Overview

Brought to you by YData

Dataset statistics

Number of variables49
Number of observations289628
Missing cells6084825
Missing cells (%)42.9%
Total size in memory108.3 MiB
Average record size in memory392.0 B

Variable types

Text49

Dataset

DescriptionNaturalis Biodiversity Center (NL) - Aves 0061686-241126133413365
URLhttps://doi.org/10.15468/dxmzbz

Alerts

license has constant value "CC0 1.0" Constant
rightsHolder has constant value "Naturalis Biodiversity Center" Constant
institutionID has constant value "https://ror.org/0566bfb96" Constant
collectionCode has constant value "Aves" Constant
associatedTaxa has constant value "has parasite: Cirrophthirius cf. recurvirostrae | Quadraceps sp." Constant
locationAccordingTo has constant value "45.0083" Constant
locationRemarks has constant value "128.0083" Constant
geodeticDatum has constant value "WGS84" Constant
namePublishedInID has constant value "Crossoptilon mantchuricum Swinhoe" Constant
namePublishedIn has constant value "Animalia" Constant
namePublishedInYear has constant value "Animalia" Constant
kingdom has constant value "Animalia" Constant
tribe has constant value "Crossoptilon" Constant
subgenus has constant value "mantchuricum" Constant
nomenclaturalCode has constant value "ICZN" Constant
recordNumber has 276338 (95.4%) missing values Missing
recordedBy has 92827 (32.1%) missing values Missing
individualCount has 30538 (10.5%) missing values Missing
sex has 98166 (33.9%) missing values Missing
lifeStage has 206842 (71.4%) missing values Missing
associatedTaxa has 289625 (> 99.9%) missing values Missing
eventDate has 74040 (25.6%) missing values Missing
verbatimEventDate has 59530 (20.6%) missing values Missing
island has 200031 (69.1%) missing values Missing
country has 45132 (15.6%) missing values Missing
stateProvince has 136488 (47.1%) missing values Missing
locality has 78963 (27.3%) missing values Missing
verbatimElevation has 287041 (99.1%) missing values Missing
locationAccordingTo has 289627 (> 99.9%) missing values Missing
locationRemarks has 289627 (> 99.9%) missing values Missing
decimalLatitude has 136554 (47.1%) missing values Missing
decimalLongitude has 135979 (46.9%) missing values Missing
coordinateUncertaintyInMeters has 287974 (99.4%) missing values Missing
typeStatus has 286162 (98.8%) missing values Missing
identifiedBy has 289216 (99.9%) missing values Missing
dateIdentified has 289371 (99.9%) missing values Missing
namePublishedInID has 289627 (> 99.9%) missing values Missing
namePublishedIn has 289627 (> 99.9%) missing values Missing
namePublishedInYear has 289627 (> 99.9%) missing values Missing
class has 286898 (99.1%) missing values Missing
order has 287366 (99.2%) missing values Missing
family has 74054 (25.6%) missing values Missing
tribe has 289627 (> 99.9%) missing values Missing
subgenus has 289627 (> 99.9%) missing values Missing
infraspecificEpithet has 89169 (30.8%) missing values Missing
scientificNameAuthorship has 17143 (5.9%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique
catalogNumber has unique values Unique

Reproduction

Analysis started2025-02-28 17:41:49.585540
Analysis finished2025-02-28 17:41:55.630726
Duration6.05 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct289628
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:55.829360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2896280
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

Unique289628 ?
Unique (%)100.0%

Sample

1st row2434047501
2nd row2434047502
3rd row2434047503
4th row2434047504
5th row2434047505
ValueCountFrequency (%)
2434047501 1
 
< 0.1%
2433858683 1
 
< 0.1%
2434047506 1
 
< 0.1%
2434047507 1
 
< 0.1%
2434047508 1
 
< 0.1%
2434047523 1
 
< 0.1%
2434047509 1
 
< 0.1%
2433858690 1
 
< 0.1%
2433858838 1
 
< 0.1%
2434047504 1
 
< 0.1%
Other values (289618) 289618
> 99.9%
2025-02-28T12:41:56.085171image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 645268
22.3%
3 506883
17.5%
2 475626
16.4%
1 243866
 
8.4%
0 212854
 
7.3%
9 194666
 
6.7%
8 173529
 
6.0%
7 150795
 
5.2%
5 148418
 
5.1%
6 144375
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2896280
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 645268
22.3%
3 506883
17.5%
2 475626
16.4%
1 243866
 
8.4%
0 212854
 
7.3%
9 194666
 
6.7%
8 173529
 
6.0%
7 150795
 
5.2%
5 148418
 
5.1%
6 144375
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2896280
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 645268
22.3%
3 506883
17.5%
2 475626
16.4%
1 243866
 
8.4%
0 212854
 
7.3%
9 194666
 
6.7%
8 173529
 
6.0%
7 150795
 
5.2%
5 148418
 
5.1%
6 144375
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2896280
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 645268
22.3%
3 506883
17.5%
2 475626
16.4%
1 243866
 
8.4%
0 212854
 
7.3%
9 194666
 
6.7%
8 173529
 
6.0%
7 150795
 
5.2%
5 148418
 
5.1%
6 144375
 
5.0%

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:56.133987image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2027396
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCC0 1.0
2nd rowCC0 1.0
3rd rowCC0 1.0
4th rowCC0 1.0
5th rowCC0 1.0
ValueCountFrequency (%)
cc0 289628
50.0%
1.0 289628
50.0%
2025-02-28T12:41:56.215273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 579256
28.6%
0 579256
28.6%
289628
14.3%
1 289628
14.3%
. 289628
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2027396
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 579256
28.6%
0 579256
28.6%
289628
14.3%
1 289628
14.3%
. 289628
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2027396
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 579256
28.6%
0 579256
28.6%
289628
14.3%
1 289628
14.3%
. 289628
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2027396
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 579256
28.6%
0 579256
28.6%
289628
14.3%
1 289628
14.3%
. 289628
14.3%
Distinct1169
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:56.251095image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2896280
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

Unique229 ?
Unique (%)0.1%

Sample

1st row2015/06/05
2nd row2023/05/16
3rd row2015/09/02
4th row2017/07/01
5th row2015/05/23
ValueCountFrequency (%)
2017/06/30 47834
16.5%
2023/05/16 41000
14.2%
2017/07/01 26280
 
9.1%
2015/05/23 17611
 
6.1%
2015/07/03 13223
 
4.6%
2015/05/18 11421
 
3.9%
2015/07/01 10549
 
3.6%
2015/06/24 9657
 
3.3%
2015/07/02 9646
 
3.3%
2015/06/23 9602
 
3.3%
Other values (1159) 92805
32.0%
2025-02-28T12:41:56.344886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 730395
25.2%
/ 579256
20.0%
2 487219
16.8%
1 369028
12.7%
5 235720
 
8.1%
3 146696
 
5.1%
6 141889
 
4.9%
7 139337
 
4.8%
8 26564
 
0.9%
9 21312
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2896280
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 730395
25.2%
/ 579256
20.0%
2 487219
16.8%
1 369028
12.7%
5 235720
 
8.1%
3 146696
 
5.1%
6 141889
 
4.9%
7 139337
 
4.8%
8 26564
 
0.9%
9 21312
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2896280
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 730395
25.2%
/ 579256
20.0%
2 487219
16.8%
1 369028
12.7%
5 235720
 
8.1%
3 146696
 
5.1%
6 141889
 
4.9%
7 139337
 
4.8%
8 26564
 
0.9%
9 21312
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2896280
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 730395
25.2%
/ 579256
20.0%
2 487219
16.8%
1 369028
12.7%
5 235720
 
8.1%
3 146696
 
5.1%
6 141889
 
4.9%
7 139337
 
4.8%
8 26564
 
0.9%
9 21312
 
0.7%

rightsHolder
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:56.376699image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters8399212
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNaturalis Biodiversity Center
2nd rowNaturalis Biodiversity Center
3rd rowNaturalis Biodiversity Center
4th rowNaturalis Biodiversity Center
5th rowNaturalis Biodiversity Center
ValueCountFrequency (%)
naturalis 289628
33.3%
biodiversity 289628
33.3%
center 289628
33.3%
2025-02-28T12:41:56.456887image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1158512
13.8%
t 868884
10.3%
r 868884
10.3%
e 868884
10.3%
579256
 
6.9%
s 579256
 
6.9%
a 579256
 
6.9%
d 289628
 
3.4%
C 289628
 
3.4%
y 289628
 
3.4%
Other values (7) 2027396
24.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8399212
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1158512
13.8%
t 868884
10.3%
r 868884
10.3%
e 868884
10.3%
579256
 
6.9%
s 579256
 
6.9%
a 579256
 
6.9%
d 289628
 
3.4%
C 289628
 
3.4%
y 289628
 
3.4%
Other values (7) 2027396
24.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8399212
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1158512
13.8%
t 868884
10.3%
r 868884
10.3%
e 868884
10.3%
579256
 
6.9%
s 579256
 
6.9%
a 579256
 
6.9%
d 289628
 
3.4%
C 289628
 
3.4%
y 289628
 
3.4%
Other values (7) 2027396
24.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8399212
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1158512
13.8%
t 868884
10.3%
r 868884
10.3%
e 868884
10.3%
579256
 
6.9%
s 579256
 
6.9%
a 579256
 
6.9%
d 289628
 
3.4%
C 289628
 
3.4%
y 289628
 
3.4%
Other values (7) 2027396
24.1%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:56.484573image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters7240700
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://ror.org/0566bfb96
2nd rowhttps://ror.org/0566bfb96
3rd rowhttps://ror.org/0566bfb96
4th rowhttps://ror.org/0566bfb96
5th rowhttps://ror.org/0566bfb96
ValueCountFrequency (%)
https://ror.org/0566bfb96 289628
100.0%
2025-02-28T12:41:56.562942image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 868884
12.0%
r 868884
12.0%
6 868884
12.0%
t 579256
 
8.0%
o 579256
 
8.0%
b 579256
 
8.0%
h 289628
 
4.0%
p 289628
 
4.0%
s 289628
 
4.0%
: 289628
 
4.0%
Other values (6) 1737768
24.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7240700
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 868884
12.0%
r 868884
12.0%
6 868884
12.0%
t 579256
 
8.0%
o 579256
 
8.0%
b 579256
 
8.0%
h 289628
 
4.0%
p 289628
 
4.0%
s 289628
 
4.0%
: 289628
 
4.0%
Other values (6) 1737768
24.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7240700
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 868884
12.0%
r 868884
12.0%
6 868884
12.0%
t 579256
 
8.0%
o 579256
 
8.0%
b 579256
 
8.0%
h 289628
 
4.0%
p 289628
 
4.0%
s 289628
 
4.0%
: 289628
 
4.0%
Other values (6) 1737768
24.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7240700
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 868884
12.0%
r 868884
12.0%
6 868884
12.0%
t 579256
 
8.0%
o 579256
 
8.0%
b 579256
 
8.0%
h 289628
 
4.0%
p 289628
 
4.0%
s 289628
 
4.0%
: 289628
 
4.0%
Other values (6) 1737768
24.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:56.589864image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1158512
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 rowAves
2nd rowAves
3rd rowAves
4th rowAves
5th rowAves
ValueCountFrequency (%)
aves 289628
100.0%
2025-02-28T12:41:56.666129image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 289628
25.0%
v 289628
25.0%
e 289628
25.0%
s 289628
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1158512
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 289628
25.0%
v 289628
25.0%
e 289628
25.0%
s 289628
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1158512
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 289628
25.0%
v 289628
25.0%
e 289628
25.0%
s 289628
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1158512
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 289628
25.0%
v 289628
25.0%
e 289628
25.0%
s 289628
25.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:56.694118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length16.99979284
Min length13

Characters and Unicode

Total characters4923616
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 289613
> 99.9%
otherspecimen 15
 
< 0.1%
2025-02-28T12:41:56.781727image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1448110
29.4%
r 579241
 
11.8%
S 289628
 
5.9%
p 289628
 
5.9%
c 289628
 
5.9%
i 289628
 
5.9%
m 289628
 
5.9%
n 289628
 
5.9%
P 289613
 
5.9%
s 289613
 
5.9%
Other values (5) 579271
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4923616
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1448110
29.4%
r 579241
 
11.8%
S 289628
 
5.9%
p 289628
 
5.9%
c 289628
 
5.9%
i 289628
 
5.9%
m 289628
 
5.9%
n 289628
 
5.9%
P 289613
 
5.9%
s 289613
 
5.9%
Other values (5) 579271
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4923616
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1448110
29.4%
r 579241
 
11.8%
S 289628
 
5.9%
p 289628
 
5.9%
c 289628
 
5.9%
i 289628
 
5.9%
m 289628
 
5.9%
n 289628
 
5.9%
P 289613
 
5.9%
s 289613
 
5.9%
Other values (5) 579271
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4923616
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1448110
29.4%
r 579241
 
11.8%
S 289628
 
5.9%
p 289628
 
5.9%
c 289628
 
5.9%
i 289628
 
5.9%
m 289628
 
5.9%
n 289628
 
5.9%
P 289613
 
5.9%
s 289613
 
5.9%
Other values (5) 579271
11.8%

occurrenceID
Text

Unique 

Distinct289628
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:56.896378image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length77
Median length71
Mean length67.19895521
Min length62

Characters and Unicode

Total characters19462699
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

Unique289628 ?
Unique (%)100.0%

Sample

1st rowhttps://data.biodiversitydata.nl/naturalis/specimen/ZMA.AVES.2
2nd rowhttps://data.biodiversitydata.nl/naturalis/specimen/RMNH.AVES.4
3rd rowhttps://data.biodiversitydata.nl/naturalis/specimen/ZMA.AVES.18
4th rowhttps://data.biodiversitydata.nl/naturalis/specimen/ZMA.AVES.27
5th rowhttps://data.biodiversitydata.nl/naturalis/specimen/ZMA.AVES.36
ValueCountFrequency (%)
https://data.biodiversitydata.nl/naturalis/specimen/zma.aves.2 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/rmnh.5069738 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/zma.aves.45 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/zma.aves.54 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/zma.aves.72 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/zma.aves.222 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/zma.aves.81 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/rmnh.5069558 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/rmnh.5069792 1
 
< 0.1%
https://data.biodiversitydata.nl/naturalis/specimen/zma.aves.27 1
 
< 0.1%
Other values (289618) 289618
> 99.9%
2025-02-28T12:41:57.084927image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1740739
 
8.9%
t 1737768
 
8.9%
/ 1448140
 
7.4%
i 1448140
 
7.4%
. 1166174
 
6.0%
s 1158512
 
6.0%
d 868963
 
4.5%
e 868894
 
4.5%
n 868884
 
4.5%
l 579256
 
3.0%
Other values (34) 7577229
38.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19462699
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1740739
 
8.9%
t 1737768
 
8.9%
/ 1448140
 
7.4%
i 1448140
 
7.4%
. 1166174
 
6.0%
s 1158512
 
6.0%
d 868963
 
4.5%
e 868894
 
4.5%
n 868884
 
4.5%
l 579256
 
3.0%
Other values (34) 7577229
38.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19462699
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1740739
 
8.9%
t 1737768
 
8.9%
/ 1448140
 
7.4%
i 1448140
 
7.4%
. 1166174
 
6.0%
s 1158512
 
6.0%
d 868963
 
4.5%
e 868894
 
4.5%
n 868884
 
4.5%
l 579256
 
3.0%
Other values (34) 7577229
38.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19462699
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1740739
 
8.9%
t 1737768
 
8.9%
/ 1448140
 
7.4%
i 1448140
 
7.4%
. 1166174
 
6.0%
s 1158512
 
6.0%
d 868963
 
4.5%
e 868894
 
4.5%
n 868884
 
4.5%
l 579256
 
3.0%
Other values (34) 7577229
38.9%

catalogNumber
Text

Unique 

Distinct289628
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:57.258959image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length19
Mean length15.19895521
Min length10

Characters and Unicode

Total characters4402043
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique289628 ?
Unique (%)100.0%

Sample

1st rowZMA.AVES.2
2nd rowRMNH.AVES.4
3rd rowZMA.AVES.18
4th rowZMA.AVES.27
5th rowZMA.AVES.36
ValueCountFrequency (%)
zma.aves.2 1
 
< 0.1%
rmnh.5069738 1
 
< 0.1%
zma.aves.45 1
 
< 0.1%
zma.aves.54 1
 
< 0.1%
zma.aves.72 1
 
< 0.1%
zma.aves.222 1
 
< 0.1%
zma.aves.81 1
 
< 0.1%
rmnh.5069558 1
 
< 0.1%
rmnh.5069792 1
 
< 0.1%
zma.aves.27 1
 
< 0.1%
Other values (289618) 289618
> 99.9%
2025-02-28T12:41:57.497590image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 586918
13.3%
A 352650
 
8.0%
M 289627
 
6.6%
E 287857
 
6.5%
V 287856
 
6.5%
S 287856
 
6.5%
1 228550
 
5.2%
N 224833
 
5.1%
R 224833
 
5.1%
H 224833
 
5.1%
Other values (21) 1406230
31.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4402043
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 586918
13.3%
A 352650
 
8.0%
M 289627
 
6.6%
E 287857
 
6.5%
V 287856
 
6.5%
S 287856
 
6.5%
1 228550
 
5.2%
N 224833
 
5.1%
R 224833
 
5.1%
H 224833
 
5.1%
Other values (21) 1406230
31.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4402043
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 586918
13.3%
A 352650
 
8.0%
M 289627
 
6.6%
E 287857
 
6.5%
V 287856
 
6.5%
S 287856
 
6.5%
1 228550
 
5.2%
N 224833
 
5.1%
R 224833
 
5.1%
H 224833
 
5.1%
Other values (21) 1406230
31.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4402043
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 586918
13.3%
A 352650
 
8.0%
M 289627
 
6.6%
E 287857
 
6.5%
V 287856
 
6.5%
S 287856
 
6.5%
1 228550
 
5.2%
N 224833
 
5.1%
R 224833
 
5.1%
H 224833
 
5.1%
Other values (21) 1406230
31.9%

recordNumber
Text

Missing 

Distinct5837
Distinct (%)43.9%
Missing276338
Missing (%)95.4%
Memory size2.2 MiB
2025-02-28T12:41:57.544606image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length22
Mean length4.631226486
Min length1

Characters and Unicode

Total characters61549
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4106 ?
Unique (%)30.9%

Sample

1st row1.3
2nd row4.3
3rd row6.4
4th row15
5th row175
ValueCountFrequency (%)
no 3016
 
17.2%
reg 601
 
3.4%
reg.no 175
 
1.0%
n 85
 
0.5%
verz 57
 
0.3%
coll.-no 49
 
0.3%
2 47
 
0.3%
3 41
 
0.2%
1 41
 
0.2%
6 34
 
0.2%
Other values (4160) 13389
76.4%
2025-02-28T12:41:57.634429image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7134
11.6%
4 4703
 
7.6%
3 4671
 
7.6%
2 4607
 
7.5%
4247
 
6.9%
. 4085
 
6.6%
5 3931
 
6.4%
6 3619
 
5.9%
7 3512
 
5.7%
o 3431
 
5.6%
Other values (63) 17609
28.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 61549
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 7134
11.6%
4 4703
 
7.6%
3 4671
 
7.6%
2 4607
 
7.5%
4247
 
6.9%
. 4085
 
6.6%
5 3931
 
6.4%
6 3619
 
5.9%
7 3512
 
5.7%
o 3431
 
5.6%
Other values (63) 17609
28.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 61549
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 7134
11.6%
4 4703
 
7.6%
3 4671
 
7.6%
2 4607
 
7.5%
4247
 
6.9%
. 4085
 
6.6%
5 3931
 
6.4%
6 3619
 
5.9%
7 3512
 
5.7%
o 3431
 
5.6%
Other values (63) 17609
28.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 61549
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 7134
11.6%
4 4703
 
7.6%
3 4671
 
7.6%
2 4607
 
7.5%
4247
 
6.9%
. 4085
 
6.6%
5 3931
 
6.4%
6 3619
 
5.9%
7 3512
 
5.7%
o 3431
 
5.6%
Other values (63) 17609
28.6%

recordedBy
Text

Missing 

Distinct11879
Distinct (%)6.0%
Missing92827
Missing (%)32.1%
Memory size2.2 MiB
2025-02-28T12:41:57.758733image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length252
Median length227
Mean length15.05751495
Min length2

Characters and Unicode

Total characters2963334
Distinct characters102
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6885 ?
Unique (%)3.5%

Sample

1st rowVan der Spruyt G.S.
2nd rowGroen J.
3rd rowPollen&vDam cf Apr'63-Jun'66
4th rowPloos van Amstel D.
5th rowEbels E.
ValueCountFrequency (%)
van 28340
 
5.3%
not 14646
 
2.7%
stated 13574
 
2.5%
12974
 
2.4%
bartels 11506
 
2.2%
j 10745
 
2.0%
de 10419
 
2.0%
heurn 8672
 
1.6%
m.e.g 8315
 
1.6%
f 7204
 
1.4%
Other values (8570) 406910
76.3%
2025-02-28T12:41:57.964024image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 346161
 
11.7%
338325
 
11.4%
e 266038
 
9.0%
n 166306
 
5.6%
a 146851
 
5.0%
r 141966
 
4.8%
o 124914
 
4.2%
t 117243
 
4.0%
s 116206
 
3.9%
l 82761
 
2.8%
Other values (92) 1116563
37.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2963334
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 346161
 
11.7%
338325
 
11.4%
e 266038
 
9.0%
n 166306
 
5.6%
a 146851
 
5.0%
r 141966
 
4.8%
o 124914
 
4.2%
t 117243
 
4.0%
s 116206
 
3.9%
l 82761
 
2.8%
Other values (92) 1116563
37.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2963334
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 346161
 
11.7%
338325
 
11.4%
e 266038
 
9.0%
n 166306
 
5.6%
a 146851
 
5.0%
r 141966
 
4.8%
o 124914
 
4.2%
t 117243
 
4.0%
s 116206
 
3.9%
l 82761
 
2.8%
Other values (92) 1116563
37.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2963334
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 346161
 
11.7%
338325
 
11.4%
e 266038
 
9.0%
n 166306
 
5.6%
a 146851
 
5.0%
r 141966
 
4.8%
o 124914
 
4.2%
t 117243
 
4.0%
s 116206
 
3.9%
l 82761
 
2.8%
Other values (92) 1116563
37.7%

individualCount
Text

Missing 

Distinct54
Distinct (%)< 0.1%
Missing30538
Missing (%)10.5%
Memory size2.2 MiB
2025-02-28T12:41:58.005148image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.003743873
Min length1

Characters and Unicode

Total characters260060
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

Unique8 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 227379
87.8%
2 11832
 
4.6%
3 6214
 
2.4%
4 5617
 
2.2%
5 3939
 
1.5%
6 1721
 
0.7%
7 695
 
0.3%
8 426
 
0.2%
9 305
 
0.1%
10 260
 
0.1%
Other values (44) 702
 
0.3%
2025-02-28T12:41:58.093822image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 228230
87.8%
2 12051
 
4.6%
3 6372
 
2.5%
4 5687
 
2.2%
5 4035
 
1.6%
6 1786
 
0.7%
7 749
 
0.3%
8 468
 
0.2%
9 372
 
0.1%
0 310
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 260060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 228230
87.8%
2 12051
 
4.6%
3 6372
 
2.5%
4 5687
 
2.2%
5 4035
 
1.6%
6 1786
 
0.7%
7 749
 
0.3%
8 468
 
0.2%
9 372
 
0.1%
0 310
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 260060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 228230
87.8%
2 12051
 
4.6%
3 6372
 
2.5%
4 5687
 
2.2%
5 4035
 
1.6%
6 1786
 
0.7%
7 749
 
0.3%
8 468
 
0.2%
9 372
 
0.1%
0 310
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 260060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 228230
87.8%
2 12051
 
4.6%
3 6372
 
2.5%
4 5687
 
2.2%
5 4035
 
1.6%
6 1786
 
0.7%
7 749
 
0.3%
8 468
 
0.2%
9 372
 
0.1%
0 310
 
0.1%

sex
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing98166
Missing (%)33.9%
Memory size2.2 MiB
2025-02-28T12:41:58.120508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.830525117
Min length4

Characters and Unicode

Total characters924862
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfemale
2nd rowfemale
3rd rowmale
4th rowmale
5th rowfemale
ValueCountFrequency (%)
male 111955
58.5%
female 79507
41.5%
2025-02-28T12:41:58.283515image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 270969
29.3%
m 191462
20.7%
a 191462
20.7%
l 191462
20.7%
f 79507
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 924862
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 270969
29.3%
m 191462
20.7%
a 191462
20.7%
l 191462
20.7%
f 79507
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 924862
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 270969
29.3%
m 191462
20.7%
a 191462
20.7%
l 191462
20.7%
f 79507
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 924862
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 270969
29.3%
m 191462
20.7%
a 191462
20.7%
l 191462
20.7%
f 79507
 
8.6%

lifeStage
Text

Missing 

Distinct96
Distinct (%)0.1%
Missing206842
Missing (%)71.4%
Memory size2.2 MiB
2025-02-28T12:41:58.313736image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length3
Mean length4.659568043
Min length1

Characters and Unicode

Total characters385747
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)< 0.1%

Sample

1st rowegg
2nd rowadult
3rd rowadult
4th rowimmature
5th rowjuvenile
ValueCountFrequency (%)
egg 41586
48.9%
adult 20714
24.3%
juvenile 13193
 
15.5%
pullus 3277
 
3.8%
c.y 1836
 
2.2%
immature 1548
 
1.8%
1st 1425
 
1.7%
2nd 563
 
0.7%
year 191
 
0.2%
kj 158
 
0.2%
Other values (74) 636
 
0.7%
2025-02-28T12:41:58.402679image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
g 83191
21.6%
e 70025
18.2%
u 42285
11.0%
l 40628
10.5%
t 23962
 
6.2%
a 22643
 
5.9%
d 21535
 
5.6%
i 14890
 
3.9%
n 13852
 
3.6%
j 13307
 
3.4%
Other values (41) 39429
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 385747
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
g 83191
21.6%
e 70025
18.2%
u 42285
11.0%
l 40628
10.5%
t 23962
 
6.2%
a 22643
 
5.9%
d 21535
 
5.6%
i 14890
 
3.9%
n 13852
 
3.6%
j 13307
 
3.4%
Other values (41) 39429
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 385747
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
g 83191
21.6%
e 70025
18.2%
u 42285
11.0%
l 40628
10.5%
t 23962
 
6.2%
a 22643
 
5.9%
d 21535
 
5.6%
i 14890
 
3.9%
n 13852
 
3.6%
j 13307
 
3.4%
Other values (41) 39429
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 385747
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
g 83191
21.6%
e 70025
18.2%
u 42285
11.0%
l 40628
10.5%
t 23962
 
6.2%
a 22643
 
5.9%
d 21535
 
5.6%
i 14890
 
3.9%
n 13852
 
3.6%
j 13307
 
3.4%
Other values (41) 39429
10.2%
Distinct132
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:41:58.434150image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length39
Median length37
Mean length16.94113829
Min length3

Characters and Unicode

Total characters4906628
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

Unique45 ?
Unique (%)< 0.1%

Sample

1st rowskin (mounted skin)
2nd rowegg (air dried)
3rd rowskin (study skin)
4th rowskin (mounted skin)
5th rowskin (study skin)
ValueCountFrequency (%)
skin 380315
44.5%
air 114349
 
13.4%
dried 114349
 
13.4%
study 108297
 
12.7%
mounted 47294
 
5.5%
egg 41587
 
4.9%
skeletonized 7000
 
0.8%
skeleton 5297
 
0.6%
nest 4724
 
0.6%
whole 4690
 
0.5%
Other values (57) 27515
 
3.2%
2025-02-28T12:41:58.541136image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 631267
12.9%
565789
11.5%
s 520452
10.6%
n 453263
9.2%
k 396125
8.1%
d 393930
8.0%
) 289431
 
5.9%
( 289431
 
5.9%
e 260269
 
5.3%
r 234946
 
4.8%
Other values (34) 871725
17.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4906628
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 631267
12.9%
565789
11.5%
s 520452
10.6%
n 453263
9.2%
k 396125
8.1%
d 393930
8.0%
) 289431
 
5.9%
( 289431
 
5.9%
e 260269
 
5.3%
r 234946
 
4.8%
Other values (34) 871725
17.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4906628
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 631267
12.9%
565789
11.5%
s 520452
10.6%
n 453263
9.2%
k 396125
8.1%
d 393930
8.0%
) 289431
 
5.9%
( 289431
 
5.9%
e 260269
 
5.3%
r 234946
 
4.8%
Other values (34) 871725
17.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4906628
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 631267
12.9%
565789
11.5%
s 520452
10.6%
n 453263
9.2%
k 396125
8.1%
d 393930
8.0%
) 289431
 
5.9%
( 289431
 
5.9%
e 260269
 
5.3%
r 234946
 
4.8%
Other values (34) 871725
17.8%

associatedTaxa
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing289625
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:41:58.573886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters192
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 rowhas parasite: Cirrophthirius cf. recurvirostrae | Quadraceps sp.
2nd rowhas parasite: Cirrophthirius cf. recurvirostrae | Quadraceps sp.
3rd rowhas parasite: Cirrophthirius cf. recurvirostrae | Quadraceps sp.
ValueCountFrequency (%)
has 3
12.5%
parasite 3
12.5%
cirrophthirius 3
12.5%
cf 3
12.5%
recurvirostrae 3
12.5%
3
12.5%
quadraceps 3
12.5%
sp 3
12.5%
2025-02-28T12:41:58.657793image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 27
14.1%
21
10.9%
s 18
9.4%
a 18
9.4%
i 15
 
7.8%
p 12
 
6.2%
e 12
 
6.2%
h 9
 
4.7%
t 9
 
4.7%
u 9
 
4.7%
Other values (10) 42
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 192
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 27
14.1%
21
10.9%
s 18
9.4%
a 18
9.4%
i 15
 
7.8%
p 12
 
6.2%
e 12
 
6.2%
h 9
 
4.7%
t 9
 
4.7%
u 9
 
4.7%
Other values (10) 42
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 192
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 27
14.1%
21
10.9%
s 18
9.4%
a 18
9.4%
i 15
 
7.8%
p 12
 
6.2%
e 12
 
6.2%
h 9
 
4.7%
t 9
 
4.7%
u 9
 
4.7%
Other values (10) 42
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 192
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 27
14.1%
21
10.9%
s 18
9.4%
a 18
9.4%
i 15
 
7.8%
p 12
 
6.2%
e 12
 
6.2%
h 9
 
4.7%
t 9
 
4.7%
u 9
 
4.7%
Other values (10) 42
21.9%

eventDate
Text

Missing 

Distinct44808
Distinct (%)20.8%
Missing74040
Missing (%)25.6%
Memory size2.2 MiB
2025-02-28T12:41:58.730881image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length11.37834202
Min length10

Characters and Unicode

Total characters2453034
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

Unique12124 ?
Unique (%)5.6%

Sample

1st row1904-07-15
2nd row1887-11-19
3rd row2014-01-05
4th row2008-09-09
5th row2006-04-22
ValueCountFrequency (%)
1875-10-01/1875-10-31 571
 
0.3%
1901-01-01/1901-12-31 442
 
0.2%
1930-01-01/1951-12-31 384
 
0.2%
1912-01-01/1916-12-31 312
 
0.1%
1820-12-01/1821-09-30 310
 
0.1%
1862-01-01/1862-12-31 290
 
0.1%
1903-01-01/1908-12-31 283
 
0.1%
1868-01-01/1868-12-31 283
 
0.1%
1982-01-01/1982-12-31 260
 
0.1%
1861-01-01/1861-12-31 240
 
0.1%
Other values (44798) 212213
98.4%
2025-02-28T12:41:58.870729image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 532867
21.7%
- 485204
19.8%
0 370078
15.1%
9 253338
10.3%
2 178215
 
7.3%
8 134256
 
5.5%
3 112582
 
4.6%
6 104197
 
4.2%
5 96176
 
3.9%
7 81018
 
3.3%
Other values (2) 105103
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2453034
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 532867
21.7%
- 485204
19.8%
0 370078
15.1%
9 253338
10.3%
2 178215
 
7.3%
8 134256
 
5.5%
3 112582
 
4.6%
6 104197
 
4.2%
5 96176
 
3.9%
7 81018
 
3.3%
Other values (2) 105103
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2453034
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 532867
21.7%
- 485204
19.8%
0 370078
15.1%
9 253338
10.3%
2 178215
 
7.3%
8 134256
 
5.5%
3 112582
 
4.6%
6 104197
 
4.2%
5 96176
 
3.9%
7 81018
 
3.3%
Other values (2) 105103
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2453034
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 532867
21.7%
- 485204
19.8%
0 370078
15.1%
9 253338
10.3%
2 178215
 
7.3%
8 134256
 
5.5%
3 112582
 
4.6%
6 104197
 
4.2%
5 96176
 
3.9%
7 81018
 
3.3%
Other values (2) 105103
 
4.3%

verbatimEventDate
Text

Missing 

Distinct75421
Distinct (%)32.8%
Missing59530
Missing (%)20.6%
Memory size2.2 MiB
2025-02-28T12:41:59.018868image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length255
Median length10
Mean length10.3775261
Min length1

Characters and Unicode

Total characters2387848
Distinct characters100
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36236 ?
Unique (%)15.7%

Sample

1st row15/7/1904
2nd row19-11-1887
3rd rowbefore 1880
4th row5 januari 2014
5th row9 september 2008
ValueCountFrequency (%)
5950
 
2.0%
on 4818
 
1.6%
label 4338
 
1.5%
may 1985
 
0.7%
april 1642
 
0.6%
september 1503
 
0.5%
october 1244
 
0.4%
june 1238
 
0.4%
december 1221
 
0.4%
november 1151
 
0.4%
Other values (69551) 267833
91.4%
2025-02-28T12:41:59.238989image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 469802
19.7%
- 338404
14.2%
9 254561
10.7%
0 217025
9.1%
2 169904
 
7.1%
8 129201
 
5.4%
6 103192
 
4.3%
5 95718
 
4.0%
3 93888
 
3.9%
/ 82961
 
3.5%
Other values (90) 433192
18.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2387848
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 469802
19.7%
- 338404
14.2%
9 254561
10.7%
0 217025
9.1%
2 169904
 
7.1%
8 129201
 
5.4%
6 103192
 
4.3%
5 95718
 
4.0%
3 93888
 
3.9%
/ 82961
 
3.5%
Other values (90) 433192
18.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2387848
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 469802
19.7%
- 338404
14.2%
9 254561
10.7%
0 217025
9.1%
2 169904
 
7.1%
8 129201
 
5.4%
6 103192
 
4.3%
5 95718
 
4.0%
3 93888
 
3.9%
/ 82961
 
3.5%
Other values (90) 433192
18.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2387848
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 469802
19.7%
- 338404
14.2%
9 254561
10.7%
0 217025
9.1%
2 169904
 
7.1%
8 129201
 
5.4%
6 103192
 
4.3%
5 95718
 
4.0%
3 93888
 
3.9%
/ 82961
 
3.5%
Other values (90) 433192
18.1%

island
Text

Missing 

Distinct1621
Distinct (%)1.8%
Missing200031
Missing (%)69.1%
Memory size2.2 MiB
2025-02-28T12:41:59.279006image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length49
Median length47
Mean length6.736609485
Min length3

Characters and Unicode

Total characters603580
Distinct characters85
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique707 ?
Unique (%)0.8%

Sample

1st rowSouth Island
2nd rowVlieland
3rd rowMoluccas
4th rowMoluccas
5th rowMoluccas
ValueCountFrequency (%)
java 34371
32.3%
sumatra 10736
 
10.1%
celebes 5387
 
5.1%
guinea 4479
 
4.2%
new 3703
 
3.5%
borneo 3663
 
3.4%
islands 3174
 
3.0%
texel 2876
 
2.7%
sunda 2297
 
2.2%
lesser 2296
 
2.2%
Other values (1285) 33356
31.4%
2025-02-28T12:41:59.383493image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 133964
22.2%
e 53532
 
8.9%
v 34897
 
5.8%
J 34642
 
5.7%
r 30497
 
5.1%
n 28902
 
4.8%
u 26445
 
4.4%
s 25512
 
4.2%
l 23542
 
3.9%
o 21887
 
3.6%
Other values (75) 189760
31.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 603580
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 133964
22.2%
e 53532
 
8.9%
v 34897
 
5.8%
J 34642
 
5.7%
r 30497
 
5.1%
n 28902
 
4.8%
u 26445
 
4.4%
s 25512
 
4.2%
l 23542
 
3.9%
o 21887
 
3.6%
Other values (75) 189760
31.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 603580
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 133964
22.2%
e 53532
 
8.9%
v 34897
 
5.8%
J 34642
 
5.7%
r 30497
 
5.1%
n 28902
 
4.8%
u 26445
 
4.4%
s 25512
 
4.2%
l 23542
 
3.9%
o 21887
 
3.6%
Other values (75) 189760
31.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 603580
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 133964
22.2%
e 53532
 
8.9%
v 34897
 
5.8%
J 34642
 
5.7%
r 30497
 
5.1%
n 28902
 
4.8%
u 26445
 
4.4%
s 25512
 
4.2%
l 23542
 
3.9%
o 21887
 
3.6%
Other values (75) 189760
31.4%

country
Text

Missing 

Distinct955
Distinct (%)0.4%
Missing45132
Missing (%)15.6%
Memory size2.2 MiB
2025-02-28T12:41:59.516691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length726566
Median length35
Mean length12.12260732
Min length1

Characters and Unicode

Total characters2963929
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique318 ?
Unique (%)0.1%

Sample

1st rowNetherlands
2nd rowAustralia
3rd rowAustralia
4th rowAustralia
5th rowSenegal
ValueCountFrequency (%)
indonesia 77317
25.0%
netherlands 71334
23.1%
suriname 13444
 
4.3%
kenya 3717
 
1.2%
brazil 3487
 
1.1%
australia 3352
 
1.1%
colombia 3024
 
1.0%
africa 2965
 
1.0%
united 2726
 
0.9%
south 2679
 
0.9%
Other values (8952) 125394
40.5%
2025-02-28T12:41:59.723979image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 313710
 
10.6%
e 305059
 
10.3%
a 290861
 
9.8%
240032
 
8.1%
s 192751
 
6.5%
i 181345
 
6.1%
d 178989
 
6.0%
r 136005
 
4.6%
l 117280
 
4.0%
o 116282
 
3.9%
Other values (88) 891615
30.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2963929
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 313710
 
10.6%
e 305059
 
10.3%
a 290861
 
9.8%
240032
 
8.1%
s 192751
 
6.5%
i 181345
 
6.1%
d 178989
 
6.0%
r 136005
 
4.6%
l 117280
 
4.0%
o 116282
 
3.9%
Other values (88) 891615
30.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2963929
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 313710
 
10.6%
e 305059
 
10.3%
a 290861
 
9.8%
240032
 
8.1%
s 192751
 
6.5%
i 181345
 
6.1%
d 178989
 
6.0%
r 136005
 
4.6%
l 117280
 
4.0%
o 116282
 
3.9%
Other values (88) 891615
30.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2963929
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 313710
 
10.6%
e 305059
 
10.3%
a 290861
 
9.8%
240032
 
8.1%
s 192751
 
6.5%
i 181345
 
6.1%
d 178989
 
6.0%
r 136005
 
4.6%
l 117280
 
4.0%
o 116282
 
3.9%
Other values (88) 891615
30.1%

stateProvince
Text

Missing 

Distinct7165
Distinct (%)4.7%
Missing136488
Missing (%)47.1%
Memory size2.2 MiB
2025-02-28T12:41:59.860983image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length80
Median length71
Mean length11.67741282
Min length1

Characters and Unicode

Total characters1788279
Distinct characters115
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3135 ?
Unique (%)2.0%

Sample

1st rowSouth Holland
2nd rowNew South Wales
3rd rowSouth Australia
4th rowQueensland
5th rowFriesland
ValueCountFrequency (%)
holland 26720
 
10.7%
north 19018
 
7.6%
south 12914
 
5.2%
preanger 9150
 
3.7%
java 8836
 
3.5%
gelderland 6559
 
2.6%
friesland 4323
 
1.7%
guinea 4254
 
1.7%
overijssel 3397
 
1.4%
utrecht 3319
 
1.3%
Other values (5322) 150886
60.5%
2025-02-28T12:42:00.074934image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 200865
 
11.2%
e 141835
 
7.9%
n 125071
 
7.0%
r 121778
 
6.8%
l 120964
 
6.8%
o 110545
 
6.2%
96244
 
5.4%
t 82822
 
4.6%
i 75442
 
4.2%
d 74476
 
4.2%
Other values (105) 638237
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1788279
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 200865
 
11.2%
e 141835
 
7.9%
n 125071
 
7.0%
r 121778
 
6.8%
l 120964
 
6.8%
o 110545
 
6.2%
96244
 
5.4%
t 82822
 
4.6%
i 75442
 
4.2%
d 74476
 
4.2%
Other values (105) 638237
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1788279
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 200865
 
11.2%
e 141835
 
7.9%
n 125071
 
7.0%
r 121778
 
6.8%
l 120964
 
6.8%
o 110545
 
6.2%
96244
 
5.4%
t 82822
 
4.6%
i 75442
 
4.2%
d 74476
 
4.2%
Other values (105) 638237
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1788279
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 200865
 
11.2%
e 141835
 
7.9%
n 125071
 
7.0%
r 121778
 
6.8%
l 120964
 
6.8%
o 110545
 
6.2%
96244
 
5.4%
t 82822
 
4.6%
i 75442
 
4.2%
d 74476
 
4.2%
Other values (105) 638237
35.7%

locality
Text

Missing 

Distinct29689
Distinct (%)14.1%
Missing78963
Missing (%)27.3%
Memory size2.2 MiB
2025-02-28T12:42:00.216058image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19409
Median length93
Mean length16.26432488
Min length2

Characters and Unicode

Total characters3426324
Distinct characters135
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16266 ?
Unique (%)7.7%

Sample

1st rowLisse
2nd rowNew South Wales, no further locality
3rd rowKangaroo I.
4th rowsine loco [SW & SE Australia]
5th rowSenegal, no further locality
ValueCountFrequency (%)
locality 9277
 
1.9%
no 9263
 
1.9%
further 9250
 
1.9%
i 8571
 
1.8%
java 8148
 
1.7%
sine 6339
 
1.3%
loco 6337
 
1.3%
west 5995
 
1.2%
area 5203
 
1.1%
pangerango 4784
 
1.0%
Other values (24964) 411903
84.9%
2025-02-28T12:42:00.436373image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 339907
 
9.9%
e 313933
 
9.2%
273601
 
8.0%
n 233233
 
6.8%
r 209604
 
6.1%
o 207755
 
6.1%
i 173151
 
5.1%
t 131760
 
3.8%
l 129558
 
3.8%
s 107158
 
3.1%
Other values (125) 1306664
38.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3426324
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 339907
 
9.9%
e 313933
 
9.2%
273601
 
8.0%
n 233233
 
6.8%
r 209604
 
6.1%
o 207755
 
6.1%
i 173151
 
5.1%
t 131760
 
3.8%
l 129558
 
3.8%
s 107158
 
3.1%
Other values (125) 1306664
38.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3426324
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 339907
 
9.9%
e 313933
 
9.2%
273601
 
8.0%
n 233233
 
6.8%
r 209604
 
6.1%
o 207755
 
6.1%
i 173151
 
5.1%
t 131760
 
3.8%
l 129558
 
3.8%
s 107158
 
3.1%
Other values (125) 1306664
38.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3426324
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 339907
 
9.9%
e 313933
 
9.2%
273601
 
8.0%
n 233233
 
6.8%
r 209604
 
6.1%
o 207755
 
6.1%
i 173151
 
5.1%
t 131760
 
3.8%
l 129558
 
3.8%
s 107158
 
3.1%
Other values (125) 1306664
38.1%

verbatimElevation
Text

Missing 

Distinct716
Distinct (%)27.7%
Missing287041
Missing (%)99.1%
Memory size2.2 MiB
2025-02-28T12:42:00.542083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length30
Median length27
Mean length7.081175106
Min length2

Characters and Unicode

Total characters18319
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique421 ?
Unique (%)16.3%

Sample

1st row1700 m.
2nd row± 100 Meter
3rd row± 100 m
4th rowasc 3000 ft
5th row7000'
ValueCountFrequency (%)
m 1564
30.9%
meter 212
 
4.2%
ft 177
 
3.5%
± 168
 
3.3%
6000 137
 
2.7%
7000 121
 
2.4%
1000 106
 
2.1%
900 102
 
2.0%
1800 101
 
2.0%
3000 101
 
2.0%
Other values (358) 2280
45.0%
2025-02-28T12:42:00.759974image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5678
31.0%
2483
13.6%
m 1262
 
6.9%
1 1022
 
5.6%
. 814
 
4.4%
5 685
 
3.7%
M 616
 
3.4%
e 596
 
3.3%
' 548
 
3.0%
2 519
 
2.8%
Other values (47) 4096
22.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18319
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 5678
31.0%
2483
13.6%
m 1262
 
6.9%
1 1022
 
5.6%
. 814
 
4.4%
5 685
 
3.7%
M 616
 
3.4%
e 596
 
3.3%
' 548
 
3.0%
2 519
 
2.8%
Other values (47) 4096
22.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18319
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 5678
31.0%
2483
13.6%
m 1262
 
6.9%
1 1022
 
5.6%
. 814
 
4.4%
5 685
 
3.7%
M 616
 
3.4%
e 596
 
3.3%
' 548
 
3.0%
2 519
 
2.8%
Other values (47) 4096
22.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18319
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 5678
31.0%
2483
13.6%
m 1262
 
6.9%
1 1022
 
5.6%
. 814
 
4.4%
5 685
 
3.7%
M 616
 
3.4%
e 596
 
3.3%
' 548
 
3.0%
2 519
 
2.8%
Other values (47) 4096
22.4%

locationAccordingTo
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing289627
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:42:00.790452image/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 row45.0083
ValueCountFrequency (%)
45.0083 1
100.0%
2025-02-28T12:42:00.864604image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
28.6%
4 1
14.3%
5 1
14.3%
. 1
14.3%
8 1
14.3%
3 1
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2
28.6%
4 1
14.3%
5 1
14.3%
. 1
14.3%
8 1
14.3%
3 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2
28.6%
4 1
14.3%
5 1
14.3%
. 1
14.3%
8 1
14.3%
3 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2
28.6%
4 1
14.3%
5 1
14.3%
. 1
14.3%
8 1
14.3%
3 1
14.3%

locationRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing289627
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:42:00.890512image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row128.0083
ValueCountFrequency (%)
128.0083 1
100.0%
2025-02-28T12:42:00.970249image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 2
25.0%
0 2
25.0%
1 1
12.5%
2 1
12.5%
. 1
12.5%
3 1
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 2
25.0%
0 2
25.0%
1 1
12.5%
2 1
12.5%
. 1
12.5%
3 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 2
25.0%
0 2
25.0%
1 1
12.5%
2 1
12.5%
. 1
12.5%
3 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 2
25.0%
0 2
25.0%
1 1
12.5%
2 1
12.5%
. 1
12.5%
3 1
12.5%

decimalLatitude
Text

Missing 

Distinct8258
Distinct (%)5.4%
Missing136554
Missing (%)47.1%
Memory size2.2 MiB
2025-02-28T12:42:01.102539image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length11
Mean length6.164364948
Min length3

Characters and Unicode

Total characters943604
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2599 ?
Unique (%)1.7%

Sample

1st row52.25
2nd row-35.8417
3rd row13.5
4th row-45.15267
5th row-13.4
ValueCountFrequency (%)
6.7667 1821
 
1.2%
52.2417 1243
 
0.8%
6.5833 1111
 
0.7%
6.775 1102
 
0.7%
52.175 936
 
0.6%
5.9417 858
 
0.6%
52.1 846
 
0.6%
3.5917 832
 
0.5%
53.3917 829
 
0.5%
52.3583 813
 
0.5%
Other values (7317) 142683
93.2%
2025-02-28T12:42:01.305845image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 153073
16.2%
5 138524
14.7%
3 108304
11.5%
1 88303
9.4%
2 84464
9.0%
7 76372
8.1%
8 60368
 
6.4%
6 56510
 
6.0%
0 52273
 
5.5%
4 49409
 
5.2%
Other values (5) 76004
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 943604
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 153073
16.2%
5 138524
14.7%
3 108304
11.5%
1 88303
9.4%
2 84464
9.0%
7 76372
8.1%
8 60368
 
6.4%
6 56510
 
6.0%
0 52273
 
5.5%
4 49409
 
5.2%
Other values (5) 76004
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 943604
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 153073
16.2%
5 138524
14.7%
3 108304
11.5%
1 88303
9.4%
2 84464
9.0%
7 76372
8.1%
8 60368
 
6.4%
6 56510
 
6.0%
0 52273
 
5.5%
4 49409
 
5.2%
Other values (5) 76004
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 943604
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 153073
16.2%
5 138524
14.7%
3 108304
11.5%
1 88303
9.4%
2 84464
9.0%
7 76372
8.1%
8 60368
 
6.4%
6 56510
 
6.0%
0 52273
 
5.5%
4 49409
 
5.2%
Other values (5) 76004
8.1%

decimalLongitude
Text

Missing 

Distinct10150
Distinct (%)6.6%
Missing135979
Missing (%)46.9%
Memory size2.2 MiB
2025-02-28T12:42:01.457151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length17
Mean length6.284388444
Min length3

Characters and Unicode

Total characters965590
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

Unique3552 ?
Unique (%)2.3%

Sample

1st row4.5333
2nd row137.5083
3rd row-16.0
4th row169.89263
5th row48.27
ValueCountFrequency (%)
106.9167 1795
 
1.2%
107.0 1161
 
0.8%
106.925 1127
 
0.7%
106.8 1065
 
0.7%
4.875 975
 
0.6%
124.8583 748
 
0.5%
4.425 748
 
0.5%
98.675 716
 
0.5%
106.825 699
 
0.5%
6.1 699
 
0.5%
Other values (9278) 143916
93.7%
2025-02-28T12:42:01.668881image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 153649
15.9%
1 124246
12.9%
5 103162
10.7%
3 91574
9.5%
7 85735
8.9%
4 75127
7.8%
0 74503
7.7%
8 73203
7.6%
6 64305
6.7%
2 52724
 
5.5%
Other values (2) 67362
7.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 965590
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 153649
15.9%
1 124246
12.9%
5 103162
10.7%
3 91574
9.5%
7 85735
8.9%
4 75127
7.8%
0 74503
7.7%
8 73203
7.6%
6 64305
6.7%
2 52724
 
5.5%
Other values (2) 67362
7.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 965590
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 153649
15.9%
1 124246
12.9%
5 103162
10.7%
3 91574
9.5%
7 85735
8.9%
4 75127
7.8%
0 74503
7.7%
8 73203
7.6%
6 64305
6.7%
2 52724
 
5.5%
Other values (2) 67362
7.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 965590
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 153649
15.9%
1 124246
12.9%
5 103162
10.7%
3 91574
9.5%
7 85735
8.9%
4 75127
7.8%
0 74503
7.7%
8 73203
7.6%
6 64305
6.7%
2 52724
 
5.5%
Other values (2) 67362
7.0%

geodeticDatum
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size2.2 MiB
2025-02-28T12:42:01.715326image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1448135
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS84
2nd rowWGS84
3rd rowWGS84
4th rowWGS84
5th rowWGS84
ValueCountFrequency (%)
wgs84 289627
100.0%
2025-02-28T12:42:01.801238image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 289627
20.0%
G 289627
20.0%
S 289627
20.0%
8 289627
20.0%
4 289627
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1448135
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
W 289627
20.0%
G 289627
20.0%
S 289627
20.0%
8 289627
20.0%
4 289627
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1448135
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
W 289627
20.0%
G 289627
20.0%
S 289627
20.0%
8 289627
20.0%
4 289627
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1448135
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
W 289627
20.0%
G 289627
20.0%
S 289627
20.0%
8 289627
20.0%
4 289627
20.0%
Distinct172
Distinct (%)10.4%
Missing287974
Missing (%)99.4%
Memory size2.2 MiB
2025-02-28T12:42:01.870382image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.42140266
Min length1

Characters and Unicode

Total characters5659
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

Unique72 ?
Unique (%)4.4%

Sample

1st row640000
2nd row20000
3rd row640000
4th row1000
5th row1
ValueCountFrequency (%)
5 399
24.1%
82230 128
 
7.7%
60697 87
 
5.3%
100 71
 
4.3%
216478 65
 
3.9%
1000 48
 
2.9%
2000 47
 
2.8%
200 41
 
2.5%
5196 40
 
2.4%
50 37
 
2.2%
Other values (162) 691
41.8%
2025-02-28T12:42:01.989919image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1808
31.9%
5 693
 
12.2%
2 579
 
10.2%
6 555
 
9.8%
1 436
 
7.7%
7 384
 
6.8%
4 329
 
5.8%
8 312
 
5.5%
3 300
 
5.3%
9 263
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5659
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1808
31.9%
5 693
 
12.2%
2 579
 
10.2%
6 555
 
9.8%
1 436
 
7.7%
7 384
 
6.8%
4 329
 
5.8%
8 312
 
5.5%
3 300
 
5.3%
9 263
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5659
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1808
31.9%
5 693
 
12.2%
2 579
 
10.2%
6 555
 
9.8%
1 436
 
7.7%
7 384
 
6.8%
4 329
 
5.8%
8 312
 
5.5%
3 300
 
5.3%
9 263
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5659
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1808
31.9%
5 693
 
12.2%
2 579
 
10.2%
6 555
 
9.8%
1 436
 
7.7%
7 384
 
6.8%
4 329
 
5.8%
8 312
 
5.5%
3 300
 
5.3%
9 263
 
4.6%

typeStatus
Text

Missing 

Distinct6
Distinct (%)0.2%
Missing286162
Missing (%)98.8%
Memory size2.2 MiB
2025-02-28T12:42:02.020820image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.704847086
Min length4

Characters and Unicode

Total characters26705
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsyntype
2nd rowsyntype
3rd rowsyntype
4th rowparatype
5th rowparatype
ValueCountFrequency (%)
syntype 2273
65.6%
paratype 500
 
14.4%
holotype 369
 
10.6%
paralectotype 239
 
6.9%
lectotype 79
 
2.3%
type 6
 
0.2%
2025-02-28T12:42:02.100572image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y 5739
21.5%
p 4205
15.7%
t 3784
14.2%
e 3784
14.2%
s 2273
 
8.5%
n 2273
 
8.5%
a 1478
 
5.5%
o 1056
 
4.0%
r 739
 
2.8%
l 687
 
2.6%
Other values (2) 687
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26705
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
y 5739
21.5%
p 4205
15.7%
t 3784
14.2%
e 3784
14.2%
s 2273
 
8.5%
n 2273
 
8.5%
a 1478
 
5.5%
o 1056
 
4.0%
r 739
 
2.8%
l 687
 
2.6%
Other values (2) 687
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26705
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
y 5739
21.5%
p 4205
15.7%
t 3784
14.2%
e 3784
14.2%
s 2273
 
8.5%
n 2273
 
8.5%
a 1478
 
5.5%
o 1056
 
4.0%
r 739
 
2.8%
l 687
 
2.6%
Other values (2) 687
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26705
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
y 5739
21.5%
p 4205
15.7%
t 3784
14.2%
e 3784
14.2%
s 2273
 
8.5%
n 2273
 
8.5%
a 1478
 
5.5%
o 1056
 
4.0%
r 739
 
2.8%
l 687
 
2.6%
Other values (2) 687
 
2.6%

identifiedBy
Text

Missing 

Distinct48
Distinct (%)11.7%
Missing289216
Missing (%)99.9%
Memory size2.2 MiB
2025-02-28T12:42:02.143372image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length9
Mean length9.708737864
Min length4

Characters and Unicode

Total characters4000
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)5.1%

Sample

1st rowRijswijk C. van
2nd rowKonter A.
3rd rowKonter A.
4th rowVoous of Wattel?
5th rowVoous
ValueCountFrequency (%)
konter 165
20.0%
a 165
20.0%
dekker 113
13.7%
r 113
13.7%
voous 32
 
3.9%
roselaar 21
 
2.5%
jansen 11
 
1.3%
j.f.j 11
 
1.3%
k 11
 
1.3%
of 9
 
1.1%
Other values (72) 173
21.0%
2025-02-28T12:42:02.249658image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 527
13.2%
412
10.3%
. 408
10.2%
r 342
 
8.6%
o 283
 
7.1%
k 242
 
6.0%
n 218
 
5.5%
t 206
 
5.1%
K 184
 
4.6%
A 166
 
4.2%
Other values (48) 1012
25.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 527
13.2%
412
10.3%
. 408
10.2%
r 342
 
8.6%
o 283
 
7.1%
k 242
 
6.0%
n 218
 
5.5%
t 206
 
5.1%
K 184
 
4.6%
A 166
 
4.2%
Other values (48) 1012
25.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 527
13.2%
412
10.3%
. 408
10.2%
r 342
 
8.6%
o 283
 
7.1%
k 242
 
6.0%
n 218
 
5.5%
t 206
 
5.1%
K 184
 
4.6%
A 166
 
4.2%
Other values (48) 1012
25.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 527
13.2%
412
10.3%
. 408
10.2%
r 342
 
8.6%
o 283
 
7.1%
k 242
 
6.0%
n 218
 
5.5%
t 206
 
5.1%
K 184
 
4.6%
A 166
 
4.2%
Other values (48) 1012
25.3%

dateIdentified
Text

Missing 

Distinct40
Distinct (%)15.6%
Missing289371
Missing (%)99.9%
Memory size2.2 MiB
2025-02-28T12:42:02.284535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2570
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

Unique25 ?
Unique (%)9.7%

Sample

1st row2022/07/01
2nd row2022/04/25
3rd row2022/04/25
4th row1964/01/01
5th row2022/04/25
ValueCountFrequency (%)
2022/04/25 165
64.2%
2018/05/31 13
 
5.1%
2021/07/01 11
 
4.3%
1964/01/01 10
 
3.9%
2014/10/28 7
 
2.7%
2014/10/20 4
 
1.6%
2023/12/28 3
 
1.2%
2022/08/31 3
 
1.2%
2017/04/17 3
 
1.2%
2023/01/01 3
 
1.2%
Other values (30) 35
 
13.6%
2025-02-28T12:42:02.372344image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 814
31.7%
0 550
21.4%
/ 514
20.0%
4 195
 
7.6%
5 184
 
7.2%
1 175
 
6.8%
8 38
 
1.5%
3 33
 
1.3%
7 28
 
1.1%
9 23
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2570
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 814
31.7%
0 550
21.4%
/ 514
20.0%
4 195
 
7.6%
5 184
 
7.2%
1 175
 
6.8%
8 38
 
1.5%
3 33
 
1.3%
7 28
 
1.1%
9 23
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2570
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 814
31.7%
0 550
21.4%
/ 514
20.0%
4 195
 
7.6%
5 184
 
7.2%
1 175
 
6.8%
8 38
 
1.5%
3 33
 
1.3%
7 28
 
1.1%
9 23
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2570
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 814
31.7%
0 550
21.4%
/ 514
20.0%
4 195
 
7.6%
5 184
 
7.2%
1 175
 
6.8%
8 38
 
1.5%
3 33
 
1.3%
7 28
 
1.1%
9 23
 
0.9%

namePublishedInID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing289627
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:42:02.402032image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length33
Mean length33
Min length33

Characters and Unicode

Total characters33
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

Unique1 ?
Unique (%)100.0%

Sample

1st rowCrossoptilon mantchuricum Swinhoe
ValueCountFrequency (%)
crossoptilon 1
33.3%
mantchuricum 1
33.3%
swinhoe 1
33.3%
2025-02-28T12:42:02.480521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 4
12.1%
i 3
 
9.1%
n 3
 
9.1%
2
 
6.1%
h 2
 
6.1%
s 2
 
6.1%
t 2
 
6.1%
r 2
 
6.1%
m 2
 
6.1%
u 2
 
6.1%
Other values (8) 9
27.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 4
12.1%
i 3
 
9.1%
n 3
 
9.1%
2
 
6.1%
h 2
 
6.1%
s 2
 
6.1%
t 2
 
6.1%
r 2
 
6.1%
m 2
 
6.1%
u 2
 
6.1%
Other values (8) 9
27.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 4
12.1%
i 3
 
9.1%
n 3
 
9.1%
2
 
6.1%
h 2
 
6.1%
s 2
 
6.1%
t 2
 
6.1%
r 2
 
6.1%
m 2
 
6.1%
u 2
 
6.1%
Other values (8) 9
27.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 4
12.1%
i 3
 
9.1%
n 3
 
9.1%
2
 
6.1%
h 2
 
6.1%
s 2
 
6.1%
t 2
 
6.1%
r 2
 
6.1%
m 2
 
6.1%
u 2
 
6.1%
Other values (8) 9
27.3%
Distinct27724
Distinct (%)9.6%
Missing1
Missing (%)< 0.1%
Memory size2.2 MiB
2025-02-28T12:42:02.609503image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length122
Median length73
Mean length38.16476019
Min length3

Characters and Unicode

Total characters11053545
Distinct characters99
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8762 ?
Unique (%)3.0%

Sample

1st rowVidua orientalis cf Heuglin, 1871
2nd rowTurdus viscivorus viscivorus Linnaeus, 1758
3rd rowNeophema splendida Gould, 1841
4th rowPlatycercus elegans melanopterus North, 1906
5th rowPolytelis anthopeplus monarchoides
ValueCountFrequency (%)
linnaeus 87214
 
6.6%
1758 62801
 
4.8%
temminck 13007
 
1.0%
vieillot 10905
 
0.8%
10567
 
0.8%
gmelin 9441
 
0.7%
horsfield 8367
 
0.6%
1766 7967
 
0.6%
1821 5912
 
0.5%
1789 5905
 
0.4%
Other values (11804) 1091525
83.1%
2025-02-28T12:42:02.821312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1024031
 
9.3%
a 952767
 
8.6%
i 790587
 
7.2%
s 746831
 
6.8%
e 660252
 
6.0%
n 635153
 
5.7%
r 588460
 
5.3%
u 586053
 
5.3%
l 504888
 
4.6%
o 487902
 
4.4%
Other values (89) 4076621
36.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11053545
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1024031
 
9.3%
a 952767
 
8.6%
i 790587
 
7.2%
s 746831
 
6.8%
e 660252
 
6.0%
n 635153
 
5.7%
r 588460
 
5.3%
u 586053
 
5.3%
l 504888
 
4.6%
o 487902
 
4.4%
Other values (89) 4076621
36.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11053545
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1024031
 
9.3%
a 952767
 
8.6%
i 790587
 
7.2%
s 746831
 
6.8%
e 660252
 
6.0%
n 635153
 
5.7%
r 588460
 
5.3%
u 586053
 
5.3%
l 504888
 
4.6%
o 487902
 
4.4%
Other values (89) 4076621
36.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11053545
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1024031
 
9.3%
a 952767
 
8.6%
i 790587
 
7.2%
s 746831
 
6.8%
e 660252
 
6.0%
n 635153
 
5.7%
r 588460
 
5.3%
u 586053
 
5.3%
l 504888
 
4.6%
o 487902
 
4.4%
Other values (89) 4076621
36.9%

namePublishedIn
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing289627
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:42:02.859293image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAnimalia
ValueCountFrequency (%)
animalia 1
100.0%
2025-02-28T12:42:02.936606image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

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

namePublishedInYear
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing289627
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:42:02.963819image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAnimalia
ValueCountFrequency (%)
animalia 1
100.0%
2025-02-28T12:42:03.042107image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 2
25.0%
a 2
25.0%
A 1
12.5%
n 1
12.5%
m 1
12.5%
l 1
12.5%
Distinct310
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size2.2 MiB
2025-02-28T12:42:03.132536image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length43
Mean length16.59742704
Min length8

Characters and Unicode

Total characters4807063
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia|Viduidae
2nd rowAnimalia|Turdidae
3rd rowAnimalia|Psittacidae
4th rowAnimalia|Psittacidae
5th rowAnimalia|Psittacidae
ValueCountFrequency (%)
animalia 73469
25.3%
animalia|turdidae 13154
 
4.5%
animalia|scolopacidae 10694
 
3.7%
animalia|sylviidae 10286
 
3.5%
animalia|emberizidae 8024
 
2.8%
animalia|fringillidae 7443
 
2.6%
animalia|corvidae 7140
 
2.5%
animalia|ardeidae 5218
 
1.8%
animalia|timaliidae 5010
 
1.7%
animalia|charadriidae 4758
 
1.6%
Other values (298) 145140
50.0%
2025-02-28T12:42:03.315571image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 933491
19.4%
a 914161
19.0%
l 392122
8.2%
n 356546
 
7.4%
m 317726
 
6.6%
A 315297
 
6.6%
e 275552
 
5.7%
d 260453
 
5.4%
| 220567
 
4.6%
r 137646
 
2.9%
Other values (42) 683502
14.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4807063
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 933491
19.4%
a 914161
19.0%
l 392122
8.2%
n 356546
 
7.4%
m 317726
 
6.6%
A 315297
 
6.6%
e 275552
 
5.7%
d 260453
 
5.4%
| 220567
 
4.6%
r 137646
 
2.9%
Other values (42) 683502
14.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4807063
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 933491
19.4%
a 914161
19.0%
l 392122
8.2%
n 356546
 
7.4%
m 317726
 
6.6%
A 315297
 
6.6%
e 275552
 
5.7%
d 260453
 
5.4%
| 220567
 
4.6%
r 137646
 
2.9%
Other values (42) 683502
14.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4807063
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 933491
19.4%
a 914161
19.0%
l 392122
8.2%
n 356546
 
7.4%
m 317726
 
6.6%
A 315297
 
6.6%
e 275552
 
5.7%
d 260453
 
5.4%
| 220567
 
4.6%
r 137646
 
2.9%
Other values (42) 683502
14.2%

kingdom
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size2.2 MiB
2025-02-28T12:42:03.353750image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters2317016
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 289627
100.0%
2025-02-28T12:42:03.508731image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 579254
25.0%
a 579254
25.0%
A 289627
12.5%
n 289627
12.5%
m 289627
12.5%
l 289627
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2317016
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 579254
25.0%
a 579254
25.0%
A 289627
12.5%
n 289627
12.5%
m 289627
12.5%
l 289627
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2317016
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 579254
25.0%
a 579254
25.0%
A 289627
12.5%
n 289627
12.5%
m 289627
12.5%
l 289627
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2317016
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 579254
25.0%
a 579254
25.0%
A 289627
12.5%
n 289627
12.5%
m 289627
12.5%
l 289627
12.5%

class
Text

Missing 

Distinct2
Distinct (%)0.1%
Missing286898
Missing (%)99.1%
Memory size2.2 MiB
2025-02-28T12:42:03.537574image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters10920
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAves
2nd rowAves
3rd rowAves
4th rowAves
5th rowAves
ValueCountFrequency (%)
aves 2730
100.0%
2025-02-28T12:42:03.617235image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 2730
25.0%
v 2516
23.0%
e 2516
23.0%
s 2516
23.0%
V 214
 
2.0%
E 214
 
2.0%
S 214
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 2730
25.0%
v 2516
23.0%
e 2516
23.0%
s 2516
23.0%
V 214
 
2.0%
E 214
 
2.0%
S 214
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 2730
25.0%
v 2516
23.0%
e 2516
23.0%
s 2516
23.0%
V 214
 
2.0%
E 214
 
2.0%
S 214
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 2730
25.0%
v 2516
23.0%
e 2516
23.0%
s 2516
23.0%
V 214
 
2.0%
E 214
 
2.0%
S 214
 
2.0%

order
Text

Missing 

Distinct4
Distinct (%)0.2%
Missing287366
Missing (%)99.2%
Memory size2.2 MiB
2025-02-28T12:42:03.647257image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.94429708
Min length4

Characters and Unicode

Total characters29280
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rowPasseriformes
2nd rowPasseriformes
3rd rowPasseriformes
4th rowPasseriformes
5th rowPasseriformes
ValueCountFrequency (%)
passeriformes 2248
99.4%
aves 14
 
0.6%
2025-02-28T12:42:03.721539image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 6745
23.0%
e 4497
15.4%
r 4496
15.4%
a 2248
 
7.7%
i 2248
 
7.7%
f 2248
 
7.7%
o 2248
 
7.7%
m 2248
 
7.7%
P 2247
 
7.7%
A 14
 
< 0.1%
Other values (5) 41
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 29280
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 6745
23.0%
e 4497
15.4%
r 4496
15.4%
a 2248
 
7.7%
i 2248
 
7.7%
f 2248
 
7.7%
o 2248
 
7.7%
m 2248
 
7.7%
P 2247
 
7.7%
A 14
 
< 0.1%
Other values (5) 41
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 29280
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 6745
23.0%
e 4497
15.4%
r 4496
15.4%
a 2248
 
7.7%
i 2248
 
7.7%
f 2248
 
7.7%
o 2248
 
7.7%
m 2248
 
7.7%
P 2247
 
7.7%
A 14
 
< 0.1%
Other values (5) 41
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 29280
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 6745
23.0%
e 4497
15.4%
r 4496
15.4%
a 2248
 
7.7%
i 2248
 
7.7%
f 2248
 
7.7%
o 2248
 
7.7%
m 2248
 
7.7%
P 2247
 
7.7%
A 14
 
< 0.1%
Other values (5) 41
 
0.1%

family
Text

Missing 

Distinct247
Distinct (%)0.1%
Missing74054
Missing (%)25.6%
Memory size2.2 MiB
2025-02-28T12:42:03.816328image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length22
Mean length10.34113576
Min length6

Characters and Unicode

Total characters2229280
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)< 0.1%

Sample

1st rowViduidae
2nd rowTurdidae
3rd rowPsittacidae
4th rowPsittacidae
5th rowPsittacidae
ValueCountFrequency (%)
turdidae 13278
 
6.1%
scolopacidae 10694
 
4.9%
sylviidae 10420
 
4.8%
emberizidae 8091
 
3.7%
fringillidae 7502
 
3.5%
corvidae 7196
 
3.3%
ardeidae 5218
 
2.4%
timaliidae 5165
 
2.4%
sturnidae 4769
 
2.2%
pycnonotidae 4762
 
2.2%
Other values (238) 139188
64.4%
2025-02-28T12:42:03.983941image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 351989
15.8%
a 332659
14.9%
e 268539
12.0%
d 260453
11.7%
r 133150
 
6.0%
l 102495
 
4.6%
c 97981
 
4.4%
o 90767
 
4.1%
n 66919
 
3.0%
t 56941
 
2.6%
Other values (41) 467387
21.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2229280
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 351989
15.8%
a 332659
14.9%
e 268539
12.0%
d 260453
11.7%
r 133150
 
6.0%
l 102495
 
4.6%
c 97981
 
4.4%
o 90767
 
4.1%
n 66919
 
3.0%
t 56941
 
2.6%
Other values (41) 467387
21.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2229280
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 351989
15.8%
a 332659
14.9%
e 268539
12.0%
d 260453
11.7%
r 133150
 
6.0%
l 102495
 
4.6%
c 97981
 
4.4%
o 90767
 
4.1%
n 66919
 
3.0%
t 56941
 
2.6%
Other values (41) 467387
21.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2229280
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 351989
15.8%
a 332659
14.9%
e 268539
12.0%
d 260453
11.7%
r 133150
 
6.0%
l 102495
 
4.6%
c 97981
 
4.4%
o 90767
 
4.1%
n 66919
 
3.0%
t 56941
 
2.6%
Other values (41) 467387
21.0%

tribe
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing289627
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:42:04.027083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
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 rowCrossoptilon
ValueCountFrequency (%)
crossoptilon 1
100.0%
2025-02-28T12:42:04.105500image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 3
25.0%
s 2
16.7%
C 1
 
8.3%
r 1
 
8.3%
p 1
 
8.3%
t 1
 
8.3%
i 1
 
8.3%
l 1
 
8.3%
n 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 3
25.0%
s 2
16.7%
C 1
 
8.3%
r 1
 
8.3%
p 1
 
8.3%
t 1
 
8.3%
i 1
 
8.3%
l 1
 
8.3%
n 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 3
25.0%
s 2
16.7%
C 1
 
8.3%
r 1
 
8.3%
p 1
 
8.3%
t 1
 
8.3%
i 1
 
8.3%
l 1
 
8.3%
n 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 3
25.0%
s 2
16.7%
C 1
 
8.3%
r 1
 
8.3%
p 1
 
8.3%
t 1
 
8.3%
i 1
 
8.3%
l 1
 
8.3%
n 1
 
8.3%

genus
Text

Distinct2534
Distinct (%)0.9%
Missing580
Missing (%)0.2%
Memory size2.2 MiB
2025-02-28T12:42:04.225447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length34
Median length26
Mean length8.144879051
Min length1

Characters and Unicode

Total characters2354261
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique306 ?
Unique (%)0.1%

Sample

1st rowVidua
2nd rowTurdus
3rd rowNeophema
4th rowPlatycercus
5th rowPolytelis
ValueCountFrequency (%)
turdus 5647
 
2.0%
larus 4361
 
1.5%
falco 3593
 
1.2%
parus 3588
 
1.2%
corvus 3377
 
1.2%
pycnonotus 3358
 
1.2%
sterna 3246
 
1.1%
passer 3110
 
1.1%
anas 2998
 
1.0%
accipiter 2973
 
1.0%
Other values (2474) 252913
87.5%
2025-02-28T12:42:04.433153image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 250286
 
10.6%
r 185196
 
7.9%
s 184735
 
7.8%
i 178828
 
7.6%
o 171056
 
7.3%
u 166327
 
7.1%
e 131882
 
5.6%
l 130804
 
5.6%
c 112924
 
4.8%
t 106201
 
4.5%
Other values (58) 736022
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2354261
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 250286
 
10.6%
r 185196
 
7.9%
s 184735
 
7.8%
i 178828
 
7.6%
o 171056
 
7.3%
u 166327
 
7.1%
e 131882
 
5.6%
l 130804
 
5.6%
c 112924
 
4.8%
t 106201
 
4.5%
Other values (58) 736022
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2354261
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 250286
 
10.6%
r 185196
 
7.9%
s 184735
 
7.8%
i 178828
 
7.6%
o 171056
 
7.3%
u 166327
 
7.1%
e 131882
 
5.6%
l 130804
 
5.6%
c 112924
 
4.8%
t 106201
 
4.5%
Other values (58) 736022
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2354261
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 250286
 
10.6%
r 185196
 
7.9%
s 184735
 
7.8%
i 178828
 
7.6%
o 171056
 
7.3%
u 166327
 
7.1%
e 131882
 
5.6%
l 130804
 
5.6%
c 112924
 
4.8%
t 106201
 
4.5%
Other values (58) 736022
31.3%

subgenus
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing289627
Missing (%)> 99.9%
Memory size2.2 MiB
2025-02-28T12:42:04.480893image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
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 rowmantchuricum
ValueCountFrequency (%)
mantchuricum 1
100.0%
2025-02-28T12:42:04.559978image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 2
16.7%
c 2
16.7%
u 2
16.7%
a 1
8.3%
n 1
8.3%
t 1
8.3%
h 1
8.3%
r 1
8.3%
i 1
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
m 2
16.7%
c 2
16.7%
u 2
16.7%
a 1
8.3%
n 1
8.3%
t 1
8.3%
h 1
8.3%
r 1
8.3%
i 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
m 2
16.7%
c 2
16.7%
u 2
16.7%
a 1
8.3%
n 1
8.3%
t 1
8.3%
h 1
8.3%
r 1
8.3%
i 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
m 2
16.7%
c 2
16.7%
u 2
16.7%
a 1
8.3%
n 1
8.3%
t 1
8.3%
h 1
8.3%
r 1
8.3%
i 1
8.3%
Distinct4845
Distinct (%)1.7%
Missing1404
Missing (%)0.5%
Memory size2.2 MiB
2025-02-28T12:42:04.671245image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length67
Median length44
Mean length8.539514405
Min length2

Characters and Unicode

Total characters2461293
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique714 ?
Unique (%)0.2%

Sample

1st roworientalis cf
2nd rowviscivorus
3rd rowsplendida
4th rowelegans
5th rowanthopeplus
ValueCountFrequency (%)
alba 2079
 
0.7%
major 1955
 
0.7%
domesticus 1905
 
0.7%
cinerea 1831
 
0.6%
vulgaris 1740
 
0.6%
chloris 1590
 
0.6%
montanus 1543
 
0.5%
chinensis 1505
 
0.5%
cristatus 1485
 
0.5%
glandarius 1450
 
0.5%
Other values (4711) 271837
94.1%
2025-02-28T12:42:04.916428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 307107
12.5%
i 241479
9.8%
s 237211
9.6%
u 187770
 
7.6%
r 183768
 
7.5%
e 169869
 
6.9%
l 157994
 
6.4%
n 151086
 
6.1%
c 143459
 
5.8%
o 140138
 
5.7%
Other values (70) 541412
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2461293
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 307107
12.5%
i 241479
9.8%
s 237211
9.6%
u 187770
 
7.6%
r 183768
 
7.5%
e 169869
 
6.9%
l 157994
 
6.4%
n 151086
 
6.1%
c 143459
 
5.8%
o 140138
 
5.7%
Other values (70) 541412
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2461293
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 307107
12.5%
i 241479
9.8%
s 237211
9.6%
u 187770
 
7.6%
r 183768
 
7.5%
e 169869
 
6.9%
l 157994
 
6.4%
n 151086
 
6.1%
c 143459
 
5.8%
o 140138
 
5.7%
Other values (70) 541412
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2461293
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 307107
12.5%
i 241479
9.8%
s 237211
9.6%
u 187770
 
7.6%
r 183768
 
7.5%
e 169869
 
6.9%
l 157994
 
6.4%
n 151086
 
6.1%
c 143459
 
5.8%
o 140138
 
5.7%
Other values (70) 541412
22.0%

infraspecificEpithet
Text

Missing 

Distinct6953
Distinct (%)3.5%
Missing89169
Missing (%)30.8%
Memory size2.2 MiB
2025-02-28T12:42:05.057137image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length87
Median length48
Mean length8.519253314
Min length1

Characters and Unicode

Total characters1707761
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1473 ?
Unique (%)0.7%

Sample

1st rowviscivorus
2nd rowmelanopterus
3rd rowmonarchoides
4th rowrubescens
5th rowmeridionalis
ValueCountFrequency (%)
subsp 2295
 
1.1%
ssp 2260
 
1.1%
domesticus 2258
 
1.1%
vulgaris 1490
 
0.7%
cinerea 1182
 
0.6%
merula 1145
 
0.6%
rubecula 1127
 
0.6%
cf 1062
 
0.5%
javanica 1020
 
0.5%
nisus 1017
 
0.5%
Other values (6582) 187257
92.6%
2025-02-28T12:42:05.268883image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 198590
11.6%
i 182188
10.7%
s 174371
10.2%
r 127411
 
7.5%
e 123135
 
7.2%
u 121483
 
7.1%
n 110399
 
6.5%
l 102692
 
6.0%
o 94165
 
5.5%
c 92151
 
5.4%
Other values (73) 381176
22.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1707761
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 198590
11.6%
i 182188
10.7%
s 174371
10.2%
r 127411
 
7.5%
e 123135
 
7.2%
u 121483
 
7.1%
n 110399
 
6.5%
l 102692
 
6.0%
o 94165
 
5.5%
c 92151
 
5.4%
Other values (73) 381176
22.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1707761
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 198590
11.6%
i 182188
10.7%
s 174371
10.2%
r 127411
 
7.5%
e 123135
 
7.2%
u 121483
 
7.1%
n 110399
 
6.5%
l 102692
 
6.0%
o 94165
 
5.5%
c 92151
 
5.4%
Other values (73) 381176
22.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1707761
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 198590
11.6%
i 182188
10.7%
s 174371
10.2%
r 127411
 
7.5%
e 123135
 
7.2%
u 121483
 
7.1%
n 110399
 
6.5%
l 102692
 
6.0%
o 94165
 
5.5%
c 92151
 
5.4%
Other values (73) 381176
22.3%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-02-28T12:42:05.313556image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.067072244
Min length5

Characters and Unicode

Total characters2626078
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowspecies
2nd rowsubspecies
3rd rowspecies
4th rowsubspecies
5th rowsubspecies
ValueCountFrequency (%)
subspecies 200450
69.2%
species 87771
30.3%
genus 850
 
0.3%
class 400
 
0.1%
family 144
 
< 0.1%
order 12
 
< 0.1%
swinhoe 1
 
< 0.1%
2025-02-28T12:42:05.395231image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 778542
29.6%
e 577305
22.0%
c 288621
 
11.0%
i 288366
 
11.0%
p 288221
 
11.0%
u 201300
 
7.7%
b 200450
 
7.6%
n 851
 
< 0.1%
g 850
 
< 0.1%
a 544
 
< 0.1%
Other values (10) 1028
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2626078
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 778542
29.6%
e 577305
22.0%
c 288621
 
11.0%
i 288366
 
11.0%
p 288221
 
11.0%
u 201300
 
7.7%
b 200450
 
7.6%
n 851
 
< 0.1%
g 850
 
< 0.1%
a 544
 
< 0.1%
Other values (10) 1028
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2626078
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 778542
29.6%
e 577305
22.0%
c 288621
 
11.0%
i 288366
 
11.0%
p 288221
 
11.0%
u 201300
 
7.7%
b 200450
 
7.6%
n 851
 
< 0.1%
g 850
 
< 0.1%
a 544
 
< 0.1%
Other values (10) 1028
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2626078
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 778542
29.6%
e 577305
22.0%
c 288621
 
11.0%
i 288366
 
11.0%
p 288221
 
11.0%
u 201300
 
7.7%
b 200450
 
7.6%
n 851
 
< 0.1%
g 850
 
< 0.1%
a 544
 
< 0.1%
Other values (10) 1028
 
< 0.1%
Distinct6059
Distinct (%)2.2%
Missing17143
Missing (%)5.9%
Memory size2.2 MiB
2025-02-28T12:42:05.517518image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length39
Mean length13.82024332
Min length1

Characters and Unicode

Total characters3765809
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1183 ?
Unique (%)0.4%

Sample

1st rowHeuglin, 1871
2nd rowLinnaeus, 1758
3rd rowGould, 1841
4th rowNorth, 1906
5th rowTemminck, 1823
ValueCountFrequency (%)
linnaeus 87214
 
16.4%
1758 62801
 
11.8%
temminck 13007
 
2.4%
vieillot 10905
 
2.0%
10530
 
2.0%
gmelin 9441
 
1.8%
horsfield 8367
 
1.6%
1766 7967
 
1.5%
1821 5912
 
1.1%
1789 5905
 
1.1%
Other values (1402) 310792
58.3%
2025-02-28T12:42:05.714065image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 267737
 
7.1%
260390
 
6.9%
1 254855
 
6.8%
e 234945
 
6.2%
, 228637
 
6.1%
a 196611
 
5.2%
8 193240
 
5.1%
i 187873
 
5.0%
s 150318
 
4.0%
7 127152
 
3.4%
Other values (71) 1664051
44.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3765809
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 267737
 
7.1%
260390
 
6.9%
1 254855
 
6.8%
e 234945
 
6.2%
, 228637
 
6.1%
a 196611
 
5.2%
8 193240
 
5.1%
i 187873
 
5.0%
s 150318
 
4.0%
7 127152
 
3.4%
Other values (71) 1664051
44.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3765809
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 267737
 
7.1%
260390
 
6.9%
1 254855
 
6.8%
e 234945
 
6.2%
, 228637
 
6.1%
a 196611
 
5.2%
8 193240
 
5.1%
i 187873
 
5.0%
s 150318
 
4.0%
7 127152
 
3.4%
Other values (71) 1664051
44.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3765809
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 267737
 
7.1%
260390
 
6.9%
1 254855
 
6.8%
e 234945
 
6.2%
, 228637
 
6.1%
a 196611
 
5.2%
8 193240
 
5.1%
i 187873
 
5.0%
s 150318
 
4.0%
7 127152
 
3.4%
Other values (71) 1664051
44.2%

nomenclaturalCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size2.2 MiB
2025-02-28T12:42:05.749665image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1158508
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 rowICZN
2nd rowICZN
3rd rowICZN
4th rowICZN
5th rowICZN
ValueCountFrequency (%)
iczn 289627
100.0%
2025-02-28T12:42:05.826669image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 289627
25.0%
C 289627
25.0%
Z 289627
25.0%
N 289627
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1158508
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
I 289627
25.0%
C 289627
25.0%
Z 289627
25.0%
N 289627
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1158508
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
I 289627
25.0%
C 289627
25.0%
Z 289627
25.0%
N 289627
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1158508
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
I 289627
25.0%
C 289627
25.0%
Z 289627
25.0%
N 289627
25.0%