Overview

Brought to you by YData

Dataset statistics

Number of variables50
Number of observations2832540
Missing cells48043115
Missing cells (%)33.9%
Total size in memory1.1 GiB
Average record size in memory400.0 B

Variable types

Text50

Dataset

DescriptionMeise Botanic Garden Herbarium (BR) 0007170-250310093411724
URLhttps://doi.org/10.15468/dl.mrp6vb

Alerts

license has constant value "http://creativecommons.org/licenses/by/4.0/" Constant
rightsHolder has constant value "Meise Botanic Garden" Constant
datasetName has constant value "Meise Botanic Garden Herbarium" Constant
establishmentMeans has constant value "Country: Corse" Constant
verbatimLocality has constant value "Petrorhagia saxifraga (L.) Link" Constant
minimumDistanceAboveSurfaceInMeters has constant value "Plantae" Constant
maximumDistanceAboveSurfaceInMeters has constant value "Tracheophyta" Constant
locationAccordingTo has constant value "Magnoliopsida" Constant
pointRadiusSpatialFit has constant value "Petrorhagia" Constant
verbatimCoordinateSystem has constant value "saxifraga" Constant
georeferenceProtocol has constant value "ICBN" Constant
georeferenceSources has constant value "accepted name" Constant
nomenclaturalCode has constant value "ICBN" Constant
recordNumber has 47412 (1.7%) missing values Missing
recordedBy has 31164 (1.1%) missing values Missing
recordedByID has 1159144 (40.9%) missing values Missing
establishmentMeans has 2832539 (> 99.9%) missing values Missing
eventDate has 643110 (22.7%) missing values Missing
year has 647971 (22.9%) missing values Missing
month has 796858 (28.1%) missing values Missing
day has 1185582 (41.9%) missing values Missing
verbatimEventDate has 1214312 (42.9%) missing values Missing
habitat has 2315970 (81.8%) missing values Missing
country has 35185 (1.2%) missing values Missing
countryCode has 39499 (1.4%) missing values Missing
locality has 223764 (7.9%) missing values Missing
verbatimLocality has 2832539 (> 99.9%) missing values Missing
minimumDistanceAboveSurfaceInMeters has 2832539 (> 99.9%) missing values Missing
maximumDistanceAboveSurfaceInMeters has 2832539 (> 99.9%) missing values Missing
locationAccordingTo has 2832539 (> 99.9%) missing values Missing
locationRemarks has 1438676 (50.8%) missing values Missing
decimalLatitude has 2145432 (75.7%) missing values Missing
decimalLongitude has 2145085 (75.7%) missing values Missing
coordinateUncertaintyInMeters has 2561936 (90.4%) missing values Missing
pointRadiusSpatialFit has 2832539 (> 99.9%) missing values Missing
verbatimCoordinateSystem has 2832539 (> 99.9%) missing values Missing
georeferenceProtocol has 2832539 (> 99.9%) missing values Missing
georeferenceSources has 2832539 (> 99.9%) missing values Missing
typeStatus has 2771615 (97.8%) missing values Missing
acceptedNameUsage has 2625200 (92.7%) missing values Missing
kingdom has 28546 (1.0%) missing values Missing
phylum has 28665 (1.0%) missing values Missing
class has 29031 (1.0%) missing values Missing
order has 29079 (1.0%) missing values Missing
genus has 56666 (2.0%) missing values Missing
taxonomicStatus has 314930 (11.1%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique
catalogNumber has unique values Unique

Reproduction

Analysis started2025-03-13 19:36:07.344328
Analysis finished2025-03-13 19:37:25.849212
Duration1 minute and 18.5 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct2832540
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:27.471201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters28325400
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

Unique2832540 ?
Unique (%)100.0%

Sample

1st row4072468249
2nd row1840134947
3rd row4073209772
4th row1840134952
5th row4072468250
ValueCountFrequency (%)
4072468249 1
 
< 0.1%
4073209774 1
 
< 0.1%
4072468254 1
 
< 0.1%
1840135015 1
 
< 0.1%
4072475964 1
 
< 0.1%
1840135013 1
 
< 0.1%
4073209772 1
 
< 0.1%
1840134952 1
 
< 0.1%
4072468250 1
 
< 0.1%
1840134965 1
 
< 0.1%
Other values (2832530) 2832530
> 99.9%
2025-03-13T15:37:29.164866image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 3856254
13.6%
0 3471015
12.3%
8 3327884
11.7%
1 3136460
11.1%
3 2861619
10.1%
2 2832133
10.0%
7 2803012
9.9%
9 2283295
8.1%
6 1899642
6.7%
5 1854086
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28325400
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 3856254
13.6%
0 3471015
12.3%
8 3327884
11.7%
1 3136460
11.1%
3 2861619
10.1%
2 2832133
10.0%
7 2803012
9.9%
9 2283295
8.1%
6 1899642
6.7%
5 1854086
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28325400
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 3856254
13.6%
0 3471015
12.3%
8 3327884
11.7%
1 3136460
11.1%
3 2861619
10.1%
2 2832133
10.0%
7 2803012
9.9%
9 2283295
8.1%
6 1899642
6.7%
5 1854086
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28325400
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 3856254
13.6%
0 3471015
12.3%
8 3327884
11.7%
1 3136460
11.1%
3 2861619
10.1%
2 2832133
10.0%
7 2803012
9.9%
9 2283295
8.1%
6 1899642
6.7%
5 1854086
6.5%

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:29.217916image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters121799220
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://creativecommons.org/licenses/by/4.0/
2nd rowhttp://creativecommons.org/licenses/by/4.0/
3rd rowhttp://creativecommons.org/licenses/by/4.0/
4th rowhttp://creativecommons.org/licenses/by/4.0/
5th rowhttp://creativecommons.org/licenses/by/4.0/
ValueCountFrequency (%)
http://creativecommons.org/licenses/by/4.0 2832540
100.0%
2025-03-13T15:37:29.302187image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 16995240
14.0%
e 11330160
 
9.3%
o 8497620
 
7.0%
c 8497620
 
7.0%
t 8497620
 
7.0%
s 8497620
 
7.0%
r 5665080
 
4.7%
i 5665080
 
4.7%
m 5665080
 
4.7%
n 5665080
 
4.7%
Other values (12) 36823020
30.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 121799220
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 16995240
14.0%
e 11330160
 
9.3%
o 8497620
 
7.0%
c 8497620
 
7.0%
t 8497620
 
7.0%
s 8497620
 
7.0%
r 5665080
 
4.7%
i 5665080
 
4.7%
m 5665080
 
4.7%
n 5665080
 
4.7%
Other values (12) 36823020
30.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 121799220
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 16995240
14.0%
e 11330160
 
9.3%
o 8497620
 
7.0%
c 8497620
 
7.0%
t 8497620
 
7.0%
s 8497620
 
7.0%
r 5665080
 
4.7%
i 5665080
 
4.7%
m 5665080
 
4.7%
n 5665080
 
4.7%
Other values (12) 36823020
30.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 121799220
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 16995240
14.0%
e 11330160
 
9.3%
o 8497620
 
7.0%
c 8497620
 
7.0%
t 8497620
 
7.0%
s 8497620
 
7.0%
r 5665080
 
4.7%
i 5665080
 
4.7%
m 5665080
 
4.7%
n 5665080
 
4.7%
Other values (12) 36823020
30.2%
Distinct4985
Distinct (%)0.2%
Missing4
Missing (%)< 0.1%
Memory size21.6 MiB
2025-03-13T15:37:29.347095image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters28325360
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

Unique68 ?
Unique (%)< 0.1%

Sample

1st row2022-12-25
2nd row2017-12-31
3rd row2022-12-25
4th row2017-12-31
5th row2022-12-25
ValueCountFrequency (%)
2022-12-25 895277
31.6%
2017-12-31 264481
 
9.3%
2018-03-16 190330
 
6.7%
2018-10-05 128948
 
4.6%
2006-08-18 127431
 
4.5%
2019-01-25 120491
 
4.3%
2021-05-05 95078
 
3.4%
2024-03-07 54219
 
1.9%
2017-11-02 39434
 
1.4%
2023-08-23 19632
 
0.7%
Other values (4975) 897215
31.7%
2025-03-13T15:37:29.438417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7864697
27.8%
- 5665072
20.0%
0 5367101
18.9%
1 4283099
15.1%
5 1557912
 
5.5%
3 883142
 
3.1%
8 864117
 
3.1%
7 610888
 
2.2%
6 608440
 
2.1%
9 339759
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28325360
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 7864697
27.8%
- 5665072
20.0%
0 5367101
18.9%
1 4283099
15.1%
5 1557912
 
5.5%
3 883142
 
3.1%
8 864117
 
3.1%
7 610888
 
2.2%
6 608440
 
2.1%
9 339759
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28325360
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 7864697
27.8%
- 5665072
20.0%
0 5367101
18.9%
1 4283099
15.1%
5 1557912
 
5.5%
3 883142
 
3.1%
8 864117
 
3.1%
7 610888
 
2.2%
6 608440
 
2.1%
9 339759
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28325360
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 7864697
27.8%
- 5665072
20.0%
0 5367101
18.9%
1 4283099
15.1%
5 1557912
 
5.5%
3 883142
 
3.1%
8 864117
 
3.1%
7 610888
 
2.2%
6 608440
 
2.1%
9 339759
 
1.2%

rightsHolder
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:29.473561image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters56650800
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 rowMeise Botanic Garden
2nd rowMeise Botanic Garden
3rd rowMeise Botanic Garden
4th rowMeise Botanic Garden
5th rowMeise Botanic Garden
ValueCountFrequency (%)
meise 2832540
33.3%
botanic 2832540
33.3%
garden 2832540
33.3%
2025-03-13T15:37:29.562495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 8497620
15.0%
i 5665080
10.0%
5665080
10.0%
a 5665080
10.0%
n 5665080
10.0%
M 2832540
 
5.0%
s 2832540
 
5.0%
B 2832540
 
5.0%
o 2832540
 
5.0%
t 2832540
 
5.0%
Other values (4) 11330160
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56650800
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 8497620
15.0%
i 5665080
10.0%
5665080
10.0%
a 5665080
10.0%
n 5665080
10.0%
M 2832540
 
5.0%
s 2832540
 
5.0%
B 2832540
 
5.0%
o 2832540
 
5.0%
t 2832540
 
5.0%
Other values (4) 11330160
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56650800
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 8497620
15.0%
i 5665080
10.0%
5665080
10.0%
a 5665080
10.0%
n 5665080
10.0%
M 2832540
 
5.0%
s 2832540
 
5.0%
B 2832540
 
5.0%
o 2832540
 
5.0%
t 2832540
 
5.0%
Other values (4) 11330160
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56650800
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 8497620
15.0%
i 5665080
10.0%
5665080
10.0%
a 5665080
10.0%
n 5665080
10.0%
M 2832540
 
5.0%
s 2832540
 
5.0%
B 2832540
 
5.0%
o 2832540
 
5.0%
t 2832540
 
5.0%
Other values (4) 11330160
20.0%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:29.591884image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length47
Median length47
Mean length46.94487068
Min length25

Characters and Unicode

Total characters132973224
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://biocol.org/urn:lsid:biocol.org:col:15605
2nd rowhttp://biocol.org/urn:lsid:biocol.org:col:15605
3rd rowhttp://biocol.org/urn:lsid:biocol.org:col:15605
4th rowhttp://biocol.org/urn:lsid:biocol.org:col:15605
5th rowhttp://biocol.org/urn:lsid:biocol.org:col:15605
ValueCountFrequency (%)
http://biocol.org/urn:lsid:biocol.org:col:15605 2825442
99.7%
https://ror.org/00cv9y106 6674
 
0.2%
https://ror.org/01r9htc13 424
 
< 0.1%
2025-03-13T15:37:29.671960image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 19792290
14.9%
: 14134308
 
10.6%
l 11301768
 
8.5%
r 8498044
 
6.4%
/ 8497620
 
6.4%
c 8483424
 
6.4%
i 8476326
 
6.4%
t 5665504
 
4.3%
g 5657982
 
4.3%
. 5657982
 
4.3%
Other values (15) 36807976
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 132973224
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 19792290
14.9%
: 14134308
 
10.6%
l 11301768
 
8.5%
r 8498044
 
6.4%
/ 8497620
 
6.4%
c 8483424
 
6.4%
i 8476326
 
6.4%
t 5665504
 
4.3%
g 5657982
 
4.3%
. 5657982
 
4.3%
Other values (15) 36807976
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 132973224
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 19792290
14.9%
: 14134308
 
10.6%
l 11301768
 
8.5%
r 8498044
 
6.4%
/ 8497620
 
6.4%
c 8483424
 
6.4%
i 8476326
 
6.4%
t 5665504
 
4.3%
g 5657982
 
4.3%
. 5657982
 
4.3%
Other values (15) 36807976
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 132973224
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 19792290
14.9%
: 14134308
 
10.6%
l 11301768
 
8.5%
r 8498044
 
6.4%
/ 8497620
 
6.4%
c 8483424
 
6.4%
i 8476326
 
6.4%
t 5665504
 
4.3%
g 5657982
 
4.3%
. 5657982
 
4.3%
Other values (15) 36807976
27.7%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:29.700062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters50985720
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 rowgbif:ih:irn:124997
2nd rowgbif:ih:irn:124997
3rd rowgbif:ih:irn:124997
4th rowgbif:ih:irn:124997
5th rowgbif:ih:irn:124997
ValueCountFrequency (%)
gbif:ih:irn:124997 2825442
99.7%
gbif:ih:irn:124613 6674
 
0.2%
gbif:ih:irn:126554 424
 
< 0.1%
2025-03-13T15:37:29.779535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 8497620
16.7%
: 8497620
16.7%
9 5650884
11.1%
1 2839214
 
5.6%
g 2832540
 
5.6%
b 2832540
 
5.6%
f 2832540
 
5.6%
h 2832540
 
5.6%
r 2832540
 
5.6%
n 2832540
 
5.6%
Other values (6) 8505142
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 50985720
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 8497620
16.7%
: 8497620
16.7%
9 5650884
11.1%
1 2839214
 
5.6%
g 2832540
 
5.6%
b 2832540
 
5.6%
f 2832540
 
5.6%
h 2832540
 
5.6%
r 2832540
 
5.6%
n 2832540
 
5.6%
Other values (6) 8505142
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 50985720
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 8497620
16.7%
: 8497620
16.7%
9 5650884
11.1%
1 2839214
 
5.6%
g 2832540
 
5.6%
b 2832540
 
5.6%
f 2832540
 
5.6%
h 2832540
 
5.6%
r 2832540
 
5.6%
n 2832540
 
5.6%
Other values (6) 8505142
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 50985720
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 8497620
16.7%
: 8497620
16.7%
9 5650884
11.1%
1 2839214
 
5.6%
g 2832540
 
5.6%
b 2832540
 
5.6%
f 2832540
 
5.6%
h 2832540
 
5.6%
r 2832540
 
5.6%
n 2832540
 
5.6%
Other values (6) 8505142
16.7%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:29.807854image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.994688866
Min length3

Characters and Unicode

Total characters19812736
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMeiseBG
2nd rowMeiseBG
3rd rowMeiseBG
4th rowMeiseBG
5th rowMeiseBG
ValueCountFrequency (%)
meisebg 2825442
99.7%
ugent 6674
 
0.2%
ulb 424
 
< 0.1%
2025-03-13T15:37:29.896483image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5650884
28.5%
G 2832116
14.3%
B 2825866
14.3%
M 2825442
14.3%
i 2825442
14.3%
s 2825442
14.3%
U 7098
 
< 0.1%
E 6674
 
< 0.1%
N 6674
 
< 0.1%
T 6674
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19812736
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5650884
28.5%
G 2832116
14.3%
B 2825866
14.3%
M 2825442
14.3%
i 2825442
14.3%
s 2825442
14.3%
U 7098
 
< 0.1%
E 6674
 
< 0.1%
N 6674
 
< 0.1%
T 6674
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19812736
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5650884
28.5%
G 2832116
14.3%
B 2825866
14.3%
M 2825442
14.3%
i 2825442
14.3%
s 2825442
14.3%
U 7098
 
< 0.1%
E 6674
 
< 0.1%
N 6674
 
< 0.1%
T 6674
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19812736
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5650884
28.5%
G 2832116
14.3%
B 2825866
14.3%
M 2825442
14.3%
i 2825442
14.3%
s 2825442
14.3%
U 7098
 
< 0.1%
E 6674
 
< 0.1%
N 6674
 
< 0.1%
T 6674
 
< 0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:29.925986image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.005012815
Min length2

Characters and Unicode

Total characters5679279
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBR
2nd rowBR
3rd rowBR
4th rowBR
5th rowBR
ValueCountFrequency (%)
br 2825439
99.7%
gent 6674
 
0.2%
brlu 424
 
< 0.1%
awh 3
 
< 0.1%
2025-03-13T15:37:30.016623image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 2825863
49.8%
R 2825863
49.8%
G 6674
 
0.1%
E 6674
 
0.1%
N 6674
 
0.1%
T 6674
 
0.1%
L 424
 
< 0.1%
U 424
 
< 0.1%
A 3
 
< 0.1%
W 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5679279
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 2825863
49.8%
R 2825863
49.8%
G 6674
 
0.1%
E 6674
 
0.1%
N 6674
 
0.1%
T 6674
 
0.1%
L 424
 
< 0.1%
U 424
 
< 0.1%
A 3
 
< 0.1%
W 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5679279
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 2825863
49.8%
R 2825863
49.8%
G 6674
 
0.1%
E 6674
 
0.1%
N 6674
 
0.1%
T 6674
 
0.1%
L 424
 
< 0.1%
U 424
 
< 0.1%
A 3
 
< 0.1%
W 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5679279
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 2825863
49.8%
R 2825863
49.8%
G 6674
 
0.1%
E 6674
 
0.1%
N 6674
 
0.1%
T 6674
 
0.1%
L 424
 
< 0.1%
U 424
 
< 0.1%
A 3
 
< 0.1%
W 3
 
< 0.1%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:30.045511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length30
Median length30
Mean length30
Min length30

Characters and Unicode

Total characters84976200
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMeise Botanic Garden Herbarium
2nd rowMeise Botanic Garden Herbarium
3rd rowMeise Botanic Garden Herbarium
4th rowMeise Botanic Garden Herbarium
5th rowMeise Botanic Garden Herbarium
ValueCountFrequency (%)
meise 2832540
25.0%
botanic 2832540
25.0%
garden 2832540
25.0%
herbarium 2832540
25.0%
2025-03-13T15:37:30.125894image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11330160
13.3%
i 8497620
 
10.0%
8497620
 
10.0%
a 8497620
 
10.0%
r 8497620
 
10.0%
n 5665080
 
6.7%
G 2832540
 
3.3%
u 2832540
 
3.3%
b 2832540
 
3.3%
H 2832540
 
3.3%
Other values (8) 22660320
26.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 84976200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 11330160
13.3%
i 8497620
 
10.0%
8497620
 
10.0%
a 8497620
 
10.0%
r 8497620
 
10.0%
n 5665080
 
6.7%
G 2832540
 
3.3%
u 2832540
 
3.3%
b 2832540
 
3.3%
H 2832540
 
3.3%
Other values (8) 22660320
26.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 84976200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 11330160
13.3%
i 8497620
 
10.0%
8497620
 
10.0%
a 8497620
 
10.0%
r 8497620
 
10.0%
n 5665080
 
6.7%
G 2832540
 
3.3%
u 2832540
 
3.3%
b 2832540
 
3.3%
H 2832540
 
3.3%
Other values (8) 22660320
26.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 84976200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 11330160
13.3%
i 8497620
 
10.0%
8497620
 
10.0%
a 8497620
 
10.0%
r 8497620
 
10.0%
n 5665080
 
6.7%
G 2832540
 
3.3%
u 2832540
 
3.3%
b 2832540
 
3.3%
H 2832540
 
3.3%
Other values (8) 22660320
26.7%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:30.156335image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length17
Mean length16.97181187
Min length10

Characters and Unicode

Total characters48073336
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 2798204
98.8%
materialsample 11471
 
0.4%
humanobservation 10850
 
0.4%
machineobservation 6188
 
0.2%
occurrence 5822
 
0.2%
livingspecimen 5
 
< 0.1%
2025-03-13T15:37:30.251004image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 14048842
29.2%
r 5636561
11.7%
n 2838112
 
5.9%
i 2832916
 
5.9%
c 2821863
 
5.9%
m 2820530
 
5.9%
v 2815247
 
5.9%
s 2815242
 
5.9%
S 2809680
 
5.8%
p 2809680
 
5.8%
Other values (14) 5824663
12.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 48073336
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 14048842
29.2%
r 5636561
11.7%
n 2838112
 
5.9%
i 2832916
 
5.9%
c 2821863
 
5.9%
m 2820530
 
5.9%
v 2815247
 
5.9%
s 2815242
 
5.9%
S 2809680
 
5.8%
p 2809680
 
5.8%
Other values (14) 5824663
12.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 48073336
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 14048842
29.2%
r 5636561
11.7%
n 2838112
 
5.9%
i 2832916
 
5.9%
c 2821863
 
5.9%
m 2820530
 
5.9%
v 2815247
 
5.9%
s 2815242
 
5.9%
S 2809680
 
5.8%
p 2809680
 
5.8%
Other values (14) 5824663
12.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 48073336
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 14048842
29.2%
r 5636561
11.7%
n 2838112
 
5.9%
i 2832916
 
5.9%
c 2821863
 
5.9%
m 2820530
 
5.9%
v 2815247
 
5.9%
s 2815242
 
5.9%
S 2809680
 
5.8%
p 2809680
 
5.8%
Other values (14) 5824663
12.1%

occurrenceID
Text

Unique 

Distinct2832540
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:31.610891image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length61
Median length59
Mean length59.0512014
Min length54

Characters and Unicode

Total characters167264890
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2832540 ?
Unique (%)100.0%

Sample

1st rowhttp://www.botanicalcollections.be/specimen/BR0000035634553
2nd rowhttp://www.botanicalcollections.be/specimen/BR0000016406988
3rd rowhttp://www.botanicalcollections.be/specimen/BR0000035634607
4th rowhttp://www.botanicalcollections.be/specimen/BR0000016407022
5th rowhttp://www.botanicalcollections.be/specimen/BR0000035634652
ValueCountFrequency (%)
http://www.botanicalcollections.be/specimen/br0000035634553 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000035634706 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000035635147 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000016407473 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000035635093 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000016407428 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000035634607 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000016407022 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000035634652 1
 
< 0.1%
http://www.botanicalcollections.be/specimen/br0000016407077 1
 
< 0.1%
Other values (2832530) 2832530
> 99.9%
2025-03-13T15:37:33.444867image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15420571
 
9.2%
t 11330160
 
6.8%
e 11330160
 
6.8%
/ 11330160
 
6.8%
c 11330160
 
6.8%
l 8497620
 
5.1%
i 8497620
 
5.1%
n 8497620
 
5.1%
o 8497620
 
5.1%
w 8497620
 
5.1%
Other values (29) 64035579
38.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 167264890
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 15420571
 
9.2%
t 11330160
 
6.8%
e 11330160
 
6.8%
/ 11330160
 
6.8%
c 11330160
 
6.8%
l 8497620
 
5.1%
i 8497620
 
5.1%
n 8497620
 
5.1%
o 8497620
 
5.1%
w 8497620
 
5.1%
Other values (29) 64035579
38.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 167264890
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 15420571
 
9.2%
t 11330160
 
6.8%
e 11330160
 
6.8%
/ 11330160
 
6.8%
c 11330160
 
6.8%
l 8497620
 
5.1%
i 8497620
 
5.1%
n 8497620
 
5.1%
o 8497620
 
5.1%
w 8497620
 
5.1%
Other values (29) 64035579
38.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 167264890
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 15420571
 
9.2%
t 11330160
 
6.8%
e 11330160
 
6.8%
/ 11330160
 
6.8%
c 11330160
 
6.8%
l 8497620
 
5.1%
i 8497620
 
5.1%
n 8497620
 
5.1%
o 8497620
 
5.1%
w 8497620
 
5.1%
Other values (29) 64035579
38.3%

catalogNumber
Text

Unique 

Distinct2832540
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size21.6 MiB
2025-03-13T15:37:34.869341image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length15.0512014
Min length10

Characters and Unicode

Total characters42633130
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

Unique2832540 ?
Unique (%)100.0%

Sample

1st rowBR0000035634553
2nd rowBR0000016406988
3rd rowBR0000035634607
4th rowBR0000016407022
5th rowBR0000035634652
ValueCountFrequency (%)
br0000035634553 1
 
< 0.1%
br0000035634706 1
 
< 0.1%
br0000035635147 1
 
< 0.1%
br0000016407473 1
 
< 0.1%
br0000035635093 1
 
< 0.1%
br0000016407428 1
 
< 0.1%
br0000035634607 1
 
< 0.1%
br0000016407022 1
 
< 0.1%
br0000035634652 1
 
< 0.1%
br0000016407077 1
 
< 0.1%
Other values (2832530) 2832530
> 99.9%
2025-03-13T15:37:36.447346image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15420571
36.2%
1 3243878
 
7.6%
2 2861511
 
6.7%
B 2824852
 
6.6%
R 2824852
 
6.6%
3 2642469
 
6.2%
5 2561382
 
6.0%
6 2055088
 
4.8%
4 2049274
 
4.8%
8 2041231
 
4.8%
Other values (12) 4108022
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42633130
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 15420571
36.2%
1 3243878
 
7.6%
2 2861511
 
6.7%
B 2824852
 
6.6%
R 2824852
 
6.6%
3 2642469
 
6.2%
5 2561382
 
6.0%
6 2055088
 
4.8%
4 2049274
 
4.8%
8 2041231
 
4.8%
Other values (12) 4108022
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42633130
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 15420571
36.2%
1 3243878
 
7.6%
2 2861511
 
6.7%
B 2824852
 
6.6%
R 2824852
 
6.6%
3 2642469
 
6.2%
5 2561382
 
6.0%
6 2055088
 
4.8%
4 2049274
 
4.8%
8 2041231
 
4.8%
Other values (12) 4108022
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42633130
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 15420571
36.2%
1 3243878
 
7.6%
2 2861511
 
6.7%
B 2824852
 
6.6%
R 2824852
 
6.6%
3 2642469
 
6.2%
5 2561382
 
6.0%
6 2055088
 
4.8%
4 2049274
 
4.8%
8 2041231
 
4.8%
Other values (12) 4108022
 
9.6%

recordNumber
Text

Missing 

Distinct284846
Distinct (%)10.2%
Missing47412
Missing (%)1.7%
Memory size21.6 MiB
2025-03-13T15:37:36.828808image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length43023956
Median length4
Mean length19.57700472
Min length1

Characters and Unicode

Total characters54524464
Distinct characters303
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203934 ?
Unique (%)7.3%

Sample

1st row328
2nd row102
3rd rowS.N.
4th row3439
5th rowS.N.
ValueCountFrequency (%)
s.n 903237
 
15.7%
garden 118527
 
2.1%
botanic 118410
 
2.1%
meise 118402
 
2.1%
br 62997
 
1.1%
herbarium 59216
 
1.0%
http://biocol.org/urn:lsid:biocol.org:col:15605 59198
 
1.0%
gbif:ih:irn:124997 59198
 
1.0%
http://creativecommons.org/licenses/by/4.0 59198
 
1.0%
icbn 59198
 
1.0%
Other values (562855) 4142332
71.9%
2025-03-13T15:37:37.355897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11188489
20.5%
. 2555706
 
4.7%
e 2540017
 
4.7%
a 1961122
 
3.6%
i 1911228
 
3.5%
1 1846406
 
3.4%
0 1834881
 
3.4%
o 1591338
 
2.9%
r 1407980
 
2.6%
2 1378501
 
2.5%
Other values (293) 26308796
48.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 54524464
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
11188489
20.5%
. 2555706
 
4.7%
e 2540017
 
4.7%
a 1961122
 
3.6%
i 1911228
 
3.5%
1 1846406
 
3.4%
0 1834881
 
3.4%
o 1591338
 
2.9%
r 1407980
 
2.6%
2 1378501
 
2.5%
Other values (293) 26308796
48.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 54524464
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
11188489
20.5%
. 2555706
 
4.7%
e 2540017
 
4.7%
a 1961122
 
3.6%
i 1911228
 
3.5%
1 1846406
 
3.4%
0 1834881
 
3.4%
o 1591338
 
2.9%
r 1407980
 
2.6%
2 1378501
 
2.5%
Other values (293) 26308796
48.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 54524464
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
11188489
20.5%
. 2555706
 
4.7%
e 2540017
 
4.7%
a 1961122
 
3.6%
i 1911228
 
3.5%
1 1846406
 
3.4%
0 1834881
 
3.4%
o 1591338
 
2.9%
r 1407980
 
2.6%
2 1378501
 
2.5%
Other values (293) 26308796
48.3%

recordedBy
Text

Missing 

Distinct93535
Distinct (%)3.3%
Missing31164
Missing (%)1.1%
Memory size21.6 MiB
2025-03-13T15:37:37.523062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length200
Median length190
Mean length13.31394036
Min length1

Characters and Unicode

Total characters37297353
Distinct characters269
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62277 ?
Unique (%)2.2%

Sample

1st rowTodaro A.
2nd rowSenderayi E.
3rd rowNitka J.
4th rowGermishuizen G.
5th rowVašák V.
ValueCountFrequency (%)
j 321208
 
4.7%
a 251086
 
3.7%
225374
 
3.3%
de 177037
 
2.6%
h 158382
 
2.3%
m 147763
 
2.2%
p 133459
 
1.9%
f 133135
 
1.9%
g 132716
 
1.9%
c 129959
 
1.9%
Other values (55730) 5047939
73.6%
2025-03-13T15:37:37.791087image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4056682
 
10.9%
. 3718920
 
10.0%
e 3233381
 
8.7%
n 2062694
 
5.5%
a 1881283
 
5.0%
r 1807623
 
4.8%
o 1647339
 
4.4%
i 1330735
 
3.6%
l 1314664
 
3.5%
s 1196219
 
3.2%
Other values (259) 15047813
40.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37297353
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4056682
 
10.9%
. 3718920
 
10.0%
e 3233381
 
8.7%
n 2062694
 
5.5%
a 1881283
 
5.0%
r 1807623
 
4.8%
o 1647339
 
4.4%
i 1330735
 
3.6%
l 1314664
 
3.5%
s 1196219
 
3.2%
Other values (259) 15047813
40.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37297353
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4056682
 
10.9%
. 3718920
 
10.0%
e 3233381
 
8.7%
n 2062694
 
5.5%
a 1881283
 
5.0%
r 1807623
 
4.8%
o 1647339
 
4.4%
i 1330735
 
3.6%
l 1314664
 
3.5%
s 1196219
 
3.2%
Other values (259) 15047813
40.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37297353
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4056682
 
10.9%
. 3718920
 
10.0%
e 3233381
 
8.7%
n 2062694
 
5.5%
a 1881283
 
5.0%
r 1807623
 
4.8%
o 1647339
 
4.4%
i 1330735
 
3.6%
l 1314664
 
3.5%
s 1196219
 
3.2%
Other values (259) 15047813
40.3%

recordedByID
Text

Missing 

Distinct1711
Distinct (%)0.1%
Missing1159144
Missing (%)40.9%
Memory size21.6 MiB
2025-03-13T15:37:37.858380image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length87
Median length81
Mean length41.38909977
Min length26

Characters and Unicode

Total characters69260354
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)< 0.1%

Sample

1st rowhttp://viaf.org/viaf/10628368
2nd rowhttp://purl.oclc.org/net/edu.harvard.huh/guid/uuid/8faac441-8d05-4bab-9c22-c97cd7df1145
3rd rowhttp://viaf.org/viaf/22916664
4th rowhttps://kiki.huh.harvard.edu/databases/botanist_search.php?mode=details&id=5495
5th rowhttp://www.wikidata.org/entity/Q6491480
ValueCountFrequency (%)
http://viaf.org/viaf/89445626 40653
 
2.4%
https://orcid.org/0000-0001-7949-2594 32096
 
1.9%
http://viaf.org/viaf/289994763 30229
 
1.8%
http://viaf.org/viaf/115629741 28271
 
1.7%
http://viaf.org/viaf/51826391 27242
 
1.6%
http://viaf.org/viaf/166699679 23648
 
1.4%
http://viaf.org/viaf/111968476 21480
 
1.3%
https://orcid.org/0000-0003-0223-8496 21429
 
1.3%
http://viaf.org/viaf/36967258 19911
 
1.2%
http://viaf.org/viaf/115629067 19137
 
1.1%
Other values (1701) 1409300
84.2%
2025-03-13T15:37:37.988167image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 6701220
 
9.7%
t 4890561
 
7.1%
i 4504825
 
6.5%
a 4363538
 
6.3%
h 3147783
 
4.5%
. 2883117
 
4.2%
r 2654261
 
3.8%
p 2395428
 
3.5%
o 2328247
 
3.4%
d 2296815
 
3.3%
Other values (38) 33094559
47.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 69260354
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 6701220
 
9.7%
t 4890561
 
7.1%
i 4504825
 
6.5%
a 4363538
 
6.3%
h 3147783
 
4.5%
. 2883117
 
4.2%
r 2654261
 
3.8%
p 2395428
 
3.5%
o 2328247
 
3.4%
d 2296815
 
3.3%
Other values (38) 33094559
47.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 69260354
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 6701220
 
9.7%
t 4890561
 
7.1%
i 4504825
 
6.5%
a 4363538
 
6.3%
h 3147783
 
4.5%
. 2883117
 
4.2%
r 2654261
 
3.8%
p 2395428
 
3.5%
o 2328247
 
3.4%
d 2296815
 
3.3%
Other values (38) 33094559
47.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 69260354
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 6701220
 
9.7%
t 4890561
 
7.1%
i 4504825
 
6.5%
a 4363538
 
6.3%
h 3147783
 
4.5%
. 2883117
 
4.2%
r 2654261
 
3.8%
p 2395428
 
3.5%
o 2328247
 
3.4%
d 2296815
 
3.3%
Other values (38) 33094559
47.8%

establishmentMeans
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:38.028450image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
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 rowCountry: Corse
ValueCountFrequency (%)
country 1
50.0%
corse 1
50.0%
2025-03-13T15:37:38.110889image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 2
14.3%
o 2
14.3%
r 2
14.3%
u 1
7.1%
n 1
7.1%
t 1
7.1%
y 1
7.1%
: 1
7.1%
1
7.1%
s 1
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 2
14.3%
o 2
14.3%
r 2
14.3%
u 1
7.1%
n 1
7.1%
t 1
7.1%
y 1
7.1%
: 1
7.1%
1
7.1%
s 1
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 2
14.3%
o 2
14.3%
r 2
14.3%
u 1
7.1%
n 1
7.1%
t 1
7.1%
y 1
7.1%
: 1
7.1%
1
7.1%
s 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 2
14.3%
o 2
14.3%
r 2
14.3%
u 1
7.1%
n 1
7.1%
t 1
7.1%
y 1
7.1%
: 1
7.1%
1
7.1%
s 1
7.1%
Distinct35
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size21.6 MiB
2025-03-13T15:37:38.151238image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length14
Mean length13.94322302
Min length3

Characters and Unicode

Total characters39494723
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowHerbariumSheet
2nd rowHerbariumSheet
3rd rowHerbariumSheet
4th rowHerbariumSheet
5th rowHerbariumSheet
ValueCountFrequency (%)
herbariumsheet 2773698
97.2%
liquidpreserved 11712
 
0.4%
silica 10869
 
0.4%
gel 10869
 
0.4%
seed 6454
 
0.2%
description 6227
 
0.2%
unknown 5822
 
0.2%
photograph:b&w 4895
 
0.2%
drawing 4563
 
0.2%
in 4506
 
0.2%
Other values (36) 13432
 
0.5%
2025-03-13T15:37:38.281365image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 8395518
21.3%
r 5595950
14.2%
i 2847372
 
7.2%
a 2802824
 
7.1%
S 2791264
 
7.1%
u 2789983
 
7.1%
h 2789746
 
7.1%
t 2789617
 
7.1%
b 2783724
 
7.0%
m 2775824
 
7.0%
Other values (26) 3132901
 
7.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 39494723
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 8395518
21.3%
r 5595950
14.2%
i 2847372
 
7.2%
a 2802824
 
7.1%
S 2791264
 
7.1%
u 2789983
 
7.1%
h 2789746
 
7.1%
t 2789617
 
7.1%
b 2783724
 
7.0%
m 2775824
 
7.0%
Other values (26) 3132901
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 39494723
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 8395518
21.3%
r 5595950
14.2%
i 2847372
 
7.2%
a 2802824
 
7.1%
S 2791264
 
7.1%
u 2789983
 
7.1%
h 2789746
 
7.1%
t 2789617
 
7.1%
b 2783724
 
7.0%
m 2775824
 
7.0%
Other values (26) 3132901
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 39494723
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 8395518
21.3%
r 5595950
14.2%
i 2847372
 
7.2%
a 2802824
 
7.1%
S 2791264
 
7.1%
u 2789983
 
7.1%
h 2789746
 
7.1%
t 2789617
 
7.1%
b 2783724
 
7.0%
m 2775824
 
7.0%
Other values (26) 3132901
 
7.9%

eventDate
Text

Missing 

Distinct69207
Distinct (%)3.2%
Missing643110
Missing (%)22.7%
Memory size21.6 MiB
2025-03-13T15:37:38.466537image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length9.129800907
Min length4

Characters and Unicode

Total characters19989060
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

Unique9510 ?
Unique (%)0.4%

Sample

1st row1977-03-30
2nd row1960-08-05
3rd row1978-08-05
4th row1826
5th row1964-07-03
ValueCountFrequency (%)
1913 3045
 
0.1%
1840 2516
 
0.1%
1868 2162
 
0.1%
1836 2118
 
0.1%
1900 2117
 
0.1%
1925 1991
 
0.1%
1840-04 1966
 
0.1%
1906 1919
 
0.1%
1921 1912
 
0.1%
1912 1907
 
0.1%
Other values (69197) 2167777
99.0%
2025-03-13T15:37:38.709142image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 3718325
18.6%
1 3692716
18.5%
0 3078693
15.4%
9 2420728
12.1%
8 1397059
 
7.0%
2 1364987
 
6.8%
7 1042924
 
5.2%
6 924637
 
4.6%
5 911111
 
4.6%
3 742077
 
3.7%
Other values (2) 695803
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19989060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 3718325
18.6%
1 3692716
18.5%
0 3078693
15.4%
9 2420728
12.1%
8 1397059
 
7.0%
2 1364987
 
6.8%
7 1042924
 
5.2%
6 924637
 
4.6%
5 911111
 
4.6%
3 742077
 
3.7%
Other values (2) 695803
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19989060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 3718325
18.6%
1 3692716
18.5%
0 3078693
15.4%
9 2420728
12.1%
8 1397059
 
7.0%
2 1364987
 
6.8%
7 1042924
 
5.2%
6 924637
 
4.6%
5 911111
 
4.6%
3 742077
 
3.7%
Other values (2) 695803
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19989060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 3718325
18.6%
1 3692716
18.5%
0 3078693
15.4%
9 2420728
12.1%
8 1397059
 
7.0%
2 1364987
 
6.8%
7 1042924
 
5.2%
6 924637
 
4.6%
5 911111
 
4.6%
3 742077
 
3.7%
Other values (2) 695803
 
3.5%

year
Text

Missing 

Distinct278
Distinct (%)< 0.1%
Missing647971
Missing (%)22.9%
Memory size21.6 MiB
2025-03-13T15:37:38.868779image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8738276
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)< 0.1%

Sample

1st row1977
2nd row1960
3rd row1978
4th row1826
5th row1964
ValueCountFrequency (%)
1958 32810
 
1.5%
1959 31822
 
1.5%
1974 30149
 
1.4%
1957 29904
 
1.4%
1971 28724
 
1.3%
1969 28117
 
1.3%
1972 27917
 
1.3%
1975 27652
 
1.3%
1952 27064
 
1.2%
1970 26838
 
1.2%
Other values (268) 1893572
86.7%
2025-03-13T15:37:39.077775image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2377505
27.2%
9 2079319
23.8%
8 968366
11.1%
0 563163
 
6.4%
7 555287
 
6.4%
6 496333
 
5.7%
5 494801
 
5.7%
2 469489
 
5.4%
3 388912
 
4.5%
4 345101
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8738276
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 2377505
27.2%
9 2079319
23.8%
8 968366
11.1%
0 563163
 
6.4%
7 555287
 
6.4%
6 496333
 
5.7%
5 494801
 
5.7%
2 469489
 
5.4%
3 388912
 
4.5%
4 345101
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8738276
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 2377505
27.2%
9 2079319
23.8%
8 968366
11.1%
0 563163
 
6.4%
7 555287
 
6.4%
6 496333
 
5.7%
5 494801
 
5.7%
2 469489
 
5.4%
3 388912
 
4.5%
4 345101
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8738276
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 2377505
27.2%
9 2079319
23.8%
8 968366
11.1%
0 563163
 
6.4%
7 555287
 
6.4%
6 496333
 
5.7%
5 494801
 
5.7%
2 469489
 
5.4%
3 388912
 
4.5%
4 345101
 
3.9%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing796858
Missing (%)28.1%
Memory size21.6 MiB
2025-03-13T15:37:39.132926image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4071364
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03
2nd row08
3rd row08
4th row07
5th row11
ValueCountFrequency (%)
07 320016
15.7%
06 259678
12.8%
08 249559
12.3%
05 235063
11.5%
04 169575
8.3%
09 168394
8.3%
10 130381
6.4%
03 113577
 
5.6%
11 109115
 
5.4%
02 95687
 
4.7%
Other values (2) 184637
9.1%
2025-03-13T15:37:39.215462image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1836316
45.1%
1 533248
 
13.1%
7 320016
 
7.9%
6 259678
 
6.4%
8 249559
 
6.1%
5 235063
 
5.8%
2 185938
 
4.6%
4 169575
 
4.2%
9 168394
 
4.1%
3 113577
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4071364
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1836316
45.1%
1 533248
 
13.1%
7 320016
 
7.9%
6 259678
 
6.4%
8 249559
 
6.1%
5 235063
 
5.8%
2 185938
 
4.6%
4 169575
 
4.2%
9 168394
 
4.1%
3 113577
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4071364
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1836316
45.1%
1 533248
 
13.1%
7 320016
 
7.9%
6 259678
 
6.4%
8 249559
 
6.1%
5 235063
 
5.8%
2 185938
 
4.6%
4 169575
 
4.2%
9 168394
 
4.1%
3 113577
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4071364
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1836316
45.1%
1 533248
 
13.1%
7 320016
 
7.9%
6 259678
 
6.4%
8 249559
 
6.1%
5 235063
 
5.8%
2 185938
 
4.6%
4 169575
 
4.2%
9 168394
 
4.1%
3 113577
 
2.8%

day
Text

Missing 

Distinct31
Distinct (%)< 0.1%
Missing1185582
Missing (%)41.9%
Memory size21.6 MiB
2025-03-13T15:37:39.259099image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters3293916
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row05
3rd row05
4th row03
5th row11
ValueCountFrequency (%)
20 61316
 
3.7%
10 61277
 
3.7%
15 61170
 
3.7%
25 55797
 
3.4%
18 55656
 
3.4%
21 55471
 
3.4%
12 55447
 
3.4%
17 55165
 
3.3%
16 54842
 
3.3%
01 54832
 
3.3%
Other values (21) 1075985
65.3%
2025-03-13T15:37:39.359459image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 745535
22.6%
2 696834
21.2%
0 651314
19.8%
3 231658
 
7.0%
5 171762
 
5.2%
8 162301
 
4.9%
6 160793
 
4.9%
7 160721
 
4.9%
4 159131
 
4.8%
9 153867
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3293916
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 745535
22.6%
2 696834
21.2%
0 651314
19.8%
3 231658
 
7.0%
5 171762
 
5.2%
8 162301
 
4.9%
6 160793
 
4.9%
7 160721
 
4.9%
4 159131
 
4.8%
9 153867
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3293916
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 745535
22.6%
2 696834
21.2%
0 651314
19.8%
3 231658
 
7.0%
5 171762
 
5.2%
8 162301
 
4.9%
6 160793
 
4.9%
7 160721
 
4.9%
4 159131
 
4.8%
9 153867
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3293916
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 745535
22.6%
2 696834
21.2%
0 651314
19.8%
3 231658
 
7.0%
5 171762
 
5.2%
8 162301
 
4.9%
6 160793
 
4.9%
7 160721
 
4.9%
4 159131
 
4.8%
9 153867
 
4.7%

verbatimEventDate
Text

Missing 

Distinct190812
Distinct (%)11.8%
Missing1214312
Missing (%)42.9%
Memory size21.6 MiB
2025-03-13T15:37:39.430672image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length322
Median length189
Mean length9.086875891
Min length1

Characters and Unicode

Total characters14704637
Distinct characters153
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83668 ?
Unique (%)5.2%

Sample

1st row[?/6/?]
2nd row[5/8/1960]
3rd row(06/11/85)
4th row[5/8/1978]
5th row[3/7/1964]
ValueCountFrequency (%)
s.d 306449
 
16.2%
00000000 27587
 
1.5%
12503
 
0.7%
aug 10412
 
0.6%
jul 8272
 
0.4%
juin 7490
 
0.4%
mai 7215
 
0.4%
juillet 6982
 
0.4%
may 4858
 
0.3%
et 4550
 
0.2%
Other values (154662) 1491223
79.0%
2025-03-13T15:37:39.581464image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1989792
13.5%
/ 1604834
 
10.9%
9 1313566
 
8.9%
0 1173449
 
8.0%
8 975499
 
6.6%
[ 736807
 
5.0%
] 736795
 
5.0%
2 681673
 
4.6%
. 665114
 
4.5%
7 644887
 
4.4%
Other values (143) 4182221
28.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14704637
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1989792
13.5%
/ 1604834
 
10.9%
9 1313566
 
8.9%
0 1173449
 
8.0%
8 975499
 
6.6%
[ 736807
 
5.0%
] 736795
 
5.0%
2 681673
 
4.6%
. 665114
 
4.5%
7 644887
 
4.4%
Other values (143) 4182221
28.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14704637
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1989792
13.5%
/ 1604834
 
10.9%
9 1313566
 
8.9%
0 1173449
 
8.0%
8 975499
 
6.6%
[ 736807
 
5.0%
] 736795
 
5.0%
2 681673
 
4.6%
. 665114
 
4.5%
7 644887
 
4.4%
Other values (143) 4182221
28.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14704637
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1989792
13.5%
/ 1604834
 
10.9%
9 1313566
 
8.9%
0 1173449
 
8.0%
8 975499
 
6.6%
[ 736807
 
5.0%
] 736795
 
5.0%
2 681673
 
4.6%
. 665114
 
4.5%
7 644887
 
4.4%
Other values (143) 4182221
28.4%

habitat
Text

Missing 

Distinct224161
Distinct (%)43.4%
Missing2315970
Missing (%)81.8%
Memory size21.6 MiB
2025-03-13T15:37:39.749536image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1207
Median length572
Mean length27.84048822
Min length1

Characters and Unicode

Total characters14381561
Distinct characters214
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178346 ?
Unique (%)34.5%

Sample

1st rowgrowing with Aloe chibaudii towards base of rock mass in open.
2nd rowIm Sumpfgebiet. In[]die Hypericum-Stamm-Geflechte.
3rd rowField layer of recently exploited forest, forming dense dominant areas in certain places.
4th rowhills behind Small Lake. On exposed hillside
5th rowOn lateritic plain.
ValueCountFrequency (%)
de 86568
 
3.8%
forêt 53763
 
2.4%
in 52720
 
2.3%
forest 38493
 
1.7%
on 38166
 
1.7%
la 32804
 
1.4%
32803
 
1.4%
sur 28699
 
1.3%
of 23142
 
1.0%
à 22597
 
1.0%
Other values (78600) 1857800
81.9%
2025-03-13T15:37:39.998746image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1750981
 
12.2%
e 1489706
 
10.4%
r 1011821
 
7.0%
a 1010258
 
7.0%
o 879137
 
6.1%
s 853755
 
5.9%
i 816449
 
5.7%
n 781521
 
5.4%
t 675589
 
4.7%
l 588096
 
4.1%
Other values (204) 4524248
31.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14381561
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1750981
 
12.2%
e 1489706
 
10.4%
r 1011821
 
7.0%
a 1010258
 
7.0%
o 879137
 
6.1%
s 853755
 
5.9%
i 816449
 
5.7%
n 781521
 
5.4%
t 675589
 
4.7%
l 588096
 
4.1%
Other values (204) 4524248
31.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14381561
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1750981
 
12.2%
e 1489706
 
10.4%
r 1011821
 
7.0%
a 1010258
 
7.0%
o 879137
 
6.1%
s 853755
 
5.9%
i 816449
 
5.7%
n 781521
 
5.4%
t 675589
 
4.7%
l 588096
 
4.1%
Other values (204) 4524248
31.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14381561
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1750981
 
12.2%
e 1489706
 
10.4%
r 1011821
 
7.0%
a 1010258
 
7.0%
o 879137
 
6.1%
s 853755
 
5.9%
i 816449
 
5.7%
n 781521
 
5.4%
t 675589
 
4.7%
l 588096
 
4.1%
Other values (204) 4524248
31.5%

country
Text

Missing 

Distinct252
Distinct (%)< 0.1%
Missing35185
Missing (%)1.2%
Memory size21.6 MiB
2025-03-13T15:37:40.163222image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length38
Median length33
Mean length12.21310559
Min length3

Characters and Unicode

Total characters34164392
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowItaly
2nd rowZimbabwe
3rd rowCzech Republic
4th rowSouth Africa
5th rowSlovakia
ValueCountFrequency (%)
republic 499399
 
9.8%
belgium 492245
 
9.7%
congo 483245
 
9.5%
of 477984
 
9.4%
the 477677
 
9.4%
democratic 477592
 
9.4%
france 280949
 
5.5%
country 171216
 
3.4%
unknown 171216
 
3.4%
usa 71240
 
1.4%
Other values (300) 1495455
29.3%
2025-03-13T15:37:40.382413image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2950275
 
8.6%
o 2764113
 
8.1%
n 2370161
 
6.9%
a 2360866
 
6.9%
i 2340562
 
6.9%
2300863
 
6.7%
c 1940807
 
5.7%
u 1682634
 
4.9%
r 1568696
 
4.6%
t 1475073
 
4.3%
Other values (53) 12410342
36.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 34164392
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2950275
 
8.6%
o 2764113
 
8.1%
n 2370161
 
6.9%
a 2360866
 
6.9%
i 2340562
 
6.9%
2300863
 
6.7%
c 1940807
 
5.7%
u 1682634
 
4.9%
r 1568696
 
4.6%
t 1475073
 
4.3%
Other values (53) 12410342
36.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 34164392
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2950275
 
8.6%
o 2764113
 
8.1%
n 2370161
 
6.9%
a 2360866
 
6.9%
i 2340562
 
6.9%
2300863
 
6.7%
c 1940807
 
5.7%
u 1682634
 
4.9%
r 1568696
 
4.6%
t 1475073
 
4.3%
Other values (53) 12410342
36.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 34164392
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2950275
 
8.6%
o 2764113
 
8.1%
n 2370161
 
6.9%
a 2360866
 
6.9%
i 2340562
 
6.9%
2300863
 
6.7%
c 1940807
 
5.7%
u 1682634
 
4.9%
r 1568696
 
4.6%
t 1475073
 
4.3%
Other values (53) 12410342
36.3%

countryCode
Text

Missing 

Distinct277
Distinct (%)< 0.1%
Missing39499
Missing (%)1.4%
Memory size21.6 MiB
2025-03-13T15:37:40.520844image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters5586082
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)< 0.1%

Sample

1st rowIT
2nd rowZW
3rd rowCZ
4th rowZA
5th rowSK
ValueCountFrequency (%)
be 492246
17.6%
cd 477592
17.1%
fr 280952
 
10.1%
zz 171206
 
6.1%
us 71240
 
2.6%
tz 60159
 
2.2%
br 57486
 
2.1%
es 56304
 
2.0%
cm 45325
 
1.6%
de 45144
 
1.6%
Other values (258) 1035387
37.1%
2025-03-13T15:37:40.695835image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 692483
12.4%
C 679896
12.2%
B 631354
11.3%
D 558996
10.0%
Z 515624
9.2%
R 479995
8.6%
F 309412
 
5.5%
M 185396
 
3.3%
T 183658
 
3.3%
S 183617
 
3.3%
Other values (27) 1165651
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5586082
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 692483
12.4%
C 679896
12.2%
B 631354
11.3%
D 558996
10.0%
Z 515624
9.2%
R 479995
8.6%
F 309412
 
5.5%
M 185396
 
3.3%
T 183658
 
3.3%
S 183617
 
3.3%
Other values (27) 1165651
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5586082
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 692483
12.4%
C 679896
12.2%
B 631354
11.3%
D 558996
10.0%
Z 515624
9.2%
R 479995
8.6%
F 309412
 
5.5%
M 185396
 
3.3%
T 183658
 
3.3%
S 183617
 
3.3%
Other values (27) 1165651
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5586082
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 692483
12.4%
C 679896
12.2%
B 631354
11.3%
D 558996
10.0%
Z 515624
9.2%
R 479995
8.6%
F 309412
 
5.5%
M 185396
 
3.3%
T 183658
 
3.3%
S 183617
 
3.3%
Other values (27) 1165651
20.9%

locality
Text

Missing 

Distinct1235078
Distinct (%)47.3%
Missing223764
Missing (%)7.9%
Memory size21.6 MiB
2025-03-13T15:37:41.230932image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length483
Median length319
Mean length31.92348289
Min length1

Characters and Unicode

Total characters83281216
Distinct characters749
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1030186 ?
Unique (%)39.5%

Sample

1st rowSicula; In montosis - Piana dei Greci
2nd rowDistrict Victoria, Makaholi Experiment Station, in the Legume Pasture Trial Plats in camp 17
3rd rowBohemia centr., distr.Praha: in locis graminosis prope vicum Modletice
4th rowRegio Transvaal, 2329BB, Louis Trichardt, open plot in town, Grassland
5th rowSlovakia orientalis: regio Slovenský kras: planities Silická planina, in colle Čertova Diera
ValueCountFrequency (%)
de 634811
 
5.0%
la 228613
 
1.8%
s.l 217561
 
1.7%
of 168954
 
1.3%
163088
 
1.3%
du 155684
 
1.2%
km 154105
 
1.2%
in 115082
 
0.9%
à 104145
 
0.8%
près 76416
 
0.6%
Other values (607239) 10758196
84.2%
2025-03-13T15:37:41.779109image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10167832
 
12.2%
e 7122348
 
8.6%
a 6811800
 
8.2%
r 4480827
 
5.4%
o 4376219
 
5.3%
i 4344112
 
5.2%
n 4265702
 
5.1%
s 3308918
 
4.0%
t 3205409
 
3.8%
l 3119121
 
3.7%
Other values (739) 32078928
38.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 83281216
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10167832
 
12.2%
e 7122348
 
8.6%
a 6811800
 
8.2%
r 4480827
 
5.4%
o 4376219
 
5.3%
i 4344112
 
5.2%
n 4265702
 
5.1%
s 3308918
 
4.0%
t 3205409
 
3.8%
l 3119121
 
3.7%
Other values (739) 32078928
38.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 83281216
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10167832
 
12.2%
e 7122348
 
8.6%
a 6811800
 
8.2%
r 4480827
 
5.4%
o 4376219
 
5.3%
i 4344112
 
5.2%
n 4265702
 
5.1%
s 3308918
 
4.0%
t 3205409
 
3.8%
l 3119121
 
3.7%
Other values (739) 32078928
38.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 83281216
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10167832
 
12.2%
e 7122348
 
8.6%
a 6811800
 
8.2%
r 4480827
 
5.4%
o 4376219
 
5.3%
i 4344112
 
5.2%
n 4265702
 
5.1%
s 3308918
 
4.0%
t 3205409
 
3.8%
l 3119121
 
3.7%
Other values (739) 32078928
38.5%

verbatimLocality
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:41.815582image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPetrorhagia saxifraga (L.) Link
ValueCountFrequency (%)
petrorhagia 1
25.0%
saxifraga 1
25.0%
l 1
25.0%
link 1
25.0%
2025-03-13T15:37:41.896362image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5
16.1%
3
 
9.7%
r 3
 
9.7%
i 3
 
9.7%
g 2
 
6.5%
L 2
 
6.5%
f 1
 
3.2%
n 1
 
3.2%
) 1
 
3.2%
. 1
 
3.2%
Other values (9) 9
29.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5
16.1%
3
 
9.7%
r 3
 
9.7%
i 3
 
9.7%
g 2
 
6.5%
L 2
 
6.5%
f 1
 
3.2%
n 1
 
3.2%
) 1
 
3.2%
. 1
 
3.2%
Other values (9) 9
29.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5
16.1%
3
 
9.7%
r 3
 
9.7%
i 3
 
9.7%
g 2
 
6.5%
L 2
 
6.5%
f 1
 
3.2%
n 1
 
3.2%
) 1
 
3.2%
. 1
 
3.2%
Other values (9) 9
29.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 31
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5
16.1%
3
 
9.7%
r 3
 
9.7%
i 3
 
9.7%
g 2
 
6.5%
L 2
 
6.5%
f 1
 
3.2%
n 1
 
3.2%
) 1
 
3.2%
. 1
 
3.2%
Other values (9) 9
29.0%

minimumDistanceAboveSurfaceInMeters
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:41.923593image/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%
2025-03-13T15:37:41.999691image/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%

maximumDistanceAboveSurfaceInMeters
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:42.025512image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

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

Unique1 ?
Unique (%)100.0%

Sample

1st rowTracheophyta
ValueCountFrequency (%)
tracheophyta 1
100.0%
2025-03-13T15:37:42.103634image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
16.7%
h 2
16.7%
T 1
8.3%
r 1
8.3%
c 1
8.3%
e 1
8.3%
o 1
8.3%
p 1
8.3%
y 1
8.3%
t 1
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2
16.7%
h 2
16.7%
T 1
8.3%
r 1
8.3%
c 1
8.3%
e 1
8.3%
o 1
8.3%
p 1
8.3%
y 1
8.3%
t 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2
16.7%
h 2
16.7%
T 1
8.3%
r 1
8.3%
c 1
8.3%
e 1
8.3%
o 1
8.3%
p 1
8.3%
y 1
8.3%
t 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2
16.7%
h 2
16.7%
T 1
8.3%
r 1
8.3%
c 1
8.3%
e 1
8.3%
o 1
8.3%
p 1
8.3%
y 1
8.3%
t 1
8.3%

locationAccordingTo
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:42.131284image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowMagnoliopsida
ValueCountFrequency (%)
magnoliopsida 1
100.0%
2025-03-13T15:37:42.215730image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
15.4%
o 2
15.4%
i 2
15.4%
M 1
7.7%
g 1
7.7%
n 1
7.7%
l 1
7.7%
p 1
7.7%
s 1
7.7%
d 1
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2
15.4%
o 2
15.4%
i 2
15.4%
M 1
7.7%
g 1
7.7%
n 1
7.7%
l 1
7.7%
p 1
7.7%
s 1
7.7%
d 1
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2
15.4%
o 2
15.4%
i 2
15.4%
M 1
7.7%
g 1
7.7%
n 1
7.7%
l 1
7.7%
p 1
7.7%
s 1
7.7%
d 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2
15.4%
o 2
15.4%
i 2
15.4%
M 1
7.7%
g 1
7.7%
n 1
7.7%
l 1
7.7%
p 1
7.7%
s 1
7.7%
d 1
7.7%

locationRemarks
Text

Missing 

Distinct256137
Distinct (%)18.4%
Missing1438676
Missing (%)50.8%
Memory size21.6 MiB
2025-03-13T15:37:42.315474image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1949
Median length1467
Mean length30.25952532
Min length10

Characters and Unicode

Total characters42177663
Distinct characters322
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210984 ?
Unique (%)15.1%

Sample

1st rowCountry: Rhodesia
2nd rowCountry: Bohemia
3rd rowCountry: Transvaal
4th rowCountry: Slovakia
5th rowCountry: C.b.s.
ValueCountFrequency (%)
country 1031623
 
18.0%
substate 202664
 
3.5%
description 195498
 
3.4%
congo 103925
 
1.8%
belge 91481
 
1.6%
de 72968
 
1.3%
france 66964
 
1.2%
vegetation 47783
 
0.8%
on 47676
 
0.8%
green 44807
 
0.8%
Other values (111920) 3823893
66.7%
2025-03-13T15:37:42.472770image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4335405
 
10.3%
e 3365597
 
8.0%
n 2922059
 
6.9%
r 2901703
 
6.9%
t 2846991
 
6.7%
o 2707692
 
6.4%
a 2438511
 
5.8%
u 2235998
 
5.3%
i 2029798
 
4.8%
s 1806050
 
4.3%
Other values (312) 14587859
34.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42177663
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4335405
 
10.3%
e 3365597
 
8.0%
n 2922059
 
6.9%
r 2901703
 
6.9%
t 2846991
 
6.7%
o 2707692
 
6.4%
a 2438511
 
5.8%
u 2235998
 
5.3%
i 2029798
 
4.8%
s 1806050
 
4.3%
Other values (312) 14587859
34.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42177663
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4335405
 
10.3%
e 3365597
 
8.0%
n 2922059
 
6.9%
r 2901703
 
6.9%
t 2846991
 
6.7%
o 2707692
 
6.4%
a 2438511
 
5.8%
u 2235998
 
5.3%
i 2029798
 
4.8%
s 1806050
 
4.3%
Other values (312) 14587859
34.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42177663
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4335405
 
10.3%
e 3365597
 
8.0%
n 2922059
 
6.9%
r 2901703
 
6.9%
t 2846991
 
6.7%
o 2707692
 
6.4%
a 2438511
 
5.8%
u 2235998
 
5.3%
i 2029798
 
4.8%
s 1806050
 
4.3%
Other values (312) 14587859
34.6%

decimalLatitude
Text

Missing 

Distinct42681
Distinct (%)6.2%
Missing2145432
Missing (%)75.7%
Memory size21.6 MiB
2025-03-13T15:37:42.609374image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.224311171
Min length1

Characters and Unicode

Total characters5650990
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

Unique17369 ?
Unique (%)2.5%

Sample

1st row9
2nd row4.033333
3rd row-29.316667
4th row-3.833333
5th row64.020833
ValueCountFrequency (%)
0.766667 8621
 
1.3%
0.056944 5554
 
0.8%
5.133333 4043
 
0.6%
0.767499 3721
 
0.5%
0.05 3710
 
0.5%
3.444444 2469
 
0.4%
2.883333 2322
 
0.3%
4 2263
 
0.3%
5.633333 1983
 
0.3%
5.137777 1974
 
0.3%
Other values (40157) 650448
94.7%
2025-03-13T15:37:42.823823image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 748646
13.2%
. 676844
12.0%
6 623790
11.0%
5 584726
10.3%
1 538038
9.5%
0 408432
7.2%
7 399037
7.1%
9 364473
6.4%
2 357909
6.3%
4 352925
6.2%
Other values (2) 596170
10.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5650990
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 748646
13.2%
. 676844
12.0%
6 623790
11.0%
5 584726
10.3%
1 538038
9.5%
0 408432
7.2%
7 399037
7.1%
9 364473
6.4%
2 357909
6.3%
4 352925
6.2%
Other values (2) 596170
10.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5650990
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 748646
13.2%
. 676844
12.0%
6 623790
11.0%
5 584726
10.3%
1 538038
9.5%
0 408432
7.2%
7 399037
7.1%
9 364473
6.4%
2 357909
6.3%
4 352925
6.2%
Other values (2) 596170
10.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5650990
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 748646
13.2%
. 676844
12.0%
6 623790
11.0%
5 584726
10.3%
1 538038
9.5%
0 408432
7.2%
7 399037
7.1%
9 364473
6.4%
2 357909
6.3%
4 352925
6.2%
Other values (2) 596170
10.5%

decimalLongitude
Text

Missing 

Distinct49783
Distinct (%)7.2%
Missing2145085
Missing (%)75.7%
Memory size21.6 MiB
2025-03-13T15:37:42.981071image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length11
Mean length7.856179677
Min length1

Characters and Unicode

Total characters5400770
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

Unique19158 ?
Unique (%)2.8%

Sample

1st row39.916667
2nd row32.85
3rd row2.5
4th row29.779166
5th row-21.218888
ValueCountFrequency (%)
24.45 8041
 
1.2%
18.309166 5385
 
0.8%
24.446944 3716
 
0.5%
18.316667 3577
 
0.5%
15.1 3099
 
0.5%
25.691944 2459
 
0.4%
29.55 2086
 
0.3%
0 2019
 
0.3%
15.071666 1974
 
0.3%
27.466667 1967
 
0.3%
Other values (47811) 653132
95.0%
2025-03-13T15:37:43.202803image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 784451
14.5%
. 679199
12.6%
6 641757
11.9%
4 496692
9.2%
2 464419
8.6%
1 450144
8.3%
5 448000
8.3%
7 415857
7.7%
9 394776
7.3%
8 381996
7.1%
Other values (12) 243479
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5400770
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 784451
14.5%
. 679199
12.6%
6 641757
11.9%
4 496692
9.2%
2 464419
8.6%
1 450144
8.3%
5 448000
8.3%
7 415857
7.7%
9 394776
7.3%
8 381996
7.1%
Other values (12) 243479
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5400770
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 784451
14.5%
. 679199
12.6%
6 641757
11.9%
4 496692
9.2%
2 464419
8.6%
1 450144
8.3%
5 448000
8.3%
7 415857
7.7%
9 394776
7.3%
8 381996
7.1%
Other values (12) 243479
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5400770
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 784451
14.5%
. 679199
12.6%
6 641757
11.9%
4 496692
9.2%
2 464419
8.6%
1 450144
8.3%
5 448000
8.3%
7 415857
7.7%
9 394776
7.3%
8 381996
7.1%
Other values (12) 243479
 
4.5%
Distinct168
Distinct (%)0.1%
Missing2561936
Missing (%)90.4%
Memory size21.6 MiB
2025-03-13T15:37:43.252677image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.964863786
Min length1

Characters and Unicode

Total characters1072908
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

Unique48 ?
Unique (%)< 0.1%

Sample

1st row1000
2nd row1000
3rd row1000
4th row10000
5th row1000
ValueCountFrequency (%)
1000 226965
83.9%
5000 16038
 
5.9%
2500 9844
 
3.6%
30 5049
 
1.9%
500 3393
 
1.3%
20000 3029
 
1.1%
250 1591
 
0.6%
100 725
 
0.3%
10000 616
 
0.2%
3000 277
 
0.1%
Other values (158) 3077
 
1.1%
2025-03-13T15:37:43.356253image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 788613
73.5%
1 229076
 
21.4%
5 31751
 
3.0%
2 15199
 
1.4%
3 5869
 
0.5%
7 880
 
0.1%
8 562
 
0.1%
6 379
 
< 0.1%
4 297
 
< 0.1%
9 282
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1072908
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 788613
73.5%
1 229076
 
21.4%
5 31751
 
3.0%
2 15199
 
1.4%
3 5869
 
0.5%
7 880
 
0.1%
8 562
 
0.1%
6 379
 
< 0.1%
4 297
 
< 0.1%
9 282
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1072908
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 788613
73.5%
1 229076
 
21.4%
5 31751
 
3.0%
2 15199
 
1.4%
3 5869
 
0.5%
7 880
 
0.1%
8 562
 
0.1%
6 379
 
< 0.1%
4 297
 
< 0.1%
9 282
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1072908
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 788613
73.5%
1 229076
 
21.4%
5 31751
 
3.0%
2 15199
 
1.4%
3 5869
 
0.5%
7 880
 
0.1%
8 562
 
0.1%
6 379
 
< 0.1%
4 297
 
< 0.1%
9 282
 
< 0.1%

pointRadiusSpatialFit
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:43.383920image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPetrorhagia
ValueCountFrequency (%)
petrorhagia 1
100.0%
2025-03-13T15:37:43.464202image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 2
18.2%
a 2
18.2%
P 1
9.1%
e 1
9.1%
t 1
9.1%
o 1
9.1%
h 1
9.1%
g 1
9.1%
i 1
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 2
18.2%
a 2
18.2%
P 1
9.1%
e 1
9.1%
t 1
9.1%
o 1
9.1%
h 1
9.1%
g 1
9.1%
i 1
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 2
18.2%
a 2
18.2%
P 1
9.1%
e 1
9.1%
t 1
9.1%
o 1
9.1%
h 1
9.1%
g 1
9.1%
i 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 2
18.2%
a 2
18.2%
P 1
9.1%
e 1
9.1%
t 1
9.1%
o 1
9.1%
h 1
9.1%
g 1
9.1%
i 1
9.1%

verbatimCoordinateSystem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:43.493054image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowsaxifraga
ValueCountFrequency (%)
saxifraga 1
100.0%
2025-03-13T15:37:43.577423image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3
33.3%
s 1
 
11.1%
x 1
 
11.1%
i 1
 
11.1%
f 1
 
11.1%
r 1
 
11.1%
g 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3
33.3%
s 1
 
11.1%
x 1
 
11.1%
i 1
 
11.1%
f 1
 
11.1%
r 1
 
11.1%
g 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3
33.3%
s 1
 
11.1%
x 1
 
11.1%
i 1
 
11.1%
f 1
 
11.1%
r 1
 
11.1%
g 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3
33.3%
s 1
 
11.1%
x 1
 
11.1%
i 1
 
11.1%
f 1
 
11.1%
r 1
 
11.1%
g 1
 
11.1%

georeferenceProtocol
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:43.607327image/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 rowICBN
ValueCountFrequency (%)
icbn 1
100.0%
2025-03-13T15:37:43.687787image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 1
25.0%
C 1
25.0%
B 1
25.0%
N 1
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
I 1
25.0%
C 1
25.0%
B 1
25.0%
N 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
I 1
25.0%
C 1
25.0%
B 1
25.0%
N 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
I 1
25.0%
C 1
25.0%
B 1
25.0%
N 1
25.0%

georeferenceSources
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2832539
Missing (%)> 99.9%
Memory size21.6 MiB
2025-03-13T15:37:43.717196image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowaccepted name
ValueCountFrequency (%)
accepted 1
50.0%
name 1
50.0%
2025-03-13T15:37:43.795420image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3
23.1%
a 2
15.4%
c 2
15.4%
p 1
 
7.7%
t 1
 
7.7%
d 1
 
7.7%
1
 
7.7%
n 1
 
7.7%
m 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3
23.1%
a 2
15.4%
c 2
15.4%
p 1
 
7.7%
t 1
 
7.7%
d 1
 
7.7%
1
 
7.7%
n 1
 
7.7%
m 1
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3
23.1%
a 2
15.4%
c 2
15.4%
p 1
 
7.7%
t 1
 
7.7%
d 1
 
7.7%
1
 
7.7%
n 1
 
7.7%
m 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3
23.1%
a 2
15.4%
c 2
15.4%
p 1
 
7.7%
t 1
 
7.7%
d 1
 
7.7%
1
 
7.7%
n 1
 
7.7%
m 1
 
7.7%

typeStatus
Text

Missing 

Distinct45836
Distinct (%)75.2%
Missing2771615
Missing (%)97.8%
Memory size21.6 MiB
2025-03-13T15:37:43.837057image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length155
Median length119
Mean length42.27701272
Min length18

Characters and Unicode

Total characters2575727
Distinct characters97
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36078 ?
Unique (%)59.2%

Sample

1st rowType of Monotes carrissoanus Bancr.
2nd rowType of Monotes hutchinsonianus Exell
3rd rowType of Clerodendrum swynnertonii S.Moore
4th rowType of Elatostema welwitschii var. cameroonense Rendle
5th rowType of Salacia pallescens Oliv.
ValueCountFrequency (%)
of 61435
 
17.0%
type 23399
 
6.5%
isotype 17856
 
5.0%
de 8240
 
2.3%
wild 7850
 
2.2%
7400
 
2.1%
var 7267
 
2.0%
syntype 6796
 
1.9%
holotype 6238
 
1.7%
ex 4267
 
1.2%
Other values (30428) 209737
58.2%
2025-03-13T15:37:43.955655image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
299560
 
11.6%
e 207866
 
8.1%
o 199267
 
7.7%
a 182164
 
7.1%
i 162206
 
6.3%
s 122790
 
4.8%
t 116014
 
4.5%
r 112450
 
4.4%
l 110345
 
4.3%
n 105044
 
4.1%
Other values (87) 958021
37.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2575727
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
299560
 
11.6%
e 207866
 
8.1%
o 199267
 
7.7%
a 182164
 
7.1%
i 162206
 
6.3%
s 122790
 
4.8%
t 116014
 
4.5%
r 112450
 
4.4%
l 110345
 
4.3%
n 105044
 
4.1%
Other values (87) 958021
37.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2575727
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
299560
 
11.6%
e 207866
 
8.1%
o 199267
 
7.7%
a 182164
 
7.1%
i 162206
 
6.3%
s 122790
 
4.8%
t 116014
 
4.5%
r 112450
 
4.4%
l 110345
 
4.3%
n 105044
 
4.1%
Other values (87) 958021
37.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2575727
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
299560
 
11.6%
e 207866
 
8.1%
o 199267
 
7.7%
a 182164
 
7.1%
i 162206
 
6.3%
s 122790
 
4.8%
t 116014
 
4.5%
r 112450
 
4.4%
l 110345
 
4.3%
n 105044
 
4.1%
Other values (87) 958021
37.2%
Distinct231162
Distinct (%)8.2%
Missing1
Missing (%)< 0.1%
Memory size21.6 MiB
2025-03-13T15:37:44.125172image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length144
Median length105
Mean length29.25051765
Min length5

Characters and Unicode

Total characters82853232
Distinct characters166
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92189 ?
Unique (%)3.3%

Sample

1st rowGalium verum L.
2nd rowLotononis bainesii Baker
3rd rowGalium verum L.
4th rowLotononis carinata Benth.
5th rowGalium verum L.
ValueCountFrequency (%)
l 694685
 
6.6%
256114
 
2.4%
ex 195621
 
1.9%
sp 154572
 
1.5%
subsp 100631
 
1.0%
var 93365
 
0.9%
dc 62668
 
0.6%
indet 56690
 
0.5%
de 48327
 
0.5%
benth 43995
 
0.4%
Other values (91908) 8862675
83.9%
2025-03-13T15:37:44.373677image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7736784
 
9.3%
a 7409727
 
8.9%
i 6008414
 
7.3%
e 5316463
 
6.4%
r 4559175
 
5.5%
s 4264807
 
5.1%
l 3990694
 
4.8%
. 3867363
 
4.7%
o 3778535
 
4.6%
n 3716684
 
4.5%
Other values (156) 32204586
38.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 82853232
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7736784
 
9.3%
a 7409727
 
8.9%
i 6008414
 
7.3%
e 5316463
 
6.4%
r 4559175
 
5.5%
s 4264807
 
5.1%
l 3990694
 
4.8%
. 3867363
 
4.7%
o 3778535
 
4.6%
n 3716684
 
4.5%
Other values (156) 32204586
38.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 82853232
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7736784
 
9.3%
a 7409727
 
8.9%
i 6008414
 
7.3%
e 5316463
 
6.4%
r 4559175
 
5.5%
s 4264807
 
5.1%
l 3990694
 
4.8%
. 3867363
 
4.7%
o 3778535
 
4.6%
n 3716684
 
4.5%
Other values (156) 32204586
38.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 82853232
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7736784
 
9.3%
a 7409727
 
8.9%
i 6008414
 
7.3%
e 5316463
 
6.4%
r 4559175
 
5.5%
s 4264807
 
5.1%
l 3990694
 
4.8%
. 3867363
 
4.7%
o 3778535
 
4.6%
n 3716684
 
4.5%
Other values (156) 32204586
38.9%

acceptedNameUsage
Text

Missing 

Distinct15439
Distinct (%)7.4%
Missing2625200
Missing (%)92.7%
Memory size21.6 MiB
2025-03-13T15:37:44.515832image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length129
Median length83
Mean length35.1144304
Min length12

Characters and Unicode

Total characters7280626
Distinct characters105
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4996 ?
Unique (%)2.4%

Sample

1st rowListia bainesii (Baker) B.-E.van Wyk & Boatwr.
2nd rowMaerua duchesnei (De Wild.) F.White
3rd rowLeobordea eriantha (Benth.) B.-E.van Wyk & Boatwr.
4th rowGalium verum L.
5th rowGalium verum subsp. wirtgenii (F.W.Schultz) Oborny
ValueCountFrequency (%)
l 52038
 
5.7%
37691
 
4.1%
subsp 19247
 
2.1%
ex 11820
 
1.3%
var 9980
 
1.1%
pers 6604
 
0.7%
dc 6014
 
0.7%
fr 5692
 
0.6%
de 3135
 
0.3%
persicaria 3037
 
0.3%
Other values (18848) 759767
83.0%
2025-03-13T15:37:44.727460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
707685
 
9.7%
a 611100
 
8.4%
i 486805
 
6.7%
e 457913
 
6.3%
r 406536
 
5.6%
s 382538
 
5.3%
. 349294
 
4.8%
l 339477
 
4.7%
o 337506
 
4.6%
n 314748
 
4.3%
Other values (95) 2887024
39.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7280626
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
707685
 
9.7%
a 611100
 
8.4%
i 486805
 
6.7%
e 457913
 
6.3%
r 406536
 
5.6%
s 382538
 
5.3%
. 349294
 
4.8%
l 339477
 
4.7%
o 337506
 
4.6%
n 314748
 
4.3%
Other values (95) 2887024
39.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7280626
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
707685
 
9.7%
a 611100
 
8.4%
i 486805
 
6.7%
e 457913
 
6.3%
r 406536
 
5.6%
s 382538
 
5.3%
. 349294
 
4.8%
l 339477
 
4.7%
o 337506
 
4.6%
n 314748
 
4.3%
Other values (95) 2887024
39.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7280626
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
707685
 
9.7%
a 611100
 
8.4%
i 486805
 
6.7%
e 457913
 
6.3%
r 406536
 
5.6%
s 382538
 
5.3%
. 349294
 
4.8%
l 339477
 
4.7%
o 337506
 
4.6%
n 314748
 
4.3%
Other values (95) 2887024
39.7%

kingdom
Text

Missing 

Distinct6
Distinct (%)< 0.1%
Missing28546
Missing (%)1.0%
Memory size21.6 MiB
2025-03-13T15:37:44.764982image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.835829178
Min length5

Characters and Unicode

Total characters19167624
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 2494470
89.0%
fungi 261803
 
9.3%
protozoa 27266
 
1.0%
chromista 15551
 
0.6%
bacteria 4150
 
0.1%
animalia 754
 
< 0.1%
2025-03-13T15:37:44.859996image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5041565
26.3%
n 2757027
14.4%
t 2541437
13.3%
P 2521736
13.2%
e 2498620
13.0%
l 2495224
13.0%
i 283012
 
1.5%
F 261803
 
1.4%
u 261803
 
1.4%
g 261803
 
1.4%
Other values (10) 243594
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19167624
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5041565
26.3%
n 2757027
14.4%
t 2541437
13.3%
P 2521736
13.2%
e 2498620
13.0%
l 2495224
13.0%
i 283012
 
1.5%
F 261803
 
1.4%
u 261803
 
1.4%
g 261803
 
1.4%
Other values (10) 243594
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19167624
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5041565
26.3%
n 2757027
14.4%
t 2541437
13.3%
P 2521736
13.2%
e 2498620
13.0%
l 2495224
13.0%
i 283012
 
1.5%
F 261803
 
1.4%
u 261803
 
1.4%
g 261803
 
1.4%
Other values (10) 243594
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19167624
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5041565
26.3%
n 2757027
14.4%
t 2541437
13.3%
P 2521736
13.2%
e 2498620
13.0%
l 2495224
13.0%
i 283012
 
1.5%
F 261803
 
1.4%
u 261803
 
1.4%
g 261803
 
1.4%
Other values (10) 243594
 
1.3%

phylum
Text

Missing 

Distinct32
Distinct (%)< 0.1%
Missing28665
Missing (%)1.0%
Memory size21.6 MiB
2025-03-13T15:37:44.891069image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length12
Mean length11.82914574
Min length7

Characters and Unicode

Total characters33167446
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowTracheophyta
2nd rowTracheophyta
3rd rowTracheophyta
4th rowTracheophyta
5th rowTracheophyta
ValueCountFrequency (%)
tracheophyta 2389693
85.2%
ascomycota 163254
 
5.8%
basidiomycota 98047
 
3.5%
bryophyta 44751
 
1.6%
mycetozoa 27227
 
1.0%
rhodophyta 23166
 
0.8%
marchantiophyta 20699
 
0.7%
ochrophyta 13397
 
0.5%
chlorophyta 12637
 
0.5%
cyanobacteria 4137
 
0.1%
Other values (22) 6867
 
0.2%
2025-03-13T15:37:44.977848image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5345266
16.1%
h 4971196
15.0%
o 3131156
9.4%
c 2882901
8.7%
y 2848118
8.6%
t 2824900
8.5%
p 2507871
7.6%
r 2490021
7.5%
e 2421397
7.3%
T 2389693
7.2%
Other values (22) 1354927
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33167446
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5345266
16.1%
h 4971196
15.0%
o 3131156
9.4%
c 2882901
8.7%
y 2848118
8.6%
t 2824900
8.5%
p 2507871
7.6%
r 2490021
7.5%
e 2421397
7.3%
T 2389693
7.2%
Other values (22) 1354927
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33167446
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5345266
16.1%
h 4971196
15.0%
o 3131156
9.4%
c 2882901
8.7%
y 2848118
8.6%
t 2824900
8.5%
p 2507871
7.6%
r 2490021
7.5%
e 2421397
7.3%
T 2389693
7.2%
Other values (22) 1354927
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33167446
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5345266
16.1%
h 4971196
15.0%
o 3131156
9.4%
c 2882901
8.7%
y 2848118
8.6%
t 2824900
8.5%
p 2507871
7.6%
r 2490021
7.5%
e 2421397
7.3%
T 2389693
7.2%
Other values (22) 1354927
 
4.1%

class
Text

Missing 

Distinct91
Distinct (%)< 0.1%
Missing29031
Missing (%)1.0%
Memory size21.6 MiB
2025-03-13T15:37:45.009163image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length13
Mean length12.66711575
Min length4

Characters and Unicode

Total characters35512373
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowMagnoliopsida
2nd rowMagnoliopsida
3rd rowMagnoliopsida
4th rowMagnoliopsida
5th rowMagnoliopsida
ValueCountFrequency (%)
magnoliopsida 1831671
65.3%
liliopsida 437861
 
15.6%
polypodiopsida 99756
 
3.6%
lecanoromycetes 90819
 
3.2%
agaricomycetes 74996
 
2.7%
bryopsida 40413
 
1.4%
myxomycetes 26950
 
1.0%
florideophyceae 22684
 
0.8%
dothideomycetes 19617
 
0.7%
jungermanniopsida 18975
 
0.7%
Other values (81) 139767
 
5.0%
2025-03-13T15:37:45.102276image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 5531203
15.6%
o 5047199
14.2%
a 4587751
12.9%
s 2751992
7.7%
d 2627333
7.4%
p 2623126
7.4%
l 2417403
6.8%
n 2033904
 
5.7%
g 1933656
 
5.4%
M 1860724
 
5.2%
Other values (34) 4098082
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 35512373
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 5531203
15.6%
o 5047199
14.2%
a 4587751
12.9%
s 2751992
7.7%
d 2627333
7.4%
p 2623126
7.4%
l 2417403
6.8%
n 2033904
 
5.7%
g 1933656
 
5.4%
M 1860724
 
5.2%
Other values (34) 4098082
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 35512373
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 5531203
15.6%
o 5047199
14.2%
a 4587751
12.9%
s 2751992
7.7%
d 2627333
7.4%
p 2623126
7.4%
l 2417403
6.8%
n 2033904
 
5.7%
g 1933656
 
5.4%
M 1860724
 
5.2%
Other values (34) 4098082
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 35512373
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 5531203
15.6%
o 5047199
14.2%
a 4587751
12.9%
s 2751992
7.7%
d 2627333
7.4%
p 2623126
7.4%
l 2417403
6.8%
n 2033904
 
5.7%
g 1933656
 
5.4%
M 1860724
 
5.2%
Other values (34) 4098082
11.5%

order
Text

Missing 

Distinct420
Distinct (%)< 0.1%
Missing29079
Missing (%)1.0%
Memory size21.6 MiB
2025-03-13T15:37:45.238181image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.520247294
Min length6

Characters and Unicode

Total characters26689642
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

Unique31 ?
Unique (%)< 0.1%

Sample

1st rowGentianales
2nd rowFabales
3rd rowGentianales
4th rowFabales
5th rowGentianales
ValueCountFrequency (%)
poales 291878
 
10.4%
asterales 220019
 
7.8%
fabales 215683
 
7.7%
lamiales 202411
 
7.2%
gentianales 189782
 
6.8%
malpighiales 145788
 
5.2%
rosales 119252
 
4.3%
caryophyllales 115447
 
4.1%
asparagales 84742
 
3.0%
polypodiales 79323
 
2.8%
Other values (410) 1139136
40.6%
2025-03-13T15:37:45.468624image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4565162
17.1%
l 3688588
13.8%
e 3524314
13.2%
s 3511980
13.2%
i 1533974
 
5.7%
r 1047644
 
3.9%
o 1046196
 
3.9%
n 857834
 
3.2%
t 698508
 
2.6%
p 639365
 
2.4%
Other values (39) 5576077
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26689642
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4565162
17.1%
l 3688588
13.8%
e 3524314
13.2%
s 3511980
13.2%
i 1533974
 
5.7%
r 1047644
 
3.9%
o 1046196
 
3.9%
n 857834
 
3.2%
t 698508
 
2.6%
p 639365
 
2.4%
Other values (39) 5576077
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26689642
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4565162
17.1%
l 3688588
13.8%
e 3524314
13.2%
s 3511980
13.2%
i 1533974
 
5.7%
r 1047644
 
3.9%
o 1046196
 
3.9%
n 857834
 
3.2%
t 698508
 
2.6%
p 639365
 
2.4%
Other values (39) 5576077
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26689642
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4565162
17.1%
l 3688588
13.8%
e 3524314
13.2%
s 3511980
13.2%
i 1533974
 
5.7%
r 1047644
 
3.9%
o 1046196
 
3.9%
n 857834
 
3.2%
t 698508
 
2.6%
p 639365
 
2.4%
Other values (39) 5576077
20.9%

family
Text

Distinct1544
Distinct (%)0.1%
Missing27842
Missing (%)1.0%
Memory size21.6 MiB
2025-03-13T15:37:45.596133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length18
Mean length10.79379063
Min length6

Characters and Unicode

Total characters30273323
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)< 0.1%

Sample

1st rowRubiaceae
2nd rowFabaceae
3rd rowRubiaceae
4th rowFabaceae
5th rowRubiaceae
ValueCountFrequency (%)
fabaceae 202840
 
7.2%
asteraceae 200990
 
7.2%
poaceae 180074
 
6.4%
rubiaceae 134796
 
4.8%
cyperaceae 88067
 
3.1%
rosaceae 85985
 
3.1%
lamiaceae 80675
 
2.9%
brassicaceae 53645
 
1.9%
caryophyllaceae 48945
 
1.7%
orchidaceae 46854
 
1.7%
Other values (1534) 1681827
60.0%
2025-03-13T15:37:45.799273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 7089383
23.4%
e 6472114
21.4%
c 3384662
11.2%
i 1364907
 
4.5%
r 1268548
 
4.2%
o 1118084
 
3.7%
l 924564
 
3.1%
n 860201
 
2.8%
t 772082
 
2.6%
s 684344
 
2.3%
Other values (45) 6334434
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30273323
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 7089383
23.4%
e 6472114
21.4%
c 3384662
11.2%
i 1364907
 
4.5%
r 1268548
 
4.2%
o 1118084
 
3.7%
l 924564
 
3.1%
n 860201
 
2.8%
t 772082
 
2.6%
s 684344
 
2.3%
Other values (45) 6334434
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30273323
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 7089383
23.4%
e 6472114
21.4%
c 3384662
11.2%
i 1364907
 
4.5%
r 1268548
 
4.2%
o 1118084
 
3.7%
l 924564
 
3.1%
n 860201
 
2.8%
t 772082
 
2.6%
s 684344
 
2.3%
Other values (45) 6334434
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30273323
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 7089383
23.4%
e 6472114
21.4%
c 3384662
11.2%
i 1364907
 
4.5%
r 1268548
 
4.2%
o 1118084
 
3.7%
l 924564
 
3.1%
n 860201
 
2.8%
t 772082
 
2.6%
s 684344
 
2.3%
Other values (45) 6334434
20.9%

genus
Text

Missing 

Distinct17967
Distinct (%)0.6%
Missing56666
Missing (%)2.0%
Memory size21.6 MiB
2025-03-13T15:37:45.943393image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.539478377
Min length2

Characters and Unicode

Total characters23704516
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

Unique2993 ?
Unique (%)0.1%

Sample

1st rowGalium
2nd rowLotononis
3rd rowGalium
4th rowLotononis
5th rowGalium
ValueCountFrequency (%)
carex 33926
 
1.2%
rubus 33018
 
1.2%
cyperus 18178
 
0.7%
ranunculus 17286
 
0.6%
rosa 17279
 
0.6%
hieracium 14398
 
0.5%
asplenium 14253
 
0.5%
cladonia 14203
 
0.5%
euphorbia 13736
 
0.5%
psychotria 13220
 
0.5%
Other values (17943) 2586377
93.2%
2025-03-13T15:37:46.171771image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2908346
 
12.3%
i 2160593
 
9.1%
e 1648255
 
7.0%
r 1589060
 
6.7%
o 1530328
 
6.5%
u 1349463
 
5.7%
s 1323963
 
5.6%
l 1272538
 
5.4%
n 1183858
 
5.0%
t 977024
 
4.1%
Other values (48) 7761088
32.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23704516
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2908346
 
12.3%
i 2160593
 
9.1%
e 1648255
 
7.0%
r 1589060
 
6.7%
o 1530328
 
6.5%
u 1349463
 
5.7%
s 1323963
 
5.6%
l 1272538
 
5.4%
n 1183858
 
5.0%
t 977024
 
4.1%
Other values (48) 7761088
32.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23704516
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2908346
 
12.3%
i 2160593
 
9.1%
e 1648255
 
7.0%
r 1589060
 
6.7%
o 1530328
 
6.5%
u 1349463
 
5.7%
s 1323963
 
5.6%
l 1272538
 
5.4%
n 1183858
 
5.0%
t 977024
 
4.1%
Other values (48) 7761088
32.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23704516
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2908346
 
12.3%
i 2160593
 
9.1%
e 1648255
 
7.0%
r 1589060
 
6.7%
o 1530328
 
6.5%
u 1349463
 
5.7%
s 1323963
 
5.6%
l 1272538
 
5.4%
n 1183858
 
5.0%
t 977024
 
4.1%
Other values (48) 7761088
32.7%
Distinct55819
Distinct (%)2.0%
Missing7583
Missing (%)0.3%
Memory size21.6 MiB
2025-03-13T15:37:46.334428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length24
Mean length8.608842542
Min length1

Characters and Unicode

Total characters24319610
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

Unique15965 ?
Unique (%)0.6%

Sample

1st rowverum
2nd rowbainesii
3rd rowverum
4th rowcarinata
5th rowverum
ValueCountFrequency (%)
sp 179465
 
6.4%
indet 23669
 
0.8%
vulgaris 12928
 
0.5%
arvensis 12177
 
0.4%
africana 11248
 
0.4%
palustris 9306
 
0.3%
officinalis 8346
 
0.3%
repens 7328
 
0.3%
abyssinica 7067
 
0.3%
alpina 6898
 
0.2%
Other values (55747) 2546547
90.1%
2025-03-13T15:37:46.594401image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3140452
12.9%
i 2757742
11.3%
s 1993341
 
8.2%
e 1747882
 
7.2%
r 1580869
 
6.5%
l 1512668
 
6.2%
n 1491143
 
6.1%
u 1436345
 
5.9%
o 1328179
 
5.5%
t 1255121
 
5.2%
Other values (50) 6075868
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24319610
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3140452
12.9%
i 2757742
11.3%
s 1993341
 
8.2%
e 1747882
 
7.2%
r 1580869
 
6.5%
l 1512668
 
6.2%
n 1491143
 
6.1%
u 1436345
 
5.9%
o 1328179
 
5.5%
t 1255121
 
5.2%
Other values (50) 6075868
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24319610
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3140452
12.9%
i 2757742
11.3%
s 1993341
 
8.2%
e 1747882
 
7.2%
r 1580869
 
6.5%
l 1512668
 
6.2%
n 1491143
 
6.1%
u 1436345
 
5.9%
o 1328179
 
5.5%
t 1255121
 
5.2%
Other values (50) 6075868
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24319610
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3140452
12.9%
i 2757742
11.3%
s 1993341
 
8.2%
e 1747882
 
7.2%
r 1580869
 
6.5%
l 1512668
 
6.2%
n 1491143
 
6.1%
u 1436345
 
5.9%
o 1328179
 
5.5%
t 1255121
 
5.2%
Other values (50) 6075868
25.0%

nomenclaturalCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size21.6 MiB
2025-03-13T15:37:46.643694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters11330156
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowICBN
2nd rowICBN
3rd rowICBN
4th rowICBN
5th rowICBN
ValueCountFrequency (%)
icbn 2832539
100.0%
2025-03-13T15:37:46.733919image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 2832539
25.0%
C 2832539
25.0%
B 2832539
25.0%
N 2832539
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11330156
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
I 2832539
25.0%
C 2832539
25.0%
B 2832539
25.0%
N 2832539
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11330156
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
I 2832539
25.0%
C 2832539
25.0%
B 2832539
25.0%
N 2832539
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11330156
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
I 2832539
25.0%
C 2832539
25.0%
B 2832539
25.0%
N 2832539
25.0%

taxonomicStatus
Text

Missing 

Distinct13
Distinct (%)< 0.1%
Missing314930
Missing (%)11.1%
Memory size21.6 MiB
2025-03-13T15:37:46.767380image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length13
Mean length12.86664892
Min length7

Characters and Unicode

Total characters32393204
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowaccepted name
2nd rowaccepted name
3rd rowunchecked name
4th rowaccepted name
5th rowaccepted name
ValueCountFrequency (%)
name 2385812
48.5%
accepted 2026029
41.2%
unchecked 355273
 
7.2%
synonym 105556
 
2.1%
tentative 17008
 
0.3%
orthog 4852
 
0.1%
variant 4852
 
0.1%
invalid 4502
 
0.1%
later 1927
 
< 0.1%
homonym 1927
 
< 0.1%
Other values (11) 8066
 
0.2%
2025-03-13T15:37:46.879171image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 7185390
22.2%
c 4762609
14.7%
a 4445070
13.7%
n 2987867
9.2%
m 2497083
 
7.7%
2398194
 
7.4%
d 2388262
 
7.4%
t 2091826
 
6.5%
p 2026203
 
6.3%
h 362052
 
1.1%
Other values (13) 1248648
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 32393204
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 7185390
22.2%
c 4762609
14.7%
a 4445070
13.7%
n 2987867
9.2%
m 2497083
 
7.7%
2398194
 
7.4%
d 2388262
 
7.4%
t 2091826
 
6.5%
p 2026203
 
6.3%
h 362052
 
1.1%
Other values (13) 1248648
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 32393204
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 7185390
22.2%
c 4762609
14.7%
a 4445070
13.7%
n 2987867
9.2%
m 2497083
 
7.7%
2398194
 
7.4%
d 2388262
 
7.4%
t 2091826
 
6.5%
p 2026203
 
6.3%
h 362052
 
1.1%
Other values (13) 1248648
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 32393204
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 7185390
22.2%
c 4762609
14.7%
a 4445070
13.7%
n 2987867
9.2%
m 2497083
 
7.7%
2398194
 
7.4%
d 2388262
 
7.4%
t 2091826
 
6.5%
p 2026203
 
6.3%
h 362052
 
1.1%
Other values (13) 1248648
 
3.9%