Overview

Brought to you by YData

Dataset statistics

Number of variables64
Number of observations601451
Missing cells14933142
Missing cells (%)38.8%
Total size in memory293.7 MiB
Average record size in memory512.0 B

Variable types

Text64

Dataset

DescriptionMammal NMNH Extant Specimen Records 0054884-241126133413365
URLhttps://doi.org/10.15468/hnhrg3

Alerts

collectionID has constant value "urn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22" Constant
collectionCode has constant value "MAMM" Constant
datasetName has constant value "NMNH Extant Biology" Constant
kingdom has constant value "Animalia" Constant
phylum has constant value "Chordata" Constant
class has constant value "Mammalia" Constant
taxonRank has constant value "subspecies" Constant
recordNumber has 50821 (8.4%) missing values Missing
recordedBy has 55563 (9.2%) missing values Missing
lifeStage has 549447 (91.4%) missing values Missing
preparations has 26965 (4.5%) missing values Missing
associatedMedia has 45503 (7.6%) missing values Missing
associatedSequences has 600397 (99.8%) missing values Missing
occurrenceRemarks has 590662 (98.2%) missing values Missing
eventDate has 28127 (4.7%) missing values Missing
startDayOfYear has 46793 (7.8%) missing values Missing
endDayOfYear has 46765 (7.8%) missing values Missing
year has 28127 (4.7%) missing values Missing
month has 44866 (7.5%) missing values Missing
day has 67482 (11.2%) missing values Missing
verbatimEventDate has 36490 (6.1%) missing values Missing
habitat has 468915 (78.0%) missing values Missing
waterBody has 539858 (89.8%) missing values Missing
islandGroup has 596682 (99.2%) missing values Missing
island has 564842 (93.9%) missing values Missing
country has 6532 (1.1%) missing values Missing
stateProvince has 93954 (15.6%) missing values Missing
county has 447402 (74.4%) missing values Missing
locality has 35404 (5.9%) missing values Missing
minimumElevationInMeters has 496901 (82.6%) missing values Missing
maximumElevationInMeters has 597572 (99.4%) missing values Missing
verbatimElevation has 599861 (99.7%) missing values Missing
minimumDepthInMeters has 601448 (> 99.9%) missing values Missing
decimalLatitude has 448433 (74.6%) missing values Missing
decimalLongitude has 448433 (74.6%) missing values Missing
geodeticDatum has 594543 (98.9%) missing values Missing
verbatimLatitude has 466631 (77.6%) missing values Missing
verbatimLongitude has 466723 (77.6%) missing values Missing
verbatimCoordinateSystem has 468202 (77.8%) missing values Missing
georeferenceProtocol has 592196 (98.5%) missing values Missing
georeferenceRemarks has 601383 (> 99.9%) missing values Missing
identificationQualifier has 599947 (99.7%) missing values Missing
typeStatus has 597685 (99.4%) missing values Missing
identifiedBy has 593267 (98.6%) missing values Missing
subgenus has 601149 (99.9%) missing values Missing
infraspecificEpithet has 314922 (52.4%) missing values Missing
taxonRank has 314922 (52.4%) missing values Missing
scientificNameAuthorship has 555607 (92.4%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique

Reproduction

Analysis started2025-02-10 18:50:30.194025
Analysis finished2025-02-10 18:50:48.573979
Duration18.38 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct601451
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:48.949517image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6014510
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

Unique601451 ?
Unique (%)100.0%

Sample

1st row1322535732
2nd row1322538146
3rd row1317206206
4th row1317210025
5th row1317210456
ValueCountFrequency (%)
1322535732 1
 
< 0.1%
1322555094 1
 
< 0.1%
1322560018 1
 
< 0.1%
1322558352 1
 
< 0.1%
1317224532 1
 
< 0.1%
4041103536 1
 
< 0.1%
1317206206 1
 
< 0.1%
1317210025 1
 
< 0.1%
1317210456 1
 
< 0.1%
1317211504 1
 
< 0.1%
Other values (601441) 601441
> 99.9%
2025-02-10T13:50:49.396499image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1342473
22.3%
3 953825
15.9%
2 772027
12.8%
8 469400
 
7.8%
9 463026
 
7.7%
0 459240
 
7.6%
7 444579
 
7.4%
4 377786
 
6.3%
5 367488
 
6.1%
6 364666
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6014510
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1342473
22.3%
3 953825
15.9%
2 772027
12.8%
8 469400
 
7.8%
9 463026
 
7.7%
0 459240
 
7.6%
7 444579
 
7.4%
4 377786
 
6.3%
5 367488
 
6.1%
6 364666
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6014510
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1342473
22.3%
3 953825
15.9%
2 772027
12.8%
8 469400
 
7.8%
9 463026
 
7.7%
0 459240
 
7.6%
7 444579
 
7.4%
4 377786
 
6.3%
5 367488
 
6.1%
6 364666
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6014510
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1342473
22.3%
3 953825
15.9%
2 772027
12.8%
8 469400
 
7.8%
9 463026
 
7.7%
0 459240
 
7.6%
7 444579
 
7.4%
4 377786
 
6.3%
5 367488
 
6.1%
6 364666
 
6.1%
Distinct29672
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:49.568439image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11427569
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

Unique12662 ?
Unique (%)2.1%

Sample

1st row2021-08-09 14:50:00
2nd row2020-04-09 11:54:00
3rd row2020-03-17 10:16:00
4th row2020-05-20 10:50:00
5th row2017-12-08 15:28:00
ValueCountFrequency (%)
2017-12-08 28553
 
2.4%
2021-01-15 25810
 
2.1%
2020-07-24 12948
 
1.1%
2020-04-09 11060
 
0.9%
2020-03-12 10837
 
0.9%
2020-04-13 9731
 
0.8%
2020-04-14 8525
 
0.7%
2020-04-06 8277
 
0.7%
2020-03-25 8028
 
0.7%
2020-04-02 7941
 
0.7%
Other values (2209) 1071192
89.1%
2025-02-10T13:50:49.788552image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3217264
28.2%
2 1683114
14.7%
1 1412891
12.4%
- 1202902
 
10.5%
: 1202902
 
10.5%
601451
 
5.3%
4 455860
 
4.0%
3 439973
 
3.9%
5 428273
 
3.7%
9 215795
 
1.9%
Other values (3) 567144
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3217264
28.2%
2 1683114
14.7%
1 1412891
12.4%
- 1202902
 
10.5%
: 1202902
 
10.5%
601451
 
5.3%
4 455860
 
4.0%
3 439973
 
3.9%
5 428273
 
3.7%
9 215795
 
1.9%
Other values (3) 567144
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3217264
28.2%
2 1683114
14.7%
1 1412891
12.4%
- 1202902
 
10.5%
: 1202902
 
10.5%
601451
 
5.3%
4 455860
 
4.0%
3 439973
 
3.9%
5 428273
 
3.7%
9 215795
 
1.9%
Other values (3) 567144
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3217264
28.2%
2 1683114
14.7%
1 1412891
12.4%
- 1202902
 
10.5%
: 1202902
 
10.5%
601451
 
5.3%
4 455860
 
4.0%
3 439973
 
3.9%
5 428273
 
3.7%
9 215795
 
1.9%
Other values (3) 567144
 
5.0%
Distinct50
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:49.834188image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length28.8108624
Min length2

Characters and Unicode

Total characters17328322
Distinct characters41
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 rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 596967
99.3%
nsmt 977
 
0.2%
uam 775
 
0.1%
nrm 386
 
0.1%
rmnh 354
 
0.1%
rcs 246
 
< 0.1%
nmv 238
 
< 0.1%
nmsz 188
 
< 0.1%
zmmu 179
 
< 0.1%
fcmm 127
 
< 0.1%
Other values (40) 1015
 
0.2%
2025-02-10T13:50:49.923892image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2387868
13.8%
: 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
g 596967
 
3.4%
7 596967
 
3.4%
8 596967
 
3.4%
4 596967
 
3.4%
Other values (31) 4792015
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17328322
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2387868
13.8%
: 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
g 596967
 
3.4%
7 596967
 
3.4%
8 596967
 
3.4%
4 596967
 
3.4%
Other values (31) 4792015
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17328322
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2387868
13.8%
: 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
g 596967
 
3.4%
7 596967
 
3.4%
8 596967
 
3.4%
4 596967
 
3.4%
Other values (31) 4792015
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17328322
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2387868
13.8%
: 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
g 596967
 
3.4%
7 596967
 
3.4%
8 596967
 
3.4%
4 596967
 
3.4%
Other values (31) 4792015
27.7%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:49.954454image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters27065295
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
2nd rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
3rd rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
4th rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
5th rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
ValueCountFrequency (%)
urn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22 601451
100.0%
2025-02-10T13:50:50.039071image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 3007255
 
11.1%
- 2405804
 
8.9%
5 2405804
 
8.9%
6 1804353
 
6.7%
e 1804353
 
6.7%
u 1804353
 
6.7%
d 1202902
 
4.4%
9 1202902
 
4.4%
: 1202902
 
4.4%
1 1202902
 
4.4%
Other values (12) 9021765
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27065295
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 3007255
 
11.1%
- 2405804
 
8.9%
5 2405804
 
8.9%
6 1804353
 
6.7%
e 1804353
 
6.7%
u 1804353
 
6.7%
d 1202902
 
4.4%
9 1202902
 
4.4%
: 1202902
 
4.4%
1 1202902
 
4.4%
Other values (12) 9021765
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27065295
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 3007255
 
11.1%
- 2405804
 
8.9%
5 2405804
 
8.9%
6 1804353
 
6.7%
e 1804353
 
6.7%
u 1804353
 
6.7%
d 1202902
 
4.4%
9 1202902
 
4.4%
: 1202902
 
4.4%
1 1202902
 
4.4%
Other values (12) 9021765
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27065295
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 3007255
 
11.1%
- 2405804
 
8.9%
5 2405804
 
8.9%
6 1804353
 
6.7%
e 1804353
 
6.7%
u 1804353
 
6.7%
d 1202902
 
4.4%
9 1202902
 
4.4%
: 1202902
 
4.4%
1 1202902
 
4.4%
Other values (12) 9021765
33.3%
Distinct50
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:50.071820image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.997244996
Min length2

Characters and Unicode

Total characters2404147
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

Unique13 ?
Unique (%)< 0.1%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 596967
99.3%
nsmt 977
 
0.2%
uam 775
 
0.1%
nrm 386
 
0.1%
rmnh 354
 
0.1%
rcs 246
 
< 0.1%
nmv 238
 
< 0.1%
nmsz 188
 
< 0.1%
zmmu 179
 
< 0.1%
fcmm 127
 
< 0.1%
Other values (40) 1015
 
0.2%
2025-02-10T13:50:50.159316image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2404147
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2404147
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2404147
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:50.189507image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2405804
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 rowMAMM
2nd rowMAMM
3rd rowMAMM
4th rowMAMM
5th rowMAMM
ValueCountFrequency (%)
mamm 601451
100.0%
2025-02-10T13:50:50.271494image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2405804
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2405804
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2405804
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:50.302474image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11427569
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 601451
33.3%
extant 601451
33.3%
biology 601451
33.3%
2025-02-10T13:50:50.389309image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1202902
 
10.5%
1202902
 
10.5%
t 1202902
 
10.5%
o 1202902
 
10.5%
M 601451
 
5.3%
H 601451
 
5.3%
E 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
n 601451
 
5.3%
Other values (5) 3007255
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1202902
 
10.5%
1202902
 
10.5%
t 1202902
 
10.5%
o 1202902
 
10.5%
M 601451
 
5.3%
H 601451
 
5.3%
E 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
n 601451
 
5.3%
Other values (5) 3007255
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1202902
 
10.5%
1202902
 
10.5%
t 1202902
 
10.5%
o 1202902
 
10.5%
M 601451
 
5.3%
H 601451
 
5.3%
E 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
n 601451
 
5.3%
Other values (5) 3007255
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1202902
 
10.5%
1202902
 
10.5%
t 1202902
 
10.5%
o 1202902
 
10.5%
M 601451
 
5.3%
H 601451
 
5.3%
E 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
n 601451
 
5.3%
Other values (5) 3007255
26.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:50.419956image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length16.95205428
Min length16

Characters and Unicode

Total characters10195830
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowHumanObservation
ValueCountFrequency (%)
preservedspecimen 572614
95.2%
humanobservation 28837
 
4.8%
2025-02-10T13:50:50.512294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2891907
28.4%
r 1174065
11.5%
n 630288
 
6.2%
i 601451
 
5.9%
s 601451
 
5.9%
v 601451
 
5.9%
m 601451
 
5.9%
c 572614
 
5.6%
P 572614
 
5.6%
p 572614
 
5.6%
Other values (9) 1375924
13.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10195830
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2891907
28.4%
r 1174065
11.5%
n 630288
 
6.2%
i 601451
 
5.9%
s 601451
 
5.9%
v 601451
 
5.9%
m 601451
 
5.9%
c 572614
 
5.6%
P 572614
 
5.6%
p 572614
 
5.6%
Other values (9) 1375924
13.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10195830
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2891907
28.4%
r 1174065
11.5%
n 630288
 
6.2%
i 601451
 
5.9%
s 601451
 
5.9%
v 601451
 
5.9%
m 601451
 
5.9%
c 572614
 
5.6%
P 572614
 
5.6%
p 572614
 
5.6%
Other values (9) 1375924
13.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10195830
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2891907
28.4%
r 1174065
11.5%
n 630288
 
6.2%
i 601451
 
5.9%
s 601451
 
5.9%
v 601451
 
5.9%
m 601451
 
5.9%
c 572614
 
5.6%
P 572614
 
5.6%
p 572614
 
5.6%
Other values (9) 1375924
13.5%

occurrenceID
Text

Unique 

Distinct601451
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:50.781617image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters37891413
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique601451 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/3ebec6a7f-5e95-4543-b061-6d73d80dd2ee
2nd rowhttp://n2t.net/ark:/65665/3ec070d5d-1893-4600-afa5-e56695ff219b
3rd rowhttp://n2t.net/ark:/65665/3002acaf9-9788-4539-8883-fe6bfd5f8d88
4th rowhttp://n2t.net/ark:/65665/300553499-1544-460e-9507-55ada241f992
5th rowhttp://n2t.net/ark:/65665/3005a3503-9c20-443c-899a-559e550dc71e
ValueCountFrequency (%)
http://n2t.net/ark:/65665/3ebec6a7f-5e95-4543-b061-6d73d80dd2ee 1
 
< 0.1%
http://n2t.net/ark:/65665/3ecc76d35-e5c5-434e-874b-88c5d85dbb91 1
 
< 0.1%
http://n2t.net/ark:/65665/3ecff6276-27d1-4ad7-aac3-32c485b9bed6 1
 
< 0.1%
http://n2t.net/ark:/65665/3eceb4d85-2fbe-4bf2-aef7-b3393445f319 1
 
< 0.1%
http://n2t.net/ark:/65665/300f96572-4f6d-48dc-9b78-1ba0e03bb0ae 1
 
< 0.1%
http://n2t.net/ark:/65665/3ec5d68e1-4786-40d2-9bdb-bb8ef2ad056d 1
 
< 0.1%
http://n2t.net/ark:/65665/3002acaf9-9788-4539-8883-fe6bfd5f8d88 1
 
< 0.1%
http://n2t.net/ark:/65665/300553499-1544-460e-9507-55ada241f992 1
 
< 0.1%
http://n2t.net/ark:/65665/3005a3503-9c20-443c-899a-559e550dc71e 1
 
< 0.1%
http://n2t.net/ark:/65665/300664e6c-5334-4a8e-b9a7-4d84389595e0 1
 
< 0.1%
Other values (601441) 601441
> 99.9%
2025-02-10T13:50:51.119296image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37891413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37891413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37891413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%
Distinct601428
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:51.377114image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length11
Mean length10.92069179
Min length4

Characters and Unicode

Total characters6568261
Distinct characters35
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

Unique601407 ?
Unique (%)> 99.9%

Sample

1st rowUSNM 449558
2nd rowUSNM 226903
3rd rowUSNM 386480
4th rowUSNM 68620
5th rowUSNM MME9342
ValueCountFrequency (%)
usnm 596967
49.8%
wam 63
 
< 0.1%
mb 40
 
< 0.1%
zin 21
 
< 0.1%
lacm 18
 
< 0.1%
nsmt 12
 
< 0.1%
sama 6
 
< 0.1%
zmmu 5
 
< 0.1%
rmnh 4
 
< 0.1%
ncsm 4
 
< 0.1%
Other values (601439) 601471
50.2%
2025-02-10T13:50:51.676460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6568261
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6568261
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6568261
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

recordNumber
Text

Missing 

Distinct172937
Distinct (%)31.4%
Missing50821
Missing (%)8.4%
Memory size4.6 MiB
2025-02-10T13:50:51.856673image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length28
Mean length5.176632221
Min length1

Characters and Unicode

Total characters2850409
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

Unique147848 ?
Unique (%)26.9%

Sample

1st rowFMG 2371
2nd row142/19534X
3rd row07960
4th row6459
5th rowB47586/R50468
ValueCountFrequency (%)
no 47434
 
6.9%
number 47222
 
6.9%
cohjr 5988
 
0.9%
nzp 3372
 
0.5%
psc 2713
 
0.4%
jwk 2021
 
0.3%
r 1947
 
0.3%
fm 1793
 
0.3%
jjg 1781
 
0.3%
rem 1569
 
0.2%
Other values (105383) 570874
83.1%
2025-02-10T13:50:52.112257image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2850409
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2850409
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2850409
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

recordedBy
Text

Missing 

Distinct17644
Distinct (%)3.2%
Missing55563
Missing (%)9.2%
Memory size4.6 MiB
2025-02-10T13:50:52.269429image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length124
Median length114
Mean length11.92282483
Min length1

Characters and Unicode

Total characters6508527
Distinct characters80
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

Unique9079 ?
Unique (%)1.7%

Sample

1st rowF. Greenwell
2nd rowJ. Silver
3rd rowSmithsonian Venezuelan Project
4th rowNelson & E. Goldman
5th rowW. Bowen & V. Thayer
ValueCountFrequency (%)
j 60783
 
4.7%
e 54366
 
4.2%
c 53496
 
4.2%
50457
 
3.9%
r 49868
 
3.9%
a 44074
 
3.4%
w 37880
 
2.9%
h 30720
 
2.4%
d 24753
 
1.9%
m 23831
 
1.9%
Other values (10447) 856734
66.6%
2025-02-10T13:50:52.503218image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6508527
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6508527
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6508527
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%
Distinct21
Distinct (%)< 0.1%
Missing44
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:50:52.539668image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.000033255
Min length1

Characters and Unicode

Total characters601427
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

Unique11 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 601314
> 99.9%
2 45
 
< 0.1%
6 8
 
< 0.1%
3 8
 
< 0.1%
4 6
 
< 0.1%
7 5
 
< 0.1%
5 4
 
< 0.1%
271 2
 
< 0.1%
11 2
 
< 0.1%
20 2
 
< 0.1%
Other values (11) 11
 
< 0.1%
2025-02-10T13:50:52.629542image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 601326
> 99.9%
2 51
 
< 0.1%
6 9
 
< 0.1%
3 9
 
< 0.1%
4 9
 
< 0.1%
7 8
 
< 0.1%
0 7
 
< 0.1%
5 6
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 601427
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 601326
> 99.9%
2 51
 
< 0.1%
6 9
 
< 0.1%
3 9
 
< 0.1%
4 9
 
< 0.1%
7 8
 
< 0.1%
0 7
 
< 0.1%
5 6
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 601427
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 601326
> 99.9%
2 51
 
< 0.1%
6 9
 
< 0.1%
3 9
 
< 0.1%
4 9
 
< 0.1%
7 8
 
< 0.1%
0 7
 
< 0.1%
5 6
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 601427
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 601326
> 99.9%
2 51
 
< 0.1%
6 9
 
< 0.1%
3 9
 
< 0.1%
4 9
 
< 0.1%
7 8
 
< 0.1%
0 7
 
< 0.1%
5 6
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%

sex
Text

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:50:52.664258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length21
Mean length5.271076114
Min length1

Characters and Unicode

Total characters3170294
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

Unique9 ?
Unique (%)< 0.1%

Sample

1st rowMale
2nd rowMale
3rd rowMale
4th rowFemale
5th rowFemale
ValueCountFrequency (%)
male 266476
44.2%
female 246781
41.0%
unknown 87925
 
14.6%
multiple 279
 
< 0.1%
animals 279
 
< 0.1%
of 279
 
< 0.1%
mixed 279
 
< 0.1%
sex 279
 
< 0.1%
12
 
< 0.1%
f 5
 
< 0.1%
Other values (6) 10
 
< 0.1%
2025-02-10T13:50:52.762106image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 760879
24.0%
l 514098
16.2%
a 513820
16.2%
M 266760
 
8.4%
n 264058
 
8.3%
m 247341
 
7.8%
F 246786
 
7.8%
o 88205
 
2.8%
w 87927
 
2.8%
U 87926
 
2.8%
Other values (17) 92494
 
2.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3170294
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 760879
24.0%
l 514098
16.2%
a 513820
16.2%
M 266760
 
8.4%
n 264058
 
8.3%
m 247341
 
7.8%
F 246786
 
7.8%
o 88205
 
2.8%
w 87927
 
2.8%
U 87926
 
2.8%
Other values (17) 92494
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3170294
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 760879
24.0%
l 514098
16.2%
a 513820
16.2%
M 266760
 
8.4%
n 264058
 
8.3%
m 247341
 
7.8%
F 246786
 
7.8%
o 88205
 
2.8%
w 87927
 
2.8%
U 87926
 
2.8%
Other values (17) 92494
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3170294
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 760879
24.0%
l 514098
16.2%
a 513820
16.2%
M 266760
 
8.4%
n 264058
 
8.3%
m 247341
 
7.8%
F 246786
 
7.8%
o 88205
 
2.8%
w 87927
 
2.8%
U 87926
 
2.8%
Other values (17) 92494
 
2.9%

lifeStage
Text

Missing 

Distinct91
Distinct (%)0.2%
Missing549447
Missing (%)91.4%
Memory size4.6 MiB
2025-02-10T13:50:52.798432image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length5
Mean length6.100703792
Min length3

Characters and Unicode

Total characters317261
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)< 0.1%

Sample

1st rowAdult
2nd rowAdult
3rd rowJuvenile
4th rowJuvenile
5th rowAdult
ValueCountFrequency (%)
adult 31151
58.8%
juvenile 9861
 
18.6%
immature 3907
 
7.4%
subadult 2173
 
4.1%
young 1853
 
3.5%
embryo 837
 
1.6%
fetus 684
 
1.3%
old 511
 
1.0%
nestling 499
 
0.9%
neonate 453
 
0.9%
Other values (55) 1019
 
1.9%
2025-02-10T13:50:52.898644image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
u 52076
16.4%
l 44573
14.0%
t 39354
12.4%
d 33936
10.7%
A 30440
9.6%
e 26241
8.3%
n 13312
 
4.2%
i 10584
 
3.3%
v 9888
 
3.1%
J 9846
 
3.1%
Other values (35) 47011
14.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 317261
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
u 52076
16.4%
l 44573
14.0%
t 39354
12.4%
d 33936
10.7%
A 30440
9.6%
e 26241
8.3%
n 13312
 
4.2%
i 10584
 
3.3%
v 9888
 
3.1%
J 9846
 
3.1%
Other values (35) 47011
14.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 317261
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
u 52076
16.4%
l 44573
14.0%
t 39354
12.4%
d 33936
10.7%
A 30440
9.6%
e 26241
8.3%
n 13312
 
4.2%
i 10584
 
3.3%
v 9888
 
3.1%
J 9846
 
3.1%
Other values (35) 47011
14.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 317261
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
u 52076
16.4%
l 44573
14.0%
t 39354
12.4%
d 33936
10.7%
A 30440
9.6%
e 26241
8.3%
n 13312
 
4.2%
i 10584
 
3.3%
v 9888
 
3.1%
J 9846
 
3.1%
Other values (35) 47011
14.8%

preparations
Text

Missing 

Distinct542
Distinct (%)0.1%
Missing26965
Missing (%)4.5%
Memory size4.6 MiB
2025-02-10T13:50:52.930582image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length73
Median length11
Mean length10.02423558
Min length4

Characters and Unicode

Total characters5758783
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique248 ?
Unique (%)< 0.1%

Sample

1st rowSkin; Skull
2nd rowSkin; Skull
3rd rowSkin; Skull
4th rowSkin; Skull
5th rowSkin; Skull
ValueCountFrequency (%)
skull 452764
44.7%
skin 367609
36.3%
fluid 101452
 
10.0%
skeleton 36584
 
3.6%
partial 10316
 
1.0%
in 8642
 
0.9%
remainder 8641
 
0.9%
anatomical 5878
 
0.6%
baculum/baubellum 3372
 
0.3%
baleen 2349
 
0.2%
Other values (42) 14726
 
1.5%
2025-02-10T13:50:53.040972image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5758783
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5758783
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5758783
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

associatedMedia
Text

Missing 

Distinct48707
Distinct (%)8.8%
Missing45503
Missing (%)7.6%
Memory size4.6 MiB
2025-02-10T13:50:53.132215image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1263
Median length49
Mean length50.56994719
Min length48

Characters and Unicode

Total characters28114261
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

Unique15254 ?
Unique (%)2.7%

Sample

1st rowhttps://collections.nmnh.si.edu/media/?i=14431681
2nd rowhttps://collections.nmnh.si.edu/media/?i=14603706
3rd rowhttps://collections.nmnh.si.edu/media/?i=14483098
4th rowhttps://collections.nmnh.si.edu/media/?i=14780717
5th rowhttps://collections.nmnh.si.edu/media/?i=14572646
ValueCountFrequency (%)
14887746 84
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14563406 60
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561922 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561911 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561967 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561909 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561974 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561968 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561972 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=14561943 50
 
< 0.1%
Other values (81691) 643161
99.9%
2025-02-10T13:50:53.308563image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2223792
 
7.9%
/ 2223792
 
7.9%
t 1667844
 
5.9%
s 1667844
 
5.9%
. 1667844
 
5.9%
n 1667844
 
5.9%
e 1667844
 
5.9%
h 1111896
 
4.0%
d 1111896
 
4.0%
m 1111896
 
4.0%
Other values (21) 11991769
42.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28114261
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 2223792
 
7.9%
/ 2223792
 
7.9%
t 1667844
 
5.9%
s 1667844
 
5.9%
. 1667844
 
5.9%
n 1667844
 
5.9%
e 1667844
 
5.9%
h 1111896
 
4.0%
d 1111896
 
4.0%
m 1111896
 
4.0%
Other values (21) 11991769
42.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28114261
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 2223792
 
7.9%
/ 2223792
 
7.9%
t 1667844
 
5.9%
s 1667844
 
5.9%
. 1667844
 
5.9%
n 1667844
 
5.9%
e 1667844
 
5.9%
h 1111896
 
4.0%
d 1111896
 
4.0%
m 1111896
 
4.0%
Other values (21) 11991769
42.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28114261
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 2223792
 
7.9%
/ 2223792
 
7.9%
t 1667844
 
5.9%
s 1667844
 
5.9%
. 1667844
 
5.9%
n 1667844
 
5.9%
e 1667844
 
5.9%
h 1111896
 
4.0%
d 1111896
 
4.0%
m 1111896
 
4.0%
Other values (21) 11991769
42.7%

associatedSequences
Text

Missing 

Distinct1050
Distinct (%)99.6%
Missing600397
Missing (%)99.8%
Memory size4.6 MiB
2025-02-10T13:50:53.359619image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length699
Median length49
Mean length99.59108159
Min length47

Characters and Unicode

Total characters104969
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

Unique1046 ?
Unique (%)99.2%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=AY922964|https://www.ncbi.nlm.nih.gov/gquery?term=AY922875
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KC753815|https://www.ncbi.nlm.nih.gov/gquery?term=KC753933|https://www.ncbi.nlm.nih.gov/gquery?term=KC754042|https://www.ncbi.nlm.nih.gov/gquery?term=KC754162|https://www.ncbi.nlm.nih.gov/gquery?term=KC754280
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KC011508|https://www.ncbi.nlm.nih.gov/gquery?term=KC011594|https://www.ncbi.nlm.nih.gov/gquery?term=KC011682
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MN707485|https://www.ncbi.nlm.nih.gov/gquery?term=MN707432
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ317640|https://www.ncbi.nlm.nih.gov/gquery?term=JQ317668
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=eu021073 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=fj383131 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=kx998919 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=eu021074 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=dq178333|https://www.ncbi.nlm.nih.gov/gquery?term=dq178344 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=ay974630|https://www.ncbi.nlm.nih.gov/gquery?term=ay974676 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=kc753815|https://www.ncbi.nlm.nih.gov/gquery?term=kc753933|https://www.ncbi.nlm.nih.gov/gquery?term=kc754042|https://www.ncbi.nlm.nih.gov/gquery?term=kc754162|https://www.ncbi.nlm.nih.gov/gquery?term=kc754280 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=kc011508|https://www.ncbi.nlm.nih.gov/gquery?term=kc011594|https://www.ncbi.nlm.nih.gov/gquery?term=kc011682 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=mn707485|https://www.ncbi.nlm.nih.gov/gquery?term=mn707432 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jq317640|https://www.ncbi.nlm.nih.gov/gquery?term=jq317668 1
 
0.1%
Other values (1040) 1040
98.7%
2025-02-10T13:50:53.465221image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8515
 
8.1%
/ 6360
 
6.1%
w 6360
 
6.1%
n 6360
 
6.1%
t 6360
 
6.1%
h 4240
 
4.0%
r 4240
 
4.0%
e 4240
 
4.0%
i 4240
 
4.0%
m 4240
 
4.0%
Other values (48) 49814
47.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 104969
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 8515
 
8.1%
/ 6360
 
6.1%
w 6360
 
6.1%
n 6360
 
6.1%
t 6360
 
6.1%
h 4240
 
4.0%
r 4240
 
4.0%
e 4240
 
4.0%
i 4240
 
4.0%
m 4240
 
4.0%
Other values (48) 49814
47.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 104969
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 8515
 
8.1%
/ 6360
 
6.1%
w 6360
 
6.1%
n 6360
 
6.1%
t 6360
 
6.1%
h 4240
 
4.0%
r 4240
 
4.0%
e 4240
 
4.0%
i 4240
 
4.0%
m 4240
 
4.0%
Other values (48) 49814
47.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 104969
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 8515
 
8.1%
/ 6360
 
6.1%
w 6360
 
6.1%
n 6360
 
6.1%
t 6360
 
6.1%
h 4240
 
4.0%
r 4240
 
4.0%
e 4240
 
4.0%
i 4240
 
4.0%
m 4240
 
4.0%
Other values (48) 49814
47.5%

occurrenceRemarks
Text

Missing 

Distinct5322
Distinct (%)49.3%
Missing590662
Missing (%)98.2%
Memory size4.6 MiB
2025-02-10T13:50:53.622543image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44804
Median length2082
Mean length214.0076003
Min length4

Characters and Unicode

Total characters2308928
Distinct characters158
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

Unique4721 ?
Unique (%)43.8%

Sample

1st rowFrom ledger catalogue 577876-577900: "field data recorded from field catalogues"
2nd rowSkin found in rotunda hallway hold-up case, 2017. May need tanning before installation into collection.
3rd rowLectotype designated by Avila Pires (1968:163).
4th rowSkull removed from alcoholic specimen.
5th rowMore than 800 dolphins stranded along a 220 km stretch pof the coast of Peru. See STR18239.; Broccetto, Marilia CNN website 22 IV 2012
ValueCountFrequency (%)
the 13880
 
3.8%
of 9359
 
2.6%
and 7684
 
2.1%
in 7077
 
1.9%
for 6435
 
1.8%
to 6041
 
1.6%
4896
 
1.3%
on 4761
 
1.3%
was 4231
 
1.2%
from 3875
 
1.1%
Other values (19019) 298259
81.4%
2025-02-10T13:50:53.850648image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2308928
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2308928
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2308928
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

eventDate
Text

Missing 

Distinct46637
Distinct (%)8.1%
Missing28127
Missing (%)4.7%
Memory size4.6 MiB
2025-02-10T13:50:54.018680image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length9.727609519
Min length4

Characters and Unicode

Total characters5577072
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

Unique7673 ?
Unique (%)1.3%

Sample

1st row1989-02-28
2nd row1917-08-08
3rd row1966-05
4th row1894-07-15
5th row1992-11-05
ValueCountFrequency (%)
1968 1160
 
0.2%
1959 769
 
0.1%
1965-06 704
 
0.1%
1966-06-02 682
 
0.1%
1903 600
 
0.1%
1905 591
 
0.1%
1965 543
 
0.1%
1967-08 537
 
0.1%
1967-05 529
 
0.1%
1968-09-02 520
 
0.1%
Other values (46627) 566689
98.8%
2025-02-10T13:50:54.247104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1092495
19.6%
- 1092362
19.6%
0 833561
14.9%
9 717766
12.9%
2 392002
 
7.0%
6 323478
 
5.8%
8 309247
 
5.5%
7 251593
 
4.5%
3 195678
 
3.5%
5 191966
 
3.4%
Other values (2) 176924
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5577072
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1092495
19.6%
- 1092362
19.6%
0 833561
14.9%
9 717766
12.9%
2 392002
 
7.0%
6 323478
 
5.8%
8 309247
 
5.5%
7 251593
 
4.5%
3 195678
 
3.5%
5 191966
 
3.4%
Other values (2) 176924
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5577072
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1092495
19.6%
- 1092362
19.6%
0 833561
14.9%
9 717766
12.9%
2 392002
 
7.0%
6 323478
 
5.8%
8 309247
 
5.5%
7 251593
 
4.5%
3 195678
 
3.5%
5 191966
 
3.4%
Other values (2) 176924
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5577072
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1092495
19.6%
- 1092362
19.6%
0 833561
14.9%
9 717766
12.9%
2 392002
 
7.0%
6 323478
 
5.8%
8 309247
 
5.5%
7 251593
 
4.5%
3 195678
 
3.5%
5 191966
 
3.4%
Other values (2) 176924
 
3.2%

startDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing46793
Missing (%)7.8%
Memory size4.6 MiB
2025-02-10T13:50:54.409831image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.724276942
Min length1

Characters and Unicode

Total characters1511042
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 row59
2nd row220
3rd row151
4th row196
5th row310
ValueCountFrequency (%)
181 3910
 
0.7%
59 3214
 
0.6%
243 3136
 
0.6%
212 3000
 
0.5%
151 2957
 
0.5%
213 2690
 
0.5%
120 2635
 
0.5%
334 2476
 
0.4%
193 2428
 
0.4%
304 2382
 
0.4%
Other values (356) 525830
94.8%
2025-02-10T13:50:54.629943image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 288485
19.1%
2 278737
18.4%
3 192107
12.7%
5 114772
 
7.6%
4 114286
 
7.6%
6 108886
 
7.2%
0 104494
 
6.9%
7 103973
 
6.9%
9 103679
 
6.9%
8 101623
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1511042
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 288485
19.1%
2 278737
18.4%
3 192107
12.7%
5 114772
 
7.6%
4 114286
 
7.6%
6 108886
 
7.2%
0 104494
 
6.9%
7 103973
 
6.9%
9 103679
 
6.9%
8 101623
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1511042
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 288485
19.1%
2 278737
18.4%
3 192107
12.7%
5 114772
 
7.6%
4 114286
 
7.6%
6 108886
 
7.2%
0 104494
 
6.9%
7 103973
 
6.9%
9 103679
 
6.9%
8 101623
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1511042
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 288485
19.1%
2 278737
18.4%
3 192107
12.7%
5 114772
 
7.6%
4 114286
 
7.6%
6 108886
 
7.2%
0 104494
 
6.9%
7 103973
 
6.9%
9 103679
 
6.9%
8 101623
 
6.7%

endDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing46765
Missing (%)7.8%
Memory size4.6 MiB
2025-02-10T13:50:54.787711image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.724321508
Min length1

Characters and Unicode

Total characters1511143
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 row59
2nd row220
3rd row151
4th row196
5th row310
ValueCountFrequency (%)
181 3912
 
0.7%
59 3215
 
0.6%
243 3146
 
0.6%
151 3016
 
0.5%
212 2960
 
0.5%
213 2646
 
0.5%
120 2638
 
0.5%
334 2464
 
0.4%
304 2406
 
0.4%
222 2369
 
0.4%
Other values (356) 525914
94.8%
2025-02-10T13:50:55.006562image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 288287
19.1%
2 278817
18.5%
3 192047
12.7%
5 114832
 
7.6%
4 114656
 
7.6%
6 108777
 
7.2%
0 104587
 
6.9%
7 103968
 
6.9%
9 103568
 
6.9%
8 101604
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1511143
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 288287
19.1%
2 278817
18.5%
3 192047
12.7%
5 114832
 
7.6%
4 114656
 
7.6%
6 108777
 
7.2%
0 104587
 
6.9%
7 103968
 
6.9%
9 103568
 
6.9%
8 101604
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1511143
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 288287
19.1%
2 278817
18.5%
3 192047
12.7%
5 114832
 
7.6%
4 114656
 
7.6%
6 108777
 
7.2%
0 104587
 
6.9%
7 103968
 
6.9%
9 103568
 
6.9%
8 101604
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1511143
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 288287
19.1%
2 278817
18.5%
3 192047
12.7%
5 114832
 
7.6%
4 114656
 
7.6%
6 108777
 
7.2%
0 104587
 
6.9%
7 103968
 
6.9%
9 103568
 
6.9%
8 101604
 
6.7%

year
Text

Missing 

Distinct350
Distinct (%)0.1%
Missing28127
Missing (%)4.7%
Memory size4.6 MiB
2025-02-10T13:50:55.158218image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2293296
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

Unique74 ?
Unique (%)< 0.1%

Sample

1st row1989
2nd row1917
3rd row1966
4th row1894
5th row1992
ValueCountFrequency (%)
1967 30814
 
5.4%
1968 27037
 
4.7%
1966 22575
 
3.9%
1969 15259
 
2.7%
1965 12690
 
2.2%
1964 12541
 
2.2%
1962 11211
 
2.0%
1970 10527
 
1.8%
1916 9955
 
1.7%
1963 9798
 
1.7%
Other values (340) 410917
71.7%
2025-02-10T13:50:55.364303image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 670022
29.2%
9 621720
27.1%
6 214950
 
9.4%
8 199846
 
8.7%
7 134632
 
5.9%
0 133037
 
5.8%
5 87362
 
3.8%
2 86888
 
3.8%
4 76111
 
3.3%
3 68728
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2293296
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 670022
29.2%
9 621720
27.1%
6 214950
 
9.4%
8 199846
 
8.7%
7 134632
 
5.9%
0 133037
 
5.8%
5 87362
 
3.8%
2 86888
 
3.8%
4 76111
 
3.3%
3 68728
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2293296
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 670022
29.2%
9 621720
27.1%
6 214950
 
9.4%
8 199846
 
8.7%
7 134632
 
5.9%
0 133037
 
5.8%
5 87362
 
3.8%
2 86888
 
3.8%
4 76111
 
3.3%
3 68728
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2293296
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 670022
29.2%
9 621720
27.1%
6 214950
 
9.4%
8 199846
 
8.7%
7 134632
 
5.9%
0 133037
 
5.8%
5 87362
 
3.8%
2 86888
 
3.8%
4 76111
 
3.3%
3 68728
 
3.0%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing44866
Missing (%)7.5%
Memory size4.6 MiB
2025-02-10T13:50:55.409282image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.192750433
Min length1

Characters and Unicode

Total characters663867
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 row2
2nd row8
3rd row5
4th row7
5th row11
ValueCountFrequency (%)
7 63622
11.4%
8 55632
10.0%
6 55508
10.0%
3 50988
9.2%
5 50119
9.0%
4 46824
8.4%
9 43994
7.9%
2 43078
7.7%
10 40461
7.3%
1 39538
7.1%
Other values (2) 66821
12.0%
2025-02-10T13:50:55.499912image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 182088
27.4%
2 74631
11.2%
7 63622
 
9.6%
8 55632
 
8.4%
6 55508
 
8.4%
3 50988
 
7.7%
5 50119
 
7.5%
4 46824
 
7.1%
9 43994
 
6.6%
0 40461
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 663867
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 182088
27.4%
2 74631
11.2%
7 63622
 
9.6%
8 55632
 
8.4%
6 55508
 
8.4%
3 50988
 
7.7%
5 50119
 
7.5%
4 46824
 
7.1%
9 43994
 
6.6%
0 40461
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 663867
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 182088
27.4%
2 74631
11.2%
7 63622
 
9.6%
8 55632
 
8.4%
6 55508
 
8.4%
3 50988
 
7.7%
5 50119
 
7.5%
4 46824
 
7.1%
9 43994
 
6.6%
0 40461
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 663867
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 182088
27.4%
2 74631
11.2%
7 63622
 
9.6%
8 55632
 
8.4%
6 55508
 
8.4%
3 50988
 
7.7%
5 50119
 
7.5%
4 46824
 
7.1%
9 43994
 
6.6%
0 40461
 
6.1%

day
Text

Missing 

Distinct31
Distinct (%)< 0.1%
Missing67482
Missing (%)11.2%
Memory size4.6 MiB
2025-02-10T13:50:55.546925image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.708157215
Min length1

Characters and Unicode

Total characters912103
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 row28
2nd row8
3rd row15
4th row5
5th row18
ValueCountFrequency (%)
10 19188
 
3.6%
20 18614
 
3.5%
22 18464
 
3.5%
15 18400
 
3.4%
18 18199
 
3.4%
14 18001
 
3.4%
5 17933
 
3.4%
16 17919
 
3.4%
27 17835
 
3.3%
21 17818
 
3.3%
Other values (21) 351598
65.8%
2025-02-10T13:50:55.652372image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 238401
26.1%
2 229686
25.2%
3 75593
 
8.3%
5 53889
 
5.9%
0 53247
 
5.8%
8 53132
 
5.8%
7 52819
 
5.8%
6 52526
 
5.8%
4 52154
 
5.7%
9 50656
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 912103
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 238401
26.1%
2 229686
25.2%
3 75593
 
8.3%
5 53889
 
5.9%
0 53247
 
5.8%
8 53132
 
5.8%
7 52819
 
5.8%
6 52526
 
5.8%
4 52154
 
5.7%
9 50656
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 912103
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 238401
26.1%
2 229686
25.2%
3 75593
 
8.3%
5 53889
 
5.9%
0 53247
 
5.8%
8 53132
 
5.8%
7 52819
 
5.8%
6 52526
 
5.8%
4 52154
 
5.7%
9 50656
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 912103
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 238401
26.1%
2 229686
25.2%
3 75593
 
8.3%
5 53889
 
5.9%
0 53247
 
5.8%
8 53132
 
5.8%
7 52819
 
5.8%
6 52526
 
5.8%
4 52154
 
5.7%
9 50656
 
5.6%

verbatimEventDate
Text

Missing 

Distinct45124
Distinct (%)8.0%
Missing36490
Missing (%)6.1%
Memory size4.6 MiB
2025-02-10T13:50:55.801952image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length82
Median length11
Mean length10.73425953
Min length3

Characters and Unicode

Total characters6064438
Distinct characters75
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

Unique7925 ?
Unique (%)1.4%

Sample

1st row28 Feb 1989
2nd row8 Aug 1917
3rd row-- May 1966
4th row15 Jul 1894
5th row5 Nov 1992
ValueCountFrequency (%)
119289
 
7.0%
jul 59029
 
3.5%
aug 52663
 
3.1%
jun 52253
 
3.1%
mar 49098
 
2.9%
may 47959
 
2.8%
apr 45015
 
2.6%
sep 41961
 
2.5%
feb 40432
 
2.4%
oct 39123
 
2.3%
Other values (873) 1153619
67.8%
2025-02-10T13:50:56.032525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6064438
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6064438
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6064438
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

habitat
Text

Missing 

Distinct7512
Distinct (%)5.7%
Missing468915
Missing (%)78.0%
Memory size4.6 MiB
2025-02-10T13:50:56.189003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1014
Median length694
Mean length27.3692808
Min length1

Characters and Unicode

Total characters3627415
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

Unique4415 ?
Unique (%)3.3%

Sample

1st rowEcological remarks by collector(s): yes
2nd rowPremontane very humid forest
3rd rowEcological remarks by collector(s): no
4th rowEcological remarks by collector(s): yes
5th rowCulvert
ValueCountFrequency (%)
by 49297
 
9.4%
ecological 48727
 
9.3%
remarks 48718
 
9.3%
collector(s 48716
 
9.3%
yes 41564
 
8.0%
forest 32139
 
6.2%
tropical 15058
 
2.9%
humid 14768
 
2.8%
no 7275
 
1.4%
in 6943
 
1.3%
Other values (3497) 208498
40.0%
2025-02-10T13:50:56.418767image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3627415
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3627415
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3627415
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%
Distinct8925
Distinct (%)1.5%
Missing440
Missing (%)0.1%
Memory size4.6 MiB
2025-02-10T13:50:56.575092image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length146
Median length124
Mean length39.09340095
Min length4

Characters and Unicode

Total characters23495564
Distinct characters91
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

Unique3023 ?
Unique (%)0.5%

Sample

1st rowNorth America, Panama, Bocas Del Toro
2nd rowNorth America, United States, Utah
3rd rowSouth America, Venezuela, Bolivar
4th rowNorth America, Mexico, Oaxaca
5th rowNorth America, North Atlantic Ocean, United States, North Carolina, Carteret
ValueCountFrequency (%)
america 390243
 
12.4%
north 378352
 
12.1%
united 229925
 
7.3%
states 225212
 
7.2%
africa 111667
 
3.6%
south 90792
 
2.9%
county 80759
 
2.6%
asia 66157
 
2.1%
ocean 58408
 
1.9%
mexico 50692
 
1.6%
Other values (5566) 1452640
46.3%
2025-02-10T13:50:56.809258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23495564
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23495564
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23495564
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%
Distinct100
Distinct (%)< 0.1%
Missing490
Missing (%)0.1%
Memory size4.6 MiB
2025-02-10T13:50:56.845793image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length13
Mean length12.45328399
Min length4

Characters and Unicode

Total characters7483938
Distinct characters32
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

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowNorth America
2nd rowNorth America
3rd rowSouth America
4th rowNorth America
5th rowNorth America, North Atlantic Ocean
ValueCountFrequency (%)
america 390237
33.6%
north 367501
31.6%
africa 99818
 
8.6%
south 74300
 
6.4%
asia 66157
 
5.7%
ocean 58129
 
5.0%
atlantic 30063
 
2.6%
pacific 21536
 
1.9%
europe 14885
 
1.3%
unknown 13134
 
1.1%
Other values (9) 26436
 
2.3%
2025-02-10T13:50:56.955589image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 882026
11.8%
a 694459
9.3%
i 652876
8.7%
c 637049
8.5%
A 593130
 
7.9%
561235
 
7.5%
t 524859
 
7.0%
o 485683
 
6.5%
e 466196
 
6.2%
h 444531
 
5.9%
Other values (22) 1541894
20.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7483938
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 882026
11.8%
a 694459
9.3%
i 652876
8.7%
c 637049
8.5%
A 593130
 
7.9%
561235
 
7.5%
t 524859
 
7.0%
o 485683
 
6.5%
e 466196
 
6.2%
h 444531
 
5.9%
Other values (22) 1541894
20.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7483938
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 882026
11.8%
a 694459
9.3%
i 652876
8.7%
c 637049
8.5%
A 593130
 
7.9%
561235
 
7.5%
t 524859
 
7.0%
o 485683
 
6.5%
e 466196
 
6.2%
h 444531
 
5.9%
Other values (22) 1541894
20.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7483938
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 882026
11.8%
a 694459
9.3%
i 652876
8.7%
c 637049
8.5%
A 593130
 
7.9%
561235
 
7.5%
t 524859
 
7.0%
o 485683
 
6.5%
e 466196
 
6.2%
h 444531
 
5.9%
Other values (22) 1541894
20.6%

waterBody
Text

Missing 

Distinct1298
Distinct (%)2.1%
Missing539858
Missing (%)89.8%
Memory size4.6 MiB
2025-02-10T13:50:56.992351image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length79
Median length75
Mean length24.02534379
Min length6

Characters and Unicode

Total characters1479793
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

Unique776 ?
Unique (%)1.3%

Sample

1st rowNorth Atlantic Ocean
2nd rowNorth Pacific Ocean, Bering Sea
3rd rowNorth Pacific Ocean
4th rowNorth Atlantic Ocean, Gulf Of Mexico
5th rowNorth Pacific Ocean
ValueCountFrequency (%)
ocean 58130
25.3%
north 49957
21.8%
atlantic 30063
13.1%
pacific 21536
 
9.4%
sea 8710
 
3.8%
of 8285
 
3.6%
gulf 7277
 
3.2%
mexico 6087
 
2.7%
south 3736
 
1.6%
indian 3443
 
1.5%
Other values (1047) 32100
14.0%
2025-02-10T13:50:57.108742image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1479793
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1479793
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1479793
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

islandGroup
Text

Missing 

Distinct68
Distinct (%)1.4%
Missing596682
Missing (%)99.2%
Memory size4.6 MiB
2025-02-10T13:50:57.140972image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length24
Mean length13.28538478
Min length8

Characters and Unicode

Total characters63358
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

Unique18 ?
Unique (%)0.4%

Sample

1st rowPribilof Islands
2nd rowPribilof Islands
3rd rowRyukyu Islands
4th rowPribilof Islands
5th rowBatan Islands
ValueCountFrequency (%)
islands 3374
40.8%
pribilof 1808
21.9%
moluccas 1194
 
14.4%
ryukyu 497
 
6.0%
babuyan 176
 
2.1%
channel 159
 
1.9%
batan 120
 
1.5%
nicobar 108
 
1.3%
bismarck 94
 
1.1%
yap 83
 
1.0%
Other values (66) 653
 
7.9%
2025-02-10T13:50:57.228608image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 63358
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 63358
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 63358
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

island
Text

Missing 

Distinct345
Distinct (%)0.9%
Missing564842
Missing (%)93.9%
Memory size4.6 MiB
2025-02-10T13:50:57.381239image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length21
Mean length8.146903767
Min length1

Characters and Unicode

Total characters298250
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)0.3%

Sample

1st rowSt. Paul Island
2nd rowSt. Paul Island
3rd rowTrinidad
4th rowBorneo
5th rowCulion Island
ValueCountFrequency (%)
island 7184
14.8%
borneo 5932
 
12.2%
sumatra 3675
 
7.5%
luzon 3124
 
6.4%
java 3005
 
6.2%
celebes 2678
 
5.5%
trinidad 2605
 
5.4%
st 1818
 
3.7%
paul 1799
 
3.7%
honshu 1290
 
2.6%
Other values (366) 15576
32.0%
2025-02-10T13:50:57.595253image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 298250
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 298250
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 298250
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%

country
Text

Missing 

Distinct322
Distinct (%)0.1%
Missing6532
Missing (%)1.1%
Memory size4.6 MiB
2025-02-10T13:50:57.752412image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44
Median length33
Mean length10.00060512
Min length1

Characters and Unicode

Total characters5949550
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)< 0.1%

Sample

1st rowPanama
2nd rowUnited States
3rd rowVenezuela
4th rowMexico
5th rowUnited States
ValueCountFrequency (%)
united 229925
25.8%
states 225212
25.3%
mexico 34730
 
3.9%
panama 25482
 
2.9%
venezuela 24981
 
2.8%
canada 19301
 
2.2%
colombia 16624
 
1.9%
indonesia 14922
 
1.7%
south 12721
 
1.4%
brazil 12246
 
1.4%
Other values (303) 274156
30.8%
2025-02-10T13:50:57.972104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 752064
12.6%
a 718314
12.1%
e 679639
11.4%
n 502391
 
8.4%
i 486974
 
8.2%
d 307154
 
5.2%
295381
 
5.0%
s 291189
 
4.9%
S 249895
 
4.2%
U 243908
 
4.1%
Other values (52) 1422641
23.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5949550
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 752064
12.6%
a 718314
12.1%
e 679639
11.4%
n 502391
 
8.4%
i 486974
 
8.2%
d 307154
 
5.2%
295381
 
5.0%
s 291189
 
4.9%
S 249895
 
4.2%
U 243908
 
4.1%
Other values (52) 1422641
23.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5949550
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 752064
12.6%
a 718314
12.1%
e 679639
11.4%
n 502391
 
8.4%
i 486974
 
8.2%
d 307154
 
5.2%
295381
 
5.0%
s 291189
 
4.9%
S 249895
 
4.2%
U 243908
 
4.1%
Other values (52) 1422641
23.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5949550
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 752064
12.6%
a 718314
12.1%
e 679639
11.4%
n 502391
 
8.4%
i 486974
 
8.2%
d 307154
 
5.2%
295381
 
5.0%
s 291189
 
4.9%
S 249895
 
4.2%
U 243908
 
4.1%
Other values (52) 1422641
23.9%

stateProvince
Text

Missing 

Distinct1750
Distinct (%)0.3%
Missing93954
Missing (%)15.6%
Memory size4.6 MiB
2025-02-10T13:50:58.128934image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length27
Mean length9.156487625
Min length1

Characters and Unicode

Total characters4646890
Distinct characters75
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

Unique314 ?
Unique (%)0.1%

Sample

1st rowBocas Del Toro
2nd rowUtah
3rd rowBolivar
4th rowOaxaca
5th rowNorth Carolina
ValueCountFrequency (%)
california 37958
 
5.7%
new 18698
 
2.8%
alaska 18000
 
2.7%
oregon 15112
 
2.3%
province 15077
 
2.2%
arizona 13072
 
1.9%
virginia 12189
 
1.8%
washington 12057
 
1.8%
texas 11524
 
1.7%
mexico 9875
 
1.5%
Other values (1720) 507096
75.6%
2025-02-10T13:50:58.355088image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4646890
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4646890
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4646890
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

county
Text

Missing 

Distinct3194
Distinct (%)2.1%
Missing447402
Missing (%)74.4%
Memory size4.6 MiB
2025-02-10T13:50:58.515550image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length47
Median length27
Mean length13.46725393
Min length1

Characters and Unicode

Total characters2074617
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

Unique663 ?
Unique (%)0.4%

Sample

1st rowCarteret
2nd rowCusco
3rd rowMonterey County
4th rowGalveston
5th rowTamana Ward
ValueCountFrequency (%)
county 80697
27.5%
district 13828
 
4.7%
islands 3705
 
1.3%
division 3460
 
1.2%
san 3315
 
1.1%
province 2619
 
0.9%
schoolcraft 2179
 
0.7%
mackenzie 1966
 
0.7%
lane 1935
 
0.7%
municipality 1862
 
0.6%
Other values (2969) 178313
60.7%
2025-02-10T13:50:58.737347image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2074617
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2074617
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2074617
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

locality
Text

Missing 

Distinct86656
Distinct (%)15.3%
Missing35404
Missing (%)5.9%
Memory size4.6 MiB
2025-02-10T13:50:58.909651image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length294
Median length159
Mean length21.69044267
Min length1

Characters and Unicode

Total characters12277810
Distinct characters126
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

Unique52764 ?
Unique (%)9.3%

Sample

1st rowTierra Oscura, 3.5 Km S. Tiger Key
2nd rowUinta Forest, Currant Creek
3rd rowkm. 125, 85 Km SSE El Dorado
4th rowTotontepec
5th rowAtlantic Beach, Atlantic Beach, 1/2 Mi E Of Triple S Pier.
ValueCountFrequency (%)
km 82857
 
3.9%
mi 82389
 
3.8%
of 34259
 
1.6%
n 30440
 
1.4%
river 28140
 
1.3%
s 27057
 
1.3%
e 26413
 
1.2%
w 26172
 
1.2%
island 23296
 
1.1%
san 23251
 
1.1%
Other values (42744) 1760837
82.1%
2025-02-10T13:50:59.155685image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1579064
 
12.9%
a 1198873
 
9.8%
e 766610
 
6.2%
i 659790
 
5.4%
n 655818
 
5.3%
o 653029
 
5.3%
r 550115
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940165
40.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12277810
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1579064
 
12.9%
a 1198873
 
9.8%
e 766610
 
6.2%
i 659790
 
5.4%
n 655818
 
5.3%
o 653029
 
5.3%
r 550115
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940165
40.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12277810
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1579064
 
12.9%
a 1198873
 
9.8%
e 766610
 
6.2%
i 659790
 
5.4%
n 655818
 
5.3%
o 653029
 
5.3%
r 550115
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940165
40.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12277810
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1579064
 
12.9%
a 1198873
 
9.8%
e 766610
 
6.2%
i 659790
 
5.4%
n 655818
 
5.3%
o 653029
 
5.3%
r 550115
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940165
40.2%
Distinct1508
Distinct (%)1.4%
Missing496901
Missing (%)82.6%
Memory size4.6 MiB
2025-02-10T13:50:59.311450image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.297771401
Min length3

Characters and Unicode

Total characters553882
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

Unique432 ?
Unique (%)0.4%

Sample

1st row1032.0
2nd row1006.0
3rd row545.0
4th row2134.0
5th row130.0
ValueCountFrequency (%)
155.0 2555
 
2.4%
150.0 2079
 
2.0%
975.0 1931
 
1.8%
1829.0 1925
 
1.8%
1524.0 1732
 
1.7%
1219.0 1705
 
1.6%
2438.0 1490
 
1.4%
2134.0 1369
 
1.3%
914.0 1339
 
1.3%
610.0 1184
 
1.1%
Other values (1495) 87241
83.4%
2025-02-10T13:50:59.527468image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 160391
29.0%
. 104550
18.9%
1 64341
11.6%
2 42599
 
7.7%
5 40675
 
7.3%
3 28323
 
5.1%
4 25625
 
4.6%
7 24670
 
4.5%
9 21989
 
4.0%
6 20905
 
3.8%
Other values (2) 19814
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 553882
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 160391
29.0%
. 104550
18.9%
1 64341
11.6%
2 42599
 
7.7%
5 40675
 
7.3%
3 28323
 
5.1%
4 25625
 
4.6%
7 24670
 
4.5%
9 21989
 
4.0%
6 20905
 
3.8%
Other values (2) 19814
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 553882
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 160391
29.0%
. 104550
18.9%
1 64341
11.6%
2 42599
 
7.7%
5 40675
 
7.3%
3 28323
 
5.1%
4 25625
 
4.6%
7 24670
 
4.5%
9 21989
 
4.0%
6 20905
 
3.8%
Other values (2) 19814
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 553882
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 160391
29.0%
. 104550
18.9%
1 64341
11.6%
2 42599
 
7.7%
5 40675
 
7.3%
3 28323
 
5.1%
4 25625
 
4.6%
7 24670
 
4.5%
9 21989
 
4.0%
6 20905
 
3.8%
Other values (2) 19814
 
3.6%
Distinct115
Distinct (%)3.0%
Missing597572
Missing (%)99.4%
Memory size4.6 MiB
2025-02-10T13:50:59.610050image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.129156999
Min length3

Characters and Unicode

Total characters19896
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

Unique27 ?
Unique (%)0.7%

Sample

1st row1951.0
2nd row2835.0
3rd row61.0
4th row2200.0
5th row1500.0
ValueCountFrequency (%)
76.0 652
16.8%
1500.0 427
 
11.0%
152.0 278
 
7.2%
914.0 240
 
6.2%
2200.0 237
 
6.1%
30.0 175
 
4.5%
2010.0 156
 
4.0%
488.0 143
 
3.7%
400.0 138
 
3.6%
305.0 120
 
3.1%
Other values (105) 1313
33.8%
2025-02-10T13:50:59.746851image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6753
33.9%
. 3879
19.5%
1 1956
 
9.8%
2 1621
 
8.1%
5 1289
 
6.5%
6 978
 
4.9%
7 921
 
4.6%
4 876
 
4.4%
3 675
 
3.4%
8 516
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19896
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 6753
33.9%
. 3879
19.5%
1 1956
 
9.8%
2 1621
 
8.1%
5 1289
 
6.5%
6 978
 
4.9%
7 921
 
4.6%
4 876
 
4.4%
3 675
 
3.4%
8 516
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19896
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 6753
33.9%
. 3879
19.5%
1 1956
 
9.8%
2 1621
 
8.1%
5 1289
 
6.5%
6 978
 
4.9%
7 921
 
4.6%
4 876
 
4.4%
3 675
 
3.4%
8 516
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19896
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 6753
33.9%
. 3879
19.5%
1 1956
 
9.8%
2 1621
 
8.1%
5 1289
 
6.5%
6 978
 
4.9%
7 921
 
4.6%
4 876
 
4.4%
3 675
 
3.4%
8 516
 
2.6%

verbatimElevation
Text

Missing 

Distinct29
Distinct (%)1.8%
Missing599861
Missing (%)99.7%
Memory size4.6 MiB
2025-02-10T13:50:59.784451image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length8
Mean length8.518867925
Min length2

Characters and Unicode

Total characters13545
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.6%

Sample

1st rowsea level
2nd rowsealevel
3rd rowsealevel
4th rowsealevel
5th rowsee Osgood 1909:214
ValueCountFrequency (%)
sealevel 1096
46.9%
sea 280
 
12.0%
level 277
 
11.9%
ft 143
 
6.1%
104
 
4.5%
100 81
 
3.5%
m 59
 
2.5%
near 32
 
1.4%
below 30
 
1.3%
3 28
 
1.2%
Other values (33) 206
 
8.8%
2025-02-10T13:50:59.877759image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13545
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13545
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13545
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

minimumDepthInMeters
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing601448
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:50:59.908538image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.666666667
Min length5

Characters and Unicode

Total characters17
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row853.0
2nd row1600.0
3rd row1600.0
ValueCountFrequency (%)
1600.0 2
66.7%
853.0 1
33.3%
2025-02-10T13:50:59.991851image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
41.2%
. 3
17.6%
1 2
 
11.8%
6 2
 
11.8%
8 1
 
5.9%
5 1
 
5.9%
3 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 7
41.2%
. 3
17.6%
1 2
 
11.8%
6 2
 
11.8%
8 1
 
5.9%
5 1
 
5.9%
3 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 7
41.2%
. 3
17.6%
1 2
 
11.8%
6 2
 
11.8%
8 1
 
5.9%
5 1
 
5.9%
3 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 7
41.2%
. 3
17.6%
1 2
 
11.8%
6 2
 
11.8%
8 1
 
5.9%
5 1
 
5.9%
3 1
 
5.9%

decimalLatitude
Text

Missing 

Distinct10264
Distinct (%)6.7%
Missing448433
Missing (%)74.6%
Memory size4.6 MiB
2025-02-10T13:51:00.144122image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.04639977
Min length3

Characters and Unicode

Total characters772190
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

Unique4985 ?
Unique (%)3.3%

Sample

1st row5.98
2nd row34.68
3rd row31.5011
4th row29.37
5th row34.4863
ValueCountFrequency (%)
5.3 1716
 
1.1%
2.78 1090
 
0.7%
5.67 1073
 
0.7%
0.88 979
 
0.6%
3.65 946
 
0.6%
8.83 814
 
0.5%
10.53 811
 
0.5%
3.17 798
 
0.5%
8.17 759
 
0.5%
7.32 742
 
0.5%
Other values (9276) 143290
93.6%
2025-02-10T13:51:00.493946image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 153018
19.8%
3 85567
11.1%
2 76884
10.0%
1 68690
8.9%
5 67202
8.7%
8 61499
8.0%
7 57931
 
7.5%
6 42374
 
5.5%
0 42282
 
5.5%
9 41004
 
5.3%
Other values (2) 75739
9.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 772190
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 153018
19.8%
3 85567
11.1%
2 76884
10.0%
1 68690
8.9%
5 67202
8.7%
8 61499
8.0%
7 57931
 
7.5%
6 42374
 
5.5%
0 42282
 
5.5%
9 41004
 
5.3%
Other values (2) 75739
9.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 772190
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 153018
19.8%
3 85567
11.1%
2 76884
10.0%
1 68690
8.9%
5 67202
8.7%
8 61499
8.0%
7 57931
 
7.5%
6 42374
 
5.5%
0 42282
 
5.5%
9 41004
 
5.3%
Other values (2) 75739
9.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 772190
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 153018
19.8%
3 85567
11.1%
2 76884
10.0%
1 68690
8.9%
5 67202
8.7%
8 61499
8.0%
7 57931
 
7.5%
6 42374
 
5.5%
0 42282
 
5.5%
9 41004
 
5.3%
Other values (2) 75739
9.8%

decimalLongitude
Text

Missing 

Distinct11880
Distinct (%)7.8%
Missing448433
Missing (%)74.6%
Memory size4.6 MiB
2025-02-10T13:51:00.656418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.651550798
Min length3

Characters and Unicode

Total characters864789
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

Unique5910 ?
Unique (%)3.9%

Sample

1st row-61.43
2nd row-76.7
3rd row65.8453
4th row-94.82
5th row74.6026
ValueCountFrequency (%)
66.22 1723
 
1.1%
16.42 1090
 
0.7%
127.68 955
 
0.6%
0.2 930
 
0.6%
70.5 790
 
0.5%
71.95 739
 
0.5%
79.62 722
 
0.5%
0.22 681
 
0.4%
0.97 651
 
0.4%
66.18 629
 
0.4%
Other values (11070) 144108
94.2%
2025-02-10T13:51:00.879588image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 153018
17.7%
- 87916
10.2%
2 86605
10.0%
1 81267
9.4%
7 80986
9.4%
3 68421
7.9%
6 62202
7.2%
8 58615
 
6.8%
5 58531
 
6.8%
0 50551
 
5.8%
Other values (2) 76677
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 864789
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 153018
17.7%
- 87916
10.2%
2 86605
10.0%
1 81267
9.4%
7 80986
9.4%
3 68421
7.9%
6 62202
7.2%
8 58615
 
6.8%
5 58531
 
6.8%
0 50551
 
5.8%
Other values (2) 76677
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 864789
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 153018
17.7%
- 87916
10.2%
2 86605
10.0%
1 81267
9.4%
7 80986
9.4%
3 68421
7.9%
6 62202
7.2%
8 58615
 
6.8%
5 58531
 
6.8%
0 50551
 
5.8%
Other values (2) 76677
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 864789
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 153018
17.7%
- 87916
10.2%
2 86605
10.0%
1 81267
9.4%
7 80986
9.4%
3 68421
7.9%
6 62202
7.2%
8 58615
 
6.8%
5 58531
 
6.8%
0 50551
 
5.8%
Other values (2) 76677
8.9%

geodeticDatum
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing594543
Missing (%)98.9%
Memory size4.6 MiB
2025-02-10T13:51:00.916829image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length17.99681529
Min length7

Characters and Unicode

Total characters124322
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS 84 (EPSG:4326)
2nd rowWGS 84 (EPSG:4326)
3rd rowWGS 84 (EPSG:4326)
4th rowWGS 84 (EPSG:4326)
5th rowWGS 84 (EPSG:4326)
ValueCountFrequency (%)
wgs 6906
33.3%
84 6906
33.3%
epsg:4326 6906
33.3%
unknown 2
 
< 0.1%
2025-02-10T13:51:01.004848image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 13812
11.1%
S 13812
11.1%
13812
11.1%
4 13812
11.1%
W 6906
 
5.6%
) 6906
 
5.6%
6 6906
 
5.6%
2 6906
 
5.6%
3 6906
 
5.6%
: 6906
 
5.6%
Other values (9) 27638
22.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 124322
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 13812
11.1%
S 13812
11.1%
13812
11.1%
4 13812
11.1%
W 6906
 
5.6%
) 6906
 
5.6%
6 6906
 
5.6%
2 6906
 
5.6%
3 6906
 
5.6%
: 6906
 
5.6%
Other values (9) 27638
22.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 124322
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 13812
11.1%
S 13812
11.1%
13812
11.1%
4 13812
11.1%
W 6906
 
5.6%
) 6906
 
5.6%
6 6906
 
5.6%
2 6906
 
5.6%
3 6906
 
5.6%
: 6906
 
5.6%
Other values (9) 27638
22.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 124322
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 13812
11.1%
S 13812
11.1%
13812
11.1%
4 13812
11.1%
W 6906
 
5.6%
) 6906
 
5.6%
6 6906
 
5.6%
2 6906
 
5.6%
3 6906
 
5.6%
: 6906
 
5.6%
Other values (9) 27638
22.2%

verbatimLatitude
Text

Missing 

Distinct11921
Distinct (%)8.8%
Missing466631
Missing (%)77.6%
Memory size4.6 MiB
2025-02-10T13:51:01.074493image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length10
Mean length9.74341344
Min length3

Characters and Unicode

Total characters1313607
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

Unique6353 ?
Unique (%)4.7%

Sample

1st row05 59 -- N
2nd row34 41 4- N
3rd row29 22 1- N
4th row02 37 -- N
5th row28 39 -- S
ValueCountFrequency (%)
106698
21.4%
n 93430
18.7%
s 28456
 
5.7%
10 13100
 
2.6%
09 10526
 
2.1%
08 8990
 
1.8%
05 8987
 
1.8%
07 8164
 
1.6%
30 8001
 
1.6%
06 7215
 
1.4%
Other values (2490) 205546
41.2%
2025-02-10T13:51:01.212156image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
364293
27.7%
- 242090
18.4%
0 121688
 
9.3%
N 102689
 
7.8%
1 82952
 
6.3%
2 72522
 
5.5%
3 69271
 
5.3%
5 58613
 
4.5%
4 50109
 
3.8%
9 32877
 
2.5%
Other values (21) 116503
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1313607
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
364293
27.7%
- 242090
18.4%
0 121688
 
9.3%
N 102689
 
7.8%
1 82952
 
6.3%
2 72522
 
5.5%
3 69271
 
5.3%
5 58613
 
4.5%
4 50109
 
3.8%
9 32877
 
2.5%
Other values (21) 116503
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1313607
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
364293
27.7%
- 242090
18.4%
0 121688
 
9.3%
N 102689
 
7.8%
1 82952
 
6.3%
2 72522
 
5.5%
3 69271
 
5.3%
5 58613
 
4.5%
4 50109
 
3.8%
9 32877
 
2.5%
Other values (21) 116503
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1313607
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
364293
27.7%
- 242090
18.4%
0 121688
 
9.3%
N 102689
 
7.8%
1 82952
 
6.3%
2 72522
 
5.5%
3 69271
 
5.3%
5 58613
 
4.5%
4 50109
 
3.8%
9 32877
 
2.5%
Other values (21) 116503
 
8.9%

verbatimLongitude
Text

Missing 

Distinct13154
Distinct (%)9.8%
Missing466723
Missing (%)77.6%
Memory size4.6 MiB
2025-02-10T13:51:01.244795image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length11
Mean length10.73756012
Min length3

Characters and Unicode

Total characters1446650
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7533 ?
Unique (%)5.6%

Sample

1st row061 26 -- W
2nd row076 42 1- W
3rd row094 49 4- W
4th row066 19 -- W
5th row020 15 -- E
ValueCountFrequency (%)
106940
21.4%
w 73770
 
14.8%
e 47858
 
9.6%
000 6910
 
1.4%
00 4768
 
1.0%
46 4542
 
0.9%
002 4510
 
0.9%
13 4306
 
0.9%
001 3732
 
0.7%
066 3560
 
0.7%
Other values (2805) 238004
47.7%
2025-02-10T13:51:01.347707image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
364172
25.2%
- 243702
16.8%
0 216851
15.0%
1 88638
 
6.1%
W 80745
 
5.6%
2 78239
 
5.4%
3 58623
 
4.1%
5 53520
 
3.7%
E 53220
 
3.7%
4 52072
 
3.6%
Other values (18) 156868
10.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1446650
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
364172
25.2%
- 243702
16.8%
0 216851
15.0%
1 88638
 
6.1%
W 80745
 
5.6%
2 78239
 
5.4%
3 58623
 
4.1%
5 53520
 
3.7%
E 53220
 
3.7%
4 52072
 
3.6%
Other values (18) 156868
10.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1446650
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
364172
25.2%
- 243702
16.8%
0 216851
15.0%
1 88638
 
6.1%
W 80745
 
5.6%
2 78239
 
5.4%
3 58623
 
4.1%
5 53520
 
3.7%
E 53220
 
3.7%
4 52072
 
3.6%
Other values (18) 156868
10.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1446650
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
364172
25.2%
- 243702
16.8%
0 216851
15.0%
1 88638
 
6.1%
W 80745
 
5.6%
2 78239
 
5.4%
3 58623
 
4.1%
5 53520
 
3.7%
E 53220
 
3.7%
4 52072
 
3.6%
Other values (18) 156868
10.8%
Distinct4
Distinct (%)< 0.1%
Missing468202
Missing (%)77.8%
Memory size4.6 MiB
2025-02-10T13:51:01.378258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.96475771
Min length3

Characters and Unicode

Total characters3060031
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 133004
33.3%
minutes 133003
33.3%
seconds 133003
33.3%
utm 192
 
< 0.1%
unknown 53
 
< 0.1%
decimal 1
 
< 0.1%
2025-02-10T13:51:01.476629image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
D 133004
 
4.3%
c 133004
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
Other values (12) 665563
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3060031
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
D 133004
 
4.3%
c 133004
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
Other values (12) 665563
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3060031
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
D 133004
 
4.3%
c 133004
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
Other values (12) 665563
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3060031
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
D 133004
 
4.3%
c 133004
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
Other values (12) 665563
21.8%

georeferenceProtocol
Text

Missing 

Distinct8
Distinct (%)0.1%
Missing592196
Missing (%)98.5%
Memory size4.6 MiB
2025-02-10T13:51:01.508978image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length26
Median length12
Mean length10.66731496
Min length3

Characters and Unicode

Total characters98726
Distinct characters32
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 rowGoogle Earth
2nd rowGoogle Earth
3rd rowGPS
4th rowGoogle Earth
5th rowGoogle Earth
ValueCountFrequency (%)
google 7074
41.5%
earth 7074
41.5%
gps 1418
 
8.3%
usgs 530
 
3.1%
topoview 530
 
3.1%
gazetteer 137
 
0.8%
atlas 42
 
0.2%
of 42
 
0.2%
canada 42
 
0.2%
42
 
0.2%
Other values (4) 96
 
0.6%
2025-02-10T13:51:01.598230image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 98726
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 98726
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 98726
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

georeferenceRemarks
Text

Missing 

Distinct8
Distinct (%)11.8%
Missing601383
Missing (%)> 99.9%
Memory size4.6 MiB
2025-02-10T13:51:01.635977image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length35
Mean length31.20588235
Min length5

Characters and Unicode

Total characters2122
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

Unique4 ?
Unique (%)5.9%

Sample

1st rowGarmin Etrex Vista HCX, Datum WGS84
2nd rowGarmin Etrex Vista HCX, Datum WGS84
3rd rowGarmin Etrex Vista HCX, Datum WGS84
4th rowGarmin Etrex Vista HCX, Datum WGS84
5th rowGarmin Etrex Vista HCX, Datum WGS84
ValueCountFrequency (%)
garmin 54
15.1%
etrex 54
15.1%
vista 54
15.1%
hcx 54
15.1%
datum 54
15.1%
wgs84 54
15.1%
camp 7
 
2.0%
coordinates 7
 
2.0%
for 6
 
1.7%
longitude 2
 
0.6%
Other values (7) 12
 
3.4%
2025-02-10T13:51:01.735315image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2122
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2122
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2122
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%
Distinct4
Distinct (%)0.3%
Missing599947
Missing (%)99.7%
Memory size4.6 MiB
2025-02-10T13:51:01.765942image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.412234043
Min length3

Characters and Unicode

Total characters12652
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowuncertain
2nd rowuncertain
3rd rowuncertain
4th rowuncertain
5th rowcf.
ValueCountFrequency (%)
uncertain 1355
90.0%
cf 147
 
9.8%
sp 2
 
0.1%
near 2
 
0.1%
2025-02-10T13:51:01.857154image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
e 1357
10.7%
r 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12652
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
e 1357
10.7%
r 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12652
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
e 1357
10.7%
r 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12652
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
e 1357
10.7%
r 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

typeStatus
Text

Missing 

Distinct10
Distinct (%)0.3%
Missing597685
Missing (%)99.4%
Memory size4.6 MiB
2025-02-10T13:51:01.889064image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length4
Mean length4.250929368
Min length4

Characters and Unicode

Total characters16009
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

Unique3 ?
Unique (%)0.1%

Sample

1st rowLectotype
2nd rowType
3rd rowType
4th rowType
5th rowType
ValueCountFrequency (%)
type 3590
94.5%
syntype 83
 
2.2%
lectotype 68
 
1.8%
renamed 28
 
0.7%
neotype 12
 
0.3%
holotype 12
 
0.3%
nomen 2
 
0.1%
nudem 2
 
0.1%
2025-02-10T13:51:01.986415image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3905
24.4%
y 3848
24.0%
p 3765
23.5%
T 3590
22.4%
t 243
 
1.5%
n 113
 
0.7%
o 106
 
0.7%
S 83
 
0.5%
L 68
 
0.4%
c 68
 
0.4%
Other values (10) 220
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16009
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3905
24.4%
y 3848
24.0%
p 3765
23.5%
T 3590
22.4%
t 243
 
1.5%
n 113
 
0.7%
o 106
 
0.7%
S 83
 
0.5%
L 68
 
0.4%
c 68
 
0.4%
Other values (10) 220
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16009
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3905
24.4%
y 3848
24.0%
p 3765
23.5%
T 3590
22.4%
t 243
 
1.5%
n 113
 
0.7%
o 106
 
0.7%
S 83
 
0.5%
L 68
 
0.4%
c 68
 
0.4%
Other values (10) 220
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16009
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3905
24.4%
y 3848
24.0%
p 3765
23.5%
T 3590
22.4%
t 243
 
1.5%
n 113
 
0.7%
o 106
 
0.7%
S 83
 
0.5%
L 68
 
0.4%
c 68
 
0.4%
Other values (10) 220
 
1.4%

identifiedBy
Text

Missing 

Distinct95
Distinct (%)1.2%
Missing593267
Missing (%)98.6%
Memory size4.6 MiB
2025-02-10T13:51:02.046317image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length132
Median length124
Mean length94.36840176
Min length10

Characters and Unicode

Total characters772311
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

Unique21 ?
Unique (%)0.3%

Sample

1st rowO'Neill, Jennifer K., Fort Hayes State University
2nd rowGardner, Alfred L., Curator (USGS), United States Geological Survey (UNITED STATES)
3rd rowWoodman, Neal, (USGS), United States Geological Survey (UNITED STATES)
4th rowLunde, Darrin P., Collections Manager (MAM), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
5th rowReeder, DeeAnn M., Bucknell University (UNITED STATES)
ValueCountFrequency (%)
states 8033
 
7.9%
united 8033
 
7.9%
of 5420
 
5.3%
museum 5255
 
5.2%
natural 5077
 
5.0%
history 5077
 
5.0%
national 5064
 
5.0%
smithsonian 5007
 
4.9%
institution 5007
 
4.9%
4859
 
4.8%
Other values (272) 44753
44.1%
2025-02-10T13:51:02.181127image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 772311
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 772311
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 772311
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%
Distinct7805
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-02-10T13:51:02.339887image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length43
Mean length22.61255364
Min length5

Characters and Unicode

Total characters13600343
Distinct characters63
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

Unique898 ?
Unique (%)0.1%

Sample

1st rowPotos flavus
2nd rowMicrotus longicaudus longicaudus
3rd rowCarollia brevicauda
4th rowPeromyscus mexicanus totontepecus
5th rowTursiops truncatus
ValueCountFrequency (%)
peromyscus 38753
 
2.6%
sp 28343
 
1.9%
rattus 21929
 
1.5%
microtus 19877
 
1.3%
maniculatus 15880
 
1.1%
sorex 15831
 
1.1%
artibeus 12470
 
0.8%
carollia 12281
 
0.8%
tursiops 11895
 
0.8%
truncatus 11875
 
0.8%
Other values (5505) 1302266
87.3%
2025-02-10T13:51:02.578319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13600343
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13600343
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13600343
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%
Distinct253
Distinct (%)< 0.1%
Missing7
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:51:02.743122image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length121
Median length113
Mean length90.64064651
Min length11

Characters and Unicode

Total characters54515273
Distinct characters48
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

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Carnivora, Caniformia, Procyonidae
2nd rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Rodentia, Myomorpha, Cricetidae, Arvicolinae
3rd rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Chiroptera, Phyllostomidae, Carolliinae
4th rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Rodentia, Myomorpha, Cricetidae, Neotominae
5th rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Cetacea, Odontoceti, Delphinidae
ValueCountFrequency (%)
animalia 601442
11.9%
vertebrata 601442
11.9%
chordata 601442
11.9%
mammalia 601441
11.9%
eutheria 593341
11.7%
rodentia 297636
 
5.9%
myomorpha 209417
 
4.1%
chiroptera 129086
 
2.5%
cricetidae 107243
 
2.1%
muridae 93911
 
1.9%
Other values (328) 1234181
24.3%
2025-02-10T13:51:02.981383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 54515273
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 54515273
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 54515273
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

kingdom
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing9
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:51:03.017383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4811536
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 601442
100.0%
2025-02-10T13:51:03.100292image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1202884
25.0%
a 1202884
25.0%
A 601442
12.5%
n 601442
12.5%
m 601442
12.5%
l 601442
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4811536
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1202884
25.0%
a 1202884
25.0%
A 601442
12.5%
n 601442
12.5%
m 601442
12.5%
l 601442
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4811536
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1202884
25.0%
a 1202884
25.0%
A 601442
12.5%
n 601442
12.5%
m 601442
12.5%
l 601442
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4811536
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1202884
25.0%
a 1202884
25.0%
A 601442
12.5%
n 601442
12.5%
m 601442
12.5%
l 601442
12.5%

phylum
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing9
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:51:03.128950image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4811536
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChordata
2nd rowChordata
3rd rowChordata
4th rowChordata
5th rowChordata
ValueCountFrequency (%)
chordata 601442
100.0%
2025-02-10T13:51:03.288023image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1202884
25.0%
C 601442
12.5%
h 601442
12.5%
o 601442
12.5%
r 601442
12.5%
d 601442
12.5%
t 601442
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4811536
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1202884
25.0%
C 601442
12.5%
h 601442
12.5%
o 601442
12.5%
r 601442
12.5%
d 601442
12.5%
t 601442
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4811536
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1202884
25.0%
C 601442
12.5%
h 601442
12.5%
o 601442
12.5%
r 601442
12.5%
d 601442
12.5%
t 601442
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4811536
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1202884
25.0%
C 601442
12.5%
h 601442
12.5%
o 601442
12.5%
r 601442
12.5%
d 601442
12.5%
t 601442
12.5%

class
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing10
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:51:03.317311image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4811528
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMammalia
2nd rowMammalia
3rd rowMammalia
4th rowMammalia
5th rowMammalia
ValueCountFrequency (%)
mammalia 601441
100.0%
2025-02-10T13:51:03.398360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1804323
37.5%
m 1202882
25.0%
M 601441
 
12.5%
l 601441
 
12.5%
i 601441
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4811528
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1804323
37.5%
m 1202882
25.0%
M 601441
 
12.5%
l 601441
 
12.5%
i 601441
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4811528
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1804323
37.5%
m 1202882
25.0%
M 601441
 
12.5%
l 601441
 
12.5%
i 601441
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4811528
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1804323
37.5%
m 1202882
25.0%
M 601441
 
12.5%
l 601441
 
12.5%
i 601441
 
12.5%

order
Text

Distinct29
Distinct (%)< 0.1%
Missing10
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:51:03.430840image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length8
Mean length8.868953064
Min length6

Characters and Unicode

Total characters5334152
Distinct characters32
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 rowCarnivora
2nd rowRodentia
3rd rowChiroptera
4th rowRodentia
5th rowCetacea
ValueCountFrequency (%)
rodentia 297636
49.5%
chiroptera 129086
21.5%
cetacea 47582
 
7.9%
carnivora 47293
 
7.9%
soricomorpha 30383
 
5.1%
lagomorpha 11977
 
2.0%
artiodactyla 11375
 
1.9%
primates 10781
 
1.8%
didelphimorphia 5643
 
0.9%
diprotodontia 1652
 
0.3%
Other values (19) 8033
 
1.3%
2025-02-10T13:51:03.523222image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 725642
13.6%
o 618973
11.6%
i 555649
10.4%
e 546091
10.2%
t 514232
9.6%
r 462546
8.7%
n 351517
6.6%
d 320912
6.0%
R 297636
5.6%
C 224380
 
4.2%
Other values (22) 716574
13.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5334152
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 725642
13.6%
o 618973
11.6%
i 555649
10.4%
e 546091
10.2%
t 514232
9.6%
r 462546
8.7%
n 351517
6.6%
d 320912
6.0%
R 297636
5.6%
C 224380
 
4.2%
Other values (22) 716574
13.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5334152
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 725642
13.6%
o 618973
11.6%
i 555649
10.4%
e 546091
10.2%
t 514232
9.6%
r 462546
8.7%
n 351517
6.6%
d 320912
6.0%
R 297636
5.6%
C 224380
 
4.2%
Other values (22) 716574
13.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5334152
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 725642
13.6%
o 618973
11.6%
i 555649
10.4%
e 546091
10.2%
t 514232
9.6%
r 462546
8.7%
n 351517
6.6%
d 320912
6.0%
R 297636
5.6%
C 224380
 
4.2%
Other values (22) 716574
13.4%

family
Text

Distinct153
Distinct (%)< 0.1%
Missing7
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:51:03.563922image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.23417143
Min length6

Characters and Unicode

Total characters6155281
Distinct characters42
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 rowProcyonidae
2nd rowCricetidae
3rd rowPhyllostomidae
4th rowCricetidae
5th rowDelphinidae
ValueCountFrequency (%)
cricetidae 107243
17.8%
muridae 93911
15.6%
phyllostomidae 55530
 
9.2%
sciuridae 46130
 
7.7%
soricidae 27470
 
4.6%
vespertilionidae 25753
 
4.3%
delphinidae 23642
 
3.9%
heteromyidae 19997
 
3.3%
molossidae 13560
 
2.3%
canidae 12559
 
2.1%
Other values (143) 175649
29.2%
2025-02-10T13:51:03.666153image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 949239
15.4%
i 924898
15.0%
a 664049
10.8%
d 634246
10.3%
r 409806
 
6.7%
o 348989
 
5.7%
t 274918
 
4.5%
l 232701
 
3.8%
c 221432
 
3.6%
u 159979
 
2.6%
Other values (32) 1335024
21.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6155281
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 949239
15.4%
i 924898
15.0%
a 664049
10.8%
d 634246
10.3%
r 409806
 
6.7%
o 348989
 
5.7%
t 274918
 
4.5%
l 232701
 
3.8%
c 221432
 
3.6%
u 159979
 
2.6%
Other values (32) 1335024
21.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6155281
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 949239
15.4%
i 924898
15.0%
a 664049
10.8%
d 634246
10.3%
r 409806
 
6.7%
o 348989
 
5.7%
t 274918
 
4.5%
l 232701
 
3.8%
c 221432
 
3.6%
u 159979
 
2.6%
Other values (32) 1335024
21.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6155281
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 949239
15.4%
i 924898
15.0%
a 664049
10.8%
d 634246
10.3%
r 409806
 
6.7%
o 348989
 
5.7%
t 274918
 
4.5%
l 232701
 
3.8%
c 221432
 
3.6%
u 159979
 
2.6%
Other values (32) 1335024
21.7%

genus
Text

Distinct1136
Distinct (%)0.2%
Missing16
Missing (%)< 0.1%
Memory size4.6 MiB
2025-02-10T13:51:03.825475image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.505181774
Min length2

Characters and Unicode

Total characters5115314
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

Unique72 ?
Unique (%)< 0.1%

Sample

1st rowPotos
2nd rowMicrotus
3rd rowCarollia
4th rowPeromyscus
5th rowTursiops
ValueCountFrequency (%)
peromyscus 38753
 
6.4%
microtus 19877
 
3.3%
rattus 16463
 
2.7%
sorex 15826
 
2.6%
artibeus 12470
 
2.1%
carollia 12281
 
2.0%
tursiops 11894
 
2.0%
tamias 11871
 
2.0%
mastomys 11447
 
1.9%
mus 10554
 
1.8%
Other values (1126) 439999
73.2%
2025-02-10T13:51:04.058765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 603660
 
11.8%
o 513897
 
10.0%
a 349432
 
6.8%
r 348676
 
6.8%
u 336000
 
6.6%
i 331710
 
6.5%
e 315840
 
6.2%
t 247363
 
4.8%
l 220400
 
4.3%
m 215951
 
4.2%
Other values (40) 1632385
31.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5115314
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 603660
 
11.8%
o 513897
 
10.0%
a 349432
 
6.8%
r 348676
 
6.8%
u 336000
 
6.6%
i 331710
 
6.5%
e 315840
 
6.2%
t 247363
 
4.8%
l 220400
 
4.3%
m 215951
 
4.2%
Other values (40) 1632385
31.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5115314
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 603660
 
11.8%
o 513897
 
10.0%
a 349432
 
6.8%
r 348676
 
6.8%
u 336000
 
6.6%
i 331710
 
6.5%
e 315840
 
6.2%
t 247363
 
4.8%
l 220400
 
4.3%
m 215951
 
4.2%
Other values (40) 1632385
31.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5115314
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 603660
 
11.8%
o 513897
 
10.0%
a 349432
 
6.8%
r 348676
 
6.8%
u 336000
 
6.6%
i 331710
 
6.5%
e 315840
 
6.2%
t 247363
 
4.8%
l 220400
 
4.3%
m 215951
 
4.2%
Other values (40) 1632385
31.9%

subgenus
Text

Missing 

Distinct3
Distinct (%)1.0%
Missing601149
Missing (%)99.9%
Memory size4.6 MiB
2025-02-10T13:51:04.102353image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.82781457
Min length9

Characters and Unicode

Total characters3270
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMallodelphys
2nd rowEumarmosa
3rd rowCaluromys
4th rowCaluromys
5th rowEumarmosa
ValueCountFrequency (%)
mallodelphys 184
60.9%
caluromys 95
31.5%
eumarmosa 23
 
7.6%
2025-02-10T13:51:04.190405image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 647
19.8%
a 325
9.9%
o 302
9.2%
s 302
9.2%
y 279
8.5%
M 184
 
5.6%
d 184
 
5.6%
e 184
 
5.6%
p 184
 
5.6%
h 184
 
5.6%
Other values (5) 495
15.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3270
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 647
19.8%
a 325
9.9%
o 302
9.2%
s 302
9.2%
y 279
8.5%
M 184
 
5.6%
d 184
 
5.6%
e 184
 
5.6%
p 184
 
5.6%
h 184
 
5.6%
Other values (5) 495
15.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3270
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 647
19.8%
a 325
9.9%
o 302
9.2%
s 302
9.2%
y 279
8.5%
M 184
 
5.6%
d 184
 
5.6%
e 184
 
5.6%
p 184
 
5.6%
h 184
 
5.6%
Other values (5) 495
15.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3270
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 647
19.8%
a 325
9.9%
o 302
9.2%
s 302
9.2%
y 279
8.5%
M 184
 
5.6%
d 184
 
5.6%
e 184
 
5.6%
p 184
 
5.6%
h 184
 
5.6%
Other values (5) 495
15.1%
Distinct2774
Distinct (%)0.5%
Missing678
Missing (%)0.1%
Memory size4.6 MiB
2025-02-10T13:51:04.343522image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length14
Mean length8.402236785
Min length2

Characters and Unicode

Total characters5047837
Distinct characters29
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

Unique260 ?
Unique (%)< 0.1%

Sample

1st rowflavus
2nd rowlongicaudus
3rd rowbrevicauda
4th rowmexicanus
5th rowtruncatus
ValueCountFrequency (%)
sp 28335
 
4.7%
maniculatus 15647
 
2.6%
truncatus 11873
 
2.0%
musculus 8553
 
1.4%
perspicillata 8339
 
1.4%
leucopus 7382
 
1.2%
brevicauda 7356
 
1.2%
pennsylvanicus 6840
 
1.1%
jamaicensis 5581
 
0.9%
rattus 5466
 
0.9%
Other values (2764) 495405
82.5%
2025-02-10T13:51:04.568178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 600065
11.9%
i 553121
11.0%
a 505496
10.0%
u 460127
9.1%
e 329136
 
6.5%
r 328084
 
6.5%
n 326046
 
6.5%
l 286917
 
5.7%
t 270410
 
5.4%
c 259844
 
5.1%
Other values (19) 1128591
22.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5047837
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 600065
11.9%
i 553121
11.0%
a 505496
10.0%
u 460127
9.1%
e 329136
 
6.5%
r 328084
 
6.5%
n 326046
 
6.5%
l 286917
 
5.7%
t 270410
 
5.4%
c 259844
 
5.1%
Other values (19) 1128591
22.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5047837
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 600065
11.9%
i 553121
11.0%
a 505496
10.0%
u 460127
9.1%
e 329136
 
6.5%
r 328084
 
6.5%
n 326046
 
6.5%
l 286917
 
5.7%
t 270410
 
5.4%
c 259844
 
5.1%
Other values (19) 1128591
22.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5047837
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 600065
11.9%
i 553121
11.0%
a 505496
10.0%
u 460127
9.1%
e 329136
 
6.5%
r 328084
 
6.5%
n 326046
 
6.5%
l 286917
 
5.7%
t 270410
 
5.4%
c 259844
 
5.1%
Other values (19) 1128591
22.4%

infraspecificEpithet
Text

Missing 

Distinct2646
Distinct (%)0.9%
Missing314922
Missing (%)52.4%
Memory size4.6 MiB
2025-02-10T13:51:04.730692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.827504371
Min length3

Characters and Unicode

Total characters2529336
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)0.1%

Sample

1st rowlongicaudus
2nd rowtotontepecus
3rd rowmarinensis
4th rowbairdii
5th rowmerriami
ValueCountFrequency (%)
noveboracensis 4836
 
1.7%
domesticus 4357
 
1.5%
pennsylvanicus 4127
 
1.4%
talpoides 3712
 
1.3%
cinereus 3602
 
1.3%
sonoriensis 2279
 
0.8%
gambelii 2247
 
0.8%
trowbridgii 2145
 
0.7%
merriami 2101
 
0.7%
longicaudus 2081
 
0.7%
Other values (2636) 255042
89.0%
2025-02-10T13:51:04.965252image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 311070
12.3%
i 300653
11.9%
a 225909
8.9%
e 216894
8.6%
n 194319
 
7.7%
u 182648
 
7.2%
r 170773
 
6.8%
o 145249
 
5.7%
l 125981
 
5.0%
c 119143
 
4.7%
Other values (16) 536697
21.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2529336
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 311070
12.3%
i 300653
11.9%
a 225909
8.9%
e 216894
8.6%
n 194319
 
7.7%
u 182648
 
7.2%
r 170773
 
6.8%
o 145249
 
5.7%
l 125981
 
5.0%
c 119143
 
4.7%
Other values (16) 536697
21.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2529336
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 311070
12.3%
i 300653
11.9%
a 225909
8.9%
e 216894
8.6%
n 194319
 
7.7%
u 182648
 
7.2%
r 170773
 
6.8%
o 145249
 
5.7%
l 125981
 
5.0%
c 119143
 
4.7%
Other values (16) 536697
21.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2529336
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 311070
12.3%
i 300653
11.9%
a 225909
8.9%
e 216894
8.6%
n 194319
 
7.7%
u 182648
 
7.2%
r 170773
 
6.8%
o 145249
 
5.7%
l 125981
 
5.0%
c 119143
 
4.7%
Other values (16) 536697
21.2%

taxonRank
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing314922
Missing (%)52.4%
Memory size4.6 MiB
2025-02-10T13:51:05.007434image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2865290
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsubspecies
2nd rowsubspecies
3rd rowsubspecies
4th rowsubspecies
5th rowsubspecies
ValueCountFrequency (%)
subspecies 286529
100.0%
2025-02-10T13:51:05.094674image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 859587
30.0%
e 573058
20.0%
u 286529
 
10.0%
b 286529
 
10.0%
p 286529
 
10.0%
c 286529
 
10.0%
i 286529
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2865290
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 859587
30.0%
e 573058
20.0%
u 286529
 
10.0%
b 286529
 
10.0%
p 286529
 
10.0%
c 286529
 
10.0%
i 286529
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2865290
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 859587
30.0%
e 573058
20.0%
u 286529
 
10.0%
b 286529
 
10.0%
p 286529
 
10.0%
c 286529
 
10.0%
i 286529
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2865290
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 859587
30.0%
e 573058
20.0%
u 286529
 
10.0%
b 286529
 
10.0%
p 286529
 
10.0%
c 286529
 
10.0%
i 286529
 
10.0%
Distinct176
Distinct (%)0.4%
Missing555607
Missing (%)92.4%
Memory size4.6 MiB
2025-02-10T13:51:05.139115image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length23
Mean length8.940755606
Min length4

Characters and Unicode

Total characters409880
Distinct characters55
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 (%)0.2%

Sample

1st row(Montagu)
2nd row(Montagu)
3rd row(Linnaeus)
4th row(Cuvier)
5th rowStejneger
ValueCountFrequency (%)
linnaeus 14516
29.5%
montagu 11845
24.1%
gray 4024
 
8.2%
cuvier 2015
 
4.1%
de 1265
 
2.6%
blainville 1263
 
2.6%
traill 1101
 
2.2%
true 1018
 
2.1%
lacepede 1006
 
2.0%
lilljeborg 934
 
1.9%
Other values (159) 10239
20.8%
2025-02-10T13:51:05.244109image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 46261
11.3%
( 37392
 
9.1%
) 37392
 
9.1%
a 37146
 
9.1%
e 31946
 
7.8%
u 30372
 
7.4%
i 24799
 
6.1%
s 19879
 
4.8%
L 17196
 
4.2%
o 17121
 
4.2%
Other values (45) 110376
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 409880
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 46261
11.3%
( 37392
 
9.1%
) 37392
 
9.1%
a 37146
 
9.1%
e 31946
 
7.8%
u 30372
 
7.4%
i 24799
 
6.1%
s 19879
 
4.8%
L 17196
 
4.2%
o 17121
 
4.2%
Other values (45) 110376
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 409880
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 46261
11.3%
( 37392
 
9.1%
) 37392
 
9.1%
a 37146
 
9.1%
e 31946
 
7.8%
u 30372
 
7.4%
i 24799
 
6.1%
s 19879
 
4.8%
L 17196
 
4.2%
o 17121
 
4.2%
Other values (45) 110376
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 409880
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 46261
11.3%
( 37392
 
9.1%
) 37392
 
9.1%
a 37146
 
9.1%
e 31946
 
7.8%
u 30372
 
7.4%
i 24799
 
6.1%
s 19879
 
4.8%
L 17196
 
4.2%
o 17121
 
4.2%
Other values (45) 110376
26.9%