Overview

Dataset statistics

Number of variables4
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory821.0 B
Average record size in memory39.1 B

Variable types

Text3
Numeric1

Dataset

Description전북특별자치도 여성단체 현황에 관한 데이터입니다. 단체명, 대표자 성명, 우편주소, 사무실 주소, 회원수를 포함하고 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/3080954/fileData.do

Alerts

단체명 has unique valuesUnique
사무실 주소 has unique valuesUnique
회원수 (명) has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:52:46.227540
Analysis finished2024-03-14 12:52:47.222441
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단체명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-14T21:52:47.815144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length13
Min length9

Characters and Unicode

Total characters273
Distinct characters87
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row(사)전라북도여성단체협의회
2nd row전라북도 간호사회
3rd row대한민국 전몰군경 미망인회 전북지부
4th row대한미용사회 전라북도지회
5th row한국부인회 전라북도지부
ValueCountFrequency (%)
전북지회 5
 
11.4%
전라북도 4
 
9.1%
전북연맹 2
 
4.5%
전라북도지부 2
 
4.5%
생각하는 1
 
2.3%
주부 1
 
2.3%
모임 1
 
2.3%
한.중여성교류협회 1
 
2.3%
한국통일여성협의회 1
 
2.3%
사)전라북도여성단체협의회 1
 
2.3%
Other values (25) 25
56.8%
2024-03-14T21:52:49.178119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 26
 
9.5%
23
 
8.4%
전 22
 
8.1%
북 20
 
7.3%
한 11
 
4.0%
지 10
 
3.7%
사 9
 
3.3%
도 9
 
3.3%
여 8
 
2.9%
라 8
 
2.9%
Other values (77) 127
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 247
90.5%
Space Separator 23
 
8.4%
Open Punctuation 1
 
0.4%
Other Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 26
 
10.5%
전 22
 
8.9%
북 20
 
8.1%
한 11
 
4.5%
지 10
 
4.0%
사 9
 
3.6%
도 9
 
3.6%
여 8
 
3.2%
라 8
 
3.2%
국 7
 
2.8%
Other values (73) 117
47.4%
Space Separator
ValueCountFrequency (%)
23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 247
90.5%
Common 26
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 26
 
10.5%
전 22
 
8.9%
북 20
 
8.1%
한 11
 
4.5%
지 10
 
4.0%
사 9
 
3.6%
도 9
 
3.6%
여 8
 
3.2%
라 8
 
3.2%
국 7
 
2.8%
Other values (73) 117
47.4%
Common
ValueCountFrequency (%)
23
88.5%
( 1
 
3.8%
. 1
 
3.8%
) 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 247
90.5%
ASCII 26
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 26
 
10.5%
전 22
 
8.9%
북 20
 
8.1%
한 11
 
4.5%
지 10
 
4.0%
사 9
 
3.6%
도 9
 
3.6%
여 8
 
3.2%
라 8
 
3.2%
국 7
 
2.8%
Other values (73) 117
47.4%
ASCII
ValueCountFrequency (%)
23
88.5%
( 1
 
3.8%
. 1
 
3.8%
) 1
 
3.8%

대표자 성명
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-14T21:52:49.910689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters63
Distinct characters26
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

Unique17 ?
Unique (%)81.0%

Sample

1st row김*희
2nd row안*희
3rd row양*이
4th row장*식
5th row임*순
ValueCountFrequency (%)
김*희 2
 
9.5%
이*경 2
 
9.5%
라*만 1
 
4.8%
이*순 1
 
4.8%
온*이 1
 
4.8%
강*경 1
 
4.8%
박*숙 1
 
4.8%
라*희 1
 
4.8%
오*빈 1
 
4.8%
곽*자 1
 
4.8%
Other values (9) 9
42.9%
2024-03-14T21:52:50.993759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 21
33.3%
이 5
 
7.9%
희 4
 
6.3%
순 4
 
6.3%
김 3
 
4.8%
경 3
 
4.8%
라 2
 
3.2%
숙 2
 
3.2%
최 2
 
3.2%
강 1
 
1.6%
Other values (16) 16
25.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
66.7%
Other Punctuation 21
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 5
 
11.9%
희 4
 
9.5%
순 4
 
9.5%
김 3
 
7.1%
경 3
 
7.1%
라 2
 
4.8%
숙 2
 
4.8%
최 2
 
4.8%
강 1
 
2.4%
박 1
 
2.4%
Other values (15) 15
35.7%
Other Punctuation
ValueCountFrequency (%)
* 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42
66.7%
Common 21
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 5
 
11.9%
희 4
 
9.5%
순 4
 
9.5%
김 3
 
7.1%
경 3
 
7.1%
라 2
 
4.8%
숙 2
 
4.8%
최 2
 
4.8%
강 1
 
2.4%
박 1
 
2.4%
Other values (15) 15
35.7%
Common
ValueCountFrequency (%)
* 21
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42
66.7%
ASCII 21
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 21
100.0%
Hangul
ValueCountFrequency (%)
이 5
 
11.9%
희 4
 
9.5%
순 4
 
9.5%
김 3
 
7.1%
경 3
 
7.1%
라 2
 
4.8%
숙 2
 
4.8%
최 2
 
4.8%
강 1
 
2.4%
박 1
 
2.4%
Other values (15) 15
35.7%

사무실 주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-14T21:52:52.028040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length30.761905
Min length21

Characters and Unicode

Total characters646
Distinct characters108
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row우)54892 전주시 덕진구 가련산로 18 리더빌딩 4층(402호)
2nd row우)54830 전주시 덕진구 시천로 58 하진빌딩 302호
3rd row우)54898 전주시 덕진구 권삼득로 285
4th row우)54873 전주시 덕진구 오공로 120 월방빌딩 303호
5th row우)54938 전주시 덕진구 숲정이3길 17
ValueCountFrequency (%)
전주시 18
 
14.2%
덕진구 10
 
7.9%
완산구 8
 
6.3%
194 2
 
1.6%
군산시 2
 
1.6%
58 2
 
1.6%
우아동 1
 
0.8%
용머리로 1
 
0.8%
우)55095 1
 
0.8%
63-6 1
 
0.8%
Other values (81) 81
63.8%
2024-03-14T21:52:53.503569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
109
 
16.9%
5 39
 
6.0%
1 27
 
4.2%
4 27
 
4.2%
0 27
 
4.2%
우 24
 
3.7%
2 23
 
3.6%
시 23
 
3.6%
) 22
 
3.4%
3 20
 
3.1%
Other values (98) 305
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 284
44.0%
Decimal Number 215
33.3%
Space Separator 109
 
16.9%
Close Punctuation 22
 
3.4%
Other Punctuation 9
 
1.4%
Dash Punctuation 6
 
0.9%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 24
 
8.5%
시 23
 
8.1%
전 19
 
6.7%
주 19
 
6.7%
구 18
 
6.3%
로 13
 
4.6%
진 11
 
3.9%
산 11
 
3.9%
덕 10
 
3.5%
완 8
 
2.8%
Other values (81) 128
45.1%
Decimal Number
ValueCountFrequency (%)
5 39
18.1%
1 27
12.6%
4 27
12.6%
0 27
12.6%
2 23
10.7%
3 20
9.3%
9 17
7.9%
8 16
7.4%
6 12
 
5.6%
7 7
 
3.3%
Other Punctuation
ValueCountFrequency (%)
/ 4
44.4%
. 3
33.3%
@ 2
22.2%
Space Separator
ValueCountFrequency (%)
109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 362
56.0%
Hangul 284
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 24
 
8.5%
시 23
 
8.1%
전 19
 
6.7%
주 19
 
6.7%
구 18
 
6.3%
로 13
 
4.6%
진 11
 
3.9%
산 11
 
3.9%
덕 10
 
3.5%
완 8
 
2.8%
Other values (81) 128
45.1%
Common
ValueCountFrequency (%)
109
30.1%
5 39
 
10.8%
1 27
 
7.5%
4 27
 
7.5%
0 27
 
7.5%
2 23
 
6.4%
) 22
 
6.1%
3 20
 
5.5%
9 17
 
4.7%
8 16
 
4.4%
Other values (7) 35
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 362
56.0%
Hangul 284
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
109
30.1%
5 39
 
10.8%
1 27
 
7.5%
4 27
 
7.5%
0 27
 
7.5%
2 23
 
6.4%
) 22
 
6.1%
3 20
 
5.5%
9 17
 
4.7%
8 16
 
4.4%
Other values (7) 35
 
9.7%
Hangul
ValueCountFrequency (%)
우 24
 
8.5%
시 23
 
8.1%
전 19
 
6.7%
주 19
 
6.7%
구 18
 
6.3%
로 13
 
4.6%
진 11
 
3.9%
산 11
 
3.9%
덕 10
 
3.5%
완 8
 
2.8%
Other values (81) 128
45.1%

회원수 (명)
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5955.1429
Minimum135
Maximum62529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-03-14T21:52:53.712883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile250
Q1500
median1200
Q36094
95-th percentile15000
Maximum62529
Range62394
Interquartile range (IQR)5594

Descriptive statistics

Standard deviation13547.741
Coefficient of variation (CV)2.2749649
Kurtosis17.064514
Mean5955.1429
Median Absolute Deviation (MAD)920
Skewness3.9998573
Sum125058
Variance1.8354128 × 108
MonotonicityNot monotonic
2024-03-14T21:52:53.986984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
62529 1
 
4.8%
6094 1
 
4.8%
347 1
 
4.8%
135 1
 
4.8%
700 1
 
4.8%
6237 1
 
4.8%
400 1
 
4.8%
1180 1
 
4.8%
500 1
 
4.8%
1200 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
135 1
4.8%
250 1
4.8%
280 1
4.8%
347 1
4.8%
400 1
4.8%
500 1
4.8%
591 1
4.8%
700 1
4.8%
1000 1
4.8%
1180 1
4.8%
ValueCountFrequency (%)
62529 1
4.8%
15000 1
4.8%
9743 1
4.8%
8600 1
4.8%
6237 1
4.8%
6094 1
4.8%
3850 1
4.8%
3222 1
4.8%
1800 1
4.8%
1400 1
4.8%

Interactions

2024-03-14T21:52:46.496426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:52:54.238854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단체명대표자 성명사무실 주소회원수 (명)
단체명1.0001.0001.0001.000
대표자 성명1.0001.0001.0000.000
사무실 주소1.0001.0001.0001.000
회원수 (명)1.0000.0001.0001.000

Missing values

2024-03-14T21:52:46.827219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:52:47.110252image/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.

Sample

단체명대표자 성명사무실 주소회원수 (명)
0(사)전라북도여성단체협의회김*희우)54892 전주시 덕진구 가련산로 18 리더빌딩 4층(402호)62529
1전라북도 간호사회안*희우)54830 전주시 덕진구 시천로 58 하진빌딩 302호6094
2대한민국 전몰군경 미망인회 전북지부양*이우)54898 전주시 덕진구 권삼득로 2853850
3대한미용사회 전라북도지회장*식우)54873 전주시 덕진구 오공로 120 월방빌딩 303호15000
4한국부인회 전라북도지부임*순우)54938 전주시 덕진구 숲정이3길 171800
5전라북도 간호조무사회최*란우)54933 전주시 덕진구 금암동 462-3 7층8600
6전라북도 여약사회이*경우)54987 전주시 완산구 서원로 355 효인약국591
7대한어머니회 전북연합회신*순우)54922 전주시 덕진구 거북바우3길 중앙하이츠@ 102/5061000
8대한영양사회 전라북도 영양사회김*진우)54969 전주시 완산구 효자로 194 로자벨시티 3층 3121400
9한국걸스카우트 전북연맹김*희우)54894 전주시 덕진구 가리내로 1223222
단체명대표자 성명사무실 주소회원수 (명)
11한.중여성교류협회 전북지회이*순우)54024 군산시 오룡로 65-1 빵굽는 오남매250
12한국통일여성협의회 전북지회이*경우)55087 전주시 완산구 삼천천변1길 201-1501호280
13세계평화여성연합 전북지회라*만우)55014 전주시 덕진구 우아동 2가 860-11200
14아이코리아전북도지회곽*자우)54140 군산시 나운5길 63-6500
15밝은사회전북전주여성클럽오*빈우)55095 전주시 완산구 용머리로 194. 101/2051180
16한국여성유권자 전북연맹라*희우)55092 전주시 완산구 백제대로 13. 우성@ 106동 205호400
17전북재향군인회여성회박*숙우)55123 전주시 완산구 소대배기로 33 101/16026237
18한국피부미용사회 전북지회강*경우)54408 김제시 화동길 58 호반에스테틱700
19한국유치원총연합회 전북지회온*이우)54877 전주시 완산구 원서곡길 39. 상원리나유치원135
20글로벌웰니스 문화교류협회최*순우)54999 전주시 완산구 전주객사 2길 12-4 최수원미용직업훈련학원347