Overview

Dataset statistics

Number of variables21
Number of observations10000
Missing cells8456
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory176.0 B

Variable types

Categorical1
Text20

Dataset

Description제20대 대통령선거 개표 결과에 대한 정보로, 전국 시도, 구시군, 읍면동, 투표구별 제20대 대통령선거의 개표 결과 데이터를 조회하실 수 있습니다.
URLhttps://www.data.go.kr/data/15101504/fileData.do

Alerts

읍면동명 has 7890 (78.9%) missing valuesMissing
투표구명 has 566 (5.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 11:05:28.258319
Analysis finished2023-12-12 11:05:30.343117
Duration2.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
2012 
서울특별시
1445 
경상북도
763 
경상남도
737 
전라남도
712 
Other values (12)
4331 

Length

Max length7
Median length5
Mean length4.1748
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row강원도
3rd row인천광역시
4th row전라남도
5th row서울특별시

Common Values

ValueCountFrequency (%)
경기도 2012
20.1%
서울특별시 1445
14.4%
경상북도 763
 
7.6%
경상남도 737
 
7.4%
전라남도 712
 
7.1%
부산광역시 617
 
6.2%
충청남도 558
 
5.6%
전라북도 504
 
5.0%
강원도 500
 
5.0%
인천광역시 497
 
5.0%
Other values (7) 1655
16.6%

Length

2023-12-12T20:05:30.472531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 2012
20.1%
서울특별시 1445
14.4%
경상북도 763
 
7.6%
경상남도 737
 
7.4%
전라남도 712
 
7.1%
부산광역시 617
 
6.2%
충청남도 558
 
5.6%
전라북도 504
 
5.0%
강원도 500
 
5.0%
인천광역시 497
 
5.0%
Other values (7) 1655
16.6%
Distinct230
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:30.921469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4217
Min length2

Characters and Unicode

Total characters34217
Distinct characters149
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row서대문구
2nd row춘천시
3rd row계양구
4th row여수시
5th row성동구
ValueCountFrequency (%)
서구 263
 
2.6%
동구 232
 
2.3%
북구 225
 
2.2%
중구 181
 
1.8%
남구 175
 
1.8%
강서구 112
 
1.1%
화성시 102
 
1.0%
제주시 92
 
0.9%
부천시 90
 
0.9%
송파구 88
 
0.9%
Other values (220) 8440
84.4%
2023-12-12T20:05:31.882580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5138
 
15.0%
4758
 
13.9%
1930
 
5.6%
1094
 
3.2%
1000
 
2.9%
874
 
2.6%
851
 
2.5%
834
 
2.4%
834
 
2.4%
811
 
2.4%
Other values (139) 16093
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34203
> 99.9%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5138
 
15.0%
4758
 
13.9%
1930
 
5.6%
1094
 
3.2%
1000
 
2.9%
874
 
2.6%
851
 
2.5%
834
 
2.4%
834
 
2.4%
811
 
2.4%
Other values (137) 16079
47.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34203
> 99.9%
Common 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5138
 
15.0%
4758
 
13.9%
1930
 
5.6%
1094
 
3.2%
1000
 
2.9%
874
 
2.6%
851
 
2.5%
834
 
2.4%
834
 
2.4%
811
 
2.4%
Other values (137) 16079
47.0%
Common
ValueCountFrequency (%)
( 7
50.0%
) 7
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34203
> 99.9%
ASCII 14
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5138
 
15.0%
4758
 
13.9%
1930
 
5.6%
1094
 
3.2%
1000
 
2.9%
874
 
2.6%
851
 
2.5%
834
 
2.4%
834
 
2.4%
811
 
2.4%
Other values (137) 16079
47.0%
ASCII
ValueCountFrequency (%)
( 7
50.0%
) 7
50.0%

읍면동명
Text

MISSING 

Distinct1471
Distinct (%)69.7%
Missing7890
Missing (%)78.9%
Memory size156.2 KiB
2023-12-12T20:05:32.453183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length4.1971564
Min length2

Characters and Unicode

Total characters8856
Distinct characters290
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1403 ?
Unique (%)66.5%

Sample

1st row거소·선상투표
2nd row복수면
3rd row지품면
4th row재외투표
5th row현도면
ValueCountFrequency (%)
합계 122
 
5.2%
투입·구분된 117
 
5.0%
투표지 117
 
5.0%
잘못 117
 
5.0%
관외사전투표 112
 
4.8%
재외투표 107
 
4.6%
거소·선상투표 101
 
4.3%
중앙동 13
 
0.6%
남면 4
 
0.2%
금성면 4
 
0.2%
Other values (1463) 1530
65.3%
2023-12-12T20:05:33.149709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
978
 
11.0%
554
 
6.3%
534
 
6.0%
437
 
4.9%
· 238
 
2.7%
234
 
2.6%
221
 
2.5%
2 166
 
1.9%
1 151
 
1.7%
146
 
1.6%
Other values (280) 5197
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7940
89.7%
Decimal Number 444
 
5.0%
Other Punctuation 238
 
2.7%
Space Separator 234
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
978
 
12.3%
554
 
7.0%
534
 
6.7%
437
 
5.5%
221
 
2.8%
146
 
1.8%
144
 
1.8%
143
 
1.8%
142
 
1.8%
142
 
1.8%
Other values (268) 4499
56.7%
Decimal Number
ValueCountFrequency (%)
2 166
37.4%
1 151
34.0%
3 63
 
14.2%
4 26
 
5.9%
5 15
 
3.4%
6 10
 
2.3%
7 5
 
1.1%
8 4
 
0.9%
9 2
 
0.5%
0 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
· 238
100.0%
Space Separator
ValueCountFrequency (%)
234
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7940
89.7%
Common 916
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
978
 
12.3%
554
 
7.0%
534
 
6.7%
437
 
5.5%
221
 
2.8%
146
 
1.8%
144
 
1.8%
143
 
1.8%
142
 
1.8%
142
 
1.8%
Other values (268) 4499
56.7%
Common
ValueCountFrequency (%)
· 238
26.0%
234
25.5%
2 166
18.1%
1 151
16.5%
3 63
 
6.9%
4 26
 
2.8%
5 15
 
1.6%
6 10
 
1.1%
7 5
 
0.5%
8 4
 
0.4%
Other values (2) 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7940
89.7%
ASCII 678
 
7.7%
None 238
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
978
 
12.3%
554
 
7.0%
534
 
6.7%
437
 
5.5%
221
 
2.8%
146
 
1.8%
144
 
1.8%
143
 
1.8%
142
 
1.8%
142
 
1.8%
Other values (268) 4499
56.7%
None
ValueCountFrequency (%)
· 238
100.0%
ASCII
ValueCountFrequency (%)
234
34.5%
2 166
24.5%
1 151
22.3%
3 63
 
9.3%
4 26
 
3.8%
5 15
 
2.2%
6 10
 
1.5%
7 5
 
0.7%
8 4
 
0.6%
9 2
 
0.3%

투표구명
Text

MISSING 

Distinct6170
Distinct (%)65.4%
Missing566
Missing (%)5.7%
Memory size156.2 KiB
2023-12-12T20:05:33.494860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length5.7306551
Min length2

Characters and Unicode

Total characters54063
Distinct characters328
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6031 ?
Unique (%)63.9%

Sample

1st row관내사전투표
2nd row관내사전투표
3rd row계양3동제5투
4th row화정면제1투
5th row남원읍제2투
ValueCountFrequency (%)
소계 1551
 
16.4%
관내사전투표 1521
 
16.1%
중앙동제1투 13
 
0.1%
중앙동제2투 12
 
0.1%
중앙동제3투 8
 
0.1%
남면제3투 6
 
0.1%
남면제2투 5
 
0.1%
송정동제1투 5
 
0.1%
북면제1투 5
 
0.1%
남면제1투 4
 
< 0.1%
Other values (6160) 6304
66.8%
2023-12-12T20:05:34.020452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7883
 
14.6%
6916
 
12.8%
4758
 
8.8%
1 2482
 
4.6%
2 2226
 
4.1%
1811
 
3.3%
1730
 
3.2%
1672
 
3.1%
1653
 
3.1%
1630
 
3.0%
Other values (318) 21302
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45192
83.6%
Decimal Number 8791
 
16.3%
Other Punctuation 80
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7883
17.4%
6916
15.3%
4758
 
10.5%
1811
 
4.0%
1730
 
3.8%
1672
 
3.7%
1653
 
3.7%
1630
 
3.6%
1625
 
3.6%
1586
 
3.5%
Other values (307) 13928
30.8%
Decimal Number
ValueCountFrequency (%)
1 2482
28.2%
2 2226
25.3%
3 1448
16.5%
4 969
 
11.0%
5 619
 
7.0%
6 425
 
4.8%
7 270
 
3.1%
8 174
 
2.0%
9 105
 
1.2%
0 73
 
0.8%
Other Punctuation
ValueCountFrequency (%)
· 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45192
83.6%
Common 8871
 
16.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7883
17.4%
6916
15.3%
4758
 
10.5%
1811
 
4.0%
1730
 
3.8%
1672
 
3.7%
1653
 
3.7%
1630
 
3.6%
1625
 
3.6%
1586
 
3.5%
Other values (307) 13928
30.8%
Common
ValueCountFrequency (%)
1 2482
28.0%
2 2226
25.1%
3 1448
16.3%
4 969
 
10.9%
5 619
 
7.0%
6 425
 
4.8%
7 270
 
3.0%
8 174
 
2.0%
9 105
 
1.2%
· 80
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45192
83.6%
ASCII 8791
 
16.3%
None 80
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7883
17.4%
6916
15.3%
4758
 
10.5%
1811
 
4.0%
1730
 
3.8%
1672
 
3.7%
1653
 
3.7%
1630
 
3.6%
1625
 
3.6%
1586
 
3.5%
Other values (307) 13928
30.8%
ASCII
ValueCountFrequency (%)
1 2482
28.2%
2 2226
25.3%
3 1448
16.5%
4 969
 
11.0%
5 619
 
7.0%
6 425
 
4.8%
7 270
 
3.1%
8 174
 
2.0%
9 105
 
1.2%
0 73
 
0.8%
None
ValueCountFrequency (%)
· 80
100.0%
Distinct4963
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:34.595537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.7122
Min length1

Characters and Unicode

Total characters47122
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2639 ?
Unique (%)26.4%

Sample

1st row5,545
2nd row6,288
3rd row3,038
4th row119
5th row339
ValueCountFrequency (%)
0 117
 
1.2%
2,349 10
 
0.1%
1,762 10
 
0.1%
2,050 9
 
0.1%
1,949 9
 
0.1%
2,402 9
 
0.1%
2,481 9
 
0.1%
1,822 9
 
0.1%
817 8
 
0.1%
2,264 8
 
0.1%
Other values (4953) 9802
98.0%
2023-12-12T20:05:35.350622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 8194
17.4%
2 6225
13.2%
1 6076
12.9%
3 4087
8.7%
4 3564
7.6%
5 3241
 
6.9%
7 3221
 
6.8%
6 3183
 
6.8%
8 3141
 
6.7%
0 3134
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38928
82.6%
Other Punctuation 8194
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6225
16.0%
1 6076
15.6%
3 4087
10.5%
4 3564
9.2%
5 3241
8.3%
7 3221
8.3%
6 3183
8.2%
8 3141
8.1%
0 3134
8.1%
9 3056
7.9%
Other Punctuation
ValueCountFrequency (%)
, 8194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47122
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 8194
17.4%
2 6225
13.2%
1 6076
12.9%
3 4087
8.7%
4 3564
7.6%
5 3241
 
6.9%
7 3221
 
6.8%
6 3183
 
6.8%
8 3141
 
6.7%
0 3134
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 8194
17.4%
2 6225
13.2%
1 6076
12.9%
3 4087
8.7%
4 3564
7.6%
5 3241
 
6.9%
7 3221
 
6.8%
6 3183
 
6.8%
8 3141
 
6.7%
0 3134
 
6.7%
Distinct4380
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:35.959851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.4606
Min length1

Characters and Unicode

Total characters44606
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2319 ?
Unique (%)23.2%

Sample

1st row5,545
2nd row6,286
3rd row1,620
4th row80
5th row301
ValueCountFrequency (%)
0 37
 
0.4%
1 26
 
0.3%
3 14
 
0.1%
2 13
 
0.1%
1,479 13
 
0.1%
4 12
 
0.1%
1,562 12
 
0.1%
1,019 11
 
0.1%
1,470 11
 
0.1%
1,240 11
 
0.1%
Other values (4370) 9840
98.4%
2023-12-12T20:05:36.822568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7565
17.0%
, 7032
15.8%
2 4257
9.5%
4 3498
7.8%
3 3481
7.8%
5 3359
7.5%
6 3213
7.2%
7 3193
7.2%
0 3021
 
6.8%
9 2997
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37574
84.2%
Other Punctuation 7032
 
15.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7565
20.1%
2 4257
11.3%
4 3498
9.3%
3 3481
9.3%
5 3359
8.9%
6 3213
8.6%
7 3193
8.5%
0 3021
 
8.0%
9 2997
 
8.0%
8 2990
 
8.0%
Other Punctuation
ValueCountFrequency (%)
, 7032
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44606
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7565
17.0%
, 7032
15.8%
2 4257
9.5%
4 3498
7.8%
3 3481
7.8%
5 3359
7.5%
6 3213
7.2%
7 3193
7.2%
0 3021
 
6.8%
9 2997
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7565
17.0%
, 7032
15.8%
2 4257
9.5%
4 3498
7.8%
3 3481
7.8%
5 3359
7.5%
6 3213
7.2%
7 3193
7.2%
0 3021
 
6.8%
9 2997
 
6.7%
Distinct3170
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:37.435291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.5301
Min length1

Characters and Unicode

Total characters35301
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1717 ?
Unique (%)17.2%

Sample

1st row2,899
2nd row3,075
3rd row897
4th row69
5th row106
ValueCountFrequency (%)
0 61
 
0.6%
1 31
 
0.3%
492 18
 
0.2%
93 17
 
0.2%
231 17
 
0.2%
581 16
 
0.2%
491 16
 
0.2%
661 15
 
0.1%
380 15
 
0.1%
146 15
 
0.1%
Other values (3160) 9779
97.8%
2023-12-12T20:05:38.329989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4674
13.2%
2 3614
10.2%
3 3517
10.0%
4 3295
9.3%
5 3208
9.1%
6 3102
8.8%
7 2944
8.3%
, 2891
8.2%
8 2825
8.0%
9 2707
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32410
91.8%
Other Punctuation 2891
 
8.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4674
14.4%
2 3614
11.2%
3 3517
10.9%
4 3295
10.2%
5 3208
9.9%
6 3102
9.6%
7 2944
9.1%
8 2825
8.7%
9 2707
8.4%
0 2524
7.8%
Other Punctuation
ValueCountFrequency (%)
, 2891
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35301
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4674
13.2%
2 3614
10.2%
3 3517
10.0%
4 3295
9.3%
5 3208
9.1%
6 3102
8.8%
7 2944
8.3%
, 2891
8.2%
8 2825
8.0%
9 2707
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4674
13.2%
2 3614
10.2%
3 3517
10.0%
4 3295
9.3%
5 3208
9.1%
6 3102
8.8%
7 2944
8.3%
, 2891
8.2%
8 2825
8.0%
9 2707
7.7%
Distinct3146
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:38.858840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.5838
Min length1

Characters and Unicode

Total characters35838
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1581 ?
Unique (%)15.8%

Sample

1st row2,449
2nd row2,958
3rd row630
4th row7
5th row151
ValueCountFrequency (%)
0 63
 
0.6%
1 36
 
0.4%
2 17
 
0.2%
127 16
 
0.2%
20 15
 
0.1%
831 15
 
0.1%
27 15
 
0.1%
681 15
 
0.1%
666 15
 
0.1%
637 14
 
0.1%
Other values (3136) 9779
97.8%
2023-12-12T20:05:39.579568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5090
14.2%
2 3409
9.5%
, 3246
9.1%
3 3227
9.0%
6 3158
8.8%
5 3123
8.7%
7 3048
8.5%
4 2999
8.4%
8 2974
8.3%
9 2830
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32592
90.9%
Other Punctuation 3246
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5090
15.6%
2 3409
10.5%
3 3227
9.9%
6 3158
9.7%
5 3123
9.6%
7 3048
9.4%
4 2999
9.2%
8 2974
9.1%
9 2830
8.7%
0 2734
8.4%
Other Punctuation
ValueCountFrequency (%)
, 3246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35838
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5090
14.2%
2 3409
9.5%
, 3246
9.1%
3 3227
9.0%
6 3158
8.8%
5 3123
8.7%
7 3048
8.5%
4 2999
8.4%
8 2974
8.3%
9 2830
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5090
14.2%
2 3409
9.5%
, 3246
9.1%
3 3227
9.0%
6 3158
8.8%
5 3123
8.7%
7 3048
8.5%
4 2999
8.4%
8 2974
8.3%
9 2830
7.9%
Distinct683
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:40.143477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.015
Min length1

Characters and Unicode

Total characters20150
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)3.0%

Sample

1st row147
2nd row176
3rd row57
4th row2
5th row2
ValueCountFrequency (%)
0 197
 
2.0%
8 196
 
2.0%
6 185
 
1.8%
10 172
 
1.7%
11 167
 
1.7%
4 167
 
1.7%
9 161
 
1.6%
5 157
 
1.6%
7 156
 
1.6%
19 149
 
1.5%
Other values (673) 8293
82.9%
2023-12-12T20:05:40.922788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3390
16.8%
2 2684
13.3%
3 2636
13.1%
4 2414
12.0%
5 1984
9.8%
6 1633
8.1%
7 1417
7.0%
0 1410
7.0%
8 1302
 
6.5%
9 1170
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20040
99.5%
Other Punctuation 110
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3390
16.9%
2 2684
13.4%
3 2636
13.2%
4 2414
12.0%
5 1984
9.9%
6 1633
8.1%
7 1417
7.1%
0 1410
7.0%
8 1302
 
6.5%
9 1170
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3390
16.8%
2 2684
13.3%
3 2636
13.1%
4 2414
12.0%
5 1984
9.8%
6 1633
8.1%
7 1417
7.0%
0 1410
7.0%
8 1302
 
6.5%
9 1170
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3390
16.8%
2 2684
13.3%
3 2636
13.1%
4 2414
12.0%
5 1984
9.8%
6 1633
8.1%
7 1417
7.0%
0 1410
7.0%
8 1302
 
6.5%
9 1170
 
5.8%
Distinct106
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:41.227407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0402
Min length1

Characters and Unicode

Total characters10402
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)0.5%

Sample

1st row1
2nd row2
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 4578
45.8%
1 2471
24.7%
2 1177
 
11.8%
3 567
 
5.7%
4 309
 
3.1%
5 189
 
1.9%
6 121
 
1.2%
7 107
 
1.1%
8 83
 
0.8%
10 49
 
0.5%
Other values (96) 349
 
3.5%
2023-12-12T20:05:41.760430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4653
44.7%
1 2766
26.6%
2 1275
 
12.3%
3 632
 
6.1%
4 362
 
3.5%
5 227
 
2.2%
6 163
 
1.6%
7 129
 
1.2%
8 117
 
1.1%
9 75
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10399
> 99.9%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4653
44.7%
1 2766
26.6%
2 1275
 
12.3%
3 632
 
6.1%
4 362
 
3.5%
5 227
 
2.2%
6 163
 
1.6%
7 129
 
1.2%
8 117
 
1.1%
9 75
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10402
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4653
44.7%
1 2766
26.6%
2 1275
 
12.3%
3 632
 
6.1%
4 362
 
3.5%
5 227
 
2.2%
6 163
 
1.6%
7 129
 
1.2%
8 117
 
1.1%
9 75
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10402
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4653
44.7%
1 2766
26.6%
2 1275
 
12.3%
3 632
 
6.1%
4 362
 
3.5%
5 227
 
2.2%
6 163
 
1.6%
7 129
 
1.2%
8 117
 
1.1%
9 75
 
0.7%
Distinct381
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:42.271234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length1.692
Min length1

Characters and Unicode

Total characters16920
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)1.9%

Sample

1st row10
2nd row24
3rd row13
4th row0
5th row9
ValueCountFrequency (%)
9 437
 
4.4%
8 434
 
4.3%
11 432
 
4.3%
7 431
 
4.3%
10 419
 
4.2%
5 411
 
4.1%
6 408
 
4.1%
12 392
 
3.9%
3 391
 
3.9%
4 370
 
3.7%
Other values (371) 5875
58.8%
2023-12-12T20:05:42.930037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4737
28.0%
2 2562
15.1%
3 1652
 
9.8%
4 1286
 
7.6%
0 1202
 
7.1%
5 1199
 
7.1%
6 1134
 
6.7%
7 1088
 
6.4%
8 1001
 
5.9%
9 987
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16848
99.6%
Other Punctuation 72
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4737
28.1%
2 2562
15.2%
3 1652
 
9.8%
4 1286
 
7.6%
0 1202
 
7.1%
5 1199
 
7.1%
6 1134
 
6.7%
7 1088
 
6.5%
8 1001
 
5.9%
9 987
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4737
28.0%
2 2562
15.1%
3 1652
 
9.8%
4 1286
 
7.6%
0 1202
 
7.1%
5 1199
 
7.1%
6 1134
 
6.7%
7 1088
 
6.4%
8 1001
 
5.9%
9 987
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4737
28.0%
2 2562
15.1%
3 1652
 
9.8%
4 1286
 
7.6%
0 1202
 
7.1%
5 1199
 
7.1%
6 1134
 
6.7%
7 1088
 
6.4%
8 1001
 
5.9%
9 987
 
5.8%
Distinct82
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:43.192573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0176
Min length1

Characters and Unicode

Total characters10176
Distinct characters11
Distinct categories2 ?
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 (%)0.4%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 6154
61.5%
1 2134
 
21.3%
2 794
 
7.9%
3 353
 
3.5%
4 166
 
1.7%
5 85
 
0.9%
7 57
 
0.6%
6 57
 
0.6%
8 29
 
0.3%
10 15
 
0.1%
Other values (72) 156
 
1.6%
2023-12-12T20:05:43.699904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6183
60.8%
1 2238
 
22.0%
2 829
 
8.1%
3 384
 
3.8%
4 192
 
1.9%
5 120
 
1.2%
7 80
 
0.8%
6 73
 
0.7%
8 52
 
0.5%
9 24
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10175
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6183
60.8%
1 2238
 
22.0%
2 829
 
8.1%
3 384
 
3.8%
4 192
 
1.9%
5 120
 
1.2%
7 80
 
0.8%
6 73
 
0.7%
8 52
 
0.5%
9 24
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10176
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6183
60.8%
1 2238
 
22.0%
2 829
 
8.1%
3 384
 
3.8%
4 192
 
1.9%
5 120
 
1.2%
7 80
 
0.8%
6 73
 
0.7%
8 52
 
0.5%
9 24
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6183
60.8%
1 2238
 
22.0%
2 829
 
8.1%
3 384
 
3.8%
4 192
 
1.9%
5 120
 
1.2%
7 80
 
0.8%
6 73
 
0.7%
8 52
 
0.5%
9 24
 
0.2%
Distinct55
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:43.923764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0108
Min length1

Characters and Unicode

Total characters10108
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)0.2%

Sample

1st row1
2nd row3
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 7306
73.1%
1 1752
 
17.5%
2 485
 
4.9%
3 177
 
1.8%
4 86
 
0.9%
5 45
 
0.4%
6 27
 
0.3%
7 10
 
0.1%
8 8
 
0.1%
20 5
 
< 0.1%
Other values (45) 99
 
1.0%
2023-12-12T20:05:44.380108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7320
72.4%
1 1804
 
17.8%
2 515
 
5.1%
3 213
 
2.1%
4 109
 
1.1%
5 61
 
0.6%
6 38
 
0.4%
7 20
 
0.2%
8 15
 
0.1%
9 12
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10107
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7320
72.4%
1 1804
 
17.8%
2 515
 
5.1%
3 213
 
2.1%
4 109
 
1.1%
5 61
 
0.6%
6 38
 
0.4%
7 20
 
0.2%
8 15
 
0.1%
9 12
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7320
72.4%
1 1804
 
17.8%
2 515
 
5.1%
3 213
 
2.1%
4 109
 
1.1%
5 61
 
0.6%
6 38
 
0.4%
7 20
 
0.2%
8 15
 
0.1%
9 12
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7320
72.4%
1 1804
 
17.8%
2 515
 
5.1%
3 213
 
2.1%
4 109
 
1.1%
5 61
 
0.6%
6 38
 
0.4%
7 20
 
0.2%
8 15
 
0.1%
9 12
 
0.1%
Distinct78
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:44.592311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0151
Min length1

Characters and Unicode

Total characters10151
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)0.5%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 6224
62.2%
1 2149
 
21.5%
2 787
 
7.9%
3 311
 
3.1%
4 150
 
1.5%
5 93
 
0.9%
6 73
 
0.7%
7 39
 
0.4%
9 19
 
0.2%
8 18
 
0.2%
Other values (68) 137
 
1.4%
2023-12-12T20:05:45.019131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6250
61.6%
1 2228
 
21.9%
2 834
 
8.2%
3 336
 
3.3%
4 176
 
1.7%
5 109
 
1.1%
6 88
 
0.9%
7 60
 
0.6%
8 36
 
0.4%
9 33
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10150
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6250
61.6%
1 2228
 
22.0%
2 834
 
8.2%
3 336
 
3.3%
4 176
 
1.7%
5 109
 
1.1%
6 88
 
0.9%
7 60
 
0.6%
8 36
 
0.4%
9 33
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10151
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6250
61.6%
1 2228
 
21.9%
2 834
 
8.2%
3 336
 
3.3%
4 176
 
1.7%
5 109
 
1.1%
6 88
 
0.9%
7 60
 
0.6%
8 36
 
0.4%
9 33
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6250
61.6%
1 2228
 
21.9%
2 834
 
8.2%
3 336
 
3.3%
4 176
 
1.7%
5 109
 
1.1%
6 88
 
0.9%
7 60
 
0.6%
8 36
 
0.4%
9 33
 
0.3%
Distinct120
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:45.333001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0641
Min length1

Characters and Unicode

Total characters10641
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)0.7%

Sample

1st row1
2nd row2
3rd row1
4th row0
5th row1
ValueCountFrequency (%)
0 3545
35.4%
1 2335
23.4%
2 1477
14.8%
3 781
 
7.8%
4 538
 
5.4%
5 313
 
3.1%
6 160
 
1.6%
7 133
 
1.3%
8 83
 
0.8%
10 81
 
0.8%
Other values (110) 554
 
5.5%
2023-12-12T20:05:45.854873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3662
34.4%
1 2816
26.5%
2 1659
15.6%
3 880
 
8.3%
4 616
 
5.8%
5 367
 
3.4%
6 215
 
2.0%
7 179
 
1.7%
8 132
 
1.2%
9 111
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10637
> 99.9%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3662
34.4%
1 2816
26.5%
2 1659
15.6%
3 880
 
8.3%
4 616
 
5.8%
5 367
 
3.5%
6 215
 
2.0%
7 179
 
1.7%
8 132
 
1.2%
9 111
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10641
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3662
34.4%
1 2816
26.5%
2 1659
15.6%
3 880
 
8.3%
4 616
 
5.8%
5 367
 
3.4%
6 215
 
2.0%
7 179
 
1.7%
8 132
 
1.2%
9 111
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10641
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3662
34.4%
1 2816
26.5%
2 1659
15.6%
3 880
 
8.3%
4 616
 
5.8%
5 367
 
3.4%
6 215
 
2.0%
7 179
 
1.7%
8 132
 
1.2%
9 111
 
1.0%
Distinct152
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:46.098670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0922
Min length1

Characters and Unicode

Total characters10922
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)0.9%

Sample

1st row9
2nd row6
3rd row2
4th row0
5th row0
ValueCountFrequency (%)
0 2978
29.8%
1 2310
23.1%
2 1435
14.3%
3 916
 
9.2%
4 515
 
5.1%
5 321
 
3.2%
6 258
 
2.6%
7 180
 
1.8%
8 151
 
1.5%
9 104
 
1.0%
Other values (142) 832
 
8.3%
2023-12-12T20:05:46.521698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3116
28.5%
1 2953
27.0%
2 1715
15.7%
3 1087
 
10.0%
4 649
 
5.9%
5 413
 
3.8%
6 332
 
3.0%
7 261
 
2.4%
8 221
 
2.0%
9 170
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10917
> 99.9%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3116
28.5%
1 2953
27.0%
2 1715
15.7%
3 1087
 
10.0%
4 649
 
5.9%
5 413
 
3.8%
6 332
 
3.0%
7 261
 
2.4%
8 221
 
2.0%
9 170
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10922
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3116
28.5%
1 2953
27.0%
2 1715
15.7%
3 1087
 
10.0%
4 649
 
5.9%
5 413
 
3.8%
6 332
 
3.0%
7 261
 
2.4%
8 221
 
2.0%
9 170
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3116
28.5%
1 2953
27.0%
2 1715
15.7%
3 1087
 
10.0%
4 649
 
5.9%
5 413
 
3.8%
6 332
 
3.0%
7 261
 
2.4%
8 221
 
2.0%
9 170
 
1.6%
Distinct84
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:46.680942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0191
Min length1

Characters and Unicode

Total characters10191
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)0.4%

Sample

1st row2
2nd row0
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
0 5381
53.8%
1 2360
23.6%
2 968
 
9.7%
3 454
 
4.5%
4 242
 
2.4%
5 170
 
1.7%
6 106
 
1.1%
7 67
 
0.7%
8 48
 
0.5%
9 30
 
0.3%
Other values (74) 174
 
1.7%
2023-12-12T20:05:47.028368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5412
53.1%
1 2455
24.1%
2 1000
 
9.8%
3 484
 
4.7%
4 283
 
2.8%
5 213
 
2.1%
6 128
 
1.3%
7 98
 
1.0%
8 67
 
0.7%
9 49
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10189
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5412
53.1%
1 2455
24.1%
2 1000
 
9.8%
3 484
 
4.8%
4 283
 
2.8%
5 213
 
2.1%
6 128
 
1.3%
7 98
 
1.0%
8 67
 
0.7%
9 49
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10191
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5412
53.1%
1 2455
24.1%
2 1000
 
9.8%
3 484
 
4.7%
4 283
 
2.8%
5 213
 
2.1%
6 128
 
1.3%
7 98
 
1.0%
8 67
 
0.7%
9 49
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10191
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5412
53.1%
1 2455
24.1%
2 1000
 
9.8%
3 484
 
4.7%
4 283
 
2.8%
5 213
 
2.1%
6 128
 
1.3%
7 98
 
1.0%
8 67
 
0.7%
9 49
 
0.5%
Distinct108
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:47.280624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.0335
Min length1

Characters and Unicode

Total characters10335
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)0.6%

Sample

1st row0
2nd row3
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 4453
44.5%
1 2534
25.3%
2 1191
 
11.9%
3 575
 
5.8%
4 349
 
3.5%
5 202
 
2.0%
6 145
 
1.5%
7 126
 
1.3%
8 76
 
0.8%
9 51
 
0.5%
Other values (98) 298
 
3.0%
2023-12-12T20:05:47.766100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4513
43.7%
1 2780
26.9%
2 1248
 
12.1%
3 639
 
6.2%
4 392
 
3.8%
5 230
 
2.2%
6 185
 
1.8%
7 152
 
1.5%
8 114
 
1.1%
9 79
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10332
> 99.9%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4513
43.7%
1 2780
26.9%
2 1248
 
12.1%
3 639
 
6.2%
4 392
 
3.8%
5 230
 
2.2%
6 185
 
1.8%
7 152
 
1.5%
8 114
 
1.1%
9 79
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10335
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4513
43.7%
1 2780
26.9%
2 1248
 
12.1%
3 639
 
6.2%
4 392
 
3.8%
5 230
 
2.2%
6 185
 
1.8%
7 152
 
1.5%
8 114
 
1.1%
9 79
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10335
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4513
43.7%
1 2780
26.9%
2 1248
 
12.1%
3 639
 
6.2%
4 392
 
3.8%
5 230
 
2.2%
6 185
 
1.8%
7 152
 
1.5%
8 114
 
1.1%
9 79
 
0.8%


Text

Distinct4382
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:48.304972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.4491
Min length1

Characters and Unicode

Total characters44491
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2374 ?
Unique (%)23.7%

Sample

1st row5,519
2nd row6,250
3rd row1,603
4th row80
5th row270
ValueCountFrequency (%)
0 37
 
0.4%
1 26
 
0.3%
2 15
 
0.1%
3 14
 
0.1%
1,408 12
 
0.1%
1,552 12
 
0.1%
1,198 12
 
0.1%
1,328 12
 
0.1%
1,745 11
 
0.1%
1,531 11
 
0.1%
Other values (4372) 9838
98.4%
2023-12-12T20:05:49.117667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7628
17.1%
, 6979
15.7%
2 4158
9.3%
4 3523
7.9%
3 3522
7.9%
5 3331
7.5%
6 3329
7.5%
7 3089
6.9%
8 2989
 
6.7%
9 2973
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37512
84.3%
Other Punctuation 6979
 
15.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7628
20.3%
2 4158
11.1%
4 3523
9.4%
3 3522
9.4%
5 3331
8.9%
6 3329
8.9%
7 3089
8.2%
8 2989
 
8.0%
9 2973
 
7.9%
0 2970
 
7.9%
Other Punctuation
ValueCountFrequency (%)
, 6979
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44491
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7628
17.1%
, 6979
15.7%
2 4158
9.3%
4 3523
7.9%
3 3522
7.9%
5 3331
7.5%
6 3329
7.5%
7 3089
6.9%
8 2989
 
6.7%
9 2973
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7628
17.1%
, 6979
15.7%
2 4158
9.3%
4 3523
7.9%
3 3522
7.9%
5 3331
7.5%
6 3329
7.5%
7 3089
6.9%
8 2989
 
6.7%
9 2973
 
6.7%
Distinct381
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:49.642231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length1.7682
Min length1

Characters and Unicode

Total characters17682
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)1.7%

Sample

1st row26
2nd row36
3rd row17
4th row0
5th row31
ValueCountFrequency (%)
11 460
 
4.6%
13 439
 
4.4%
14 429
 
4.3%
10 426
 
4.3%
9 414
 
4.1%
8 402
 
4.0%
12 393
 
3.9%
7 377
 
3.8%
16 373
 
3.7%
5 368
 
3.7%
Other values (371) 5919
59.2%
2023-12-12T20:05:50.358419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5332
30.2%
2 2655
15.0%
3 1577
 
8.9%
4 1326
 
7.5%
5 1194
 
6.8%
6 1193
 
6.7%
0 1183
 
6.7%
7 1076
 
6.1%
8 1042
 
5.9%
9 1031
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17609
99.6%
Other Punctuation 73
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5332
30.3%
2 2655
15.1%
3 1577
 
9.0%
4 1326
 
7.5%
5 1194
 
6.8%
6 1193
 
6.8%
0 1183
 
6.7%
7 1076
 
6.1%
8 1042
 
5.9%
9 1031
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17682
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5332
30.2%
2 2655
15.0%
3 1577
 
8.9%
4 1326
 
7.5%
5 1194
 
6.8%
6 1193
 
6.7%
0 1183
 
6.7%
7 1076
 
6.1%
8 1042
 
5.9%
9 1031
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5332
30.2%
2 2655
15.0%
3 1577
 
8.9%
4 1326
 
7.5%
5 1194
 
6.8%
6 1193
 
6.7%
0 1183
 
6.7%
7 1076
 
6.1%
8 1042
 
5.9%
9 1031
 
5.8%
Distinct2483
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:05:50.908008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.1002
Min length1

Characters and Unicode

Total characters31002
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1116 ?
Unique (%)11.2%

Sample

1st row0
2nd row2
3rd row1,418
4th row39
5th row38
ValueCountFrequency (%)
0 1334
 
13.3%
1 204
 
2.0%
2 79
 
0.8%
3 44
 
0.4%
4 35
 
0.4%
6 24
 
0.2%
776 18
 
0.2%
660 16
 
0.2%
702 16
 
0.2%
646 16
 
0.2%
Other values (2463) 8214
82.1%
2023-12-12T20:05:51.678284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4068
13.1%
0 3538
11.4%
6 2816
9.1%
7 2763
8.9%
2 2760
8.9%
3 2740
8.8%
4 2670
8.6%
5 2600
8.4%
8 2385
7.7%
, 2277
7.3%
Other values (2) 2385
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28614
92.3%
Other Punctuation 2277
 
7.3%
Dash Punctuation 111
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4068
14.2%
0 3538
12.4%
6 2816
9.8%
7 2763
9.7%
2 2760
9.6%
3 2740
9.6%
4 2670
9.3%
5 2600
9.1%
8 2385
8.3%
9 2274
7.9%
Other Punctuation
ValueCountFrequency (%)
, 2277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31002
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4068
13.1%
0 3538
11.4%
6 2816
9.1%
7 2763
8.9%
2 2760
8.9%
3 2740
8.8%
4 2670
8.6%
5 2600
8.4%
8 2385
7.7%
, 2277
7.3%
Other values (2) 2385
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4068
13.1%
0 3538
11.4%
6 2816
9.1%
7 2763
8.9%
2 2760
8.9%
3 2740
8.8%
4 2670
8.6%
5 2600
8.4%
8 2385
7.7%
, 2277
7.3%
Other values (2) 2385
7.7%

Sample

시도구시군읍면동명투표구명선거인수투표수더불어민주당 이재명국민의힘 윤석열정의당 심상정기본소득당 오준호국가혁명당 허경영노동당 이백윤새누리당 옥은호신자유민주연합 김경재우리공화당 조원진진보당 김재연통일한국당 이경희한류연합당 김민찬무효투표수기권수
1479서울특별시서대문구<NA>관내사전투표5,5455,5452,8992,44914711001019205,519260
13093강원도춘천시<NA>관내사전투표6,2886,2863,0752,95817622413026036,250362
6419인천광역시계양구<NA>계양3동제5투3,0381,6208976305711300112101,603171,418
17593전라남도여수시<NA>화정면제1투11980697200000001180039
262서울특별시성동구거소·선상투표<NA>33930110615120900010102703138
22647제주특별자치도서귀포시<NA>남원읍제2투897568285250901000004225626329
6681인천광역시옹진군<NA>대청면제2투160722045202000000069388
8840경기도성남시수정구<NA>산성동제1투2,4111,5699285733501100002031,55217842
15756충청남도금산군복수면소계2,4891,8746401,1542922300132111,85618615
20645경상북도영덕군지품면소계1,6761,4042211,1182211110130421,38420272
시도구시군읍면동명투표구명선거인수투표수더불어민주당 이재명국민의힘 윤석열정의당 심상정기본소득당 오준호국가혁명당 허경영노동당 이백윤새누리당 옥은호신자유민주연합 김경재우리공화당 조원진진보당 김재연통일한국당 이경희한류연합당 김민찬무효투표수기권수
12412경기도안성시<NA>관내사전투표1,1931,192511627242800113011,178141
288서울특별시성동구<NA>옥수동제3투2,4821,7125681,080450600062001,7075770
14158충청북도청주시상당구<NA>금천동제6투2,8421,7448397946011910025011,722221,098
22458제주특별자치도제주시<NA>애월읍제11투3,3932,0751,1028369002510113102,060151,318
1648서울특별시양천구<NA>목1동제3투2,7741,9928201,0884711600040001,97616782
1149서울특별시노원구<NA>공릉2동제6투2,4361,6667038566211110226011,64521770
12098경기도용인시처인구<NA>남사읍제4투923577202343809001200056512346
2049서울특별시구로구<NA>개봉제1동제6투2,0921,254520658441800040001,23519838
7431대전광역시중구<NA>관내사전투표1,5991,5997517863631210100001,59090
14515충청북도충주시<NA>관내사전투표531531202310903000020052650