Overview

Dataset statistics

Number of variables5
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory45.3 B

Variable types

Categorical1
Text4

Dataset

Description사회적경제분야 창업 인큐베이팅을 지원할 수 있는 창업지원기관 현황입니다. 권역 / 기관명 / 주소 / 전화번호 / 대표자명 제공
URLhttps://www.data.go.kr/data/15038605/fileData.do

Alerts

기관명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique
대표자명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:45:28.184431
Analysis finished2023-12-12 04:45:28.806354
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct12
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
강원·충청
광주·전라·제주
서울·인천·경기
부산·울산·경남
대구·경북
Other values (7)

Length

Max length20
Median length18
Mean length9.04
Min length5

Unique

Unique7 ?
Unique (%)28.0%

Sample

1st row서울·인천·경기
2nd row서울·인천·경기
3rd row서울·인천·경기
4th row강원·충청
5th row강원·충청

Common Values

ValueCountFrequency (%)
강원·충청 5
20.0%
광주·전라·제주 5
20.0%
서울·인천·경기 3
12.0%
부산·울산·경남 3
12.0%
대구·경북 2
 
8.0%
특화 전담(교육/청소년자립) 1
 
4.0%
특화 전담(사회서비스) 1
 
4.0%
특화 전담(문화예술-서비스디자인) 1
 
4.0%
특화 전담(농어촌/산림) 1
 
4.0%
특화 전담(환경) 1
 
4.0%
Other values (2) 2
 
8.0%

Length

2023-12-12T13:45:28.917398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
특화 7
21.9%
강원·충청 5
15.6%
광주·전라·제주 5
15.6%
서울·인천·경기 3
9.4%
부산·울산·경남 3
9.4%
대구·경북 2
 
6.2%
전담(교육/청소년자립 1
 
3.1%
전담(사회서비스 1
 
3.1%
전담(문화예술-서비스디자인 1
 
3.1%
전담(농어촌/산림 1
 
3.1%
Other values (3) 3
9.4%

기관명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T13:45:29.195584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length12.88
Min length8

Characters and Unicode

Total characters322
Distinct characters93
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row재단법인 함께일하는재단
2nd row사단법인 피피엘
3rd row사회적협동조합 사람과세상
4th row사회적협동조합 세상만사
5th row(사)충남사회경제네트워크
ValueCountFrequency (%)
사회적협동조합 6
 
15.8%
사단법인 2
 
5.3%
산학협력단 2
 
5.3%
재단법인 1
 
2.6%
열매나눔재단 1
 
2.6%
사)사회적기업연구원 1
 
2.6%
울산사회적경제지원센터 1
 
2.6%
모두의경제 1
 
2.6%
사회복지법인 1
 
2.6%
재)부산디자인진흥원 1
 
2.6%
Other values (21) 21
55.3%
2023-12-12T13:45:29.654000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
8.1%
17
 
5.3%
14
 
4.3%
12
 
3.7%
) 11
 
3.4%
( 11
 
3.4%
11
 
3.4%
11
 
3.4%
9
 
2.8%
8
 
2.5%
Other values (83) 192
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
88.8%
Space Separator 14
 
4.3%
Close Punctuation 11
 
3.4%
Open Punctuation 11
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
26
 
9.1%
17
 
5.9%
12
 
4.2%
11
 
3.8%
11
 
3.8%
9
 
3.1%
8
 
2.8%
8
 
2.8%
8
 
2.8%
7
 
2.4%
Other values (80) 169
59.1%
Space Separator
ValueCountFrequency (%)
14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
88.8%
Common 36
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
26
 
9.1%
17
 
5.9%
12
 
4.2%
11
 
3.8%
11
 
3.8%
9
 
3.1%
8
 
2.8%
8
 
2.8%
8
 
2.8%
7
 
2.4%
Other values (80) 169
59.1%
Common
ValueCountFrequency (%)
14
38.9%
) 11
30.6%
( 11
30.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
88.8%
ASCII 36
 
11.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
26
 
9.1%
17
 
5.9%
12
 
4.2%
11
 
3.8%
11
 
3.8%
9
 
3.1%
8
 
2.8%
8
 
2.8%
8
 
2.8%
7
 
2.4%
Other values (80) 169
59.1%
ASCII
ValueCountFrequency (%)
14
38.9%
) 11
30.6%
( 11
30.6%

주소
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T13:45:30.135112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length36
Mean length33.8
Min length19

Characters and Unicode

Total characters845
Distinct characters164
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row서울특별시 마포구 월드컵북로 6길 36, 5층
2nd row서울특별시 마포구 토정로 296, 이연빌딩 4층 사단법인 피피엘
3rd row경기도 수원시 영통구 동탄지성로 470번길 34, 상가동 2층(망포동, 수원영통 경기행복주택)
4th row대전광역시 유성구 농대로2번길 15, 3층
5th row충청남도 아산시 번영로 86번길 27-3 아산시 어울림경제센터 3~4층
ValueCountFrequency (%)
3층 6
 
3.5%
서울특별시 5
 
2.9%
5층 3
 
1.8%
2층 3
 
1.8%
경기도 3
 
1.8%
안산시 2
 
1.2%
빌딩 2
 
1.2%
광주광역시 2
 
1.2%
청주시 2
 
1.2%
충청북도 2
 
1.2%
Other values (132) 141
82.5%
2023-12-12T13:45:30.807087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
17.6%
28
 
3.3%
26
 
3.1%
, 26
 
3.1%
22
 
2.6%
1 21
 
2.5%
2 20
 
2.4%
20
 
2.4%
3 20
 
2.4%
7 16
 
1.9%
Other values (154) 497
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 508
60.1%
Space Separator 149
 
17.6%
Decimal Number 134
 
15.9%
Other Punctuation 26
 
3.1%
Open Punctuation 8
 
0.9%
Close Punctuation 8
 
0.9%
Uppercase Letter 6
 
0.7%
Dash Punctuation 5
 
0.6%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
28
 
5.5%
26
 
5.1%
22
 
4.3%
20
 
3.9%
14
 
2.8%
13
 
2.6%
12
 
2.4%
11
 
2.2%
11
 
2.2%
10
 
2.0%
Other values (135) 341
67.1%
Decimal Number
ValueCountFrequency (%)
1 21
15.7%
2 20
14.9%
3 20
14.9%
7 16
11.9%
0 15
11.2%
4 14
10.4%
5 12
9.0%
6 9
6.7%
8 4
 
3.0%
9 3
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
B 2
33.3%
Y 2
33.3%
Space Separator
ValueCountFrequency (%)
149
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 508
60.1%
Common 331
39.2%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
28
 
5.5%
26
 
5.1%
22
 
4.3%
20
 
3.9%
14
 
2.8%
13
 
2.6%
12
 
2.4%
11
 
2.2%
11
 
2.2%
10
 
2.0%
Other values (135) 341
67.1%
Common
ValueCountFrequency (%)
149
45.0%
, 26
 
7.9%
1 21
 
6.3%
2 20
 
6.0%
3 20
 
6.0%
7 16
 
4.8%
0 15
 
4.5%
4 14
 
4.2%
5 12
 
3.6%
6 9
 
2.7%
Other values (6) 29
 
8.8%
Latin
ValueCountFrequency (%)
C 2
33.3%
B 2
33.3%
Y 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 508
60.1%
ASCII 337
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
44.2%
, 26
 
7.7%
1 21
 
6.2%
2 20
 
5.9%
3 20
 
5.9%
7 16
 
4.7%
0 15
 
4.5%
4 14
 
4.2%
5 12
 
3.6%
6 9
 
2.7%
Other values (9) 35
 
10.4%
Hangul
ValueCountFrequency (%)
28
 
5.5%
26
 
5.1%
22
 
4.3%
20
 
3.9%
14
 
2.8%
13
 
2.6%
12
 
2.4%
11
 
2.2%
11
 
2.2%
10
 
2.0%
Other values (135) 341
67.1%

전화번호
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T13:45:31.083693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length15.12
Min length11

Characters and Unicode

Total characters378
Distinct characters21
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row02-330-0765
2nd row070-4610-5684,6
3rd row070-4763-0130(내선번호3)
4th row042-320-9540 / 042-331-0119
5th row041-415-2012 (내선번호3)
ValueCountFrequency (%)
3
 
9.4%
02-330-0765 1
 
3.1%
053-213-3070~1 1
 
3.1%
031-362-5421 1
 
3.1%
02-2135-1730 1
 
3.1%
02-365-0326 1
 
3.1%
043-264-9979 1
 
3.1%
051-950-1231,8 1
 
3.1%
070-5057-2992 1
 
3.1%
070-5057-3610 1
 
3.1%
Other values (20) 20
62.5%
2023-12-12T13:45:31.530747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 67
17.7%
- 56
14.8%
3 39
10.3%
1 33
8.7%
2 32
8.5%
5 28
7.4%
7 27
7.1%
6 23
 
6.1%
4 22
 
5.8%
9 14
 
3.7%
Other values (11) 37
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 293
77.5%
Dash Punctuation 56
 
14.8%
Other Letter 8
 
2.1%
Space Separator 7
 
1.9%
Other Punctuation 6
 
1.6%
Math Symbol 4
 
1.1%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67
22.9%
3 39
13.3%
1 33
11.3%
2 32
10.9%
5 28
9.6%
7 27
9.2%
6 23
 
7.8%
4 22
 
7.5%
9 14
 
4.8%
8 8
 
2.7%
Other Letter
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
50.0%
, 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 370
97.9%
Hangul 8
 
2.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 67
18.1%
- 56
15.1%
3 39
10.5%
1 33
8.9%
2 32
8.6%
5 28
7.6%
7 27
7.3%
6 23
 
6.2%
4 22
 
5.9%
9 14
 
3.8%
Other values (7) 29
7.8%
Hangul
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 370
97.9%
Hangul 8
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 67
18.1%
- 56
15.1%
3 39
10.5%
1 33
8.9%
2 32
8.6%
5 28
7.6%
7 27
7.3%
6 23
 
6.2%
4 22
 
5.9%
9 14
 
3.8%
Other values (7) 29
7.8%
Hangul
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%

대표자명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T13:45:31.764227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7
Min length6

Characters and Unicode

Total characters175
Distinct characters64
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

Unique25 ?
Unique (%)100.0%

Sample

1st row이사장 이세중
2nd row이사장 김동호
3rd row이사장 주태규
4th row이사장 정완숙
5th row이사장 신재학
ValueCountFrequency (%)
이사장 11
22.0%
대표 7
 
14.0%
회장 3
 
6.0%
주태규 1
 
2.0%
사회적경제지원단장 1
 
2.0%
경창수 1
 
2.0%
이선우 1
 
2.0%
홍용석 1
 
2.0%
강필현 1
 
2.0%
오병전 1
 
2.0%
Other values (22) 22
44.0%
2023-12-12T13:45:32.167334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
14.3%
18
 
10.3%
18
 
10.3%
13
 
7.4%
8
 
4.6%
8
 
4.6%
4
 
2.3%
4
 
2.3%
4
 
2.3%
3
 
1.7%
Other values (54) 70
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150
85.7%
Space Separator 25
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
12.0%
18
 
12.0%
13
 
8.7%
8
 
5.3%
8
 
5.3%
4
 
2.7%
4
 
2.7%
4
 
2.7%
3
 
2.0%
2
 
1.3%
Other values (53) 68
45.3%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150
85.7%
Common 25
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
12.0%
18
 
12.0%
13
 
8.7%
8
 
5.3%
8
 
5.3%
4
 
2.7%
4
 
2.7%
4
 
2.7%
3
 
2.0%
2
 
1.3%
Other values (53) 68
45.3%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150
85.7%
ASCII 25
 
14.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
100.0%
Hangul
ValueCountFrequency (%)
18
 
12.0%
18
 
12.0%
13
 
8.7%
8
 
5.3%
8
 
5.3%
4
 
2.7%
4
 
2.7%
4
 
2.7%
3
 
2.0%
2
 
1.3%
Other values (53) 68
45.3%

Correlations

2023-12-12T13:45:32.292261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권역(특화 분야)기관명주소전화번호대표자명
권역(특화 분야)1.0001.0001.0001.0001.000
기관명1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
대표자명1.0001.0001.0001.0001.000

Missing values

2023-12-12T13:45:28.614079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:45:28.757900image/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

권역(특화 분야)기관명주소전화번호대표자명
0서울·인천·경기재단법인 함께일하는재단서울특별시 마포구 월드컵북로 6길 36, 5층02-330-0765이사장 이세중
1서울·인천·경기사단법인 피피엘서울특별시 마포구 토정로 296, 이연빌딩 4층 사단법인 피피엘070-4610-5684,6이사장 김동호
2서울·인천·경기사회적협동조합 사람과세상경기도 수원시 영통구 동탄지성로 470번길 34, 상가동 2층(망포동, 수원영통 경기행복주택)070-4763-0130(내선번호3)이사장 주태규
3강원·충청사회적협동조합 세상만사대전광역시 유성구 농대로2번길 15, 3층042-320-9540 / 042-331-0119이사장 정완숙
4강원·충청(사)충남사회경제네트워크충청남도 아산시 번영로 86번길 27-3 아산시 어울림경제센터 3~4층041-415-2012 (내선번호3)이사장 신재학
5강원·충청(사)충북시민재단충청북도 청주시 흥덕구 흥덕로 159, BYC 빌딩 5층(운천동 1373)043-273-0335이사장 오원근
6강원·충청(사)강원도사회적경제지원센터강원도 원주시 단구로 354-27, 우리빌딩 5층033-749-3950~5대표 이길주
7강원·충청(재)강릉과학산업진흥원강원도 강릉시 과학단지로 106-11033-650-3310대표 김남수
8광주·전라·제주광주대학교 산학협력단광주광역시 남구 효덕로 277, 인성관 3층 사회적기업사업단062-670-2794산학협력단장 나종희
9광주·전라·제주사회적협동조합 살림광주광역시 서구 상무중앙로 43, BYC빌딩 7층062-383-1136이사장 윤봉란
권역(특화 분야)기관명주소전화번호대표자명
15부산·울산·경남(사)사회적기업연구원부산광역시 연제구 아시아드대로 107, 현대오일뱅크 2층051-504-0275이사장 조영복
16부산·울산·경남사회적협동조합 울산사회적경제지원센터울산광역시 남구 번영로 145, 10층(달동, 울산극동방송)052-700-6176센터장 문흥석
17부산·울산·경남모두의경제 사회적협동조합경상남도 창원시 의창구 우곡로217번길 17, 3층 모두의경제055-286-6379이사장 신영규
18특화 전담(교육/청소년자립)사회복지법인 열매나눔재단서울특별시 중구 퇴계로20길 37, 열매나눔재단 빌딩 302호02-2665-0718~9대표이사 이장호
19특화 전담(사회서비스)에스이임파워 사회적협동조합서울특별시 구로구 신도림로13길 51, 2층070-5057-3610 / 070-5057-2992이사장 오병전
20특화 전담(문화예술-서비스디자인)(재)부산디자인진흥원부산광역시 해운대구 센텀동로 57, 4층 408호(우동1457)051-950-1231,8대표 강필현
21특화 전담(농어촌/산림)(사)퍼스트경영기술연구원충청북도 청주시 상당구 교서로 8-4, 2층043-264-9979이사장 홍용석
22특화 전담(환경)(사)한국마이크로크레디트 신나는조합서울특별시 서대문구 통일로 107-39, 200호 (충정로 2가, 본관)02-365-0326 / 02-2135-1730대표 이선우
23특화 전담(사회서비스/의료-사회복지)한국의료복지사회적협동조합연합회경기도 안산시 예술광장 1로 46, 307호(월피동)031-362-5421회장 경창수
24특화 전담(에너지-재생에너지)전국시민발전협동조합연합회경기도 안산시 상록구 광덕산안길 20 광덕종합시장 3층 , 10호 (안산시사회적경제지원센터)070-4121-0705회장 이창수