Overview

Brought to you by YData

Dataset statistics

Number of variables60
Number of observations5019782
Missing cells166704518
Missing cells (%)55.3%
Total size in memory2.2 GiB
Average record size in memory480.0 B

Variable types

Text60

Dataset

DescriptionNaturalis Biodiversity Center (NL) - Botany 0061690-241126133413365
URLhttps://doi.org/10.15468/ib5ypt

Alerts

license has constant value "CC0 1.0" Constant
rightsHolder has constant value "Naturalis Biodiversity Center" Constant
institutionID has constant value "https://ror.org/0566bfb96" Constant
collectionCode has constant value "Botany" Constant
basisOfRecord has constant value "PreservedSpecimen" Constant
samplingEffort has constant value "0.0 m" Constant
island has constant value "51.41942" Constant
countryCode has constant value "WGS84" Constant
maximumDistanceAboveSurfaceInMeters has constant value "Asia" Constant
geodeticDatum has constant value "WGS84" Constant
coordinateUncertaintyInMeters has constant value "South-Western" Constant
verbatimCoordinates has constant value "Siam [Thailand], Kwae Noi Basin Expedition, near Neeckey, near Wangka." Constant
verbatimSRS has constant value "150.0 m" Constant
geologicalContextID has constant value "15.1" Constant
earliestEonOrLowestEonothem has constant value "98.46667" Constant
latestEonOrHighestEonothem has constant value "WGS84" Constant
identificationVerificationStatus has constant value "Fungi-Ascomycota" Constant
identificationRemarks has constant value "Lichenes-Lecanoromycetes" Constant
namePublishedIn has constant value "species" Constant
subgenus has constant value "Fimbristylis bisumbellata (Forssk.) Bubani" Constant
vernacularName has constant value "Plantae" Constant
nomenclaturalCode has constant value "ICN" Constant
nomenclaturalStatus has constant value "Poales" Constant
otherCatalogNumbers has 3742862 (74.6%) missing values Missing
eventDate has 856201 (17.1%) missing values Missing
habitat has 4109448 (81.9%) missing values Missing
samplingEffort has 5019781 (> 99.9%) missing values Missing
continent has 902365 (18.0%) missing values Missing
island has 5019781 (> 99.9%) missing values Missing
countryCode has 5019780 (> 99.9%) missing values Missing
stateProvince has 3065004 (61.1%) missing values Missing
locality has 763737 (15.2%) missing values Missing
verbatimElevation has 3265629 (65.1%) missing values Missing
maximumDistanceAboveSurfaceInMeters has 5019781 (> 99.9%) missing values Missing
decimalLatitude has 2925885 (58.3%) missing values Missing
decimalLongitude has 2925885 (58.3%) missing values Missing
coordinateUncertaintyInMeters has 5019781 (> 99.9%) missing values Missing
verbatimCoordinates has 5019781 (> 99.9%) missing values Missing
verbatimSRS has 5019781 (> 99.9%) missing values Missing
geologicalContextID has 5019781 (> 99.9%) missing values Missing
earliestEonOrLowestEonothem has 5019781 (> 99.9%) missing values Missing
latestEonOrHighestEonothem has 5019781 (> 99.9%) missing values Missing
earliestEraOrLowestErathem has 5019780 (> 99.9%) missing values Missing
bed has 5019780 (> 99.9%) missing values Missing
typeStatus has 4932431 (98.3%) missing values Missing
identifiedBy has 4152104 (82.7%) missing values Missing
dateIdentified has 4581006 (91.3%) missing values Missing
identificationReferences has 5019780 (> 99.9%) missing values Missing
identificationVerificationStatus has 5019781 (> 99.9%) missing values Missing
identificationRemarks has 5019781 (> 99.9%) missing values Missing
taxonID has 5019780 (> 99.9%) missing values Missing
acceptedNameUsageID has 5019780 (> 99.9%) missing values Missing
namePublishedInID has 5019780 (> 99.9%) missing values Missing
parentNameUsage has 5019780 (> 99.9%) missing values Missing
namePublishedIn has 5019780 (> 99.9%) missing values Missing
phylum has 4742156 (94.5%) missing values Missing
class has 4741605 (94.5%) missing values Missing
order has 143842 (2.9%) missing values Missing
subgenus has 5019781 (> 99.9%) missing values Missing
specificEpithet has 420613 (8.4%) missing values Missing
infraspecificEpithet has 4607995 (91.8%) missing values Missing
scientificNameAuthorship has 355313 (7.1%) missing values Missing
vernacularName has 5019781 (> 99.9%) missing values Missing
nomenclaturalStatus has 5019781 (> 99.9%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique
catalogNumber has unique values Unique

Reproduction

Analysis started2025-02-28 17:43:09.993924
Analysis finished2025-02-28 17:45:42.229007
Duration2 minutes and 32.24 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct5019782
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.3 MiB
2025-02-28T12:45:44.765986image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters50197820
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

Unique5019782 ?
Unique (%)100.0%

Sample

1st row2514633172
2nd row2980371442
3rd row2514602651
4th row2980366433
5th row2514610075
ValueCountFrequency (%)
2514633172 1
 
< 0.1%
2980357438 1
 
< 0.1%
2516414075 1
 
< 0.1%
2980344448 1
 
< 0.1%
2516430099 1
 
< 0.1%
2980380439 1
 
< 0.1%
2516309267 1
 
< 0.1%
2980358429 1
 
< 0.1%
2514610078 1
 
< 0.1%
2516623054 1
 
< 0.1%
Other values (5019772) 5019772
> 99.9%
2025-02-28T12:45:47.359351image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 8927787
17.8%
2 7962993
15.9%
1 7915696
15.8%
4 4128324
8.2%
3 4110468
8.2%
6 4020457
8.0%
7 3910237
7.8%
0 3130209
 
6.2%
8 3047255
 
6.1%
9 3044394
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 50197820
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 8927787
17.8%
2 7962993
15.9%
1 7915696
15.8%
4 4128324
8.2%
3 4110468
8.2%
6 4020457
8.0%
7 3910237
7.8%
0 3130209
 
6.2%
8 3047255
 
6.1%
9 3044394
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 50197820
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 8927787
17.8%
2 7962993
15.9%
1 7915696
15.8%
4 4128324
8.2%
3 4110468
8.2%
6 4020457
8.0%
7 3910237
7.8%
0 3130209
 
6.2%
8 3047255
 
6.1%
9 3044394
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 50197820
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 8927787
17.8%
2 7962993
15.9%
1 7915696
15.8%
4 4128324
8.2%
3 4110468
8.2%
6 4020457
8.0%
7 3910237
7.8%
0 3130209
 
6.2%
8 3047255
 
6.1%
9 3044394
 
6.1%

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.3 MiB
2025-02-28T12:45:47.410755image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters35138474
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 rowCC0 1.0
2nd rowCC0 1.0
3rd rowCC0 1.0
4th rowCC0 1.0
5th rowCC0 1.0
ValueCountFrequency (%)
cc0 5019782
50.0%
1.0 5019782
50.0%
2025-02-28T12:45:47.490986image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 10039564
28.6%
0 10039564
28.6%
5019782
14.3%
1 5019782
14.3%
. 5019782
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 35138474
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 10039564
28.6%
0 10039564
28.6%
5019782
14.3%
1 5019782
14.3%
. 5019782
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 35138474
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 10039564
28.6%
0 10039564
28.6%
5019782
14.3%
1 5019782
14.3%
. 5019782
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 35138474
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 10039564
28.6%
0 10039564
28.6%
5019782
14.3%
1 5019782
14.3%
. 5019782
14.3%

rightsHolder
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.3 MiB
2025-02-28T12:45:47.522635image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters145573678
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNaturalis Biodiversity Center
2nd rowNaturalis Biodiversity Center
3rd rowNaturalis Biodiversity Center
4th rowNaturalis Biodiversity Center
5th rowNaturalis Biodiversity Center
ValueCountFrequency (%)
naturalis 5019782
33.3%
biodiversity 5019782
33.3%
center 5019782
33.3%
2025-02-28T12:45:47.602216image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 20079128
13.8%
t 15059346
10.3%
r 15059346
10.3%
e 15059346
10.3%
10039564
 
6.9%
s 10039564
 
6.9%
a 10039564
 
6.9%
d 5019782
 
3.4%
C 5019782
 
3.4%
y 5019782
 
3.4%
Other values (7) 35138474
24.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 145573678
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 20079128
13.8%
t 15059346
10.3%
r 15059346
10.3%
e 15059346
10.3%
10039564
 
6.9%
s 10039564
 
6.9%
a 10039564
 
6.9%
d 5019782
 
3.4%
C 5019782
 
3.4%
y 5019782
 
3.4%
Other values (7) 35138474
24.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 145573678
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 20079128
13.8%
t 15059346
10.3%
r 15059346
10.3%
e 15059346
10.3%
10039564
 
6.9%
s 10039564
 
6.9%
a 10039564
 
6.9%
d 5019782
 
3.4%
C 5019782
 
3.4%
y 5019782
 
3.4%
Other values (7) 35138474
24.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 145573678
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 20079128
13.8%
t 15059346
10.3%
r 15059346
10.3%
e 15059346
10.3%
10039564
 
6.9%
s 10039564
 
6.9%
a 10039564
 
6.9%
d 5019782
 
3.4%
C 5019782
 
3.4%
y 5019782
 
3.4%
Other values (7) 35138474
24.1%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.3 MiB
2025-02-28T12:45:47.629975image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters125494550
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://ror.org/0566bfb96
2nd rowhttps://ror.org/0566bfb96
3rd rowhttps://ror.org/0566bfb96
4th rowhttps://ror.org/0566bfb96
5th rowhttps://ror.org/0566bfb96
ValueCountFrequency (%)
https://ror.org/0566bfb96 5019782
100.0%
2025-02-28T12:45:47.709719image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 15059346
12.0%
r 15059346
12.0%
6 15059346
12.0%
t 10039564
 
8.0%
o 10039564
 
8.0%
b 10039564
 
8.0%
h 5019782
 
4.0%
p 5019782
 
4.0%
s 5019782
 
4.0%
: 5019782
 
4.0%
Other values (6) 30118692
24.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 125494550
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 15059346
12.0%
r 15059346
12.0%
6 15059346
12.0%
t 10039564
 
8.0%
o 10039564
 
8.0%
b 10039564
 
8.0%
h 5019782
 
4.0%
p 5019782
 
4.0%
s 5019782
 
4.0%
: 5019782
 
4.0%
Other values (6) 30118692
24.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 125494550
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 15059346
12.0%
r 15059346
12.0%
6 15059346
12.0%
t 10039564
 
8.0%
o 10039564
 
8.0%
b 10039564
 
8.0%
h 5019782
 
4.0%
p 5019782
 
4.0%
s 5019782
 
4.0%
: 5019782
 
4.0%
Other values (6) 30118692
24.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 125494550
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 15059346
12.0%
r 15059346
12.0%
6 15059346
12.0%
t 10039564
 
8.0%
o 10039564
 
8.0%
b 10039564
 
8.0%
h 5019782
 
4.0%
p 5019782
 
4.0%
s 5019782
 
4.0%
: 5019782
 
4.0%
Other values (6) 30118692
24.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.3 MiB
2025-02-28T12:45:47.736663image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters30118692
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBotany
2nd rowBotany
3rd rowBotany
4th rowBotany
5th rowBotany
ValueCountFrequency (%)
botany 5019782
100.0%
2025-02-28T12:45:47.815116image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 5019782
16.7%
o 5019782
16.7%
t 5019782
16.7%
a 5019782
16.7%
n 5019782
16.7%
y 5019782
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30118692
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 5019782
16.7%
o 5019782
16.7%
t 5019782
16.7%
a 5019782
16.7%
n 5019782
16.7%
y 5019782
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30118692
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 5019782
16.7%
o 5019782
16.7%
t 5019782
16.7%
a 5019782
16.7%
n 5019782
16.7%
y 5019782
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30118692
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 5019782
16.7%
o 5019782
16.7%
t 5019782
16.7%
a 5019782
16.7%
n 5019782
16.7%
y 5019782
16.7%

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing785
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:45:47.841639image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters85322949
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 5018997
100.0%
2025-02-28T12:45:47.919345image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 25094985
29.4%
r 10037994
 
11.8%
P 5018997
 
5.9%
s 5018997
 
5.9%
v 5018997
 
5.9%
d 5018997
 
5.9%
S 5018997
 
5.9%
p 5018997
 
5.9%
c 5018997
 
5.9%
i 5018997
 
5.9%
Other values (2) 10037994
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 85322949
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 25094985
29.4%
r 10037994
 
11.8%
P 5018997
 
5.9%
s 5018997
 
5.9%
v 5018997
 
5.9%
d 5018997
 
5.9%
S 5018997
 
5.9%
p 5018997
 
5.9%
c 5018997
 
5.9%
i 5018997
 
5.9%
Other values (2) 10037994
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 85322949
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 25094985
29.4%
r 10037994
 
11.8%
P 5018997
 
5.9%
s 5018997
 
5.9%
v 5018997
 
5.9%
d 5018997
 
5.9%
S 5018997
 
5.9%
p 5018997
 
5.9%
c 5018997
 
5.9%
i 5018997
 
5.9%
Other values (2) 10037994
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 85322949
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 25094985
29.4%
r 10037994
 
11.8%
P 5018997
 
5.9%
s 5018997
 
5.9%
v 5018997
 
5.9%
d 5018997
 
5.9%
S 5018997
 
5.9%
p 5018997
 
5.9%
c 5018997
 
5.9%
i 5018997
 
5.9%
Other values (2) 10037994
 
11.8%

occurrenceID
Text

Unique 

Distinct5019782
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.3 MiB
2025-02-28T12:45:50.191058image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length81
Median length61
Mean length61.70256258
Min length58

Characters and Unicode

Total characters309733413
Distinct characters65
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

Unique5019782 ?
Unique (%)100.0%

Sample

1st rowhttps://data.biodiversitydata.nl/naturalis/specimen/L.2851604
2nd rowhttps://data.biodiversitydata.nl/naturalis/specimen/L%20%200971472
3rd rowhttps://data.biodiversitydata.nl/naturalis/specimen/L.2851644
4th rowhttps://data.biodiversitydata.nl/naturalis/specimen/L%20%200971531
5th rowhttps://data.biodiversitydata.nl/naturalis/specimen/L.2851686
ValueCountFrequency (%)
https://data.biodiversitydata.nl/naturalis/specimen/wag.1226003 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/wag.1816421 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/wag0454007 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/l.4308389 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/wag0100360 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/l%20%200981551 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/l%20%200820195 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/wag.1250897 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/l.4434831 2
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/l.4373010 2
 
< 0.1%
Other values (5019737) 5019762
> 99.9%
2025-02-28T12:45:52.743798image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 30118729
 
9.7%
t 30118693
 
9.7%
/ 25098912
 
8.1%
i 25098910
 
8.1%
s 20079128
 
6.5%
n 15059347
 
4.9%
e 15059347
 
4.9%
d 15059346
 
4.9%
. 14670101
 
4.7%
l 10039580
 
3.2%
Other values (55) 109331320
35.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 309733413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 30118729
 
9.7%
t 30118693
 
9.7%
/ 25098912
 
8.1%
i 25098910
 
8.1%
s 20079128
 
6.5%
n 15059347
 
4.9%
e 15059347
 
4.9%
d 15059346
 
4.9%
. 14670101
 
4.7%
l 10039580
 
3.2%
Other values (55) 109331320
35.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 309733413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 30118729
 
9.7%
t 30118693
 
9.7%
/ 25098912
 
8.1%
i 25098910
 
8.1%
s 20079128
 
6.5%
n 15059347
 
4.9%
e 15059347
 
4.9%
d 15059346
 
4.9%
. 14670101
 
4.7%
l 10039580
 
3.2%
Other values (55) 109331320
35.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 309733413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 30118729
 
9.7%
t 30118693
 
9.7%
/ 25098912
 
8.1%
i 25098910
 
8.1%
s 20079128
 
6.5%
n 15059347
 
4.9%
e 15059347
 
4.9%
d 15059346
 
4.9%
. 14670101
 
4.7%
l 10039580
 
3.2%
Other values (55) 109331320
35.3%

catalogNumber
Text

Unique 

Distinct5019782
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.3 MiB
2025-02-28T12:45:55.387473image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length9
Mean length9.425454532
Min length6

Characters and Unicode

Total characters47313727
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

Unique5019782 ?
Unique (%)100.0%

Sample

1st rowL.2851604
2nd rowL 0971472
3rd rowL.2851644
4th rowL 0971531
5th rowL.2851686
ValueCountFrequency (%)
l 285081
 
5.3%
u 62704
 
1.2%
04 7
 
< 0.1%
0012538 3
 
< 0.1%
3
 
< 0.1%
0228872 2
 
< 0.1%
0004574 2
 
< 0.1%
0229129 2
 
< 0.1%
0004635 2
 
< 0.1%
0256210 2
 
< 0.1%
Other values (4994407) 5019794
93.5%
2025-02-28T12:45:57.793932image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5550526
11.7%
. 4630537
9.8%
2 4070617
8.6%
3 3919831
 
8.3%
0 3465436
 
7.3%
4 3413591
 
7.2%
L 3368280
 
7.1%
7 2998891
 
6.3%
5 2992563
 
6.3%
6 2885861
 
6.1%
Other values (48) 10017594
21.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 47313727
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 5550526
11.7%
. 4630537
9.8%
2 4070617
8.6%
3 3919831
 
8.3%
0 3465436
 
7.3%
4 3413591
 
7.2%
L 3368280
 
7.1%
7 2998891
 
6.3%
5 2992563
 
6.3%
6 2885861
 
6.1%
Other values (48) 10017594
21.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 47313727
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 5550526
11.7%
. 4630537
9.8%
2 4070617
8.6%
3 3919831
 
8.3%
0 3465436
 
7.3%
4 3413591
 
7.2%
L 3368280
 
7.1%
7 2998891
 
6.3%
5 2992563
 
6.3%
6 2885861
 
6.1%
Other values (48) 10017594
21.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 47313727
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 5550526
11.7%
. 4630537
9.8%
2 4070617
8.6%
3 3919831
 
8.3%
0 3465436
 
7.3%
4 3413591
 
7.2%
L 3368280
 
7.1%
7 2998891
 
6.3%
5 2992563
 
6.3%
6 2885861
 
6.1%
Other values (48) 10017594
21.2%
Distinct2852768
Distinct (%)56.8%
Missing1
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:45:58.014193image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length121
Median length104
Mean length21.23713803
Min length1

Characters and Unicode

Total characters106605782
Distinct characters139
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

Unique2358777 ?
Unique (%)47.0%

Sample

1st rowUnknown s.n.
2nd rowZainoeddin bb 17357
3rd rowWijk, JH van s.n.
4th rowUnknown bb 17412
5th rowKoster, JT 6255
ValueCountFrequency (%)
s.n 1517120
 
7.6%
unknown 403748
 
2.0%
van 402082
 
2.0%
de 306350
 
1.5%
a 267054
 
1.3%
j 265883
 
1.3%
m 160895
 
0.8%
h 141882
 
0.7%
p 138822
 
0.7%
c 138103
 
0.7%
Other values (172568) 16227490
81.3%
2025-02-28T12:45:58.311217image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14949623
 
14.0%
n 6590984
 
6.2%
e 6135300
 
5.8%
, 5592121
 
5.2%
a 4397488
 
4.1%
s 3844877
 
3.6%
r 3532381
 
3.3%
o 3476858
 
3.3%
. 3240362
 
3.0%
i 2918794
 
2.7%
Other values (129) 51926994
48.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 106605782
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
14949623
 
14.0%
n 6590984
 
6.2%
e 6135300
 
5.8%
, 5592121
 
5.2%
a 4397488
 
4.1%
s 3844877
 
3.6%
r 3532381
 
3.3%
o 3476858
 
3.3%
. 3240362
 
3.0%
i 2918794
 
2.7%
Other values (129) 51926994
48.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 106605782
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
14949623
 
14.0%
n 6590984
 
6.2%
e 6135300
 
5.8%
, 5592121
 
5.2%
a 4397488
 
4.1%
s 3844877
 
3.6%
r 3532381
 
3.3%
o 3476858
 
3.3%
. 3240362
 
3.0%
i 2918794
 
2.7%
Other values (129) 51926994
48.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 106605782
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
14949623
 
14.0%
n 6590984
 
6.2%
e 6135300
 
5.8%
, 5592121
 
5.2%
a 4397488
 
4.1%
s 3844877
 
3.6%
r 3532381
 
3.3%
o 3476858
 
3.3%
. 3240362
 
3.0%
i 2918794
 
2.7%
Other values (129) 51926994
48.7%
Distinct101508
Distinct (%)2.0%
Missing11448
Missing (%)0.2%
Memory size38.3 MiB
2025-02-28T12:45:58.469223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length108
Median length96
Mean length14.60004524
Min length1

Characters and Unicode

Total characters73121903
Distinct characters125
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

Unique37149 ?
Unique (%)0.7%

Sample

1st rowUnknown
2nd rowZainoeddin
3rd rowWijk JH van
4th rowUnknown
5th rowKoster JT
ValueCountFrequency (%)
unknown 403744
 
2.9%
van 402079
 
2.9%
de 306325
 
2.2%
j 264889
 
1.9%
a 210805
 
1.5%
m 155481
 
1.1%
al 137949
 
1.0%
h 137879
 
1.0%
r 135106
 
1.0%
p 133204
 
0.9%
Other values (40914) 11811523
83.8%
2025-02-28T12:45:58.723458image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9090878
 
12.4%
e 6123944
 
8.4%
n 5043429
 
6.9%
a 4353925
 
6.0%
r 3514483
 
4.8%
o 3466711
 
4.7%
i 2903594
 
4.0%
s 2322445
 
3.2%
l 2220840
 
3.0%
t 2048480
 
2.8%
Other values (115) 32033174
43.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 73121903
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9090878
 
12.4%
e 6123944
 
8.4%
n 5043429
 
6.9%
a 4353925
 
6.0%
r 3514483
 
4.8%
o 3466711
 
4.7%
i 2903594
 
4.0%
s 2322445
 
3.2%
l 2220840
 
3.0%
t 2048480
 
2.8%
Other values (115) 32033174
43.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 73121903
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9090878
 
12.4%
e 6123944
 
8.4%
n 5043429
 
6.9%
a 4353925
 
6.0%
r 3514483
 
4.8%
o 3466711
 
4.7%
i 2903594
 
4.0%
s 2322445
 
3.2%
l 2220840
 
3.0%
t 2048480
 
2.8%
Other values (115) 32033174
43.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 73121903
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9090878
 
12.4%
e 6123944
 
8.4%
n 5043429
 
6.9%
a 4353925
 
6.0%
r 3514483
 
4.8%
o 3466711
 
4.7%
i 2903594
 
4.0%
s 2322445
 
3.2%
l 2220840
 
3.0%
t 2048480
 
2.8%
Other values (115) 32033174
43.8%

otherCatalogNumbers
Text

Missing 

Distinct1247855
Distinct (%)97.7%
Missing3742862
Missing (%)74.6%
Memory size38.3 MiB
2025-02-28T12:45:59.494182image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length10
Mean length11.00010729
Min length1

Characters and Unicode

Total characters14046257
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

Unique1228633 ?
Unique (%)96.2%

Sample

1st rowL 0215467
2nd rowL 0215532
3rd rowL 0204325
4th rowL 0542724
5th rowL 0973113
ValueCountFrequency (%)
l 605823
25.3%
176059
 
7.3%
u 146244
 
6.1%
uw 6074
 
0.3%
b 4013
 
0.2%
a 2407
 
0.1%
0 681
 
< 0.1%
k 377
 
< 0.1%
jan.99 305
 
< 0.1%
okt.00 265
 
< 0.1%
Other values (1309143) 1457050
60.7%
2025-02-28T12:46:00.122960image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2090566
14.9%
1874427
13.3%
1 1087243
 
7.7%
2 1003157
 
7.1%
3 926296
 
6.6%
9 902389
 
6.4%
4 845700
 
6.0%
5 836296
 
6.0%
8 818449
 
5.8%
6 793280
 
5.6%
Other values (69) 2868454
20.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14046257
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2090566
14.9%
1874427
13.3%
1 1087243
 
7.7%
2 1003157
 
7.1%
3 926296
 
6.6%
9 902389
 
6.4%
4 845700
 
6.0%
5 836296
 
6.0%
8 818449
 
5.8%
6 793280
 
5.6%
Other values (69) 2868454
20.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14046257
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2090566
14.9%
1874427
13.3%
1 1087243
 
7.7%
2 1003157
 
7.1%
3 926296
 
6.6%
9 902389
 
6.4%
4 845700
 
6.0%
5 836296
 
6.0%
8 818449
 
5.8%
6 793280
 
5.6%
Other values (69) 2868454
20.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14046257
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2090566
14.9%
1874427
13.3%
1 1087243
 
7.7%
2 1003157
 
7.1%
3 926296
 
6.6%
9 902389
 
6.4%
4 845700
 
6.0%
5 836296
 
6.0%
8 818449
 
5.8%
6 793280
 
5.6%
Other values (69) 2868454
20.4%

eventDate
Text

Missing 

Distinct67961
Distinct (%)1.6%
Missing856201
Missing (%)17.1%
Memory size38.3 MiB
2025-02-28T12:46:00.220417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length11.80088967
Min length10

Characters and Unicode

Total characters49133960
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

Unique6056 ?
Unique (%)0.1%

Sample

1st row1933-04-24
2nd row1956-05-14
3rd row1939-05-21
4th row1955-04-26
5th row1838-05-01/1838-05-31
ValueCountFrequency (%)
1859-01-01/1859-12-31 5064
 
0.1%
1857-01-01/1857-12-31 3575
 
0.1%
1898-01-01/1898-12-31 3352
 
0.1%
1922-10-01/1922-10-31 2927
 
0.1%
1912-01-01/1912-12-31 2915
 
0.1%
1840-01-01/1840-12-31 2864
 
0.1%
1880-01-01/1880-12-31 2677
 
0.1%
1893-01-01/1893-12-31 2625
 
0.1%
1909-01-01/1909-12-31 2617
 
0.1%
1900-01-01/1900-12-31 2597
 
0.1%
Other values (67951) 4132368
99.3%
2025-02-28T12:46:00.391937image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9868786
20.1%
- 9690462
19.7%
0 7477809
15.2%
9 5666608
11.5%
2 3122979
 
6.4%
8 2608202
 
5.3%
3 2323651
 
4.7%
6 2166097
 
4.4%
7 2156107
 
4.4%
5 1905253
 
3.9%
Other values (2) 2148006
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49133960
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 9868786
20.1%
- 9690462
19.7%
0 7477809
15.2%
9 5666608
11.5%
2 3122979
 
6.4%
8 2608202
 
5.3%
3 2323651
 
4.7%
6 2166097
 
4.4%
7 2156107
 
4.4%
5 1905253
 
3.9%
Other values (2) 2148006
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49133960
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 9868786
20.1%
- 9690462
19.7%
0 7477809
15.2%
9 5666608
11.5%
2 3122979
 
6.4%
8 2608202
 
5.3%
3 2323651
 
4.7%
6 2166097
 
4.4%
7 2156107
 
4.4%
5 1905253
 
3.9%
Other values (2) 2148006
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49133960
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 9868786
20.1%
- 9690462
19.7%
0 7477809
15.2%
9 5666608
11.5%
2 3122979
 
6.4%
8 2608202
 
5.3%
3 2323651
 
4.7%
6 2166097
 
4.4%
7 2156107
 
4.4%
5 1905253
 
3.9%
Other values (2) 2148006
 
4.4%

habitat
Text

Missing 

Distinct339001
Distinct (%)37.2%
Missing4109448
Missing (%)81.9%
Memory size38.3 MiB
2025-02-28T12:46:00.579284image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24282
Median length668
Mean length39.6989929
Min length1

Characters and Unicode

Total characters36139343
Distinct characters168
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

Unique233613 ?
Unique (%)25.7%

Sample

1st rowOld forest
2nd rowOld forest Very scanty
3rd rowOld forest, steep ridge
4th rowOld forest, clayey soil, sloping country, scanty
5th rowDegrade forest
ValueCountFrequency (%)
forest 416697
 
7.7%
in 196774
 
3.7%
on 168551
 
3.1%
of 89312
 
1.7%
soil 89138
 
1.7%
primary 81686
 
1.5%
with 73747
 
1.4%
secondary 71636
 
1.3%
the 66144
 
1.2%
and 64092
 
1.2%
Other values (93782) 4061990
75.5%
2025-02-28T12:46:00.827906image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4478314
 
12.4%
e 3514056
 
9.7%
r 2590696
 
7.2%
a 2510661
 
6.9%
o 2468359
 
6.8%
n 2068334
 
5.7%
s 1995921
 
5.5%
t 1847880
 
5.1%
i 1812691
 
5.0%
d 1411076
 
3.9%
Other values (158) 11441355
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36139343
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4478314
 
12.4%
e 3514056
 
9.7%
r 2590696
 
7.2%
a 2510661
 
6.9%
o 2468359
 
6.8%
n 2068334
 
5.7%
s 1995921
 
5.5%
t 1847880
 
5.1%
i 1812691
 
5.0%
d 1411076
 
3.9%
Other values (158) 11441355
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36139343
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4478314
 
12.4%
e 3514056
 
9.7%
r 2590696
 
7.2%
a 2510661
 
6.9%
o 2468359
 
6.8%
n 2068334
 
5.7%
s 1995921
 
5.5%
t 1847880
 
5.1%
i 1812691
 
5.0%
d 1411076
 
3.9%
Other values (158) 11441355
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36139343
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4478314
 
12.4%
e 3514056
 
9.7%
r 2590696
 
7.2%
a 2510661
 
6.9%
o 2468359
 
6.8%
n 2068334
 
5.7%
s 1995921
 
5.5%
t 1847880
 
5.1%
i 1812691
 
5.0%
d 1411076
 
3.9%
Other values (158) 11441355
31.7%

samplingEffort
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:00.865668image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row0.0 m
ValueCountFrequency (%)
0.0 1
50.0%
m 1
50.0%
2025-02-28T12:46:00.944988image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
40.0%
. 1
20.0%
1
20.0%
m 1
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2
40.0%
. 1
20.0%
1
20.0%
m 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2
40.0%
. 1
20.0%
1
20.0%
m 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2
40.0%
. 1
20.0%
1
20.0%
m 1
20.0%

continent
Text

Missing 

Distinct9
Distinct (%)< 0.1%
Missing902365
Missing (%)18.0%
Memory size38.3 MiB
2025-02-28T12:46:00.976570image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length15
Mean length7.327123048
Min length4

Characters and Unicode

Total characters30168821
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 rowEurope
2nd rowAsia
3rd rowEurope
4th rowAsia
5th rowEurope
ValueCountFrequency (%)
asia 1235811
25.9%
europe 1145221
24.0%
africa 713929
14.9%
america 661234
13.8%
southern 417866
 
8.7%
australasia 358600
 
7.5%
central 124578
 
2.6%
north 118790
 
2.5%
antarctica 1561
 
< 0.1%
africa/asia 1061
 
< 0.1%
2025-02-28T12:46:01.067463image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3816596
12.7%
r 3542840
11.7%
A 2973257
9.9%
i 2973257
9.9%
e 2348899
 
7.8%
s 1954072
 
6.5%
u 1921687
 
6.4%
o 1681877
 
5.6%
c 1379346
 
4.6%
p 1145221
 
3.8%
Other values (12) 6431769
21.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30168821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3816596
12.7%
r 3542840
11.7%
A 2973257
9.9%
i 2973257
9.9%
e 2348899
 
7.8%
s 1954072
 
6.5%
u 1921687
 
6.4%
o 1681877
 
5.6%
c 1379346
 
4.6%
p 1145221
 
3.8%
Other values (12) 6431769
21.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30168821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3816596
12.7%
r 3542840
11.7%
A 2973257
9.9%
i 2973257
9.9%
e 2348899
 
7.8%
s 1954072
 
6.5%
u 1921687
 
6.4%
o 1681877
 
5.6%
c 1379346
 
4.6%
p 1145221
 
3.8%
Other values (12) 6431769
21.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30168821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3816596
12.7%
r 3542840
11.7%
A 2973257
9.9%
i 2973257
9.9%
e 2348899
 
7.8%
s 1954072
 
6.5%
u 1921687
 
6.4%
o 1681877
 
5.6%
c 1379346
 
4.6%
p 1145221
 
3.8%
Other values (12) 6431769
21.3%

island
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:01.094821image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row51.41942
ValueCountFrequency (%)
51.41942 1
100.0%
2025-02-28T12:46:01.174118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
25.0%
4 2
25.0%
5 1
12.5%
. 1
12.5%
9 1
12.5%
2 1
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 2
25.0%
4 2
25.0%
5 1
12.5%
. 1
12.5%
9 1
12.5%
2 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 2
25.0%
4 2
25.0%
5 1
12.5%
. 1
12.5%
9 1
12.5%
2 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 2
25.0%
4 2
25.0%
5 1
12.5%
. 1
12.5%
9 1
12.5%
2 1
12.5%
Distinct259
Distinct (%)< 0.1%
Missing375
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:01.306239image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length38
Median length33
Mean length9.385069392
Min length4

Characters and Unicode

Total characters47107483
Distinct characters67
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 rowFrance
2nd rowIndonesia
3rd rowFrance
4th rowIndonesia
5th rowGreece
ValueCountFrequency (%)
unknown 901458
 
14.7%
netherlands 668769
 
10.9%
indonesia 566953
 
9.2%
new 190960
 
3.1%
guinea 166419
 
2.7%
papua 152664
 
2.5%
brazil 120044
 
2.0%
united 119751
 
2.0%
france 116205
 
1.9%
australia 110396
 
1.8%
Other values (304) 3021381
49.2%
2025-02-28T12:46:01.524295image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 6455572
13.7%
a 6144718
 
13.0%
e 3683911
 
7.8%
i 3049965
 
6.5%
o 2676245
 
5.7%
s 2153854
 
4.6%
r 2077292
 
4.4%
d 1855222
 
3.9%
l 1850248
 
3.9%
t 1563534
 
3.3%
Other values (57) 15596922
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 47107483
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 6455572
13.7%
a 6144718
 
13.0%
e 3683911
 
7.8%
i 3049965
 
6.5%
o 2676245
 
5.7%
s 2153854
 
4.6%
r 2077292
 
4.4%
d 1855222
 
3.9%
l 1850248
 
3.9%
t 1563534
 
3.3%
Other values (57) 15596922
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 47107483
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 6455572
13.7%
a 6144718
 
13.0%
e 3683911
 
7.8%
i 3049965
 
6.5%
o 2676245
 
5.7%
s 2153854
 
4.6%
r 2077292
 
4.4%
d 1855222
 
3.9%
l 1850248
 
3.9%
t 1563534
 
3.3%
Other values (57) 15596922
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 47107483
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 6455572
13.7%
a 6144718
 
13.0%
e 3683911
 
7.8%
i 3049965
 
6.5%
o 2676245
 
5.7%
s 2153854
 
4.6%
r 2077292
 
4.4%
d 1855222
 
3.9%
l 1850248
 
3.9%
t 1563534
 
3.3%
Other values (57) 15596922
33.1%

countryCode
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:01.565509image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
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 rowWGS84
2nd rowWGS84
ValueCountFrequency (%)
wgs84 2
100.0%
2025-02-28T12:46:01.646867image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 2
20.0%
G 2
20.0%
S 2
20.0%
8 2
20.0%
4 2
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
W 2
20.0%
G 2
20.0%
S 2
20.0%
8 2
20.0%
4 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
W 2
20.0%
G 2
20.0%
S 2
20.0%
8 2
20.0%
4 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
W 2
20.0%
G 2
20.0%
S 2
20.0%
8 2
20.0%
4 2
20.0%

stateProvince
Text

Missing 

Distinct3223
Distinct (%)0.2%
Missing3065004
Missing (%)61.1%
Memory size38.3 MiB
2025-02-28T12:46:01.801765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length28
Mean length8.864043385
Min length3

Characters and Unicode

Total characters17327237
Distinct characters108
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

Unique408 ?
Unique (%)< 0.1%

Sample

1st rowSumatra
2nd rowBorneo
3rd rowBorneo
4th rowSumatra
5th rowSumatra
ValueCountFrequency (%)
borneo 230539
 
9.3%
new 206395
 
8.3%
guinea 192672
 
7.8%
java 135629
 
5.5%
sumatra 84195
 
3.4%
region 83893
 
3.4%
northern 54146
 
2.2%
zuid-holland 53025
 
2.1%
gelderland 42250
 
1.7%
sulawesi 38230
 
1.5%
Other values (3222) 1356524
54.8%
2025-02-28T12:46:02.018670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1947747
 
11.2%
e 1641332
 
9.5%
o 1463019
 
8.4%
n 1452254
 
8.4%
r 1147603
 
6.6%
i 879429
 
5.1%
u 873773
 
5.0%
l 667117
 
3.9%
t 638970
 
3.7%
s 549587
 
3.2%
Other values (98) 6066406
35.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17327237
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1947747
 
11.2%
e 1641332
 
9.5%
o 1463019
 
8.4%
n 1452254
 
8.4%
r 1147603
 
6.6%
i 879429
 
5.1%
u 873773
 
5.0%
l 667117
 
3.9%
t 638970
 
3.7%
s 549587
 
3.2%
Other values (98) 6066406
35.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17327237
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1947747
 
11.2%
e 1641332
 
9.5%
o 1463019
 
8.4%
n 1452254
 
8.4%
r 1147603
 
6.6%
i 879429
 
5.1%
u 873773
 
5.0%
l 667117
 
3.9%
t 638970
 
3.7%
s 549587
 
3.2%
Other values (98) 6066406
35.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17327237
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1947747
 
11.2%
e 1641332
 
9.5%
o 1463019
 
8.4%
n 1452254
 
8.4%
r 1147603
 
6.6%
i 879429
 
5.1%
u 873773
 
5.0%
l 667117
 
3.9%
t 638970
 
3.7%
s 549587
 
3.2%
Other values (98) 6066406
35.0%

locality
Text

Missing 

Distinct2397188
Distinct (%)56.3%
Missing763737
Missing (%)15.2%
Memory size38.3 MiB
2025-02-28T12:46:02.951097image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length736849
Median length84356
Mean length47.16343342
Min length1

Characters and Unicode

Total characters200729695
Distinct characters211
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

Unique1909729 ?
Unique (%)44.9%

Sample

1st rowNice.
2nd rowE. Coast Sumatra, Siak, Indrapura
3rd rowCorsica; Cargèse.
4th rowPatras, op rots, bij ruine.
5th rowWest Borneo, Sintang G. Pahoe
ValueCountFrequency (%)
of 993695
 
3.3%
de 528801
 
1.8%
km 423817
 
1.4%
366885
 
1.2%
in 319701
 
1.1%
the 236036
 
0.8%
road 222131
 
0.7%
near 220755
 
0.7%
bij 193361
 
0.6%
district 189242
 
0.6%
Other values (1181095) 26099389
87.6%
2025-02-28T12:46:03.896002image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25605653
 
12.8%
a 17766400
 
8.9%
e 14813627
 
7.4%
n 11419769
 
5.7%
o 10867963
 
5.4%
i 10448228
 
5.2%
r 10001236
 
5.0%
t 7769321
 
3.9%
. 7553473
 
3.8%
s 6867565
 
3.4%
Other values (201) 77616460
38.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 200729695
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
25605653
 
12.8%
a 17766400
 
8.9%
e 14813627
 
7.4%
n 11419769
 
5.7%
o 10867963
 
5.4%
i 10448228
 
5.2%
r 10001236
 
5.0%
t 7769321
 
3.9%
. 7553473
 
3.8%
s 6867565
 
3.4%
Other values (201) 77616460
38.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 200729695
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
25605653
 
12.8%
a 17766400
 
8.9%
e 14813627
 
7.4%
n 11419769
 
5.7%
o 10867963
 
5.4%
i 10448228
 
5.2%
r 10001236
 
5.0%
t 7769321
 
3.9%
. 7553473
 
3.8%
s 6867565
 
3.4%
Other values (201) 77616460
38.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 200729695
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
25605653
 
12.8%
a 17766400
 
8.9%
e 14813627
 
7.4%
n 11419769
 
5.7%
o 10867963
 
5.4%
i 10448228
 
5.2%
r 10001236
 
5.0%
t 7769321
 
3.9%
. 7553473
 
3.8%
s 6867565
 
3.4%
Other values (201) 77616460
38.7%

verbatimElevation
Text

Missing 

Distinct7745
Distinct (%)0.4%
Missing3265629
Missing (%)65.1%
Memory size38.3 MiB
2025-02-28T12:46:03.937192image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length5
Mean length6.313657931
Min length5

Characters and Unicode

Total characters11075122
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

Unique2081 ?
Unique (%)0.1%

Sample

1st row10.0 m
2nd row600.0 m
3rd row250.0 m
4th row20.0 m
5th row4.0 m
ValueCountFrequency (%)
m 1754153
47.7%
0.0 971270
26.4%
83446
 
2.3%
100.0 30322
 
0.8%
200.0 27380
 
0.7%
50.0 25985
 
0.7%
300.0 21545
 
0.6%
400.0 20709
 
0.6%
500.0 20313
 
0.6%
1000.0 18743
 
0.5%
Other values (3230) 701332
 
19.1%
2025-02-28T12:46:04.042810image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3847172
34.7%
1921045
17.3%
. 1837599
16.6%
m 1754153
15.8%
1 378270
 
3.4%
5 310048
 
2.8%
2 249943
 
2.3%
3 159594
 
1.4%
4 133323
 
1.2%
6 114954
 
1.0%
Other values (4) 369021
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11075122
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3847172
34.7%
1921045
17.3%
. 1837599
16.6%
m 1754153
15.8%
1 378270
 
3.4%
5 310048
 
2.8%
2 249943
 
2.3%
3 159594
 
1.4%
4 133323
 
1.2%
6 114954
 
1.0%
Other values (4) 369021
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11075122
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3847172
34.7%
1921045
17.3%
. 1837599
16.6%
m 1754153
15.8%
1 378270
 
3.4%
5 310048
 
2.8%
2 249943
 
2.3%
3 159594
 
1.4%
4 133323
 
1.2%
6 114954
 
1.0%
Other values (4) 369021
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11075122
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3847172
34.7%
1921045
17.3%
. 1837599
16.6%
m 1754153
15.8%
1 378270
 
3.4%
5 310048
 
2.8%
2 249943
 
2.3%
3 159594
 
1.4%
4 133323
 
1.2%
6 114954
 
1.0%
Other values (4) 369021
 
3.3%

maximumDistanceAboveSurfaceInMeters
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:04.074413image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia
ValueCountFrequency (%)
asia 1
100.0%
2025-02-28T12:46:04.158159image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1
25.0%
s 1
25.0%
i 1
25.0%
a 1
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1
25.0%
s 1
25.0%
i 1
25.0%
a 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1
25.0%
s 1
25.0%
i 1
25.0%
a 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1
25.0%
s 1
25.0%
i 1
25.0%
a 1
25.0%

decimalLatitude
Text

Missing 

Distinct85312
Distinct (%)4.1%
Missing2925885
Missing (%)58.3%
Memory size38.3 MiB
2025-02-28T12:46:04.316659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.935163477
Min length3

Characters and Unicode

Total characters14521518
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

Unique32905 ?
Unique (%)1.6%

Sample

1st row-2.06667
2nd row0.0
3rd row-2.18333
4th row-2.18333
5th row1.16667
ValueCountFrequency (%)
52.16011 15831
 
0.8%
7.25 9141
 
0.4%
5.83333 8412
 
0.4%
3.08333 7806
 
0.4%
1.0 7629
 
0.4%
6.08333 7109
 
0.3%
5.38333 6962
 
0.3%
5.33333 6857
 
0.3%
52.14714 6321
 
0.3%
5.0 6138
 
0.3%
Other values (80543) 2011691
96.1%
2025-02-28T12:46:04.549411image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2185740
15.1%
. 2093897
14.4%
6 1593621
11.0%
5 1522084
10.5%
1 1433173
9.9%
7 1070771
7.4%
2 1042278
7.2%
8 898646
6.2%
4 733048
 
5.0%
0 727483
 
5.0%
Other values (3) 1220777
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14521518
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 2185740
15.1%
. 2093897
14.4%
6 1593621
11.0%
5 1522084
10.5%
1 1433173
9.9%
7 1070771
7.4%
2 1042278
7.2%
8 898646
6.2%
4 733048
 
5.0%
0 727483
 
5.0%
Other values (3) 1220777
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14521518
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 2185740
15.1%
. 2093897
14.4%
6 1593621
11.0%
5 1522084
10.5%
1 1433173
9.9%
7 1070771
7.4%
2 1042278
7.2%
8 898646
6.2%
4 733048
 
5.0%
0 727483
 
5.0%
Other values (3) 1220777
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14521518
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 2185740
15.1%
. 2093897
14.4%
6 1593621
11.0%
5 1522084
10.5%
1 1433173
9.9%
7 1070771
7.4%
2 1042278
7.2%
8 898646
6.2%
4 733048
 
5.0%
0 727483
 
5.0%
Other values (3) 1220777
8.4%

decimalLongitude
Text

Missing 

Distinct95316
Distinct (%)4.6%
Missing2925885
Missing (%)58.3%
Memory size38.3 MiB
2025-02-28T12:46:04.716846image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.304637239
Min length3

Characters and Unicode

Total characters15295158
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

Unique35846 ?
Unique (%)1.7%

Sample

1st row100.93333
2nd row112.0
3rd row99.65
4th row99.65
5th row124.58333
ValueCountFrequency (%)
4.49701 15831
 
0.8%
10.41667 7696
 
0.4%
4.05 7530
 
0.4%
3.01667 7109
 
0.3%
4.47406 6117
 
0.3%
5.85874 5829
 
0.3%
106.7913 5061
 
0.2%
4.32798 5000
 
0.2%
4.90993 4858
 
0.2%
4.47863 4793
 
0.2%
Other values (91291) 2024073
96.7%
2025-02-28T12:46:04.945278image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2153780
14.1%
. 2093896
13.7%
1 2080828
13.6%
6 1818372
11.9%
7 1184132
7.7%
5 1165208
7.6%
4 1075292
7.0%
8 917920
6.0%
0 850927
 
5.6%
9 849460
 
5.6%
Other values (10) 1105343
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15295158
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 2153780
14.1%
. 2093896
13.7%
1 2080828
13.6%
6 1818372
11.9%
7 1184132
7.7%
5 1165208
7.6%
4 1075292
7.0%
8 917920
6.0%
0 850927
 
5.6%
9 849460
 
5.6%
Other values (10) 1105343
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15295158
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 2153780
14.1%
. 2093896
13.7%
1 2080828
13.6%
6 1818372
11.9%
7 1184132
7.7%
5 1165208
7.6%
4 1075292
7.0%
8 917920
6.0%
0 850927
 
5.6%
9 849460
 
5.6%
Other values (10) 1105343
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15295158
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 2153780
14.1%
. 2093896
13.7%
1 2080828
13.6%
6 1818372
11.9%
7 1184132
7.7%
5 1165208
7.6%
4 1075292
7.0%
8 917920
6.0%
0 850927
 
5.6%
9 849460
 
5.6%
Other values (10) 1105343
7.2%

geodeticDatum
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:05.001923image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters25098895
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 rowWGS84
2nd rowWGS84
3rd rowWGS84
4th rowWGS84
5th rowWGS84
ValueCountFrequency (%)
wgs84 5019779
100.0%
2025-02-28T12:46:05.091433image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 5019779
20.0%
G 5019779
20.0%
S 5019779
20.0%
8 5019779
20.0%
4 5019779
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25098895
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
W 5019779
20.0%
G 5019779
20.0%
S 5019779
20.0%
8 5019779
20.0%
4 5019779
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25098895
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
W 5019779
20.0%
G 5019779
20.0%
S 5019779
20.0%
8 5019779
20.0%
4 5019779
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25098895
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
W 5019779
20.0%
G 5019779
20.0%
S 5019779
20.0%
8 5019779
20.0%
4 5019779
20.0%

coordinateUncertaintyInMeters
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.120009image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowSouth-Western
ValueCountFrequency (%)
south-western 1
100.0%
2025-02-28T12:46:05.204694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2
15.4%
e 2
15.4%
S 1
7.7%
o 1
7.7%
u 1
7.7%
h 1
7.7%
- 1
7.7%
W 1
7.7%
s 1
7.7%
r 1
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 2
15.4%
e 2
15.4%
S 1
7.7%
o 1
7.7%
u 1
7.7%
h 1
7.7%
- 1
7.7%
W 1
7.7%
s 1
7.7%
r 1
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 2
15.4%
e 2
15.4%
S 1
7.7%
o 1
7.7%
u 1
7.7%
h 1
7.7%
- 1
7.7%
W 1
7.7%
s 1
7.7%
r 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 2
15.4%
e 2
15.4%
S 1
7.7%
o 1
7.7%
u 1
7.7%
h 1
7.7%
- 1
7.7%
W 1
7.7%
s 1
7.7%
r 1
7.7%

verbatimCoordinates
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.239036image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length70
Median length70
Mean length70
Min length70

Characters and Unicode

Total characters70
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

Unique1 ?
Unique (%)100.0%

Sample

1st rowSiam [Thailand], Kwae Noi Basin Expedition, near Neeckey, near Wangka.
ValueCountFrequency (%)
near 2
20.0%
siam 1
10.0%
thailand 1
10.0%
kwae 1
10.0%
noi 1
10.0%
basin 1
10.0%
expedition 1
10.0%
neeckey 1
10.0%
wangka 1
10.0%
2025-02-28T12:46:05.332686image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
12.9%
a 9
12.9%
e 7
 
10.0%
i 6
 
8.6%
n 6
 
8.6%
, 3
 
4.3%
k 2
 
2.9%
d 2
 
2.9%
r 2
 
2.9%
N 2
 
2.9%
Other values (21) 22
31.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9
12.9%
a 9
12.9%
e 7
 
10.0%
i 6
 
8.6%
n 6
 
8.6%
, 3
 
4.3%
k 2
 
2.9%
d 2
 
2.9%
r 2
 
2.9%
N 2
 
2.9%
Other values (21) 22
31.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9
12.9%
a 9
12.9%
e 7
 
10.0%
i 6
 
8.6%
n 6
 
8.6%
, 3
 
4.3%
k 2
 
2.9%
d 2
 
2.9%
r 2
 
2.9%
N 2
 
2.9%
Other values (21) 22
31.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9
12.9%
a 9
12.9%
e 7
 
10.0%
i 6
 
8.6%
n 6
 
8.6%
, 3
 
4.3%
k 2
 
2.9%
d 2
 
2.9%
r 2
 
2.9%
N 2
 
2.9%
Other values (21) 22
31.4%

verbatimSRS
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.364758image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row150.0 m
ValueCountFrequency (%)
150.0 1
50.0%
m 1
50.0%
2025-02-28T12:46:05.448083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
28.6%
1 1
14.3%
5 1
14.3%
. 1
14.3%
1
14.3%
m 1
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2
28.6%
1 1
14.3%
5 1
14.3%
. 1
14.3%
1
14.3%
m 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2
28.6%
1 1
14.3%
5 1
14.3%
. 1
14.3%
1
14.3%
m 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2
28.6%
1 1
14.3%
5 1
14.3%
. 1
14.3%
1
14.3%
m 1
14.3%

geologicalContextID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.476002image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row15.1
ValueCountFrequency (%)
15.1 1
100.0%
2025-02-28T12:46:05.563001image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
. 1
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
. 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
. 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
. 1
25.0%

earliestEonOrLowestEonothem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.595526image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row98.46667
ValueCountFrequency (%)
98.46667 1
100.0%
2025-02-28T12:46:05.687383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 3
37.5%
9 1
 
12.5%
8 1
 
12.5%
. 1
 
12.5%
4 1
 
12.5%
7 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
6 3
37.5%
9 1
 
12.5%
8 1
 
12.5%
. 1
 
12.5%
4 1
 
12.5%
7 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
6 3
37.5%
9 1
 
12.5%
8 1
 
12.5%
. 1
 
12.5%
4 1
 
12.5%
7 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
6 3
37.5%
9 1
 
12.5%
8 1
 
12.5%
. 1
 
12.5%
4 1
 
12.5%
7 1
 
12.5%

latestEonOrHighestEonothem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.719007image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowWGS84
ValueCountFrequency (%)
wgs84 1
100.0%
2025-02-28T12:46:05.808543image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 1
20.0%
G 1
20.0%
S 1
20.0%
8 1
20.0%
4 1
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
W 1
20.0%
G 1
20.0%
S 1
20.0%
8 1
20.0%
4 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
W 1
20.0%
G 1
20.0%
S 1
20.0%
8 1
20.0%
4 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
W 1
20.0%
G 1
20.0%
S 1
20.0%
8 1
20.0%
4 1
20.0%
Distinct2
Distinct (%)100.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.843037image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length9.5
Mean length9.5
Min length8

Characters and Unicode

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

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowBakker S
2nd rowPedersen TM
ValueCountFrequency (%)
bakker 1
25.0%
s 1
25.0%
pedersen 1
25.0%
tm 1
25.0%
2025-02-28T12:46:05.940141image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4
21.1%
k 2
10.5%
r 2
10.5%
2
10.5%
B 1
 
5.3%
a 1
 
5.3%
S 1
 
5.3%
P 1
 
5.3%
d 1
 
5.3%
s 1
 
5.3%
Other values (3) 3
15.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 4
21.1%
k 2
10.5%
r 2
10.5%
2
10.5%
B 1
 
5.3%
a 1
 
5.3%
S 1
 
5.3%
P 1
 
5.3%
d 1
 
5.3%
s 1
 
5.3%
Other values (3) 3
15.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 4
21.1%
k 2
10.5%
r 2
10.5%
2
10.5%
B 1
 
5.3%
a 1
 
5.3%
S 1
 
5.3%
P 1
 
5.3%
d 1
 
5.3%
s 1
 
5.3%
Other values (3) 3
15.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 4
21.1%
k 2
10.5%
r 2
10.5%
2
10.5%
B 1
 
5.3%
a 1
 
5.3%
S 1
 
5.3%
P 1
 
5.3%
d 1
 
5.3%
s 1
 
5.3%
Other values (3) 3
15.8%

bed
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:05.974921image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length39
Median length32.5
Mean length32.5
Min length26

Characters and Unicode

Total characters65
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

Unique2 ?
Unique (%)100.0%

Sample

1st rowPhyscia caesia (Hoffm.) Hampe ex Fürnr.
2nd rowPaullinia elegans Cambess.
ValueCountFrequency (%)
physcia 1
11.1%
caesia 1
11.1%
hoffm 1
11.1%
hampe 1
11.1%
ex 1
11.1%
fürnr 1
11.1%
paullinia 1
11.1%
elegans 1
11.1%
cambess 1
11.1%
2025-02-28T12:46:06.070178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8
 
12.3%
7
 
10.8%
e 6
 
9.2%
s 5
 
7.7%
i 4
 
6.2%
m 3
 
4.6%
l 3
 
4.6%
n 3
 
4.6%
. 3
 
4.6%
f 2
 
3.1%
Other values (17) 21
32.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 65
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 8
 
12.3%
7
 
10.8%
e 6
 
9.2%
s 5
 
7.7%
i 4
 
6.2%
m 3
 
4.6%
l 3
 
4.6%
n 3
 
4.6%
. 3
 
4.6%
f 2
 
3.1%
Other values (17) 21
32.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 65
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 8
 
12.3%
7
 
10.8%
e 6
 
9.2%
s 5
 
7.7%
i 4
 
6.2%
m 3
 
4.6%
l 3
 
4.6%
n 3
 
4.6%
. 3
 
4.6%
f 2
 
3.1%
Other values (17) 21
32.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 65
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 8
 
12.3%
7
 
10.8%
e 6
 
9.2%
s 5
 
7.7%
i 4
 
6.2%
m 3
 
4.6%
l 3
 
4.6%
n 3
 
4.6%
. 3
 
4.6%
f 2
 
3.1%
Other values (17) 21
32.3%

typeStatus
Text

Missing 

Distinct14
Distinct (%)< 0.1%
Missing4932431
Missing (%)98.3%
Memory size38.3 MiB
2025-02-28T12:46:06.103396image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length7
Mean length6.994413344
Min length4

Characters and Unicode

Total characters610969
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowholotype
2nd rowisotype
3rd rowtype
4th rowlectotype
5th rowtype
ValueCountFrequency (%)
isotype 39000
44.6%
holotype 14456
 
16.5%
type 14207
 
16.3%
syntype 8771
 
10.0%
lectotype 3004
 
3.4%
paratype 2913
 
3.3%
isolectotype 2782
 
3.2%
isosyntype 1268
 
1.5%
neotype 578
 
0.7%
isoneotype 275
 
0.3%
Other values (4) 97
 
0.1%
2025-02-28T12:46:06.193005image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y 97390
15.9%
e 94065
15.4%
t 93181
15.3%
p 90361
14.8%
o 78963
12.9%
s 53385
8.7%
i 43399
7.1%
l 20264
 
3.3%
h 14456
 
2.4%
n 10892
 
1.8%
Other values (3) 14613
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 610969
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
y 97390
15.9%
e 94065
15.4%
t 93181
15.3%
p 90361
14.8%
o 78963
12.9%
s 53385
8.7%
i 43399
7.1%
l 20264
 
3.3%
h 14456
 
2.4%
n 10892
 
1.8%
Other values (3) 14613
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 610969
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
y 97390
15.9%
e 94065
15.4%
t 93181
15.3%
p 90361
14.8%
o 78963
12.9%
s 53385
8.7%
i 43399
7.1%
l 20264
 
3.3%
h 14456
 
2.4%
n 10892
 
1.8%
Other values (3) 14613
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 610969
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
y 97390
15.9%
e 94065
15.4%
t 93181
15.3%
p 90361
14.8%
o 78963
12.9%
s 53385
8.7%
i 43399
7.1%
l 20264
 
3.3%
h 14456
 
2.4%
n 10892
 
1.8%
Other values (3) 14613
 
2.4%

identifiedBy
Text

Missing 

Distinct12783
Distinct (%)1.5%
Missing4152104
Missing (%)82.7%
Memory size38.3 MiB
2025-02-28T12:46:06.326981image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length72
Median length54
Mean length11.4119028
Min length1

Characters and Unicode

Total characters9901857
Distinct characters109
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

Unique4702 ?
Unique (%)0.5%

Sample

1st rowWood GHS
2nd rowSteenis CGGJ van
3rd rowPereira JT; Wong KM
4th rowAshton PS
5th rowNooteboom HP
ValueCountFrequency (%)
van 89759
 
4.4%
de 47967
 
2.4%
der 26776
 
1.3%
p 26721
 
1.3%
a 25734
 
1.3%
maas 25086
 
1.2%
j 24227
 
1.2%
jongkind 21969
 
1.1%
cch 21965
 
1.1%
d 21201
 
1.0%
Other values (9388) 1699526
83.7%
2025-02-28T12:46:06.559697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1163257
 
11.7%
e 898443
 
9.1%
n 642275
 
6.5%
a 603392
 
6.1%
r 456478
 
4.6%
o 414361
 
4.2%
J 355793
 
3.6%
i 334328
 
3.4%
s 326378
 
3.3%
l 308100
 
3.1%
Other values (99) 4399052
44.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9901857
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1163257
 
11.7%
e 898443
 
9.1%
n 642275
 
6.5%
a 603392
 
6.1%
r 456478
 
4.6%
o 414361
 
4.2%
J 355793
 
3.6%
i 334328
 
3.4%
s 326378
 
3.3%
l 308100
 
3.1%
Other values (99) 4399052
44.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9901857
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1163257
 
11.7%
e 898443
 
9.1%
n 642275
 
6.5%
a 603392
 
6.1%
r 456478
 
4.6%
o 414361
 
4.2%
J 355793
 
3.6%
i 334328
 
3.4%
s 326378
 
3.3%
l 308100
 
3.1%
Other values (99) 4399052
44.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9901857
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1163257
 
11.7%
e 898443
 
9.1%
n 642275
 
6.5%
a 603392
 
6.1%
r 456478
 
4.6%
o 414361
 
4.2%
J 355793
 
3.6%
i 334328
 
3.4%
s 326378
 
3.3%
l 308100
 
3.1%
Other values (99) 4399052
44.4%

dateIdentified
Text

Missing 

Distinct16460
Distinct (%)3.8%
Missing4581006
Missing (%)91.3%
Memory size38.3 MiB
2025-02-28T12:46:06.716498image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length10
Mean length10.00016409
Min length10

Characters and Unicode

Total characters4387832
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

Unique4674 ?
Unique (%)1.1%

Sample

1st row1956/11/22
2nd row1995/09/27
3rd row1968/07/01
4th row1972/06/01
5th row1957/01/18
ValueCountFrequency (%)
1955/03/01 2137
 
0.5%
1972/06/01 2001
 
0.5%
1968/07/01 1800
 
0.4%
2001/12/01 1724
 
0.4%
1995/10/01 1545
 
0.4%
1979/08/01 1473
 
0.3%
1989/08/01 1409
 
0.3%
2000/06/01 1393
 
0.3%
2000/01/01 1358
 
0.3%
2000/12/01 1344
 
0.3%
Other values (16450) 422592
96.3%
2025-02-28T12:46:06.907760image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1100102
25.1%
1 886397
20.2%
/ 877548
20.0%
2 396674
 
9.0%
9 393348
 
9.0%
8 143873
 
3.3%
7 131859
 
3.0%
5 122219
 
2.8%
6 121562
 
2.8%
3 110818
 
2.5%
Other values (25) 103432
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4387832
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1100102
25.1%
1 886397
20.2%
/ 877548
20.0%
2 396674
 
9.0%
9 393348
 
9.0%
8 143873
 
3.3%
7 131859
 
3.0%
5 122219
 
2.8%
6 121562
 
2.8%
3 110818
 
2.5%
Other values (25) 103432
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4387832
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1100102
25.1%
1 886397
20.2%
/ 877548
20.0%
2 396674
 
9.0%
9 393348
 
9.0%
8 143873
 
3.3%
7 131859
 
3.0%
5 122219
 
2.8%
6 121562
 
2.8%
3 110818
 
2.5%
Other values (25) 103432
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4387832
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1100102
25.1%
1 886397
20.2%
/ 877548
20.0%
2 396674
 
9.0%
9 393348
 
9.0%
8 143873
 
3.3%
7 131859
 
3.0%
5 122219
 
2.8%
6 121562
 
2.8%
3 110818
 
2.5%
Other values (25) 103432
 
2.4%
Distinct2
Distinct (%)100.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:06.960334image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6
Min length5

Characters and Unicode

Total characters12
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowFungi
2nd rowPlantae
ValueCountFrequency (%)
fungi 1
50.0%
plantae 1
50.0%
2025-02-28T12:46:07.070952image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2
16.7%
a 2
16.7%
F 1
8.3%
u 1
8.3%
g 1
8.3%
i 1
8.3%
P 1
8.3%
l 1
8.3%
t 1
8.3%
e 1
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 2
16.7%
a 2
16.7%
F 1
8.3%
u 1
8.3%
g 1
8.3%
i 1
8.3%
P 1
8.3%
l 1
8.3%
t 1
8.3%
e 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 2
16.7%
a 2
16.7%
F 1
8.3%
u 1
8.3%
g 1
8.3%
i 1
8.3%
P 1
8.3%
l 1
8.3%
t 1
8.3%
e 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 2
16.7%
a 2
16.7%
F 1
8.3%
u 1
8.3%
g 1
8.3%
i 1
8.3%
P 1
8.3%
l 1
8.3%
t 1
8.3%
e 1
8.3%

identificationVerificationStatus
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:07.105526image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters16
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowFungi-Ascomycota
ValueCountFrequency (%)
fungi-ascomycota 1
100.0%
2025-02-28T12:46:07.221944image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 2
12.5%
o 2
12.5%
F 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%
g 1
 
6.2%
i 1
 
6.2%
- 1
 
6.2%
A 1
 
6.2%
s 1
 
6.2%
Other values (4) 4
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 2
12.5%
o 2
12.5%
F 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%
g 1
 
6.2%
i 1
 
6.2%
- 1
 
6.2%
A 1
 
6.2%
s 1
 
6.2%
Other values (4) 4
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 2
12.5%
o 2
12.5%
F 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%
g 1
 
6.2%
i 1
 
6.2%
- 1
 
6.2%
A 1
 
6.2%
s 1
 
6.2%
Other values (4) 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 2
12.5%
o 2
12.5%
F 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%
g 1
 
6.2%
i 1
 
6.2%
- 1
 
6.2%
A 1
 
6.2%
s 1
 
6.2%
Other values (4) 4
25.0%

identificationRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:07.261911image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters24
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowLichenes-Lecanoromycetes
ValueCountFrequency (%)
lichenes-lecanoromycetes 1
100.0%
2025-02-28T12:46:07.350059image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5
20.8%
c 3
12.5%
L 2
 
8.3%
n 2
 
8.3%
s 2
 
8.3%
o 2
 
8.3%
i 1
 
4.2%
h 1
 
4.2%
- 1
 
4.2%
a 1
 
4.2%
Other values (4) 4
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5
20.8%
c 3
12.5%
L 2
 
8.3%
n 2
 
8.3%
s 2
 
8.3%
o 2
 
8.3%
i 1
 
4.2%
h 1
 
4.2%
- 1
 
4.2%
a 1
 
4.2%
Other values (4) 4
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5
20.8%
c 3
12.5%
L 2
 
8.3%
n 2
 
8.3%
s 2
 
8.3%
o 2
 
8.3%
i 1
 
4.2%
h 1
 
4.2%
- 1
 
4.2%
a 1
 
4.2%
Other values (4) 4
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5
20.8%
c 3
12.5%
L 2
 
8.3%
n 2
 
8.3%
s 2
 
8.3%
o 2
 
8.3%
i 1
 
4.2%
h 1
 
4.2%
- 1
 
4.2%
a 1
 
4.2%
Other values (4) 4
16.7%

taxonID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:07.383608image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters20
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

Unique2 ?
Unique (%)100.0%

Sample

1st rowCaliciales
2nd rowSapindales
ValueCountFrequency (%)
caliciales 1
50.0%
sapindales 1
50.0%
2025-02-28T12:46:07.471047image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
20.0%
l 3
15.0%
i 3
15.0%
e 2
10.0%
s 2
10.0%
C 1
 
5.0%
c 1
 
5.0%
S 1
 
5.0%
p 1
 
5.0%
n 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4
20.0%
l 3
15.0%
i 3
15.0%
e 2
10.0%
s 2
10.0%
C 1
 
5.0%
c 1
 
5.0%
S 1
 
5.0%
p 1
 
5.0%
n 1
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4
20.0%
l 3
15.0%
i 3
15.0%
e 2
10.0%
s 2
10.0%
C 1
 
5.0%
c 1
 
5.0%
S 1
 
5.0%
p 1
 
5.0%
n 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4
20.0%
l 3
15.0%
i 3
15.0%
e 2
10.0%
s 2
10.0%
C 1
 
5.0%
c 1
 
5.0%
S 1
 
5.0%
p 1
 
5.0%
n 1
 
5.0%

acceptedNameUsageID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:07.500471image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length15.5
Mean length15.5
Min length11

Characters and Unicode

Total characters31
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

Unique2 ?
Unique (%)100.0%

Sample

1st rowLichenes-Physciaceae
2nd rowSapindaceae
ValueCountFrequency (%)
lichenes-physciaceae 1
50.0%
sapindaceae 1
50.0%
2025-02-28T12:46:07.587053image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6
19.4%
a 5
16.1%
c 4
12.9%
i 3
9.7%
h 2
 
6.5%
n 2
 
6.5%
s 2
 
6.5%
L 1
 
3.2%
- 1
 
3.2%
P 1
 
3.2%
Other values (4) 4
12.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 6
19.4%
a 5
16.1%
c 4
12.9%
i 3
9.7%
h 2
 
6.5%
n 2
 
6.5%
s 2
 
6.5%
L 1
 
3.2%
- 1
 
3.2%
P 1
 
3.2%
Other values (4) 4
12.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 6
19.4%
a 5
16.1%
c 4
12.9%
i 3
9.7%
h 2
 
6.5%
n 2
 
6.5%
s 2
 
6.5%
L 1
 
3.2%
- 1
 
3.2%
P 1
 
3.2%
Other values (4) 4
12.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 6
19.4%
a 5
16.1%
c 4
12.9%
i 3
9.7%
h 2
 
6.5%
n 2
 
6.5%
s 2
 
6.5%
L 1
 
3.2%
- 1
 
3.2%
P 1
 
3.2%
Other values (4) 4
12.9%

namePublishedInID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:07.617236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8
Min length7

Characters and Unicode

Total characters16
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowPhyscia
2nd rowPaullinia
ValueCountFrequency (%)
physcia 1
50.0%
paullinia 1
50.0%
2025-02-28T12:46:07.714525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 3
18.8%
a 3
18.8%
P 2
12.5%
l 2
12.5%
h 1
 
6.2%
y 1
 
6.2%
s 1
 
6.2%
c 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 3
18.8%
a 3
18.8%
P 2
12.5%
l 2
12.5%
h 1
 
6.2%
y 1
 
6.2%
s 1
 
6.2%
c 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 3
18.8%
a 3
18.8%
P 2
12.5%
l 2
12.5%
h 1
 
6.2%
y 1
 
6.2%
s 1
 
6.2%
c 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 3
18.8%
a 3
18.8%
P 2
12.5%
l 2
12.5%
h 1
 
6.2%
y 1
 
6.2%
s 1
 
6.2%
c 1
 
6.2%
u 1
 
6.2%
n 1
 
6.2%
Distinct376061
Distinct (%)7.5%
Missing224
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:07.932362image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length105
Median length90
Mean length28.47094744
Min length2

Characters and Unicode

Total characters142911572
Distinct characters132
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133003 ?
Unique (%)2.6%

Sample

1st rowPlantago psyllium L.
2nd rowShorea platycarpa Heim
3rd rowPlantago psyllium L.
4th rowAgathis borneensis Warb.
5th rowPlantago psyllium L.
ValueCountFrequency (%)
l 1223482
 
6.8%
361839
 
2.0%
ex 258858
 
1.4%
var 234755
 
1.3%
blume 178015
 
1.0%
subsp 159935
 
0.9%
dc 110044
 
0.6%
benth 87621
 
0.5%
indet 79377
 
0.4%
miq 74956
 
0.4%
Other values (123549) 15222043
84.6%
2025-02-28T12:46:08.214929image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 13264086
 
9.3%
12971975
 
9.1%
i 10267217
 
7.2%
e 8900034
 
6.2%
r 8009635
 
5.6%
l 7115999
 
5.0%
s 6980933
 
4.9%
o 6762853
 
4.7%
n 6461888
 
4.5%
. 6448256
 
4.5%
Other values (122) 55728696
39.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 142911572
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 13264086
 
9.3%
12971975
 
9.1%
i 10267217
 
7.2%
e 8900034
 
6.2%
r 8009635
 
5.6%
l 7115999
 
5.0%
s 6980933
 
4.9%
o 6762853
 
4.7%
n 6461888
 
4.5%
. 6448256
 
4.5%
Other values (122) 55728696
39.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 142911572
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 13264086
 
9.3%
12971975
 
9.1%
i 10267217
 
7.2%
e 8900034
 
6.2%
r 8009635
 
5.6%
l 7115999
 
5.0%
s 6980933
 
4.9%
o 6762853
 
4.7%
n 6461888
 
4.5%
. 6448256
 
4.5%
Other values (122) 55728696
39.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 142911572
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 13264086
 
9.3%
12971975
 
9.1%
i 10267217
 
7.2%
e 8900034
 
6.2%
r 8009635
 
5.6%
l 7115999
 
5.0%
s 6980933
 
4.9%
o 6762853
 
4.7%
n 6461888
 
4.5%
. 6448256
 
4.5%
Other values (122) 55728696
39.0%

parentNameUsage
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:08.252956image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

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

Characters and Unicode

Total characters13
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowcaesia
2nd rowelegans
ValueCountFrequency (%)
caesia 1
50.0%
elegans 1
50.0%
2025-02-28T12:46:08.338918image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3
23.1%
e 3
23.1%
s 2
15.4%
c 1
 
7.7%
i 1
 
7.7%
l 1
 
7.7%
g 1
 
7.7%
n 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3
23.1%
e 3
23.1%
s 2
15.4%
c 1
 
7.7%
i 1
 
7.7%
l 1
 
7.7%
g 1
 
7.7%
n 1
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3
23.1%
e 3
23.1%
s 2
15.4%
c 1
 
7.7%
i 1
 
7.7%
l 1
 
7.7%
g 1
 
7.7%
n 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3
23.1%
e 3
23.1%
s 2
15.4%
c 1
 
7.7%
i 1
 
7.7%
l 1
 
7.7%
g 1
 
7.7%
n 1
 
7.7%

namePublishedIn
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing5019780
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:08.368374image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
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 rowspecies
2nd rowspecies
ValueCountFrequency (%)
species 2
100.0%
2025-02-28T12:46:08.445471image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 4
28.6%
e 4
28.6%
p 2
14.3%
c 2
14.3%
i 2
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 4
28.6%
e 4
28.6%
p 2
14.3%
c 2
14.3%
i 2
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 4
28.6%
e 4
28.6%
p 2
14.3%
c 2
14.3%
i 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 4
28.6%
e 4
28.6%
p 2
14.3%
c 2
14.3%
i 2
14.3%
Distinct1414
Distinct (%)< 0.1%
Missing488
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:08.506633image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length79
Median length68
Mean length29.82403601
Min length8

Characters and Unicode

Total characters149695605
Distinct characters60
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

Unique116 ?
Unique (%)< 0.1%

Sample

1st rowPlantae|Lamiales|Plantaginaceae
2nd rowPlantae|Malvales|Dipterocarpaceae
3rd rowPlantae|Lamiales|Plantaginaceae
4th rowPlantae|Cupressales|Araucariaceae
5th rowPlantae|Lamiales|Plantaginaceae
ValueCountFrequency (%)
plantae|fabales|fabaceae 308028
 
6.1%
plantae|asterales|asteraceae 302803
 
6.0%
plantae|poales|poaceae 281272
 
5.6%
plantae|gentianales|rubiaceae 189877
 
3.8%
plantae|poales|cyperaceae 141951
 
2.8%
plantae|lamiales|lamiaceae 116077
 
2.3%
plantae|rosales|rosaceae 114928
 
2.3%
plantae|asparagales|orchidaceae 94113
 
1.9%
plantae|malpighiales|euphorbiaceae 91199
 
1.8%
plantae|malvales|malvaceae 80345
 
1.6%
Other values (1415) 3309436
65.8%
2025-02-28T12:46:08.661716image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 30545157
20.4%
e 22993015
15.4%
l 13087306
8.7%
| 10172681
 
6.8%
n 8204441
 
5.5%
t 7522789
 
5.0%
s 7327084
 
4.9%
c 7056672
 
4.7%
P 6334479
 
4.2%
i 5649209
 
3.8%
Other values (50) 30802772
20.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 149695605
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 30545157
20.4%
e 22993015
15.4%
l 13087306
8.7%
| 10172681
 
6.8%
n 8204441
 
5.5%
t 7522789
 
5.0%
s 7327084
 
4.9%
c 7056672
 
4.7%
P 6334479
 
4.2%
i 5649209
 
3.8%
Other values (50) 30802772
20.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 149695605
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 30545157
20.4%
e 22993015
15.4%
l 13087306
8.7%
| 10172681
 
6.8%
n 8204441
 
5.5%
t 7522789
 
5.0%
s 7327084
 
4.9%
c 7056672
 
4.7%
P 6334479
 
4.2%
i 5649209
 
3.8%
Other values (50) 30802772
20.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 149695605
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 30545157
20.4%
e 22993015
15.4%
l 13087306
8.7%
| 10172681
 
6.8%
n 8204441
 
5.5%
t 7522789
 
5.0%
s 7327084
 
4.9%
c 7056672
 
4.7%
P 6334479
 
4.2%
i 5649209
 
3.8%
Other values (50) 30802772
20.6%
Distinct5
Distinct (%)< 0.1%
Missing496
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:08.703777image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.982224563
Min length5

Characters and Unicode

Total characters35045782
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlantae
2nd rowPlantae
3rd rowPlantae
4th rowPlantae
5th rowPlantae
ValueCountFrequency (%)
plantae 4861934
96.9%
fungi 104468
 
2.1%
chromista 37916
 
0.8%
eubacteria 14458
 
0.3%
protozoa 510
 
< 0.1%
2025-02-28T12:46:08.791236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 9791210
27.9%
n 4966402
14.2%
t 4914818
14.0%
e 4876392
13.9%
P 4862444
13.9%
l 4861934
13.9%
i 156842
 
0.4%
u 118926
 
0.3%
F 104468
 
0.3%
g 104468
 
0.3%
Other values (10) 287878
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 35045782
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 9791210
27.9%
n 4966402
14.2%
t 4914818
14.0%
e 4876392
13.9%
P 4862444
13.9%
l 4861934
13.9%
i 156842
 
0.4%
u 118926
 
0.3%
F 104468
 
0.3%
g 104468
 
0.3%
Other values (10) 287878
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 35045782
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 9791210
27.9%
n 4966402
14.2%
t 4914818
14.0%
e 4876392
13.9%
P 4862444
13.9%
l 4861934
13.9%
i 156842
 
0.4%
u 118926
 
0.3%
F 104468
 
0.3%
g 104468
 
0.3%
Other values (10) 287878
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 35045782
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 9791210
27.9%
n 4966402
14.2%
t 4914818
14.0%
e 4876392
13.9%
P 4862444
13.9%
l 4861934
13.9%
i 156842
 
0.4%
u 118926
 
0.3%
F 104468
 
0.3%
g 104468
 
0.3%
Other values (10) 287878
 
0.8%

phylum
Text

Missing 

Distinct29
Distinct (%)< 0.1%
Missing4742156
Missing (%)94.5%
Memory size38.3 MiB
2025-02-28T12:46:08.823792image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length22
Mean length13.09837695
Min length3

Characters and Unicode

Total characters3636450
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowFungi-Ascomycota
2nd rowFungi-Ascomycota
3rd rowFungi-Ascomycota
4th rowFungi-Ascomycota
5th rowFungi-Ascomycota
ValueCountFrequency (%)
rhodophyta 69790
25.1%
fungi-basidiomycota 52456
18.9%
fungi-ascomycota 45602
16.4%
chlorophyta 45198
16.3%
ochrophyta 32323
11.6%
cyanobacteria 14344
 
5.2%
charophyta 11679
 
4.2%
bacillariophyta 5278
 
1.9%
amoebozoa 445
 
0.2%
oomycota 248
 
0.1%
Other values (19) 263
 
0.1%
2025-02-28T12:46:08.926699image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 492110
13.5%
a 381066
 
10.5%
h 323307
 
8.9%
t 277145
 
7.6%
y 277061
 
7.6%
i 228102
 
6.3%
c 196019
 
5.4%
p 164308
 
4.5%
d 122285
 
3.4%
n 112587
 
3.1%
Other values (28) 1062460
29.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3636450
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 492110
13.5%
a 381066
 
10.5%
h 323307
 
8.9%
t 277145
 
7.6%
y 277061
 
7.6%
i 228102
 
6.3%
c 196019
 
5.4%
p 164308
 
4.5%
d 122285
 
3.4%
n 112587
 
3.1%
Other values (28) 1062460
29.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3636450
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 492110
13.5%
a 381066
 
10.5%
h 323307
 
8.9%
t 277145
 
7.6%
y 277061
 
7.6%
i 228102
 
6.3%
c 196019
 
5.4%
p 164308
 
4.5%
d 122285
 
3.4%
n 112587
 
3.1%
Other values (28) 1062460
29.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3636450
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 492110
13.5%
a 381066
 
10.5%
h 323307
 
8.9%
t 277145
 
7.6%
y 277061
 
7.6%
i 228102
 
6.3%
c 196019
 
5.4%
p 164308
 
4.5%
d 122285
 
3.4%
n 112587
 
3.1%
Other values (28) 1062460
29.2%

class
Text

Missing 

Distinct91
Distinct (%)< 0.1%
Missing4741605
Missing (%)94.5%
Memory size38.3 MiB
2025-02-28T12:46:08.966539image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length26
Mean length15.96505103
Min length6

Characters and Unicode

Total characters4441110
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

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowLichenes-
2nd rowLichenes-
3rd rowLichenes-
4th rowLichenes-
5th rowLichenes-
ValueCountFrequency (%)
florideophyceae 65290
23.5%
fungi-agaricomycetes 48215
17.3%
phaeophyceae 30367
10.9%
ulvophyceae 29708
10.7%
lichenes-lecanoromycetes 26216
9.4%
chlorophyceae 13735
 
4.9%
cyanophyceae 13043
 
4.7%
charophyceae 7130
 
2.6%
fungi-pezizomycetes 6007
 
2.2%
lichenes 5353
 
1.9%
Other values (82) 33337
12.0%
2025-02-28T12:46:09.070508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 745781
16.8%
o 397801
 
9.0%
c 389649
 
8.8%
a 323750
 
7.3%
y 285919
 
6.4%
h 262782
 
5.9%
i 255647
 
5.8%
r 180931
 
4.1%
p 175103
 
3.9%
n 153502
 
3.5%
Other values (33) 1270245
28.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4441110
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 745781
16.8%
o 397801
 
9.0%
c 389649
 
8.8%
a 323750
 
7.3%
y 285919
 
6.4%
h 262782
 
5.9%
i 255647
 
5.8%
r 180931
 
4.1%
p 175103
 
3.9%
n 153502
 
3.5%
Other values (33) 1270245
28.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4441110
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 745781
16.8%
o 397801
 
9.0%
c 389649
 
8.8%
a 323750
 
7.3%
y 285919
 
6.4%
h 262782
 
5.9%
i 255647
 
5.8%
r 180931
 
4.1%
p 175103
 
3.9%
n 153502
 
3.5%
Other values (33) 1270245
28.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4441110
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 745781
16.8%
o 397801
 
9.0%
c 389649
 
8.8%
a 323750
 
7.3%
y 285919
 
6.4%
h 262782
 
5.9%
i 255647
 
5.8%
r 180931
 
4.1%
p 175103
 
3.9%
n 153502
 
3.5%
Other values (33) 1270245
28.6%

order
Text

Missing 

Distinct380
Distinct (%)< 0.1%
Missing143842
Missing (%)2.9%
Memory size38.3 MiB
2025-02-28T12:46:09.197237image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length18
Mean length9.414907279
Min length1

Characters and Unicode

Total characters45906523
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

Unique34 ?
Unique (%)< 0.1%

Sample

1st rowLamiales
2nd rowMalvales
3rd rowLamiales
4th rowCupressales
5th rowLamiales
ValueCountFrequency (%)
poales 469510
 
9.6%
malpighiales 338062
 
6.9%
asterales 336633
 
6.9%
fabales 327880
 
6.7%
lamiales 320256
 
6.6%
gentianales 310878
 
6.4%
rosales 239690
 
4.9%
ericales 188588
 
3.9%
caryophyllales 183655
 
3.8%
sapindales 166440
 
3.4%
Other values (371) 1994349
40.9%
2025-02-28T12:46:09.399509image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 7993736
17.4%
l 6487296
14.1%
s 6014249
13.1%
e 5900801
12.9%
i 2811732
 
6.1%
o 1694688
 
3.7%
r 1659025
 
3.6%
n 1397350
 
3.0%
p 1231222
 
2.7%
t 1086092
 
2.4%
Other values (39) 9630332
21.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 45906523
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 7993736
17.4%
l 6487296
14.1%
s 6014249
13.1%
e 5900801
12.9%
i 2811732
 
6.1%
o 1694688
 
3.7%
r 1659025
 
3.6%
n 1397350
 
3.0%
p 1231222
 
2.7%
t 1086092
 
2.4%
Other values (39) 9630332
21.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 45906523
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 7993736
17.4%
l 6487296
14.1%
s 6014249
13.1%
e 5900801
12.9%
i 2811732
 
6.1%
o 1694688
 
3.7%
r 1659025
 
3.6%
n 1397350
 
3.0%
p 1231222
 
2.7%
t 1086092
 
2.4%
Other values (39) 9630332
21.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 45906523
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 7993736
17.4%
l 6487296
14.1%
s 6014249
13.1%
e 5900801
12.9%
i 2811732
 
6.1%
o 1694688
 
3.7%
r 1659025
 
3.6%
n 1397350
 
3.0%
p 1231222
 
2.7%
t 1086092
 
2.4%
Other values (39) 9630332
21.0%

family
Text

Distinct1406
Distinct (%)< 0.1%
Missing1212
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:09.529998image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length25
Mean length10.7858368
Min length1

Characters and Unicode

Total characters54129477
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)< 0.1%

Sample

1st rowPlantaginaceae
2nd rowDipterocarpaceae
3rd rowPlantaginaceae
4th rowAraucariaceae
5th rowPlantaginaceae
ValueCountFrequency (%)
fabaceae 308028
 
6.1%
asteraceae 302803
 
6.0%
poaceae 281272
 
5.6%
rubiaceae 189877
 
3.8%
cyperaceae 141951
 
2.8%
lamiaceae 116077
 
2.3%
rosaceae 114928
 
2.3%
orchidaceae 94113
 
1.9%
euphorbiaceae 91199
 
1.8%
malvaceae 80345
 
1.6%
Other values (1398) 3308484
65.8%
2025-02-28T12:46:09.721578image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 12436459
23.0%
e 11470038
21.2%
c 6036012
11.2%
i 2424988
 
4.5%
r 2326369
 
4.3%
o 2005164
 
3.7%
n 1687186
 
3.1%
l 1617349
 
3.0%
t 1411236
 
2.6%
s 1142952
 
2.1%
Other values (46) 11571724
21.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 54129477
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 12436459
23.0%
e 11470038
21.2%
c 6036012
11.2%
i 2424988
 
4.5%
r 2326369
 
4.3%
o 2005164
 
3.7%
n 1687186
 
3.1%
l 1617349
 
3.0%
t 1411236
 
2.6%
s 1142952
 
2.1%
Other values (46) 11571724
21.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 54129477
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 12436459
23.0%
e 11470038
21.2%
c 6036012
11.2%
i 2424988
 
4.5%
r 2326369
 
4.3%
o 2005164
 
3.7%
n 1687186
 
3.1%
l 1617349
 
3.0%
t 1411236
 
2.6%
s 1142952
 
2.1%
Other values (46) 11571724
21.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 54129477
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 12436459
23.0%
e 11470038
21.2%
c 6036012
11.2%
i 2424988
 
4.5%
r 2326369
 
4.3%
o 2005164
 
3.7%
n 1687186
 
3.1%
l 1617349
 
3.0%
t 1411236
 
2.6%
s 1142952
 
2.1%
Other values (46) 11571724
21.4%

genus
Text

Distinct20571
Distinct (%)0.4%
Missing224
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:09.877303image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length20
Mean length8.494074976
Min length2

Characters and Unicode

Total characters42636502
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

Unique3021 ?
Unique (%)0.1%

Sample

1st rowPlantago
2nd rowShorea
3rd rowPlantago
4th rowAgathis
5th rowPlantago
ValueCountFrequency (%)
indet 79377
 
1.6%
carex 59786
 
1.2%
ficus 43081
 
0.9%
rubus 36824
 
0.7%
taraxacum 28101
 
0.6%
hieracium 27463
 
0.5%
cyperus 23409
 
0.5%
salix 21702
 
0.4%
ranunculus 21385
 
0.4%
euphorbia 19128
 
0.4%
Other values (20562) 4659308
92.8%
2025-02-28T12:46:10.091418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5220873
 
12.2%
i 3825339
 
9.0%
e 2967585
 
7.0%
r 2820232
 
6.6%
o 2777638
 
6.5%
u 2380535
 
5.6%
s 2337197
 
5.5%
n 2234005
 
5.2%
l 2185796
 
5.1%
t 1806151
 
4.2%
Other values (47) 14081151
33.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42636502
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5220873
 
12.2%
i 3825339
 
9.0%
e 2967585
 
7.0%
r 2820232
 
6.6%
o 2777638
 
6.5%
u 2380535
 
5.6%
s 2337197
 
5.5%
n 2234005
 
5.2%
l 2185796
 
5.1%
t 1806151
 
4.2%
Other values (47) 14081151
33.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42636502
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5220873
 
12.2%
i 3825339
 
9.0%
e 2967585
 
7.0%
r 2820232
 
6.6%
o 2777638
 
6.5%
u 2380535
 
5.6%
s 2337197
 
5.5%
n 2234005
 
5.2%
l 2185796
 
5.1%
t 1806151
 
4.2%
Other values (47) 14081151
33.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42636502
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5220873
 
12.2%
i 3825339
 
9.0%
e 2967585
 
7.0%
r 2820232
 
6.6%
o 2777638
 
6.5%
u 2380535
 
5.6%
s 2337197
 
5.5%
n 2234005
 
5.2%
l 2185796
 
5.1%
t 1806151
 
4.2%
Other values (47) 14081151
33.0%

subgenus
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:10.139641image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
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

Unique1 ?
Unique (%)100.0%

Sample

1st rowFimbristylis bisumbellata (Forssk.) Bubani
ValueCountFrequency (%)
fimbristylis 1
25.0%
bisumbellata 1
25.0%
forssk 1
25.0%
bubani 1
25.0%
2025-02-28T12:46:10.225564image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 5
11.9%
s 5
11.9%
b 4
 
9.5%
l 3
 
7.1%
a 3
 
7.1%
3
 
7.1%
F 2
 
4.8%
u 2
 
4.8%
t 2
 
4.8%
r 2
 
4.8%
Other values (10) 11
26.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 5
11.9%
s 5
11.9%
b 4
 
9.5%
l 3
 
7.1%
a 3
 
7.1%
3
 
7.1%
F 2
 
4.8%
u 2
 
4.8%
t 2
 
4.8%
r 2
 
4.8%
Other values (10) 11
26.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 5
11.9%
s 5
11.9%
b 4
 
9.5%
l 3
 
7.1%
a 3
 
7.1%
3
 
7.1%
F 2
 
4.8%
u 2
 
4.8%
t 2
 
4.8%
r 2
 
4.8%
Other values (10) 11
26.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 5
11.9%
s 5
11.9%
b 4
 
9.5%
l 3
 
7.1%
a 3
 
7.1%
3
 
7.1%
F 2
 
4.8%
u 2
 
4.8%
t 2
 
4.8%
r 2
 
4.8%
Other values (10) 11
26.2%

specificEpithet
Text

Missing 

Distinct74468
Distinct (%)1.6%
Missing420613
Missing (%)8.4%
Memory size38.3 MiB
2025-02-28T12:46:10.377910image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length37
Median length23
Mean length9.008492186
Min length2

Characters and Unicode

Total characters41431578
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

Unique19361 ?
Unique (%)0.4%

Sample

1st rowpsyllium
2nd rowplatycarpa
3rd rowpsyllium
4th rowborneensis
5th rowpsyllium
ValueCountFrequency (%)
vulgaris 23406
 
0.5%
palustris 17443
 
0.4%
arvensis 16770
 
0.4%
indica 15214
 
0.3%
officinalis 15193
 
0.3%
repens 13144
 
0.3%
maritima 12040
 
0.3%
alpina 11689
 
0.3%
tomentosa 11026
 
0.2%
montana 10538
 
0.2%
Other values (74399) 4454027
96.8%
2025-02-28T12:46:10.616827image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5674666
13.7%
i 4678236
11.3%
s 3099567
 
7.5%
e 2899018
 
7.0%
r 2736809
 
6.6%
l 2697840
 
6.5%
n 2575102
 
6.2%
u 2534175
 
6.1%
o 2373564
 
5.7%
t 2185739
 
5.3%
Other values (70) 9976862
24.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41431578
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5674666
13.7%
i 4678236
11.3%
s 3099567
 
7.5%
e 2899018
 
7.0%
r 2736809
 
6.6%
l 2697840
 
6.5%
n 2575102
 
6.2%
u 2534175
 
6.1%
o 2373564
 
5.7%
t 2185739
 
5.3%
Other values (70) 9976862
24.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41431578
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5674666
13.7%
i 4678236
11.3%
s 3099567
 
7.5%
e 2899018
 
7.0%
r 2736809
 
6.6%
l 2697840
 
6.5%
n 2575102
 
6.2%
u 2534175
 
6.1%
o 2373564
 
5.7%
t 2185739
 
5.3%
Other values (70) 9976862
24.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41431578
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5674666
13.7%
i 4678236
11.3%
s 3099567
 
7.5%
e 2899018
 
7.0%
r 2736809
 
6.6%
l 2697840
 
6.5%
n 2575102
 
6.2%
u 2534175
 
6.1%
o 2373564
 
5.7%
t 2185739
 
5.3%
Other values (70) 9976862
24.1%

infraspecificEpithet
Text

Missing 

Distinct25248
Distinct (%)6.1%
Missing4607995
Missing (%)91.8%
Memory size38.3 MiB
2025-02-28T12:46:10.758862image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length22
Mean length9.160235753
Min length1

Characters and Unicode

Total characters3772066
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9012 ?
Unique (%)2.2%

Sample

1st rowvelutinata
2nd rowmollis
3rd rowbract brevioribus
4th rowvrieseanum
5th rowcandollei
ValueCountFrequency (%)
angustifolia 2329
 
0.6%
glabra 2075
 
0.5%
pubescens 1991
 
0.5%
vulgaris 1822
 
0.4%
minor 1585
 
0.4%
major 1573
 
0.4%
album 1571
 
0.4%
montana 1497
 
0.4%
alba 1374
 
0.3%
typica 1327
 
0.3%
Other values (25081) 396330
95.9%
2025-02-28T12:46:10.966367image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 508708
13.5%
i 418276
11.1%
s 281997
 
7.5%
e 267917
 
7.1%
l 258041
 
6.8%
r 245993
 
6.5%
u 238357
 
6.3%
n 229721
 
6.1%
o 218434
 
5.8%
t 200564
 
5.3%
Other values (56) 904058
24.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3772066
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 508708
13.5%
i 418276
11.1%
s 281997
 
7.5%
e 267917
 
7.1%
l 258041
 
6.8%
r 245993
 
6.5%
u 238357
 
6.3%
n 229721
 
6.1%
o 218434
 
5.8%
t 200564
 
5.3%
Other values (56) 904058
24.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3772066
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 508708
13.5%
i 418276
11.1%
s 281997
 
7.5%
e 267917
 
7.1%
l 258041
 
6.8%
r 245993
 
6.5%
u 238357
 
6.3%
n 229721
 
6.1%
o 218434
 
5.8%
t 200564
 
5.3%
Other values (56) 904058
24.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3772066
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 508708
13.5%
i 418276
11.1%
s 281997
 
7.5%
e 267917
 
7.1%
l 258041
 
6.8%
r 245993
 
6.5%
u 238357
 
6.3%
n 229721
 
6.1%
o 218434
 
5.8%
t 200564
 
5.3%
Other values (56) 904058
24.0%
Distinct5
Distinct (%)< 0.1%
Missing224
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:11.013587image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.632937601
Min length2

Characters and Unicode

Total characters33294415
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 rowspecies
2nd rowspecies
3rd rowspecies
4th rowspecies
5th rowspecies
ValueCountFrequency (%)
species 4187406
83.4%
genus 420365
 
8.4%
var 230817
 
4.6%
subsp 148885
 
3.0%
f 32085
 
0.6%
2025-02-28T12:46:11.095116image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 9092947
27.3%
e 8795177
26.4%
p 4336291
13.0%
c 4187406
12.6%
i 4187406
12.6%
u 569250
 
1.7%
g 420365
 
1.3%
n 420365
 
1.3%
. 411787
 
1.2%
v 230817
 
0.7%
Other values (4) 642604
 
1.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33294415
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 9092947
27.3%
e 8795177
26.4%
p 4336291
13.0%
c 4187406
12.6%
i 4187406
12.6%
u 569250
 
1.7%
g 420365
 
1.3%
n 420365
 
1.3%
. 411787
 
1.2%
v 230817
 
0.7%
Other values (4) 642604
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33294415
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 9092947
27.3%
e 8795177
26.4%
p 4336291
13.0%
c 4187406
12.6%
i 4187406
12.6%
u 569250
 
1.7%
g 420365
 
1.3%
n 420365
 
1.3%
. 411787
 
1.2%
v 230817
 
0.7%
Other values (4) 642604
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33294415
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 9092947
27.3%
e 8795177
26.4%
p 4336291
13.0%
c 4187406
12.6%
i 4187406
12.6%
u 569250
 
1.7%
g 420365
 
1.3%
n 420365
 
1.3%
. 411787
 
1.2%
v 230817
 
0.7%
Other values (4) 642604
 
1.9%
Distinct65242
Distinct (%)1.4%
Missing355313
Missing (%)7.1%
Memory size38.3 MiB
2025-02-28T12:46:11.133954image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length77
Median length70
Mean length9.034118996
Min length1

Characters and Unicode

Total characters42139368
Distinct characters110
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

Unique15043 ?
Unique (%)0.3%

Sample

1st rowL.
2nd rowHeim
3rd rowL.
4th rowWarb.
5th rowL.
ValueCountFrequency (%)
l 1269845
 
17.0%
360987
 
4.8%
ex 256772
 
3.4%
blume 179897
 
2.4%
dc 108295
 
1.4%
benth 85823
 
1.1%
miq 72408
 
1.0%
r.br 65429
 
0.9%
willd 61790
 
0.8%
merr 59114
 
0.8%
Other values (13133) 4949569
66.3%
2025-02-28T12:46:11.252138image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5991115
 
14.2%
2806041
 
6.7%
e 2684191
 
6.4%
r 1931749
 
4.6%
l 1914225
 
4.5%
L 1600647
 
3.8%
a 1554933
 
3.7%
) 1480364
 
3.5%
( 1480364
 
3.5%
n 1371375
 
3.3%
Other values (100) 19324364
45.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42139368
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 5991115
 
14.2%
2806041
 
6.7%
e 2684191
 
6.4%
r 1931749
 
4.6%
l 1914225
 
4.5%
L 1600647
 
3.8%
a 1554933
 
3.7%
) 1480364
 
3.5%
( 1480364
 
3.5%
n 1371375
 
3.3%
Other values (100) 19324364
45.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42139368
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 5991115
 
14.2%
2806041
 
6.7%
e 2684191
 
6.4%
r 1931749
 
4.6%
l 1914225
 
4.5%
L 1600647
 
3.8%
a 1554933
 
3.7%
) 1480364
 
3.5%
( 1480364
 
3.5%
n 1371375
 
3.3%
Other values (100) 19324364
45.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42139368
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 5991115
 
14.2%
2806041
 
6.7%
e 2684191
 
6.4%
r 1931749
 
4.6%
l 1914225
 
4.5%
L 1600647
 
3.8%
a 1554933
 
3.7%
) 1480364
 
3.5%
( 1480364
 
3.5%
n 1371375
 
3.3%
Other values (100) 19324364
45.9%

vernacularName
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:11.281348image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPlantae
ValueCountFrequency (%)
plantae 1
100.0%
2025-02-28T12:46:11.360320image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

nomenclaturalCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size38.3 MiB
2025-02-28T12:46:11.386432image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters15059337
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowICN
2nd rowICN
3rd rowICN
4th rowICN
5th rowICN
ValueCountFrequency (%)
icn 5019779
100.0%
2025-02-28T12:46:11.469102image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 5019779
33.3%
C 5019779
33.3%
N 5019779
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15059337
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
I 5019779
33.3%
C 5019779
33.3%
N 5019779
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15059337
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
I 5019779
33.3%
C 5019779
33.3%
N 5019779
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15059337
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
I 5019779
33.3%
C 5019779
33.3%
N 5019779
33.3%

nomenclaturalStatus
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing5019781
Missing (%)> 99.9%
Memory size38.3 MiB
2025-02-28T12:46:11.500119image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPoales
ValueCountFrequency (%)
poales 1
100.0%
2025-02-28T12:46:11.583897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 1
16.7%
o 1
16.7%
a 1
16.7%
l 1
16.7%
e 1
16.7%
s 1
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
P 1
16.7%
o 1
16.7%
a 1
16.7%
l 1
16.7%
e 1
16.7%
s 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
P 1
16.7%
o 1
16.7%
a 1
16.7%
l 1
16.7%
e 1
16.7%
s 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
P 1
16.7%
o 1
16.7%
a 1
16.7%
l 1
16.7%
e 1
16.7%
s 1
16.7%