 
8.2%
e 5778
 
8.1%
n 5224
 
7.3%
l 4722
 
6.6%
r 4193
 
5.9%
i 3784
 
5.3%
s 3270
 
4.6%
3093
 
4.3%
t 2752
 
3.9%
Other values (76) 25283
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 71159
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 7195
 
10.1%
o 5865
 
8.2%
e 5778
 
8.1%
n 5224
 
7.3%
l 4722
 
6.6%
r 4193
 
5.9%
i 3784
 
5.3%
s 3270
 
4.6%
3093
 
4.3%
t 2752
 
3.9%
Other values (76) 25283
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 71159
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 7195
 
10.1%
o 5865
 
8.2%
e 5778
 
8.1%
n 5224
 
7.3%
l 4722
 
6.6%
r 4193
 
5.9%
i 3784
 
5.3%
s 3270
 
4.6%
3093
 
4.3%
t 2752
 
3.9%
Other values (76) 25283
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 71159
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 7195
 
10.1%
o 5865
 
8.2%
e 5778
 
8.1%
n 5224
 
7.3%
l 4722
 
6.6%
r 4193
 
5.9%
i 3784
 
5.3%
s 3270
 
4.6%
3093
 
4.3%
t 2752
 
3.9%
Other values (76) 25283
35.5%

locality
Text

Missing 

Distinct12586
Distinct (%)28.6%
Missing16084
Missing (%)26.8%
Memory size469.2 KiB
2025-02-14T15:18:22.619058image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length258
Median length184
Mean length43.55882888
Min length2

Characters and Unicode

Total characters1914759
Distinct characters133
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

Unique7990 ?
Unique (%)18.2%

Sample

1st rowStanford University, Stock Farm
2nd rowPacific Grove
3rd rowsummit of Hart Mt.
4th rowMonte Aymond
5th rowGreat Smoky Mountains National Park, Queens Trail, near Smokemont campground
ValueCountFrequency (%)
of 19372
 
6.2%
km 7422
 
2.4%
near 5932
 
1.9%
park 5023
 
1.6%
road 4685
 
1.5%
san 4153
 
1.3%
to 4135
 
1.3%
national 3510
 
1.1%
area 3358
 
1.1%
station 3267
 
1.0%
Other values (15136) 253390
80.6%
2025-02-14T15:18:22.834062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270320
14.1%
a 178774
 
9.3%
o 139998
 
7.3%
e 134544
 
7.0%
n 111038
 
5.8%
r 106444
 
5.6%
i 97640
 
5.1%
t 93831
 
4.9%
l 69439
 
3.6%
s 69363
 
3.6%
Other values (123) 643368
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1914759
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
270320
14.1%
a 178774
 
9.3%
o 139998
 
7.3%
e 134544
 
7.0%
n 111038
 
5.8%
r 106444
 
5.6%
i 97640
 
5.1%
t 93831
 
4.9%
l 69439
 
3.6%
s 69363
 
3.6%
Other values (123) 643368
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1914759
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
270320
14.1%
a 178774
 
9.3%
o 139998
 
7.3%
e 134544
 
7.0%
n 111038
 
5.8%
r 106444
 
5.6%
i 97640
 
5.1%
t 93831
 
4.9%
l 69439
 
3.6%
s 69363
 
3.6%
Other values (123) 643368
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1914759
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
270320
14.1%
a 178774
 
9.3%
o 139998
 
7.3%
e 134544
 
7.0%
n 111038
 
5.8%
r 106444
 
5.6%
i 97640
 
5.1%
t 93831
 
4.9%
l 69439
 
3.6%
s 69363
 
3.6%
Other values (123) 643368
33.6%
Distinct1125
Distinct (%)4.7%
Missing36294
Missing (%)60.4%
Memory size469.2 KiB
2025-02-14T15:18:22.975291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.226376958
Min length1

Characters and Unicode

Total characters76620
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

Unique344 ?
Unique (%)1.4%

Sample

1st row851
2nd row339
3rd row139
4th row2240
5th row201
ValueCountFrequency (%)
100 917
 
3.9%
0 875
 
3.7%
1500 731
 
3.1%
700 728
 
3.1%
800 523
 
2.2%
50 509
 
2.1%
1200 494
 
2.1%
1 454
 
1.9%
1600 449
 
1.9%
1100 424
 
1.8%
Other values (1115) 17644
74.3%
2025-02-14T15:18:23.174048image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27065
35.3%
1 12208
15.9%
2 7744
 
10.1%
5 6920
 
9.0%
3 5688
 
7.4%
4 3791
 
4.9%
7 3636
 
4.7%
6 3512
 
4.6%
8 3350
 
4.4%
9 2704
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 76620
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 27065
35.3%
1 12208
15.9%
2 7744
 
10.1%
5 6920
 
9.0%
3 5688
 
7.4%
4 3791
 
4.9%
7 3636
 
4.7%
6 3512
 
4.6%
8 3350
 
4.4%
9 2704
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 76620
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 27065
35.3%
1 12208
15.9%
2 7744
 
10.1%
5 6920
 
9.0%
3 5688
 
7.4%
4 3791
 
4.9%
7 3636
 
4.7%
6 3512
 
4.6%
8 3350
 
4.4%
9 2704
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 76620
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 27065
35.3%
1 12208
15.9%
2 7744
 
10.1%
5 6920
 
9.0%
3 5688
 
7.4%
4 3791
 
4.9%
7 3636
 
4.7%
6 3512
 
4.6%
8 3350
 
4.4%
9 2704
 
3.5%
Distinct486
Distinct (%)6.2%
Missing52179
Missing (%)86.9%
Memory size469.2 KiB
2025-02-14T15:18:23.311890image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.3035737
Min length1

Characters and Unicode

Total characters25976
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

Unique162 ?
Unique (%)2.1%

Sample

1st row851
2nd row139
3rd row2240
4th row201
5th row2311
ValueCountFrequency (%)
10 484
 
6.2%
900 453
 
5.8%
800 330
 
4.2%
1400 259
 
3.3%
1300 252
 
3.2%
600 207
 
2.6%
1600 198
 
2.5%
1000 184
 
2.3%
710 180
 
2.3%
100 146
 
1.9%
Other values (476) 5170
65.8%
2025-02-14T15:18:23.511068image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10224
39.4%
1 4514
17.4%
2 2226
 
8.6%
5 1905
 
7.3%
3 1577
 
6.1%
4 1248
 
4.8%
8 1137
 
4.4%
6 1126
 
4.3%
9 1084
 
4.2%
7 934
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25976
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 10224
39.4%
1 4514
17.4%
2 2226
 
8.6%
5 1905
 
7.3%
3 1577
 
6.1%
4 1248
 
4.8%
8 1137
 
4.4%
6 1126
 
4.3%
9 1084
 
4.2%
7 934
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25976
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 10224
39.4%
1 4514
17.4%
2 2226
 
8.6%
5 1905
 
7.3%
3 1577
 
6.1%
4 1248
 
4.8%
8 1137
 
4.4%
6 1126
 
4.3%
9 1084
 
4.2%
7 934
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25976
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 10224
39.4%
1 4514
17.4%
2 2226
 
8.6%
5 1905
 
7.3%
3 1577
 
6.1%
4 1248
 
4.8%
8 1137
 
4.4%
6 1126
 
4.3%
9 1084
 
4.2%
7 934
 
3.6%

decimalLatitude
Text

Missing 

Distinct7761
Distinct (%)15.7%
Missing10516
Missing (%)17.5%
Memory size469.2 KiB
2025-02-14T15:18:23.650844image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.61733231
Min length1

Characters and Unicode

Total characters327730
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

Unique4044 ?
Unique (%)8.2%

Sample

1st row-42.91763
2nd row-38.447734
3rd row-41.767325
4th row20.227479
5th row37.43039
ValueCountFrequency (%)
62 2130
 
4.3%
42.8333 975
 
2.0%
37 943
 
1.9%
48.35 820
 
1.7%
47 705
 
1.4%
51.5 605
 
1.2%
28 428
 
0.9%
44 389
 
0.8%
30.332184 322
 
0.7%
46 305
 
0.6%
Other values (7680) 41904
84.6%
2025-02-14T15:18:23.847754image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 42076
12.8%
3 41697
12.7%
4 37729
11.5%
2 29443
9.0%
1 27782
8.5%
8 27760
8.5%
6 26047
7.9%
5 25333
7.7%
7 25240
7.7%
9 20474
6.2%
Other values (2) 24149
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 327730
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 42076
12.8%
3 41697
12.7%
4 37729
11.5%
2 29443
9.0%
1 27782
8.5%
8 27760
8.5%
6 26047
7.9%
5 25333
7.7%
7 25240
7.7%
9 20474
6.2%
Other values (2) 24149
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 327730
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 42076
12.8%
3 41697
12.7%
4 37729
11.5%
2 29443
9.0%
1 27782
8.5%
8 27760
8.5%
6 26047
7.9%
5 25333
7.7%
7 25240
7.7%
9 20474
6.2%
Other values (2) 24149
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 327730
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 42076
12.8%
3 41697
12.7%
4 37729
11.5%
2 29443
9.0%
1 27782
8.5%
8 27760
8.5%
6 26047
7.9%
5 25333
7.7%
7 25240
7.7%
9 20474
6.2%
Other values (2) 24149
7.4%

decimalLongitude
Text

Missing 

Distinct7858
Distinct (%)15.9%
Missing10516
Missing (%)17.5%
Memory size469.2 KiB
2025-02-14T15:18:23.990355image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.626579978
Min length1

Characters and Unicode

Total characters377714
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

Unique4117 ?
Unique (%)8.3%

Sample

1st row171.554593
2nd row146.537933
3rd row172.192894
4th row-99.898902
5th row-122.182327
ValueCountFrequency (%)
15 2238
 
4.5%
12.8333 999
 
2.0%
119 915
 
1.8%
89.28 845
 
1.7%
10.5 599
 
1.2%
120 520
 
1.0%
82 417
 
0.8%
81.655651 322
 
0.7%
35.97 316
 
0.6%
80 315
 
0.6%
Other values (7809) 42040
84.9%
2025-02-14T15:18:24.189120image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 49313
13.1%
. 41361
11.0%
8 38126
10.1%
- 35520
9.4%
2 32721
8.7%
3 32093
8.5%
7 28765
7.6%
5 26275
7.0%
9 25262
6.7%
6 24964
6.6%
Other values (2) 43314
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 377714
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 49313
13.1%
. 41361
11.0%
8 38126
10.1%
- 35520
9.4%
2 32721
8.7%
3 32093
8.5%
7 28765
7.6%
5 26275
7.0%
9 25262
6.7%
6 24964
6.6%
Other values (2) 43314
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 377714
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 49313
13.1%
. 41361
11.0%
8 38126
10.1%
- 35520
9.4%
2 32721
8.7%
3 32093
8.5%
7 28765
7.6%
5 26275
7.0%
9 25262
6.7%
6 24964
6.6%
Other values (2) 43314
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 377714
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 49313
13.1%
. 41361
11.0%
8 38126
10.1%
- 35520
9.4%
2 32721
8.7%
3 32093
8.5%
7 28765
7.6%
5 26275
7.0%
9 25262
6.7%
6 24964
6.6%
Other values (2) 43314
11.5%

geodeticDatum
Text

Missing 

Distinct2
Distinct (%)0.3%
Missing59376
Missing (%)98.9%
Memory size469.2 KiB
2025-02-14T15:18:24.224486image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length5
Mean length5.414414414
Min length5

Characters and Unicode

Total characters3606
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 rowWGS84
2nd rowWGS84
3rd rowWGS84
4th rowWGS84
5th rowWGS84
ValueCountFrequency (%)
wgs84 620
93.1%
wgs84/nad83 46
 
6.9%
2025-02-14T15:18:24.311046image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 712
19.7%
W 666
18.5%
G 666
18.5%
S 666
18.5%
4 666
18.5%
/ 46
 
1.3%
N 46
 
1.3%
A 46
 
1.3%
D 46
 
1.3%
3 46
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3606
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 712
19.7%
W 666
18.5%
G 666
18.5%
S 666
18.5%
4 666
18.5%
/ 46
 
1.3%
N 46
 
1.3%
A 46
 
1.3%
D 46
 
1.3%
3 46
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3606
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 712
19.7%
W 666
18.5%
G 666
18.5%
S 666
18.5%
4 666
18.5%
/ 46
 
1.3%
N 46
 
1.3%
A 46
 
1.3%
D 46
 
1.3%
3 46
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3606
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 712
19.7%
W 666
18.5%
G 666
18.5%
S 666
18.5%
4 666
18.5%
/ 46
 
1.3%
N 46
 
1.3%
A 46
 
1.3%
D 46
 
1.3%
3 46
 
1.3%
Distinct2829
Distinct (%)13.8%
Missing39477
Missing (%)65.7%
Memory size469.2 KiB
2025-02-14T15:18:24.441289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.071772429
Min length1

Characters and Unicode

Total characters83736
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

Unique1165 ?
Unique (%)5.7%

Sample

1st row365
2nd row519
3rd row409
4th row455
5th row473
ValueCountFrequency (%)
3036 781
 
3.8%
3000 516
 
2.5%
1807 411
 
2.0%
1000 395
 
1.9%
26447 322
 
1.6%
5000 318
 
1.5%
6000 250
 
1.2%
10562 236
 
1.1%
2000 221
 
1.1%
1500 211
 
1.0%
Other values (2819) 16904
82.2%
2025-02-14T15:18:24.639576image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18505
22.1%
1 11444
13.7%
3 8541
10.2%
2 8022
9.6%
5 7409
8.8%
6 7262
 
8.7%
4 6642
 
7.9%
7 5754
 
6.9%
8 5565
 
6.6%
9 4588
 
5.5%
Other values (2) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 83736
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 18505
22.1%
1 11444
13.7%
3 8541
10.2%
2 8022
9.6%
5 7409
8.8%
6 7262
 
8.7%
4 6642
 
7.9%
7 5754
 
6.9%
8 5565
 
6.6%
9 4588
 
5.5%
Other values (2) 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 83736
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 18505
22.1%
1 11444
13.7%
3 8541
10.2%
2 8022
9.6%
5 7409
8.8%
6 7262
 
8.7%
4 6642
 
7.9%
7 5754
 
6.9%
8 5565
 
6.6%
9 4588
 
5.5%
Other values (2) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 83736
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 18505
22.1%
1 11444
13.7%
3 8541
10.2%
2 8022
9.6%
5 7409
8.8%
6 7262
 
8.7%
4 6642
 
7.9%
7 5754
 
6.9%
8 5565
 
6.6%
9 4588
 
5.5%
Other values (2) 4
 
< 0.1%

georeferencedBy
Text

Missing 

Distinct89
Distinct (%)0.4%
Missing38000
Missing (%)63.3%
Memory size469.2 KiB
2025-02-14T15:18:24.692005image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length95
Median length77
Mean length50.35541239
Min length5

Characters and Unicode

Total characters1109934
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

Unique16 ?
Unique (%)0.1%

Sample

1st rowT. J. Widhelm : Field Museum of Natural History - Botany Department
2nd rowT. J. Widhelm : Field Museum of Natural History - Botany Department
3rd rowT. J. Widhelm : Field Museum of Natural History - Botany Department
4th rowT. J. Widhelm : Field Museum of Natural History - Botany Department
5th rowM. Pritza : Field Museum of Natural History
ValueCountFrequency (%)
30035
15.1%
of 18405
 
9.3%
field 17573
 
8.9%
history 17502
 
8.8%
natural 17502
 
8.8%
museum 17031
 
8.6%
department 12154
 
6.1%
botany 11268
 
5.7%
c 5247
 
2.6%
m 4725
 
2.4%
Other values (143) 46869
23.6%
2025-02-14T15:18:24.795146image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176269
15.9%
t 84847
 
7.6%
e 75113
 
6.8%
a 74109
 
6.7%
r 62840
 
5.7%
o 58688
 
5.3%
u 54171
 
4.9%
i 49133
 
4.4%
l 43349
 
3.9%
s 41280
 
3.7%
Other values (48) 390135
35.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1109934
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
176269
15.9%
t 84847
 
7.6%
e 75113
 
6.8%
a 74109
 
6.7%
r 62840
 
5.7%
o 58688
 
5.3%
u 54171
 
4.9%
i 49133
 
4.4%
l 43349
 
3.9%
s 41280
 
3.7%
Other values (48) 390135
35.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1109934
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
176269
15.9%
t 84847
 
7.6%
e 75113
 
6.8%
a 74109
 
6.7%
r 62840
 
5.7%
o 58688
 
5.3%
u 54171
 
4.9%
i 49133
 
4.4%
l 43349
 
3.9%
s 41280
 
3.7%
Other values (48) 390135
35.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1109934
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
176269
15.9%
t 84847
 
7.6%
e 75113
 
6.8%
a 74109
 
6.7%
r 62840
 
5.7%
o 58688
 
5.3%
u 54171
 
4.9%
i 49133
 
4.4%
l 43349
 
3.9%
s 41280
 
3.7%
Other values (48) 390135
35.1%

georeferencedDate
Text

Missing 

Distinct421
Distinct (%)5.2%
Missing51876
Missing (%)86.4%
Memory size469.2 KiB
2025-02-14T15:18:24.923980image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.799657115
Min length4

Characters and Unicode

Total characters71858
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

Unique126 ?
Unique (%)1.5%

Sample

1st row4/8/2021
2nd row2/10/2021
3rd row4/8/2021
4th row6/21/2021
5th row6/21/2021
ValueCountFrequency (%)
9/21/2016 467
 
5.7%
6/21/2021 385
 
4.7%
2021-02 347
 
4.2%
9/9/2019 260
 
3.2%
3/24/2022 206
 
2.5%
10/25/2016 204
 
2.5%
9/18/2019 196
 
2.4%
9/30/2016 183
 
2.2%
9/26/2021 172
 
2.1%
9/29/2016 165
 
2.0%
Other values (411) 5581
68.3%
2025-02-14T15:18:25.127769image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16272
22.6%
/ 15106
21.0%
1 12252
17.1%
0 10864
15.1%
9 5170
 
7.2%
6 4012
 
5.6%
7 1687
 
2.3%
3 1673
 
2.3%
4 1609
 
2.2%
5 1330
 
1.9%
Other values (2) 1883
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 71858
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 16272
22.6%
/ 15106
21.0%
1 12252
17.1%
0 10864
15.1%
9 5170
 
7.2%
6 4012
 
5.6%
7 1687
 
2.3%
3 1673
 
2.3%
4 1609
 
2.2%
5 1330
 
1.9%
Other values (2) 1883
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 71858
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 16272
22.6%
/ 15106
21.0%
1 12252
17.1%
0 10864
15.1%
9 5170
 
7.2%
6 4012
 
5.6%
7 1687
 
2.3%
3 1673
 
2.3%
4 1609
 
2.2%
5 1330
 
1.9%
Other values (2) 1883
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 71858
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 16272
22.6%
/ 15106
21.0%
1 12252
17.1%
0 10864
15.1%
9 5170
 
7.2%
6 4012
 
5.6%
7 1687
 
2.3%
3 1673
 
2.3%
4 1609
 
2.2%
5 1330
 
1.9%
Other values (2) 1883
 
2.6%

georeferenceProtocol
Text

Missing 

Distinct8
Distinct (%)0.1%
Missing47686
Missing (%)79.4%
Memory size469.2 KiB
2025-02-14T15:18:25.177460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length22
Mean length17.41494011
Min length3

Characters and Unicode

Total characters215179
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowGeoLocate
2nd rowCollector Notes
3rd rowGeoLocate
4th rowTGN - Centroid
5th rowTGN - Country Centroid
ValueCountFrequency (%)
tgn 11484
27.9%
11484
27.9%
centroid 11484
27.9%
country 5852
14.2%
geolocate 811
 
2.0%
gps 51
 
0.1%
google 9
 
< 0.1%
earth 5
 
< 0.1%
maps 4
 
< 0.1%
collector 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
2025-02-14T15:18:25.266565image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28832
13.4%
o 18979
 
8.8%
t 18155
 
8.4%
r 17342
 
8.1%
n 17337
 
8.1%
C 17337
 
8.1%
e 13117
 
6.1%
G 12355
 
5.7%
i 11486
 
5.3%
N 11485
 
5.3%
Other values (21) 48754
22.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 215179
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
28832
13.4%
o 18979
 
8.8%
t 18155
 
8.4%
r 17342
 
8.1%
n 17337
 
8.1%
C 17337
 
8.1%
e 13117
 
6.1%
G 12355
 
5.7%
i 11486
 
5.3%
N 11485
 
5.3%
Other values (21) 48754
22.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 215179
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
28832
13.4%
o 18979
 
8.8%
t 18155
 
8.4%
r 17342
 
8.1%
n 17337
 
8.1%
C 17337
 
8.1%
e 13117
 
6.1%
G 12355
 
5.7%
i 11486
 
5.3%
N 11485
 
5.3%
Other values (21) 48754
22.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 215179
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
28832
13.4%
o 18979
 
8.8%
t 18155
 
8.4%
r 17342
 
8.1%
n 17337
 
8.1%
C 17337
 
8.1%
e 13117
 
6.1%
G 12355
 
5.7%
i 11486
 
5.3%
N 11485
 
5.3%
Other values (21) 48754
22.7%

georeferenceSources
Text

Missing 

Distinct20
Distinct (%)0.1%
Missing24313
Missing (%)40.5%
Memory size469.2 KiB
2025-02-14T15:18:25.299161image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length49
Median length9
Mean length20.18892216
Min length3

Characters and Unicode

Total characters721330
Distinct characters47
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 (%)< 0.1%

Sample

1st rowGEOlocate
2nd rowGEOlocate
3rd rowGEOlocate
4th rowGEOlocate
5th rowGEOlocate
ValueCountFrequency (%)
geolocate 20866
20.4%
thesaurus 11466
11.2%
of 11466
11.2%
geographic 11466
11.2%
names 11466
11.2%
tgn 11466
11.2%
getty 11466
11.2%
label 3042
 
3.0%
on 3038
 
3.0%
printed 3038
 
3.0%
Other values (25) 3657
 
3.6%
2025-02-14T15:18:25.387904image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 74031
 
10.3%
66708
 
9.2%
a 61858
 
8.6%
G 55510
 
7.7%
o 47737
 
6.6%
t 47159
 
6.5%
s 37529
 
5.2%
c 32524
 
4.5%
l 26676
 
3.7%
r 26096
 
3.6%
Other values (37) 245502
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 721330
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 74031
 
10.3%
66708
 
9.2%
a 61858
 
8.6%
G 55510
 
7.7%
o 47737
 
6.6%
t 47159
 
6.5%
s 37529
 
5.2%
c 32524
 
4.5%
l 26676
 
3.7%
r 26096
 
3.6%
Other values (37) 245502
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 721330
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 74031
 
10.3%
66708
 
9.2%
a 61858
 
8.6%
G 55510
 
7.7%
o 47737
 
6.6%
t 47159
 
6.5%
s 37529
 
5.2%
c 32524
 
4.5%
l 26676
 
3.7%
r 26096
 
3.6%
Other values (37) 245502
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 721330
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 74031
 
10.3%
66708
 
9.2%
a 61858
 
8.6%
G 55510
 
7.7%
o 47737
 
6.6%
t 47159
 
6.5%
s 37529
 
5.2%
c 32524
 
4.5%
l 26676
 
3.7%
r 26096
 
3.6%
Other values (37) 245502
34.0%

georeferenceRemarks
Text

Missing 

Distinct561
Distinct (%)7.1%
Missing52148
Missing (%)86.9%
Memory size469.2 KiB
2025-02-14T15:18:25.419568image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length232
Median length28
Mean length34.51988852
Min length8

Characters and Unicode

Total characters272500
Distinct characters117
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

Unique373 ?
Unique (%)4.7%

Sample

1st rowFrom label
2nd rowFrom label
3rd rowLake is within Vaca Mts. Uncert. radius contains a small amount of tributaries connected to the lake.
4th rowThe uncert. radius extends just beyond the city limits.
5th rowFrom label
ValueCountFrequency (%)
centroid 6206
19.0%
generalised 6199
18.9%
country 5975
18.3%
from 1113
 
3.4%
coordinates 919
 
2.8%
copied 658
 
2.0%
duplicate 654
 
2.0%
to 520
 
1.6%
label 387
 
1.2%
wis 372
 
1.1%
Other values (1545) 9732
29.7%
2025-02-14T15:18:25.522201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 32681
 
12.0%
24859
 
9.1%
r 17599
 
6.5%
i 17382
 
6.4%
n 16629
 
6.1%
d 16495
 
6.1%
o 13920
 
5.1%
a 13146
 
4.8%
t 11127
 
4.1%
l 10283
 
3.8%
Other values (107) 98379
36.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 272500
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 32681
 
12.0%
24859
 
9.1%
r 17599
 
6.5%
i 17382
 
6.4%
n 16629
 
6.1%
d 16495
 
6.1%
o 13920
 
5.1%
a 13146
 
4.8%
t 11127
 
4.1%
l 10283
 
3.8%
Other values (107) 98379
36.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 272500
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 32681
 
12.0%
24859
 
9.1%
r 17599
 
6.5%
i 17382
 
6.4%
n 16629
 
6.1%
d 16495
 
6.1%
o 13920
 
5.1%
a 13146
 
4.8%
t 11127
 
4.1%
l 10283
 
3.8%
Other values (107) 98379
36.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 272500
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 32681
 
12.0%
24859
 
9.1%
r 17599
 
6.5%
i 17382
 
6.4%
n 16629
 
6.1%
d 16495
 
6.1%
o 13920
 
5.1%
a 13146
 
4.8%
t 11127
 
4.1%
l 10283
 
3.8%
Other values (107) 98379
36.1%
Distinct2
Distinct (%)2.0%
Missing59943
Missing (%)99.8%
Memory size469.2 KiB
2025-02-14T15:18:25.552522image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.111111111
Min length3

Characters and Unicode

Total characters308
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 rowaff.
2nd rowaff.
3rd rowaff.
4th rowaff.
5th rowaff.
ValueCountFrequency (%)
cf 88
88.9%
aff 11
 
11.1%
2025-02-14T15:18:25.632312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 110
35.7%
. 99
32.1%
c 88
28.6%
a 11
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 308
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
f 110
35.7%
. 99
32.1%
c 88
28.6%
a 11
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 308
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
f 110
35.7%
. 99
32.1%
c 88
28.6%
a 11
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 308
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
f 110
35.7%
. 99
32.1%
c 88
28.6%
a 11
 
3.6%

typeStatus
Text

Missing 

Distinct13
Distinct (%)0.9%
Missing58591
Missing (%)97.6%
Memory size469.2 KiB
2025-02-14T15:18:25.739735image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length13
Mean length9.795313577
Min length6

Characters and Unicode

Total characters14213
Distinct characters27
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 rowIsotype
2nd rowIsotype
3rd rowIsotype
4th rowIsotype
5th rowIsotype
ValueCountFrequency (%)
isotype 623
30.6%
type 502
24.7%
possible 422
20.8%
paratype 118
 
5.8%
holotype 97
 
4.8%
status 80
 
3.9%
unknown 80
 
3.9%
syntype 43
 
2.1%
isolectotype 28
 
1.4%
topotype 19
 
0.9%
Other values (5) 21
 
1.0%
2025-02-14T15:18:25.839089image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1912
13.5%
s 1663
11.7%
t 1568
11.0%
y 1497
10.5%
p 1474
10.4%
o 1432
10.1%
I 656
 
4.6%
582
 
4.1%
l 547
 
3.8%
P 540
 
3.8%
Other values (17) 2342
16.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14213
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1912
13.5%
s 1663
11.7%
t 1568
11.0%
y 1497
10.5%
p 1474
10.4%
o 1432
10.1%
I 656
 
4.6%
582
 
4.1%
l 547
 
3.8%
P 540
 
3.8%
Other values (17) 2342
16.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14213
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1912
13.5%
s 1663
11.7%
t 1568
11.0%
y 1497
10.5%
p 1474
10.4%
o 1432
10.1%
I 656
 
4.6%
582
 
4.1%
l 547
 
3.8%
P 540
 
3.8%
Other values (17) 2342
16.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14213
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1912
13.5%
s 1663
11.7%
t 1568
11.0%
y 1497
10.5%
p 1474
10.4%
o 1432
10.1%
I 656
 
4.6%
582
 
4.1%
l 547
 
3.8%
P 540
 
3.8%
Other values (17) 2342
16.5%

identifiedBy
Text

Missing 

Distinct562
Distinct (%)2.2%
Missing34027
Missing (%)56.7%
Memory size469.2 KiB
2025-02-14T15:18:25.972457image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length127
Median length95
Mean length24.92035364
Min length4

Characters and Unicode

Total characters648303
Distinct characters78
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

Unique206 ?
Unique (%)0.8%

Sample

1st rowT. J. Widhelm : Field Museum of Natural History - Botany Department
2nd rowH. T. Lumbsch : Field Museum of Natural History - Botany Department
3rd rowT. J. Widhelm : Field Museum of Natural History - Botany Department
4th rowJ. Buschbom
5th rowH. T. Lumbsch : Field Museum of Natural History - Botany Department
ValueCountFrequency (%)
11647
 
9.3%
j 7089
 
5.6%
of 5873
 
4.7%
museum 4967
 
4.0%
natural 4893
 
3.9%
buschbom 4802
 
3.8%
history 4758
 
3.8%
a 4729
 
3.8%
department 4665
 
3.7%
botany 4652
 
3.7%
Other values (716) 67528
53.8%
2025-02-14T15:18:26.194053image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99588
 
15.4%
. 40779
 
6.3%
e 40606
 
6.3%
t 32890
 
5.1%
a 32442
 
5.0%
o 31859
 
4.9%
r 29633
 
4.6%
u 25109
 
3.9%
n 23330
 
3.6%
s 23261
 
3.6%
Other values (68) 268806
41.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 648303
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
99588
 
15.4%
. 40779
 
6.3%
e 40606
 
6.3%
t 32890
 
5.1%
a 32442
 
5.0%
o 31859
 
4.9%
r 29633
 
4.6%
u 25109
 
3.9%
n 23330
 
3.6%
s 23261
 
3.6%
Other values (68) 268806
41.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 648303
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
99588
 
15.4%
. 40779
 
6.3%
e 40606
 
6.3%
t 32890
 
5.1%
a 32442
 
5.0%
o 31859
 
4.9%
r 29633
 
4.6%
u 25109
 
3.9%
n 23330
 
3.6%
s 23261
 
3.6%
Other values (68) 268806
41.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 648303
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
99588
 
15.4%
. 40779
 
6.3%
e 40606
 
6.3%
t 32890
 
5.1%
a 32442
 
5.0%
o 31859
 
4.9%
r 29633
 
4.6%
u 25109
 
3.9%
n 23330
 
3.6%
s 23261
 
3.6%
Other values (68) 268806
41.5%

dateIdentified
Text

Missing 

Distinct121
Distinct (%)0.7%
Missing42731
Missing (%)71.2%
Memory size469.2 KiB
2025-02-14T15:18:26.277244image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters69244
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

Unique23 ?
Unique (%)0.1%

Sample

1st row2017
2nd row2016
3rd row2017
4th row2000
5th row2022
ValueCountFrequency (%)
2000 5901
34.1%
2004 1154
 
6.7%
2003 1116
 
6.4%
2005 722
 
4.2%
2001 562
 
3.2%
1987 534
 
3.1%
1964 486
 
2.8%
2017 371
 
2.1%
1999 340
 
2.0%
1973 338
 
2.0%
Other values (111) 5787
33.4%
2025-02-14T15:18:26.409145image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28212
40.7%
2 13215
19.1%
1 8102
 
11.7%
9 7776
 
11.2%
4 2601
 
3.8%
7 2149
 
3.1%
5 2023
 
2.9%
6 1995
 
2.9%
3 1752
 
2.5%
8 1419
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 69244
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 28212
40.7%
2 13215
19.1%
1 8102
 
11.7%
9 7776
 
11.2%
4 2601
 
3.8%
7 2149
 
3.1%
5 2023
 
2.9%
6 1995
 
2.9%
3 1752
 
2.5%
8 1419
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 69244
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 28212
40.7%
2 13215
19.1%
1 8102
 
11.7%
9 7776
 
11.2%
4 2601
 
3.8%
7 2149
 
3.1%
5 2023
 
2.9%
6 1995
 
2.9%
3 1752
 
2.5%
8 1419
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 69244
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 28212
40.7%
2 13215
19.1%
1 8102
 
11.7%
9 7776
 
11.2%
4 2601
 
3.8%
7 2149
 
3.1%
5 2023
 
2.9%
6 1995
 
2.9%
3 1752
 
2.5%
8 1419
 
2.0%
Distinct8992
Distinct (%)15.0%
Missing282
Missing (%)0.5%
Memory size469.2 KiB
2025-02-14T15:18:26.546267image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length78
Median length61
Mean length32.33268072
Min length6

Characters and Unicode

Total characters1932201
Distinct characters74
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

Unique4267 ?
Unique (%)7.1%

Sample

1st rowPseudocyphellaria glabra (Hook. f. & Taylor) C. W. Dodge
2nd rowBunodophoron A. Massal.
3rd rowPseudocyphellaria glabra (Hook. f. & Taylor) C. W. Dodge
4th rowXanthoparmelia coloradoensis (Gyeln.) Hale
5th rowRamalina menziesii Taylor
ValueCountFrequency (%)
ach 11659
 
4.5%
cladonia 8171
 
3.2%
l 7235
 
2.8%
nyl 5835
 
2.3%
5822
 
2.3%
hoffm 3388
 
1.3%
ex 3379
 
1.3%
a 3247
 
1.3%
fr 3219
 
1.3%
vain 2886
 
1.1%
Other values (7470) 201896
78.6%
2025-02-14T15:18:26.774924image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 205986
 
10.7%
196977
 
10.2%
i 120107
 
6.2%
e 118069
 
6.1%
l 112378
 
5.8%
r 108711
 
5.6%
. 97162
 
5.0%
o 88438
 
4.6%
n 76598
 
4.0%
c 74773
 
3.9%
Other values (64) 733002
37.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1932201
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 205986
 
10.7%
196977
 
10.2%
i 120107
 
6.2%
e 118069
 
6.1%
l 112378
 
5.8%
r 108711
 
5.6%
. 97162
 
5.0%
o 88438
 
4.6%
n 76598
 
4.0%
c 74773
 
3.9%
Other values (64) 733002
37.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1932201
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 205986
 
10.7%
196977
 
10.2%
i 120107
 
6.2%
e 118069
 
6.1%
l 112378
 
5.8%
r 108711
 
5.6%
. 97162
 
5.0%
o 88438
 
4.6%
n 76598
 
4.0%
c 74773
 
3.9%
Other values (64) 733002
37.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1932201
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 205986
 
10.7%
196977
 
10.2%
i 120107
 
6.2%
e 118069
 
6.1%
l 112378
 
5.8%
r 108711
 
5.6%
. 97162
 
5.0%
o 88438
 
4.6%
n 76598
 
4.0%
c 74773
 
3.9%
Other values (64) 733002
37.9%
Distinct193
Distinct (%)0.3%
Missing282
Missing (%)0.5%
Memory size469.2 KiB
2025-02-14T15:18:26.830695image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length72
Median length71
Mean length56.37735944
Min length5

Characters and Unicode

Total characters3369111
Distinct characters47
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

Unique37 ?
Unique (%)0.1%

Sample

1st rowFungi Ascomycota Lecanoromycetes Peltigerales Lobariaceae
2nd rowFungi Ascomycota Lecanoromycetes Lecanorales Sphaerophoraceae
3rd rowFungi Ascomycota Lecanoromycetes Peltigerales Lobariaceae
4th rowFungi Ascomycota Lecanoromycetes Lecanorales Parmeliaceae
5th rowFungi Ascomycota Lecanoromycetes Lecanorales Ramalinaceae
ValueCountFrequency (%)
fungi 59759
20.4%
ascomycota 58233
19.9%
lecanoromycetes 52145
17.8%
lecanorales 28069
9.6%
parmeliaceae 11425
 
3.9%
cladoniaceae 8494
 
2.9%
ostropales 5525
 
1.9%
peltigerales 5359
 
1.8%
caliciales 4702
 
1.6%
graphidaceae 3712
 
1.3%
Other values (221) 55486
18.9%
2025-02-14T15:18:26.946694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 425934
12.6%
a 374857
11.1%
c 345866
 
10.3%
o 303715
 
9.0%
233149
 
6.9%
s 199969
 
5.9%
n 165916
 
4.9%
t 151584
 
4.5%
r 149099
 
4.4%
i 148860
 
4.4%
Other values (37) 870162
25.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3369111
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 425934
12.6%
a 374857
11.1%
c 345866
 
10.3%
o 303715
 
9.0%
233149
 
6.9%
s 199969
 
5.9%
n 165916
 
4.9%
t 151584
 
4.5%
r 149099
 
4.4%
i 148860
 
4.4%
Other values (37) 870162
25.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3369111
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 425934
12.6%
a 374857
11.1%
c 345866
 
10.3%
o 303715
 
9.0%
233149
 
6.9%
s 199969
 
5.9%
n 165916
 
4.9%
t 151584
 
4.5%
r 149099
 
4.4%
i 148860
 
4.4%
Other values (37) 870162
25.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3369111
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 425934
12.6%
a 374857
11.1%
c 345866
 
10.3%
o 303715
 
9.0%
233149
 
6.9%
s 199969
 
5.9%
n 165916
 
4.9%
t 151584
 
4.5%
r 149099
 
4.4%
i 148860
 
4.4%
Other values (37) 870162
25.8%
Distinct2
Distinct (%)< 0.1%
Missing282
Missing (%)0.5%
Memory size469.2 KiB
2025-02-14T15:18:26.979543image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.000033467
Min length5

Characters and Unicode

Total characters298802
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowFungi
2nd rowFungi
3rd rowFungi
4th rowFungi
5th rowFungi
ValueCountFrequency (%)
fungi 59759
> 99.9%
plantae 1
 
< 0.1%
2025-02-14T15:18:27.071984image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 59760
20.0%
F 59759
20.0%
u 59759
20.0%
g 59759
20.0%
i 59759
20.0%
a 2
 
< 0.1%
P 1
 
< 0.1%
l 1
 
< 0.1%
t 1
 
< 0.1%
e 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 298802
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 59760
20.0%
F 59759
20.0%
u 59759
20.0%
g 59759
20.0%
i 59759
20.0%
a 2
 
< 0.1%
P 1
 
< 0.1%
l 1
 
< 0.1%
t 1
 
< 0.1%
e 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 298802
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 59760
20.0%
F 59759
20.0%
u 59759
20.0%
g 59759
20.0%
i 59759
20.0%
a 2
 
< 0.1%
P 1
 
< 0.1%
l 1
 
< 0.1%
t 1
 
< 0.1%
e 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 298802
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 59760
20.0%
F 59759
20.0%
u 59759
20.0%
g 59759
20.0%
i 59759
20.0%
a 2
 
< 0.1%
P 1
 
< 0.1%
l 1
 
< 0.1%
t 1
 
< 0.1%
e 1
 
< 0.1%

phylum
Text

Missing 

Distinct4
Distinct (%)< 0.1%
Missing1617
Missing (%)2.7%
Memory size469.2 KiB
2025-02-14T15:18:27.101641image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length10
Mean length10.00992726
Min length10

Characters and Unicode

Total characters584830
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowAscomycota
2nd rowAscomycota
3rd rowAscomycota
4th rowAscomycota
5th rowAscomycota
ValueCountFrequency (%)
ascomycota 58233
99.7%
basidiomycota 190
 
0.3%
chytridiomycota 1
 
< 0.1%
marchantiophyta 1
 
< 0.1%
2025-02-14T15:18:27.186847image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 116849
20.0%
c 116658
19.9%
a 58617
10.0%
t 58427
10.0%
y 58426
10.0%
m 58424
10.0%
s 58423
10.0%
A 58233
10.0%
i 383
 
0.1%
d 191
 
< 0.1%
Other values (7) 199
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 584830
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 116849
20.0%
c 116658
19.9%
a 58617
10.0%
t 58427
10.0%
y 58426
10.0%
m 58424
10.0%
s 58423
10.0%
A 58233
10.0%
i 383
 
0.1%
d 191
 
< 0.1%
Other values (7) 199
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 584830
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 116849
20.0%
c 116658
19.9%
a 58617
10.0%
t 58427
10.0%
y 58426
10.0%
m 58424
10.0%
s 58423
10.0%
A 58233
10.0%
i 383
 
0.1%
d 191
 
< 0.1%
Other values (7) 199
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 584830
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 116849
20.0%
c 116658
19.9%
a 58617
10.0%
t 58427
10.0%
y 58426
10.0%
m 58424
10.0%
s 58423
10.0%
A 58233
10.0%
i 383
 
0.1%
d 191
 
< 0.1%
Other values (7) 199
 
< 0.1%

class
Text

Missing 

Distinct17
Distinct (%)< 0.1%
Missing1919
Missing (%)3.2%
Memory size469.2 KiB
2025-02-14T15:18:27.216204image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length14.97596476
Min length13

Characters and Unicode

Total characters870448
Distinct characters33
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 rowLecanoromycetes
2nd rowLecanoromycetes
3rd rowLecanoromycetes
4th rowLecanoromycetes
5th rowLecanoromycetes
ValueCountFrequency (%)
lecanoromycetes 52145
89.6%
arthoniomycetes 1960
 
3.4%
eurotiomycetes 1814
 
3.1%
dothideomycetes 1022
 
1.8%
candelariomycetes 337
 
0.6%
lichinomycetes 280
 
0.5%
coniocybomycetes 192
 
0.3%
agaricomycetes 180
 
0.3%
sordariomycetes 130
 
0.2%
incertae 48
 
0.1%
Other values (7) 63
 
0.1%
2025-02-14T15:18:27.310137image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 169817
19.5%
o 115533
13.3%
c 110919
12.7%
t 62922
 
7.2%
y 58267
 
6.7%
s 58171
 
6.7%
m 58082
 
6.7%
r 56754
 
6.5%
n 54966
 
6.3%
a 53179
 
6.1%
Other values (23) 71838
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 870448
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 169817
19.5%
o 115533
13.3%
c 110919
12.7%
t 62922
 
7.2%
y 58267
 
6.7%
s 58171
 
6.7%
m 58082
 
6.7%
r 56754
 
6.5%
n 54966
 
6.3%
a 53179
 
6.1%
Other values (23) 71838
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 870448
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 169817
19.5%
o 115533
13.3%
c 110919
12.7%
t 62922
 
7.2%
y 58267
 
6.7%
s 58171
 
6.7%
m 58082
 
6.7%
r 56754
 
6.5%
n 54966
 
6.3%
a 53179
 
6.1%
Other values (23) 71838
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 870448
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 169817
19.5%
o 115533
13.3%
c 110919
12.7%
t 62922
 
7.2%
y 58267
 
6.7%
s 58171
 
6.7%
m 58082
 
6.7%
r 56754
 
6.5%
n 54966
 
6.3%
a 53179
 
6.1%
Other values (23) 71838
8.3%

order
Text

Missing 

Distinct57
Distinct (%)0.1%
Missing2077
Missing (%)3.5%
Memory size469.2 KiB
2025-02-14T15:18:27.343101image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length11
Mean length11.29505736
Min length9

Characters and Unicode

Total characters654718
Distinct characters40
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

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowPeltigerales
2nd rowLecanorales
3rd rowPeltigerales
4th rowLecanorales
5th rowLecanorales
ValueCountFrequency (%)
lecanorales 28069
48.4%
ostropales 5523
 
9.5%
peltigerales 5359
 
9.2%
caliciales 4702
 
8.1%
teloschistales 2758
 
4.8%
arthoniales 2077
 
3.6%
pertusariales 1999
 
3.4%
umbilicariales 1122
 
1.9%
verrucariales 940
 
1.6%
lecideales 773
 
1.3%
Other values (47) 4702
 
8.1%
2025-02-14T15:18:27.437107image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 107095
16.4%
a 97685
14.9%
l 74314
11.4%
s 72138
11.0%
r 53559
8.2%
o 41752
 
6.4%
c 40783
 
6.2%
n 31855
 
4.9%
i 29648
 
4.5%
L 29124
 
4.4%
Other values (30) 76765
11.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 654718
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 107095
16.4%
a 97685
14.9%
l 74314
11.4%
s 72138
11.0%
r 53559
8.2%
o 41752
 
6.4%
c 40783
 
6.2%
n 31855
 
4.9%
i 29648
 
4.5%
L 29124
 
4.4%
Other values (30) 76765
11.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 654718
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 107095
16.4%
a 97685
14.9%
l 74314
11.4%
s 72138
11.0%
r 53559
8.2%
o 41752
 
6.4%
c 40783
 
6.2%
n 31855
 
4.9%
i 29648
 
4.5%
L 29124
 
4.4%
Other values (30) 76765
11.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 654718
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 107095
16.4%
a 97685
14.9%
l 74314
11.4%
s 72138
11.0%
r 53559
8.2%
o 41752
 
6.4%
c 40783
 
6.2%
n 31855
 
4.9%
i 29648
 
4.5%
L 29124
 
4.4%
Other values (30) 76765
11.7%

family
Text

Missing 

Distinct154
Distinct (%)0.3%
Missing1848
Missing (%)3.1%
Memory size469.2 KiB
2025-02-14T15:18:27.499010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length12
Mean length12.50311029
Min length9

Characters and Unicode

Total characters727606
Distinct characters46
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

Unique26 ?
Unique (%)< 0.1%

Sample

1st rowLobariaceae
2nd rowSphaerophoraceae
3rd rowLobariaceae
4th rowParmeliaceae
5th rowRamalinaceae
ValueCountFrequency (%)
parmeliaceae 11425
19.5%
cladoniaceae 8494
14.5%
graphidaceae 3712
 
6.3%
physciaceae 3055
 
5.2%
ramalinaceae 2650
 
4.5%
lecanoraceae 2618
 
4.5%
teloschistaceae 2300
 
3.9%
lobariaceae 2037
 
3.5%
caliciaceae 1888
 
3.2%
collemataceae 1331
 
2.3%
Other values (146) 19019
32.5%
2025-02-14T15:18:27.624346image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 165374
22.7%
e 149021
20.5%
c 77506
10.7%
i 52783
 
7.3%
l 39295
 
5.4%
r 38784
 
5.3%
o 29581
 
4.1%
n 19334
 
2.7%
m 18964
 
2.6%
P 18837
 
2.6%
Other values (36) 118127
16.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 727606
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 165374
22.7%
e 149021
20.5%
c 77506
10.7%
i 52783
 
7.3%
l 39295
 
5.4%
r 38784
 
5.3%
o 29581
 
4.1%
n 19334
 
2.7%
m 18964
 
2.6%
P 18837
 
2.6%
Other values (36) 118127
16.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 727606
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 165374
22.7%
e 149021
20.5%
c 77506
10.7%
i 52783
 
7.3%
l 39295
 
5.4%
r 38784
 
5.3%
o 29581
 
4.1%
n 19334
 
2.7%
m 18964
 
2.6%
P 18837
 
2.6%
Other values (36) 118127
16.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 727606
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 165374
22.7%
e 149021
20.5%
c 77506
10.7%
i 52783
 
7.3%
l 39295
 
5.4%
r 38784
 
5.3%
o 29581
 
4.1%
n 19334
 
2.7%
m 18964
 
2.6%
P 18837
 
2.6%
Other values (36) 118127
16.2%

genus
Text

Missing 

Distinct874
Distinct (%)1.5%
Missing1559
Missing (%)2.6%
Memory size469.2 KiB
2025-02-14T15:18:27.748491image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length17
Mean length9.09544654
Min length4

Characters and Unicode

Total characters531929
Distinct characters51
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

Unique218 ?
Unique (%)0.4%

Sample

1st rowPseudocyphellaria
2nd rowBunodophoron
3rd rowPseudocyphellaria
4th rowXanthoparmelia
5th rowRamalina
ValueCountFrequency (%)
cladonia 8155
 
13.9%
usnea 2220
 
3.8%
lecanora 1985
 
3.4%
caloplaca 1330
 
2.3%
graphis 1216
 
2.1%
parmelia 1119
 
1.9%
ramalina 1104
 
1.9%
physcia 1094
 
1.9%
xanthoparmelia 972
 
1.7%
pertusaria 889
 
1.5%
Other values (864) 38399
65.7%
2025-02-14T15:18:27.950176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 93601
17.6%
i 51823
 
9.7%
o 40370
 
7.6%
l 39736
 
7.5%
e 37704
 
7.1%
r 35785
 
6.7%
n 29188
 
5.5%
c 20938
 
3.9%
t 17471
 
3.3%
p 16667
 
3.1%
Other values (41) 148646
27.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 531929
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 93601
17.6%
i 51823
 
9.7%
o 40370
 
7.6%
l 39736
 
7.5%
e 37704
 
7.1%
r 35785
 
6.7%
n 29188
 
5.5%
c 20938
 
3.9%
t 17471
 
3.3%
p 16667
 
3.1%
Other values (41) 148646
27.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 531929
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 93601
17.6%
i 51823
 
9.7%
o 40370
 
7.6%
l 39736
 
7.5%
e 37704
 
7.1%
r 35785
 
6.7%
n 29188
 
5.5%
c 20938
 
3.9%
t 17471
 
3.3%
p 16667
 
3.1%
Other values (41) 148646
27.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 531929
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 93601
17.6%
i 51823
 
9.7%
o 40370
 
7.6%
l 39736
 
7.5%
e 37704
 
7.1%
r 35785
 
6.7%
n 29188
 
5.5%
c 20938
 
3.9%
t 17471
 
3.3%
p 16667
 
3.1%
Other values (41) 148646
27.9%

subgenus
Text

Missing 

Distinct2
Distinct (%)3.5%
Missing59985
Missing (%)99.9%
Memory size469.2 KiB
2025-02-14T15:18:27.995915image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.859649123
Min length7

Characters and Unicode

Total characters448
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowLopadium
2nd rowLopadium
3rd rowLopadium
4th rowLopadium
5th rowLopadium
ValueCountFrequency (%)
lopadium 49
86.0%
brassia 8
 
14.0%
2025-02-14T15:18:28.076865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 65
14.5%
i 57
12.7%
L 49
10.9%
o 49
10.9%
p 49
10.9%
d 49
10.9%
u 49
10.9%
m 49
10.9%
s 16
 
3.6%
B 8
 
1.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 448
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 65
14.5%
i 57
12.7%
L 49
10.9%
o 49
10.9%
p 49
10.9%
d 49
10.9%
u 49
10.9%
m 49
10.9%
s 16
 
3.6%
B 8
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 448
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 65
14.5%
i 57
12.7%
L 49
10.9%
o 49
10.9%
p 49
10.9%
d 49
10.9%
u 49
10.9%
m 49
10.9%
s 16
 
3.6%
B 8
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 448
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 65
14.5%
i 57
12.7%
L 49
10.9%
o 49
10.9%
p 49
10.9%
d 49
10.9%
u 49
10.9%
m 49
10.9%
s 16
 
3.6%
B 8
 
1.8%

specificEpithet
Text

Missing 

Distinct5322
Distinct (%)10.4%
Missing8744
Missing (%)14.6%
Memory size469.2 KiB
2025-02-14T15:18:28.196943image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length19
Mean length9.110491637
Min length3

Characters and Unicode

Total characters467350
Distinct characters34
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

Unique1977 ?
Unique (%)3.9%

Sample

1st rowglabra
2nd rowglabra
3rd rowcoloradoensis
4th rowmenziesii
5th rowcaperata
ValueCountFrequency (%)
fimbriata 445
 
0.9%
furcata 440
 
0.9%
glabra 395
 
0.8%
gracilis 395
 
0.8%
rangiferina 385
 
0.8%
pyxidata 374
 
0.7%
squamosa 372
 
0.7%
caperata 295
 
0.6%
coniocraea 278
 
0.5%
stellaris 272
 
0.5%
Other values (5313) 47649
92.9%
2025-02-14T15:18:28.389257image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 71166
15.2%
i 48172
10.3%
e 36105
 
7.7%
r 33935
 
7.3%
s 32660
 
7.0%
l 31677
 
6.8%
c 28242
 
6.0%
o 26351
 
5.6%
n 25200
 
5.4%
t 24274
 
5.2%
Other values (24) 109568
23.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 467350
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 71166
15.2%
i 48172
10.3%
e 36105
 
7.7%
r 33935
 
7.3%
s 32660
 
7.0%
l 31677
 
6.8%
c 28242
 
6.0%
o 26351
 
5.6%
n 25200
 
5.4%
t 24274
 
5.2%
Other values (24) 109568
23.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 467350
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 71166
15.2%
i 48172
10.3%
e 36105
 
7.7%
r 33935
 
7.3%
s 32660
 
7.0%
l 31677
 
6.8%
c 28242
 
6.0%
o 26351
 
5.6%
n 25200
 
5.4%
t 24274
 
5.2%
Other values (24) 109568
23.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 467350
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 71166
15.2%
i 48172
10.3%
e 36105
 
7.7%
r 33935
 
7.3%
s 32660
 
7.0%
l 31677
 
6.8%
c 28242
 
6.0%
o 26351
 
5.6%
n 25200
 
5.4%
t 24274
 
5.2%
Other values (24) 109568
23.4%

infraspecificEpithet
Text

Missing 

Distinct819
Distinct (%)27.2%
Missing57027
Missing (%)95.0%
Memory size469.2 KiB
2025-02-14T15:18:28.522475image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length16
Mean length9.12238806
Min length1

Characters and Unicode

Total characters27504
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

Unique458 ?
Unique (%)15.2%

Sample

1st rowcaespitosum
2nd rowdarrowii
3rd rowmyriophyllinum
4th rowleucophaea
5th rowleucophaea
ValueCountFrequency (%)
racemosa 102
 
3.4%
dilatata 79
 
2.6%
pinnata 64
 
2.1%
evoluta 53
 
1.8%
simplex 48
 
1.6%
chordalis 44
 
1.5%
neglecta 43
 
1.4%
subulata 40
 
1.3%
pocillum 39
 
1.3%
coniocraea 37
 
1.2%
Other values (812) 2469
81.8%
2025-02-14T15:18:28.789081image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4472
16.3%
i 2509
9.1%
l 2061
 
7.5%
e 2016
 
7.3%
s 1937
 
7.0%
o 1923
 
7.0%
r 1863
 
6.8%
c 1797
 
6.5%
t 1577
 
5.7%
u 1178
 
4.3%
Other values (20) 6171
22.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27504
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4472
16.3%
i 2509
9.1%
l 2061
 
7.5%
e 2016
 
7.3%
s 1937
 
7.0%
o 1923
 
7.0%
r 1863
 
6.8%
c 1797
 
6.5%
t 1577
 
5.7%
u 1178
 
4.3%
Other values (20) 6171
22.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27504
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4472
16.3%
i 2509
9.1%
l 2061
 
7.5%
e 2016
 
7.3%
s 1937
 
7.0%
o 1923
 
7.0%
r 1863
 
6.8%
c 1797
 
6.5%
t 1577
 
5.7%
u 1178
 
4.3%
Other values (20) 6171
22.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27504
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4472
16.3%
i 2509
9.1%
l 2061
 
7.5%
e 2016
 
7.3%
s 1937
 
7.0%
o 1923
 
7.0%
r 1863
 
6.8%
c 1797
 
6.5%
t 1577
 
5.7%
u 1178
 
4.3%
Other values (20) 6171
22.4%

taxonRank
Text

Missing 

Distinct2
Distinct (%)0.1%
Missing57027
Missing (%)95.0%
Memory size469.2 KiB
2025-02-14T15:18:28.835613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.098507463
Min length4

Characters and Unicode

Total characters18387
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 rowForm
2nd rowVariety
3rd rowVariety
4th rowForm
5th rowForm
ValueCountFrequency (%)
variety 2109
70.0%
form 906
30.0%
2025-02-14T15:18:28.918995image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 3015
16.4%
V 2109
11.5%
a 2109
11.5%
i 2109
11.5%
e 2109
11.5%
t 2109
11.5%
y 2109
11.5%
F 906
 
4.9%
o 906
 
4.9%
m 906
 
4.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18387
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 3015
16.4%
V 2109
11.5%
a 2109
11.5%
i 2109
11.5%
e 2109
11.5%
t 2109
11.5%
y 2109
11.5%
F 906
 
4.9%
o 906
 
4.9%
m 906
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18387
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 3015
16.4%
V 2109
11.5%
a 2109
11.5%
i 2109
11.5%
e 2109
11.5%
t 2109
11.5%
y 2109
11.5%
F 906
 
4.9%
o 906
 
4.9%
m 906
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18387
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 3015
16.4%
V 2109
11.5%
a 2109
11.5%
i 2109
11.5%
e 2109
11.5%
t 2109
11.5%
y 2109
11.5%
F 906
 
4.9%
o 906
 
4.9%
m 906
 
4.9%
Distinct3321
Distinct (%)5.7%
Missing1308
Missing (%)2.2%
Memory size469.2 KiB
2025-02-14T15:18:29.053416image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length42
Mean length12.94274185
Min length2

Characters and Unicode

Total characters760179
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

Unique1036 ?
Unique (%)1.8%

Sample

1st row(Hook. f. & Taylor) C. W. Dodge
2nd rowA. Massal.
3rd row(Hook. f. & Taylor) C. W. Dodge
4th row(Gyeln.) Hale
5th rowTaylor
ValueCountFrequency (%)
ach 11660
 
8.4%
l 7236
 
5.2%
nyl 5855
 
4.2%
5810
 
4.2%
ex 3392
 
2.4%
hoffm 3388
 
2.4%
a 3259
 
2.3%
fr 3219
 
2.3%
vain 2903
 
2.1%
hale 2857
 
2.1%
Other values (850) 89496
64.4%
2025-02-14T15:18:29.267771image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 94010
 
12.4%
80341
 
10.6%
e 38740
 
5.1%
l 37941
 
5.0%
( 37781
 
5.0%
) 37781
 
5.0%
r 34108
 
4.5%
a 31996
 
4.2%
h 25599
 
3.4%
c 22286
 
2.9%
Other values (60) 319596
42.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 760179
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 94010
 
12.4%
80341
 
10.6%
e 38740
 
5.1%
l 37941
 
5.0%
( 37781
 
5.0%
) 37781
 
5.0%
r 34108
 
4.5%
a 31996
 
4.2%
h 25599
 
3.4%
c 22286
 
2.9%
Other values (60) 319596
42.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 760179
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 94010
 
12.4%
80341
 
10.6%
e 38740
 
5.1%
l 37941
 
5.0%
( 37781
 
5.0%
) 37781
 
5.0%
r 34108
 
4.5%
a 31996
 
4.2%
h 25599
 
3.4%
c 22286
 
2.9%
Other values (60) 319596
42.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 760179
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 94010
 
12.4%
80341
 
10.6%
e 38740
 
5.1%
l 37941
 
5.0%
( 37781
 
5.0%
) 37781
 
5.0%
r 34108
 
4.5%
a 31996
 
4.2%
h 25599
 
3.4%
c 22286
 
2.9%
Other values (60) 319596
42.0%

nomenclaturalCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size469.2 KiB
2025-02-14T15:18:29.309160image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters240168
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 rowICBN
2nd rowICBN
3rd rowICBN
4th rowICBN
5th rowICBN
ValueCountFrequency (%)
icbn 60042
100.0%
2025-02-14T15:18:29.390319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 60042
25.0%
C 60042
25.0%
B 60042
25.0%
N 60042
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 240168
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
I 60042
25.0%
C 60042
25.0%
B 60042
25.0%
N 60042
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 240168
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
I 60042
25.0%
C 60042
25.0%
B 60042
25.0%
N 60042
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 240168
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
I 60042
25.0%
C 60042
25.0%
B 60042
25.0%
N 60042
25.0%