Overview

Dataset statistics

Number of variables13
Number of observations911
Missing cells2778
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory95.3 KiB
Average record size in memory107.1 B

Variable types

Text8
Categorical2
Unsupported3

Dataset

Description비영리민간단체등록현황201510
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202564

Alerts

Unnamed: 7 is highly overall correlated with Unnamed: 8High correlation
Unnamed: 8 is highly overall correlated with Unnamed: 7High correlation
Unnamed: 8 is highly imbalanced (54.9%)Imbalance
Unnamed: 6 has 35 (3.8%) missing valuesMissing
Unnamed: 10 has 911 (100.0%) missing valuesMissing
Unnamed: 11 has 911 (100.0%) missing valuesMissing
Unnamed: 12 has 911 (100.0%) missing valuesMissing
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:35:20.302098
Analysis finished2024-03-14 02:35:21.537770
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Text

Distinct910
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2024-03-14T11:35:21.825130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8824176
Min length1

Characters and Unicode

Total characters2623
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique910 ?
Unique (%)100.0%

Sample

1st row일련번호
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
일련번호 1
 
0.1%
625 1
 
0.1%
599 1
 
0.1%
611 1
 
0.1%
600 1
 
0.1%
601 1
 
0.1%
602 1
 
0.1%
603 1
 
0.1%
604 1
 
0.1%
605 1
 
0.1%
Other values (900) 900
98.9%
2024-03-14T11:35:22.327473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 281
10.7%
7 281
10.7%
1 281
10.7%
3 281
10.7%
2 281
10.7%
4 281
10.7%
6 281
10.7%
8 281
10.7%
9 191
7.3%
0 180
6.9%
Other values (4) 4
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2619
99.8%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 281
10.7%
7 281
10.7%
1 281
10.7%
3 281
10.7%
2 281
10.7%
4 281
10.7%
6 281
10.7%
8 281
10.7%
9 191
7.3%
0 180
6.9%
Other Letter
ValueCountFrequency (%)
일 1
25.0%
련 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2619
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
5 281
10.7%
7 281
10.7%
1 281
10.7%
3 281
10.7%
2 281
10.7%
4 281
10.7%
6 281
10.7%
8 281
10.7%
9 191
7.3%
0 180
6.9%
Hangul
ValueCountFrequency (%)
일 1
25.0%
련 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2619
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 281
10.7%
7 281
10.7%
1 281
10.7%
3 281
10.7%
2 281
10.7%
4 281
10.7%
6 281
10.7%
8 281
10.7%
9 191
7.3%
0 180
6.9%
Hangul
ValueCountFrequency (%)
일 1
25.0%
련 1
25.0%
번 1
25.0%
호 1
25.0%

비영리민간단체 등록대장
Text

Distinct910
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2024-03-14T11:35:22.549698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length16.034066
Min length12

Characters and Unicode

Total characters14591
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique910 ?
Unique (%)100.0%

Sample

1st row등록번호 (구등록번호)
2nd row2000-1-전라북도-1(1)
3rd row2000-1-전라북도-2(3)
4th row2000-1-전라북도-3(4)
5th row2000-1-전라북도-4(5)
ValueCountFrequency (%)
등록번호 1
 
0.1%
2009-1-전라북도-29 1
 
0.1%
2008-1-전라북도-104 1
 
0.1%
2009-1-전라북도-12 1
 
0.1%
2009-1-전라북도-1 1
 
0.1%
2009-1-전라북도-2 1
 
0.1%
2009-1-전라북도-3 1
 
0.1%
2009-1-전라북도-4 1
 
0.1%
2009-1-전라북도-5 1
 
0.1%
2009-1-전라북도-6 1
 
0.1%
Other values (901) 901
98.9%
2024-03-14T11:35:22.827600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2741
18.8%
0 2014
13.8%
1 1704
11.7%
2 1392
9.5%
도 911
 
6.2%
북 911
 
6.2%
전 911
 
6.2%
라 911
 
6.2%
3 460
 
3.2%
) 393
 
2.7%
Other values (16) 2243
15.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7404
50.7%
Other Letter 3659
25.1%
Dash Punctuation 2741
 
18.8%
Close Punctuation 393
 
2.7%
Open Punctuation 393
 
2.7%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 911
24.9%
북 911
24.9%
전 911
24.9%
라 911
24.9%
호 4
 
0.1%
제 2
 
0.1%
등 2
 
0.1%
록 2
 
0.1%
번 2
 
0.1%
구 1
 
< 0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 2014
27.2%
1 1704
23.0%
2 1392
18.8%
3 460
 
6.2%
4 336
 
4.5%
5 306
 
4.1%
9 305
 
4.1%
7 304
 
4.1%
8 298
 
4.0%
6 285
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 2741
100.0%
Close Punctuation
ValueCountFrequency (%)
) 393
100.0%
Open Punctuation
ValueCountFrequency (%)
( 393
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10932
74.9%
Hangul 3659
 
25.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2741
25.1%
0 2014
18.4%
1 1704
15.6%
2 1392
12.7%
3 460
 
4.2%
) 393
 
3.6%
( 393
 
3.6%
4 336
 
3.1%
5 306
 
2.8%
9 305
 
2.8%
Other values (4) 888
 
8.1%
Hangul
ValueCountFrequency (%)
도 911
24.9%
북 911
24.9%
전 911
24.9%
라 911
24.9%
호 4
 
0.1%
제 2
 
0.1%
등 2
 
0.1%
록 2
 
0.1%
번 2
 
0.1%
구 1
 
< 0.1%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10932
74.9%
Hangul 3659
 
25.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2741
25.1%
0 2014
18.4%
1 1704
15.6%
2 1392
12.7%
3 460
 
4.2%
) 393
 
3.6%
( 393
 
3.6%
4 336
 
3.1%
5 306
 
2.8%
9 305
 
2.8%
Other values (4) 888
 
8.1%
Hangul
ValueCountFrequency (%)
도 911
24.9%
북 911
24.9%
전 911
24.9%
라 911
24.9%
호 4
 
0.1%
제 2
 
0.1%
등 2
 
0.1%
록 2
 
0.1%
번 2
 
0.1%
구 1
 
< 0.1%
Other values (2) 2
 
0.1%

Unnamed: 2
Text

Distinct908
Distinct (%)99.8%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2024-03-14T11:35:22.999038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length10.781319
Min length3

Characters and Unicode

Total characters9811
Distinct characters434
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique906 ?
Unique (%)99.6%

Sample

1st row단체명칭
2nd row대한주부클럽연합회 전북지회
3rd row자연보호 전주시협의회
4th row자연보호 전라북도협의회
5th row전주여성의전화
ValueCountFrequency (%)
전북지부 15
 
1.2%
바르게살기운동 15
 
1.2%
한국농업경영인 14
 
1.1%
전라북도 8
 
0.6%
전라북도지부 7
 
0.5%
전주 7
 
0.5%
자연보호 7
 
0.5%
익산시 6
 
0.5%
여성단체협의회 6
 
0.5%
익산지부 6
 
0.5%
Other values (1069) 1192
92.9%
2024-03-14T11:35:23.275986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 519
 
5.3%
전 416
 
4.2%
374
 
3.8%
북 276
 
2.8%
지 251
 
2.6%
연 215
 
2.2%
사 200
 
2.0%
부 178
 
1.8%
협 173
 
1.8%
국 167
 
1.7%
Other values (424) 7042
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9229
94.1%
Space Separator 374
 
3.8%
Uppercase Letter 83
 
0.8%
Decimal Number 42
 
0.4%
Close Punctuation 37
 
0.4%
Other Punctuation 20
 
0.2%
Lowercase Letter 12
 
0.1%
Open Punctuation 10
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 519
 
5.6%
전 416
 
4.5%
북 276
 
3.0%
지 251
 
2.7%
연 215
 
2.3%
사 200
 
2.2%
부 178
 
1.9%
협 173
 
1.9%
국 167
 
1.8%
한 163
 
1.8%
Other values (383) 6671
72.3%
Uppercase Letter
ValueCountFrequency (%)
C 15
18.1%
A 14
16.9%
Y 11
13.3%
M 9
10.8%
O 5
 
6.0%
W 5
 
6.0%
N 4
 
4.8%
H 4
 
4.8%
G 4
 
4.8%
B 3
 
3.6%
Other values (6) 9
10.8%
Decimal Number
ValueCountFrequency (%)
2 12
28.6%
1 8
19.0%
5 7
16.7%
6 6
14.3%
4 4
 
9.5%
3 2
 
4.8%
0 2
 
4.8%
8 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
y 2
16.7%
p 2
16.7%
a 2
16.7%
g 1
8.3%
t 1
8.3%
n 1
8.3%
o 1
8.3%
Other Punctuation
ValueCountFrequency (%)
. 13
65.0%
· 5
 
25.0%
, 2
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 36
97.3%
] 1
 
2.7%
Open Punctuation
ValueCountFrequency (%)
( 9
90.0%
[ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
374
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9229
94.1%
Common 487
 
5.0%
Latin 95
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 519
 
5.6%
전 416
 
4.5%
북 276
 
3.0%
지 251
 
2.7%
연 215
 
2.3%
사 200
 
2.2%
부 178
 
1.9%
협 173
 
1.9%
국 167
 
1.8%
한 163
 
1.8%
Other values (383) 6671
72.3%
Latin
ValueCountFrequency (%)
C 15
15.8%
A 14
14.7%
Y 11
11.6%
M 9
9.5%
O 5
 
5.3%
W 5
 
5.3%
N 4
 
4.2%
H 4
 
4.2%
G 4
 
4.2%
B 3
 
3.2%
Other values (14) 21
22.1%
Common
ValueCountFrequency (%)
374
76.8%
) 36
 
7.4%
. 13
 
2.7%
2 12
 
2.5%
( 9
 
1.8%
1 8
 
1.6%
5 7
 
1.4%
6 6
 
1.2%
· 5
 
1.0%
4 4
 
0.8%
Other values (7) 13
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9229
94.1%
ASCII 577
 
5.9%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 519
 
5.6%
전 416
 
4.5%
북 276
 
3.0%
지 251
 
2.7%
연 215
 
2.3%
사 200
 
2.2%
부 178
 
1.9%
협 173
 
1.9%
국 167
 
1.8%
한 163
 
1.8%
Other values (383) 6671
72.3%
ASCII
ValueCountFrequency (%)
374
64.8%
) 36
 
6.2%
C 15
 
2.6%
A 14
 
2.4%
. 13
 
2.3%
2 12
 
2.1%
Y 11
 
1.9%
M 9
 
1.6%
( 9
 
1.6%
1 8
 
1.4%
Other values (30) 76
 
13.2%
None
ValueCountFrequency (%)
· 5
100.0%

Unnamed: 3
Text

Distinct859
Distinct (%)94.6%
Missing3
Missing (%)0.3%
Memory size7.2 KiB
2024-03-14T11:35:23.621572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length26.497797
Min length8

Characters and Unicode

Total characters24060
Distinct characters301
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique821 ?
Unique (%)90.4%

Sample

1st row사무소의 소재지
2nd row전라북도 전주시 완산구 전룡4길 8 (서신동)
3rd row전라북도 전주시덕진구 금암동 금암2동 1587-76
4th row전라북도 전주시 덕진구 기린대로 451 (덕진동1가)
5th row전라북도 전주시 완산구 효자로 338, 3호 (중화산동2가)
ValueCountFrequency (%)
전라북도 907
 
19.2%
전주시완산구 181
 
3.8%
익산시 142
 
3.0%
전주시 126
 
2.7%
전주시덕진구 105
 
2.2%
완산구 84
 
1.8%
군산시 72
 
1.5%
1호 56
 
1.2%
정읍시 48
 
1.0%
덕진구 42
 
0.9%
Other values (1411) 2972
62.8%
2024-03-14T11:35:24.000320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5157
21.4%
전 1360
 
5.7%
북 952
 
4.0%
도 928
 
3.9%
라 926
 
3.8%
1 891
 
3.7%
동 793
 
3.3%
시 749
 
3.1%
2 572
 
2.4%
산 571
 
2.4%
Other values (291) 11161
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14197
59.0%
Space Separator 5157
 
21.4%
Decimal Number 3845
 
16.0%
Dash Punctuation 272
 
1.1%
Close Punctuation 247
 
1.0%
Open Punctuation 246
 
1.0%
Other Punctuation 74
 
0.3%
Uppercase Letter 11
 
< 0.1%
Math Symbol 10
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 1360
 
9.6%
북 952
 
6.7%
도 928
 
6.5%
라 926
 
6.5%
동 793
 
5.6%
시 749
 
5.3%
산 571
 
4.0%
주 491
 
3.5%
지 462
 
3.3%
구 428
 
3.0%
Other values (267) 6537
46.0%
Decimal Number
ValueCountFrequency (%)
1 891
23.2%
2 572
14.9%
4 397
10.3%
3 397
10.3%
5 315
 
8.2%
6 295
 
7.7%
0 291
 
7.6%
7 255
 
6.6%
8 217
 
5.6%
9 215
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
C 3
27.3%
Y 2
18.2%
M 2
18.2%
A 2
18.2%
F 1
 
9.1%
G 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 72
97.3%
@ 2
 
2.7%
Space Separator
ValueCountFrequency (%)
5157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 272
100.0%
Close Punctuation
ValueCountFrequency (%)
) 247
100.0%
Open Punctuation
ValueCountFrequency (%)
( 246
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14197
59.0%
Common 9851
40.9%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 1360
 
9.6%
북 952
 
6.7%
도 928
 
6.5%
라 926
 
6.5%
동 793
 
5.6%
시 749
 
5.3%
산 571
 
4.0%
주 491
 
3.5%
지 462
 
3.3%
구 428
 
3.0%
Other values (267) 6537
46.0%
Common
ValueCountFrequency (%)
5157
52.4%
1 891
 
9.0%
2 572
 
5.8%
4 397
 
4.0%
3 397
 
4.0%
5 315
 
3.2%
6 295
 
3.0%
0 291
 
3.0%
- 272
 
2.8%
7 255
 
2.6%
Other values (7) 1009
 
10.2%
Latin
ValueCountFrequency (%)
C 3
25.0%
Y 2
16.7%
M 2
16.7%
A 2
16.7%
e 1
 
8.3%
F 1
 
8.3%
G 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14197
59.0%
ASCII 9863
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5157
52.3%
1 891
 
9.0%
2 572
 
5.8%
4 397
 
4.0%
3 397
 
4.0%
5 315
 
3.2%
6 295
 
3.0%
0 291
 
3.0%
- 272
 
2.8%
7 255
 
2.6%
Other values (14) 1021
 
10.4%
Hangul
ValueCountFrequency (%)
전 1360
 
9.6%
북 952
 
6.7%
도 928
 
6.5%
라 926
 
6.5%
동 793
 
5.6%
시 749
 
5.3%
산 571
 
4.0%
주 491
 
3.5%
지 462
 
3.3%
구 428
 
3.0%
Other values (267) 6537
46.0%

Unnamed: 4
Text

Distinct837
Distinct (%)92.1%
Missing2
Missing (%)0.2%
Memory size7.2 KiB
2024-03-14T11:35:24.291352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.0737074
Min length2

Characters and Unicode

Total characters2794
Distinct characters205
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique777 ?
Unique (%)85.5%

Sample

1st row대표자성명
2nd row정순례
3rd row강찬원
4th row진창환
5th row조 숙
ValueCountFrequency (%)
김영구 4
 
0.4%
외 4
 
0.4%
박재만 3
 
0.3%
서주상 3
 
0.3%
여형일 3
 
0.3%
김종영 3
 
0.3%
조현숙 3
 
0.3%
허종현 3
 
0.3%
김재승 3
 
0.3%
김택천 3
 
0.3%
Other values (846) 900
96.6%
2024-03-14T11:35:24.768772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 200
 
7.2%
이 133
 
4.8%
정 91
 
3.3%
영 84
 
3.0%
박 59
 
2.1%
수 48
 
1.7%
순 48
 
1.7%
희 47
 
1.7%
최 44
 
1.6%
종 39
 
1.4%
Other values (195) 2001
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2753
98.5%
Space Separator 24
 
0.9%
Decimal Number 8
 
0.3%
Other Punctuation 7
 
0.3%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 200
 
7.3%
이 133
 
4.8%
정 91
 
3.3%
영 84
 
3.1%
박 59
 
2.1%
수 48
 
1.7%
순 48
 
1.7%
희 47
 
1.7%
최 44
 
1.6%
종 39
 
1.4%
Other values (186) 1960
71.2%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
3 2
25.0%
4 2
25.0%
2 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2753
98.5%
Common 41
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 200
 
7.3%
이 133
 
4.8%
정 91
 
3.3%
영 84
 
3.1%
박 59
 
2.1%
수 48
 
1.7%
순 48
 
1.7%
희 47
 
1.7%
최 44
 
1.6%
종 39
 
1.4%
Other values (186) 1960
71.2%
Common
ValueCountFrequency (%)
24
58.5%
, 6
 
14.6%
1 3
 
7.3%
3 2
 
4.9%
4 2
 
4.9%
2 1
 
2.4%
) 1
 
2.4%
. 1
 
2.4%
( 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2753
98.5%
ASCII 41
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 200
 
7.3%
이 133
 
4.8%
정 91
 
3.3%
영 84
 
3.1%
박 59
 
2.1%
수 48
 
1.7%
순 48
 
1.7%
희 47
 
1.7%
최 44
 
1.6%
종 39
 
1.4%
Other values (186) 1960
71.2%
ASCII
ValueCountFrequency (%)
24
58.5%
, 6
 
14.6%
1 3
 
7.3%
3 2
 
4.9%
4 2
 
4.9%
2 1
 
2.4%
) 1
 
2.4%
. 1
 
2.4%
( 1
 
2.4%

Unnamed: 5
Text

Distinct639
Distinct (%)70.2%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2024-03-14T11:35:25.011671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9967033
Min length5

Characters and Unicode

Total characters7277
Distinct characters16
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

Unique509 ?
Unique (%)55.9%

Sample

1st row등록연월일
2nd row00/04/19
3rd row00/04/20
4th row00/04/20
5th row00/04/26
ValueCountFrequency (%)
00/05/16 55
 
6.0%
00/04/27 21
 
2.3%
00/05/17 11
 
1.2%
00/10/02 11
 
1.2%
00/05/18 7
 
0.8%
01/03/27 5
 
0.5%
04/02/20 5
 
0.5%
12/05/16 5
 
0.5%
00/04/26 4
 
0.4%
11/11/22 4
 
0.4%
Other values (629) 782
85.9%
2024-03-14T11:35:25.342650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1940
26.7%
/ 1818
25.0%
1 1086
14.9%
2 618
 
8.5%
3 310
 
4.3%
5 288
 
4.0%
7 271
 
3.7%
9 247
 
3.4%
4 237
 
3.3%
6 236
 
3.2%
Other values (6) 226
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5454
74.9%
Other Punctuation 1818
 
25.0%
Other Letter 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1940
35.6%
1 1086
19.9%
2 618
 
11.3%
3 310
 
5.7%
5 288
 
5.3%
7 271
 
5.0%
9 247
 
4.5%
4 237
 
4.3%
6 236
 
4.3%
8 221
 
4.1%
Other Letter
ValueCountFrequency (%)
등 1
20.0%
록 1
20.0%
연 1
20.0%
월 1
20.0%
일 1
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 1818
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7272
99.9%
Hangul 5
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1940
26.7%
/ 1818
25.0%
1 1086
14.9%
2 618
 
8.5%
3 310
 
4.3%
5 288
 
4.0%
7 271
 
3.7%
9 247
 
3.4%
4 237
 
3.3%
6 236
 
3.2%
Hangul
ValueCountFrequency (%)
등 1
20.0%
록 1
20.0%
연 1
20.0%
월 1
20.0%
일 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7272
99.9%
Hangul 5
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1940
26.7%
/ 1818
25.0%
1 1086
14.9%
2 618
 
8.5%
3 310
 
4.3%
5 288
 
4.0%
7 271
 
3.7%
9 247
 
3.4%
4 237
 
3.3%
6 236
 
3.2%
Hangul
ValueCountFrequency (%)
등 1
20.0%
록 1
20.0%
연 1
20.0%
월 1
20.0%
일 1
20.0%

Unnamed: 6
Text

MISSING 

Distinct849
Distinct (%)96.9%
Missing35
Missing (%)3.8%
Memory size7.2 KiB
2024-03-14T11:35:25.656385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length303
Median length137
Mean length38.553653
Min length4

Characters and Unicode

Total characters33773
Distinct characters546
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique830 ?
Unique (%)94.7%

Sample

1st row주된사업
2nd row소비자 고발센타 운영
3rd row환경보전(자연보호 운동)
4th row환경보전(자연보호 운동)
5th row여성의 인권과 복지증진, 위기의 여성상담
ValueCountFrequency (%)
및 570
 
7.2%
등 286
 
3.6%
위한 241
 
3.0%
226
 
2.9%
사업 151
 
1.9%
교육 85
 
1.1%
○ 77
 
1.0%
활동 64
 
0.8%
청소년 61
 
0.8%
운영 58
 
0.7%
Other values (3246) 6102
77.0%
2024-03-14T11:35:26.082202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6753
 
20.0%
사 1081
 
3.2%
, 647
 
1.9%
및 626
 
1.9%
업 605
 
1.8%
592
 
1.8%
지 585
 
1.7%
동 506
 
1.5%
한 494
 
1.5%
의 451
 
1.3%
Other values (536) 21433
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24678
73.1%
Space Separator 6753
 
20.0%
Other Punctuation 999
 
3.0%
Control 592
 
1.8%
Decimal Number 244
 
0.7%
Dash Punctuation 239
 
0.7%
Other Symbol 79
 
0.2%
Open Punctuation 53
 
0.2%
Close Punctuation 52
 
0.2%
Lowercase Letter 50
 
0.1%
Other values (3) 34
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1081
 
4.4%
및 626
 
2.5%
업 605
 
2.5%
지 585
 
2.4%
동 506
 
2.1%
한 494
 
2.0%
의 451
 
1.8%
교 422
 
1.7%
활 415
 
1.7%
화 371
 
1.5%
Other values (486) 19122
77.5%
Lowercase Letter
ValueCountFrequency (%)
o 34
68.0%
n 3
 
6.0%
m 2
 
4.0%
e 2
 
4.0%
a 2
 
4.0%
k 1
 
2.0%
d 1
 
2.0%
r 1
 
2.0%
t 1
 
2.0%
l 1
 
2.0%
Other values (2) 2
 
4.0%
Decimal Number
ValueCountFrequency (%)
2 47
19.3%
1 47
19.3%
3 41
16.8%
4 37
15.2%
0 31
12.7%
5 16
 
6.6%
6 12
 
4.9%
7 7
 
2.9%
9 3
 
1.2%
8 3
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 647
64.8%
. 286
28.6%
· 35
 
3.5%
? 23
 
2.3%
: 3
 
0.3%
' 2
 
0.2%
/ 1
 
0.1%
& 1
 
0.1%
@ 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
H 9
39.1%
O 8
34.8%
M 2
 
8.7%
E 1
 
4.3%
A 1
 
4.3%
G 1
 
4.3%
N 1
 
4.3%
Other Number
ValueCountFrequency (%)
① 2
25.0%
③ 2
25.0%
④ 2
25.0%
② 2
25.0%
Modifier Symbol
ValueCountFrequency (%)
˙ 2
66.7%
` 1
33.3%
Space Separator
ValueCountFrequency (%)
6753
100.0%
Control
ValueCountFrequency (%)
592
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 239
100.0%
Other Symbol
ValueCountFrequency (%)
○ 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24678
73.1%
Common 9022
 
26.7%
Latin 73
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1081
 
4.4%
및 626
 
2.5%
업 605
 
2.5%
지 585
 
2.4%
동 506
 
2.1%
한 494
 
2.0%
의 451
 
1.8%
교 422
 
1.7%
활 415
 
1.7%
화 371
 
1.5%
Other values (486) 19122
77.5%
Common
ValueCountFrequency (%)
6753
74.9%
, 647
 
7.2%
592
 
6.6%
. 286
 
3.2%
- 239
 
2.6%
○ 79
 
0.9%
( 53
 
0.6%
) 52
 
0.6%
2 47
 
0.5%
1 47
 
0.5%
Other values (21) 227
 
2.5%
Latin
ValueCountFrequency (%)
o 34
46.6%
H 9
 
12.3%
O 8
 
11.0%
n 3
 
4.1%
M 2
 
2.7%
m 2
 
2.7%
e 2
 
2.7%
a 2
 
2.7%
k 1
 
1.4%
E 1
 
1.4%
Other values (9) 9
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24650
73.0%
ASCII 8971
 
26.6%
Geometric Shapes 79
 
0.2%
None 35
 
0.1%
Compat Jamo 28
 
0.1%
Enclosed Alphanum 8
 
< 0.1%
Modifier Letters 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6753
75.3%
, 647
 
7.2%
592
 
6.6%
. 286
 
3.2%
- 239
 
2.7%
( 53
 
0.6%
) 52
 
0.6%
2 47
 
0.5%
1 47
 
0.5%
3 41
 
0.5%
Other values (33) 214
 
2.4%
Hangul
ValueCountFrequency (%)
사 1081
 
4.4%
및 626
 
2.5%
업 605
 
2.5%
지 585
 
2.4%
동 506
 
2.1%
한 494
 
2.0%
의 451
 
1.8%
교 422
 
1.7%
활 415
 
1.7%
화 371
 
1.5%
Other values (484) 19094
77.5%
Geometric Shapes
ValueCountFrequency (%)
○ 79
100.0%
None
ValueCountFrequency (%)
· 35
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 27
96.4%
ㆍ 1
 
3.6%
Modifier Letters
ValueCountFrequency (%)
˙ 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 2
25.0%
③ 2
25.0%
④ 2
25.0%
② 2
25.0%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
문화예술과
167 
여성청소년과
136 
대외협력과
105 
노인장애인복지과
79 
행정지원관실
77 
Other values (39)
347 

Length

Max length13
Median length5
Mean length5.6245884
Min length3

Unique

Unique20 ?
Unique (%)2.2%

Sample

1st row주관과
2nd row여성청소년과
3rd row환경보전과
4th row환경보전과
5th row여성청소년과

Common Values

ValueCountFrequency (%)
문화예술과 167
18.3%
여성청소년과 136
14.9%
대외협력과 105
11.5%
노인장애인복지과 79
8.7%
행정지원관실 77
8.5%
환경보전과 75
8.2%
다문화교류과 42
 
4.6%
미래농업과 34
 
3.7%
사회복지과 30
 
3.3%
보건의료과 22
 
2.4%
Other values (34) 144
15.8%

Length

2024-03-14T11:35:26.192131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
문화예술과 167
18.3%
여성청소년과 136
14.9%
대외협력과 105
11.5%
노인장애인복지과 79
8.7%
행정지원관실 77
8.4%
환경보전과 75
8.2%
다문화교류과 42
 
4.6%
미래농업과 34
 
3.7%
사회복지과 30
 
3.3%
보건의료과 22
 
2.4%
Other values (35) 146
16.0%

Unnamed: 8
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
등록
736 
<NA>
174 
등록구분 (신규,변경)
 
1

Length

Max length12
Median length2
Mean length2.3929748
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row등록구분 (신규,변경)
2nd row등록
3rd row등록
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
등록 736
80.8%
<NA> 174
 
19.1%
등록구분 (신규,변경) 1
 
0.1%

Length

2024-03-14T11:35:26.278341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:35:26.373275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록 736
80.7%
na 174
 
19.1%
등록구분 1
 
0.1%
신규,변경 1
 
0.1%

Unnamed: 9
Text

Distinct257
Distinct (%)28.2%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2024-03-14T11:35:26.678309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7461538
Min length1

Characters and Unicode

Total characters2499
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)18.9%

Sample

1st row회원수
2nd row2300
3rd row150
4th row1893
5th row550
ValueCountFrequency (%)
0 161
 
17.7%
100 75
 
8.2%
105 27
 
3.0%
110 25
 
2.7%
120 24
 
2.6%
102 22
 
2.4%
104 21
 
2.3%
101 21
 
2.3%
103 18
 
2.0%
150 17
 
1.9%
Other values (247) 499
54.8%
2024-03-14T11:35:27.120157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 759
30.4%
0 710
28.4%
2 242
 
9.7%
5 194
 
7.8%
3 139
 
5.6%
4 122
 
4.9%
7 101
 
4.0%
8 83
 
3.3%
6 82
 
3.3%
9 64
 
2.6%
Other values (3) 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2496
99.9%
Other Letter 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 759
30.4%
0 710
28.4%
2 242
 
9.7%
5 194
 
7.8%
3 139
 
5.6%
4 122
 
4.9%
7 101
 
4.0%
8 83
 
3.3%
6 82
 
3.3%
9 64
 
2.6%
Other Letter
ValueCountFrequency (%)
회 1
33.3%
원 1
33.3%
수 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2496
99.9%
Hangul 3
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 759
30.4%
0 710
28.4%
2 242
 
9.7%
5 194
 
7.8%
3 139
 
5.6%
4 122
 
4.9%
7 101
 
4.0%
8 83
 
3.3%
6 82
 
3.3%
9 64
 
2.6%
Hangul
ValueCountFrequency (%)
회 1
33.3%
원 1
33.3%
수 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2496
99.9%
Hangul 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 759
30.4%
0 710
28.4%
2 242
 
9.7%
5 194
 
7.8%
3 139
 
5.6%
4 122
 
4.9%
7 101
 
4.0%
8 83
 
3.3%
6 82
 
3.3%
9 64
 
2.6%
Hangul
ValueCountFrequency (%)
회 1
33.3%
원 1
33.3%
수 1
33.3%

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing911
Missing (%)100.0%
Memory size8.1 KiB

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing911
Missing (%)100.0%
Memory size8.1 KiB

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing911
Missing (%)100.0%
Memory size8.1 KiB

Correlations

2024-03-14T11:35:27.199029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 7Unnamed: 8
Unnamed: 71.0001.000
Unnamed: 81.0001.000
2024-03-14T11:35:27.264657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 7Unnamed: 8
Unnamed: 71.0000.974
Unnamed: 80.9741.000
2024-03-14T11:35:27.539478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 7Unnamed: 8
Unnamed: 71.0000.974
Unnamed: 80.9741.000

Missing values

2024-03-14T11:35:21.113269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:35:21.318942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-14T11:35:21.442324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0비영리민간단체 등록대장Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
0일련번호등록번호 (구등록번호)단체명칭사무소의 소재지대표자성명등록연월일주된사업주관과등록구분 (신규,변경)회원수<NA><NA><NA>
112000-1-전라북도-1(1)대한주부클럽연합회 전북지회전라북도 전주시 완산구 전룡4길 8 (서신동)정순례00/04/19소비자 고발센타 운영여성청소년과등록2300<NA><NA><NA>
222000-1-전라북도-2(3)자연보호 전주시협의회전라북도 전주시덕진구 금암동 금암2동 1587-76강찬원00/04/20환경보전(자연보호 운동)환경보전과등록150<NA><NA><NA>
332000-1-전라북도-3(4)자연보호 전라북도협의회전라북도 전주시 덕진구 기린대로 451 (덕진동1가)진창환00/04/20환경보전(자연보호 운동)환경보전과<NA>1893<NA><NA><NA>
442000-1-전라북도-4(5)전주여성의전화전라북도 전주시 완산구 효자로 338, 3호 (중화산동2가)조 숙00/04/26여성의 인권과 복지증진, 위기의 여성상담여성청소년과<NA>550<NA><NA><NA>
552000-1-전라북도-5(6)전북여성농민회연합전라북도 전주시완산구 서신동 813-1이재현00/04/26여성농민을 위한 정책사업, 여름 농활 동시 연대사업여성청소년과등록2000<NA><NA><NA>
662000-1-전라북도-6(7)남원YWCA전라북도 남원시 시청로 65 (향교동)이채옥00/04/26청소년 어울마당, 가정폭력 상담, 여성교육여성청소년과<NA>725<NA><NA><NA>
772000-1-전라북도-7(8)법률구조법인한국가정법률상담소전주지부전라북도 전주시 완산구 노송광장로 7 (서노송동)김완자00/04/26무료법률구조사업여성청소년과<NA>180<NA><NA><NA>
882000-1-전라북도-8(10)전북여성단체연합전라북도 전주시완산구 서서학동 331번지 16호조선희00/04/27여성의 지위향상, 여성 사회참여 확대 등여성청소년과등록54473<NA><NA><NA>
992000-1-전라북도-9(11)전북여성노동자회전라북도 전주시완산구 평화동1가 422번지 2호신민경00/04/27여성모성 보호권을 위한 사업, 여성 권리향상을 위한 사업여성청소년과<NA>105<NA><NA><NA>
Unnamed: 0비영리민간단체 등록대장Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
9019012015-1-전라북도-17부안청년회의소전라북도 부안군 부풍로 9-1임석문15/06/23조사연구사업, 사회단체 협조, 기타 목적사업 등정무기획과등록130<NA><NA><NA>
9029022015-1-전라북도-18(사)전국농업기술자협회 완주군지회전라북도 완주군 이서면 상개리 570번지 5호강재원15/07/17○ 회원간의 농업정보교환과 농업기술의 연구개발 및 교류 ○ 환경보전 및 농업기술의 보급과 선도농가의 자질향상을 위한 교육 ○ 농업정보 교환과 신농업 기술보급을 위한 지방농민대학 개최 ○ 우리 농산물 보급확대를 위한 농산물 직거래사업 등농업정책과등록120<NA><NA><NA>
9039032015-1-전라북도-19전국한우협회 익산시지부<NA><NA>15/07/27<NA><NA>등록0<NA><NA><NA>
9049042015-1-전라북도-20전국한우협회 익산시지부<NA>진택섭15/07/27<NA><NA>등록0<NA><NA><NA>
9059052015-1-전라북도-21완주재향경우회전라북도 완주군 봉동로 28배준수15/07/28지역 치안 업무 협조 지원 및 아동 지킴이 선발 등 지역봉사활동 전개자치행정과등록139<NA><NA><NA>
9069062015-1-전라북도-22익산시애향운동본부전라북도 익산시 인북로 68-2, 2층 (갈산동)최낙환15/09/111. 시민의식구조 개혁 2. 시민의 품위 향상 3. 향토번영과 나라발전에 기여자치행정과등록104<NA><NA><NA>
9079072015-1-전라북도-23완주군애향운동본부전라북도 완주군 봉동읍 봉동로 133, 3층정완철15/09/111. 인재육성과 지역 개발사업 2. 향토문화의 개발과 보존 3. 향우회와 유대강화 4. 환경보존사업자치행정과등록154<NA><NA><NA>
9089082015-1-전라북도-24부안청년회의소전라북도 부안군 부풍로 9-1임석문15/07/01조사연구사업, 사회단체 협조, 기타 목적사업 등정무기획과등록130<NA><NA><NA>
9099092015-1-전라북도-25순창청년회의소전라북도 순창군 순창읍 순창로 159-11장승필15/09/23어르신위안잔치, 장학사업, 노인교통안전캠페인, 광복절행사 등정무기획과등록124<NA><NA><NA>
910<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>