Overview

Dataset statistics

Number of variables15
Number of observations450
Missing cells513
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory53.3 KiB
Average record size in memory121.3 B

Variable types

Text7
Categorical7
Numeric1

Dataset

Description고용노동부 인증 사회적기업 현황 자료(2022년 4월)에 대한 데이터로 고용노동부 인증 사회적기업에 대한 정보를 제공합니다.
Author한국사회적기업진흥원
URLhttps://www.data.go.kr/data/15083319/fileData.do

Alerts

사회적목적유형 has constant value ""Constant
회차 is highly overall correlated with 지정일High correlation
지정일 is highly overall correlated with 회차High correlation
관할행정관서(시도) is highly overall correlated with 관할행정관서(고용관서)High correlation
관할행정관서(고용관서) is highly overall correlated with 관할행정관서(시도)High correlation
조직형태 is highly imbalanced (53.0%)Imbalance
사업내용 has 131 (29.1%) missing valuesMissing
회사메일 has 382 (84.9%) missing valuesMissing
기업명 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:05:52.338584
Analysis finished2023-12-13 00:05:54.039371
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Text

Distinct448
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T09:05:54.195127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length9.9911111
Min length9

Characters and Unicode

Total characters4496
Distinct characters19
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

Unique446 ?
Unique (%)99.1%

Sample

1st row제2021-069호
2nd row제2021-107호
3rd row제2021-068호
4th row제2021-094호
5th row제2021-053호
ValueCountFrequency (%)
제2019-43호 2
 
0.4%
제2019-140호 2
 
0.4%
제2020-206호 1
 
0.2%
제2019-120호 1
 
0.2%
제2019-124호 1
 
0.2%
제2019-062호 1
 
0.2%
제2019-179호 1
 
0.2%
제2020-053호 1
 
0.2%
제2019-176호 1
 
0.2%
제2019-143호 1
 
0.2%
Other values (439) 439
97.3%
2023-12-13T09:05:54.518695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 982
21.8%
2 882
19.6%
1 546
12.1%
제 450
10.0%
- 450
10.0%
호 450
10.0%
9 215
 
4.8%
3 92
 
2.0%
4 91
 
2.0%
8 89
 
2.0%
Other values (9) 249
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3140
69.8%
Other Letter 905
 
20.1%
Dash Punctuation 450
 
10.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 982
31.3%
2 882
28.1%
1 546
17.4%
9 215
 
6.8%
3 92
 
2.9%
4 91
 
2.9%
8 89
 
2.8%
6 83
 
2.6%
7 81
 
2.6%
5 79
 
2.5%
Other Letter
ValueCountFrequency (%)
제 450
49.7%
호 450
49.7%
고 1
 
0.1%
용 1
 
0.1%
노 1
 
0.1%
동 1
 
0.1%
부 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 450
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3591
79.9%
Hangul 905
 
20.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 982
27.3%
2 882
24.6%
1 546
15.2%
- 450
12.5%
9 215
 
6.0%
3 92
 
2.6%
4 91
 
2.5%
8 89
 
2.5%
6 83
 
2.3%
7 81
 
2.3%
Other values (2) 80
 
2.2%
Hangul
ValueCountFrequency (%)
제 450
49.7%
호 450
49.7%
고 1
 
0.1%
용 1
 
0.1%
노 1
 
0.1%
동 1
 
0.1%
부 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3591
79.9%
Hangul 905
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 982
27.3%
2 882
24.6%
1 546
15.2%
- 450
12.5%
9 215
 
6.0%
3 92
 
2.6%
4 91
 
2.5%
8 89
 
2.5%
6 83
 
2.3%
7 81
 
2.3%
Other values (2) 80
 
2.2%
Hangul
ValueCountFrequency (%)
제 450
49.7%
호 450
49.7%
고 1
 
0.1%
용 1
 
0.1%
노 1
 
0.1%
동 1
 
0.1%
부 1
 
0.1%

지정일
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2020-12-28
144 
2021-12-30
108 
2019-12-26
95 
2020-08-27
35 
2021-10-18
26 
Other values (4)
42 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2021-12-30
2nd row2021-12-30
3rd row2021-12-30
4th row2021-12-30
5th row2021-12-30

Common Values

ValueCountFrequency (%)
2020-12-28 144
32.0%
2021-12-30 108
24.0%
2019-12-26 95
21.1%
2020-08-27 35
 
7.8%
2021-10-18 26
 
5.8%
2019-06-21 25
 
5.6%
2019-08-07 10
 
2.2%
2020-12-15 6
 
1.3%
2020-10-28 1
 
0.2%

Length

2023-12-13T09:05:54.623886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:54.718823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-28 144
32.0%
2021-12-30 108
24.0%
2019-12-26 95
21.1%
2020-08-27 35
 
7.8%
2021-10-18 26
 
5.8%
2019-06-21 25
 
5.6%
2019-08-07 10
 
2.2%
2020-12-15 6
 
1.3%
2020-10-28 1
 
0.2%

관할행정관서(시도)
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
서울
150 
부산
54 
경기
47 
경남
37 
광주
29 
Other values (12)
133 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row충북
2nd row광주
3rd row충북
4th row서울
5th row서울

Common Values

ValueCountFrequency (%)
서울 150
33.3%
부산 54
 
12.0%
경기 47
 
10.4%
경남 37
 
8.2%
광주 29
 
6.4%
충남 20
 
4.4%
울산 18
 
4.0%
전남 17
 
3.8%
경북 16
 
3.6%
충북 14
 
3.1%
Other values (7) 48
 
10.7%

Length

2023-12-13T09:05:54.814094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 150
33.3%
부산 54
 
12.0%
경기 47
 
10.4%
경남 37
 
8.2%
광주 29
 
6.4%
충남 20
 
4.4%
울산 18
 
4.0%
전남 17
 
3.8%
경북 16
 
3.6%
충북 14
 
3.1%
Other values (7) 48
 
10.7%

관할 행정관서(시군)
Text

Distinct124
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T09:05:55.048839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9466667
Min length2

Characters and Unicode

Total characters1326
Distinct characters106
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)9.1%

Sample

1st row청주시
2nd row동구
3rd row청주시
4th row동대문구
5th row종로구
ValueCountFrequency (%)
중구 21
 
4.7%
북구 21
 
4.7%
남구 20
 
4.4%
구로구 15
 
3.3%
성동구 14
 
3.1%
마포구 13
 
2.9%
동구 12
 
2.7%
영등포구 11
 
2.4%
창원시 11
 
2.4%
서구 10
 
2.2%
Other values (114) 302
67.1%
2023-12-13T09:05:55.391208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 331
25.0%
시 100
 
7.5%
동 48
 
3.6%
군 42
 
3.2%
성 37
 
2.8%
서 36
 
2.7%
포 35
 
2.6%
북 34
 
2.6%
남 33
 
2.5%
주 26
 
2.0%
Other values (96) 604
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1326
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 331
25.0%
시 100
 
7.5%
동 48
 
3.6%
군 42
 
3.2%
성 37
 
2.8%
서 36
 
2.7%
포 35
 
2.6%
북 34
 
2.6%
남 33
 
2.5%
주 26
 
2.0%
Other values (96) 604
45.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1326
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 331
25.0%
시 100
 
7.5%
동 48
 
3.6%
군 42
 
3.2%
성 37
 
2.8%
서 36
 
2.7%
포 35
 
2.6%
북 34
 
2.6%
남 33
 
2.5%
주 26
 
2.0%
Other values (96) 604
45.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1326
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 331
25.0%
시 100
 
7.5%
동 48
 
3.6%
군 42
 
3.2%
성 37
 
2.8%
서 36
 
2.7%
포 35
 
2.6%
북 34
 
2.6%
남 33
 
2.5%
주 26
 
2.0%
Other values (96) 604
45.6%

관할행정관서(고용관서)
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
광주고용센터
35 
부산고용센터
35 
서울서부고용센터
32 
서울고용센터
 
29
서울관악고용센터
 
26
Other values (42)
293 

Length

Max length8
Median length6
Mean length6.5844444
Min length3

Unique

Unique9 ?
Unique (%)2.0%

Sample

1st row청주지청
2nd row광주고용센터
3rd row청주지청
4th row서울고용센터
5th row서울고용센터

Common Values

ValueCountFrequency (%)
광주고용센터 35
 
7.8%
부산고용센터 35
 
7.8%
서울서부고용센터 32
 
7.1%
서울고용센터 29
 
6.4%
서울관악고용센터 26
 
5.8%
서울동부고용센터 25
 
5.6%
서울남부고용센터 19
 
4.2%
대전고용센터 18
 
4.0%
울산고용센터 18
 
4.0%
성남고용센터 17
 
3.8%
Other values (37) 196
43.6%

Length

2023-12-13T09:05:55.524943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광주고용센터 35
 
7.8%
부산고용센터 35
 
7.8%
서울서부고용센터 32
 
7.1%
서울고용센터 29
 
6.4%
서울관악고용센터 26
 
5.8%
서울동부고용센터 25
 
5.6%
서울남부고용센터 19
 
4.2%
대전고용센터 18
 
4.0%
울산고용센터 18
 
4.0%
성남고용센터 17
 
3.8%
Other values (37) 196
43.6%

기업명
Text

UNIQUE 

Distinct450
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T09:05:55.693001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length9.6111111
Min length3

Characters and Unicode

Total characters4325
Distinct characters486
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

Unique450 ?
Unique (%)100.0%

Sample

1st row주식회사 나너드림
2nd row주식회사 이리바
3rd row다빈사회적협동조합
4th row(주)시프트미러
5th row주식회사청년비스튜디오
ValueCountFrequency (%)
주식회사 116
 
19.3%
협동조합 5
 
0.8%
농업회사법인 5
 
0.8%
사회적협동조합 4
 
0.7%
유한책임회사 3
 
0.5%
주 3
 
0.5%
작가 1
 
0.2%
주식회사툴스미스 1
 
0.2%
주)실비스트 1
 
0.2%
교육공동체우리자리사회적협동조합 1
 
0.2%
Other values (462) 462
76.7%
2023-12-13T09:05:55.991922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 382
 
8.8%
사 345
 
8.0%
회 326
 
7.5%
식 287
 
6.6%
154
 
3.6%
) 107
 
2.5%
( 106
 
2.5%
이 96
 
2.2%
스 86
 
2.0%
동 58
 
1.3%
Other values (476) 2378
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3789
87.6%
Space Separator 154
 
3.6%
Close Punctuation 107
 
2.5%
Open Punctuation 106
 
2.5%
Lowercase Letter 75
 
1.7%
Uppercase Letter 61
 
1.4%
Other Punctuation 18
 
0.4%
Decimal Number 14
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 382
 
10.1%
사 345
 
9.1%
회 326
 
8.6%
식 287
 
7.6%
이 96
 
2.5%
스 86
 
2.3%
동 58
 
1.5%
리 57
 
1.5%
합 50
 
1.3%
조 49
 
1.3%
Other values (424) 2053
54.2%
Uppercase Letter
ValueCountFrequency (%)
L 10
16.4%
O 6
 
9.8%
A 5
 
8.2%
C 5
 
8.2%
Y 4
 
6.6%
S 4
 
6.6%
D 3
 
4.9%
R 3
 
4.9%
E 3
 
4.9%
P 3
 
4.9%
Other values (9) 15
24.6%
Lowercase Letter
ValueCountFrequency (%)
o 11
14.7%
t 9
12.0%
s 8
10.7%
d 8
10.7%
e 7
9.3%
a 6
8.0%
i 5
6.7%
r 4
 
5.3%
b 3
 
4.0%
c 2
 
2.7%
Other values (8) 12
16.0%
Decimal Number
ValueCountFrequency (%)
0 3
21.4%
1 3
21.4%
9 2
14.3%
2 2
14.3%
7 1
 
7.1%
3 1
 
7.1%
6 1
 
7.1%
5 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 11
61.1%
, 6
33.3%
& 1
 
5.6%
Space Separator
ValueCountFrequency (%)
154
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3789
87.6%
Common 400
 
9.2%
Latin 136
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 382
 
10.1%
사 345
 
9.1%
회 326
 
8.6%
식 287
 
7.6%
이 96
 
2.5%
스 86
 
2.3%
동 58
 
1.5%
리 57
 
1.5%
합 50
 
1.3%
조 49
 
1.3%
Other values (424) 2053
54.2%
Latin
ValueCountFrequency (%)
o 11
 
8.1%
L 10
 
7.4%
t 9
 
6.6%
s 8
 
5.9%
d 8
 
5.9%
e 7
 
5.1%
O 6
 
4.4%
a 6
 
4.4%
A 5
 
3.7%
C 5
 
3.7%
Other values (27) 61
44.9%
Common
ValueCountFrequency (%)
154
38.5%
) 107
26.8%
( 106
26.5%
. 11
 
2.8%
, 6
 
1.5%
0 3
 
0.8%
1 3
 
0.8%
9 2
 
0.5%
2 2
 
0.5%
7 1
 
0.2%
Other values (5) 5
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3789
87.6%
ASCII 536
 
12.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 382
 
10.1%
사 345
 
9.1%
회 326
 
8.6%
식 287
 
7.6%
이 96
 
2.5%
스 86
 
2.3%
동 58
 
1.5%
리 57
 
1.5%
합 50
 
1.3%
조 49
 
1.3%
Other values (424) 2053
54.2%
ASCII
ValueCountFrequency (%)
154
28.7%
) 107
20.0%
( 106
19.8%
o 11
 
2.1%
. 11
 
2.1%
L 10
 
1.9%
t 9
 
1.7%
s 8
 
1.5%
d 8
 
1.5%
e 7
 
1.3%
Other values (42) 105
19.6%

사업내용
Text

MISSING 

Distinct148
Distinct (%)46.4%
Missing131
Missing (%)29.1%
Memory size3.6 KiB
2023-12-13T09:05:56.281495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length27
Mean length6.6833856
Min length2

Characters and Unicode

Total characters2132
Distinct characters198
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)39.2%

Sample

1st row인형극, 학술연구용역, 교육컨설팅
2nd row제조업, 과학 및 기술서비스업
3rd row소프트웨어 개발 및 공급
4th row정보통신업
5th row광고대행업
ValueCountFrequency (%)
서비스 71
 
14.3%
서비스업 40
 
8.0%
및 35
 
7.0%
제조업 31
 
6.2%
교육서비스업 17
 
3.4%
소매업 16
 
3.2%
정보통신업 12
 
2.4%
도매 11
 
2.2%
교육서비스 10
 
2.0%
도소매 10
 
2.0%
Other values (185) 245
49.2%
2023-12-13T09:05:56.673655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 197
 
9.2%
186
 
8.7%
스 169
 
7.9%
서 165
 
7.7%
비 164
 
7.7%
, 64
 
3.0%
매 62
 
2.9%
제 55
 
2.6%
소 53
 
2.5%
조 49
 
2.3%
Other values (188) 968
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1862
87.3%
Space Separator 186
 
8.7%
Other Punctuation 71
 
3.3%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Uppercase Letter 4
 
0.2%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 197
 
10.6%
스 169
 
9.1%
서 165
 
8.9%
비 164
 
8.8%
매 62
 
3.3%
제 55
 
3.0%
소 53
 
2.8%
조 49
 
2.6%
교 43
 
2.3%
육 43
 
2.3%
Other values (177) 862
46.3%
Uppercase Letter
ValueCountFrequency (%)
M 1
25.0%
D 1
25.0%
R 1
25.0%
V 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 64
90.1%
. 4
 
5.6%
/ 3
 
4.2%
Space Separator
ValueCountFrequency (%)
186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1862
87.3%
Common 266
 
12.5%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 197
 
10.6%
스 169
 
9.1%
서 165
 
8.9%
비 164
 
8.8%
매 62
 
3.3%
제 55
 
3.0%
소 53
 
2.8%
조 49
 
2.6%
교 43
 
2.3%
육 43
 
2.3%
Other values (177) 862
46.3%
Common
ValueCountFrequency (%)
186
69.9%
, 64
 
24.1%
. 4
 
1.5%
) 4
 
1.5%
( 4
 
1.5%
/ 3
 
1.1%
3 1
 
0.4%
Latin
ValueCountFrequency (%)
M 1
25.0%
D 1
25.0%
R 1
25.0%
V 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1862
87.3%
ASCII 270
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 197
 
10.6%
스 169
 
9.1%
서 165
 
8.9%
비 164
 
8.8%
매 62
 
3.3%
제 55
 
3.0%
소 53
 
2.8%
조 49
 
2.6%
교 43
 
2.3%
육 43
 
2.3%
Other values (177) 862
46.3%
ASCII
ValueCountFrequency (%)
186
68.9%
, 64
 
23.7%
. 4
 
1.5%
) 4
 
1.5%
( 4
 
1.5%
/ 3
 
1.1%
3 1
 
0.4%
M 1
 
0.4%
D 1
 
0.4%
R 1
 
0.4%

업종
Categorical

Distinct16
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
교육 서비스업(P)
108 
제조업(C)
76 
도매 및 소매업(G)
60 
출판, 영상, 방송통신 및 정보서비스업(J)
56 
예술, 스포츠 및 여가관련 서비스업(R)
49 
Other values (11)
101 

Length

Max length24
Median length21
Mean length13.917778
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row교육 서비스업(P)
2nd row예술, 스포츠 및 여가관련 서비스업(R)
3rd row교육 서비스업(P)
4th row제조업(C)
5th row출판, 영상, 방송통신 및 정보서비스업(J)

Common Values

ValueCountFrequency (%)
교육 서비스업(P) 108
24.0%
제조업(C) 76
16.9%
도매 및 소매업(G) 60
13.3%
출판, 영상, 방송통신 및 정보서비스업(J) 56
12.4%
예술, 스포츠 및 여가관련 서비스업(R) 49
10.9%
전문, 과학 및 기술 서비스업(M) 29
 
6.4%
숙박 및 음식점업(I) 18
 
4.0%
농업, 임업 및 어업(A) 14
 
3.1%
보건업 및 사회복지 서비스업(Q) 11
 
2.4%
협회 및 단체, 수리 및 개인 서비스업(S) 8
 
1.8%
Other values (6) 21
 
4.7%

Length

2023-12-13T09:05:56.781027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 263
18.8%
교육 108
 
7.7%
서비스업(p 108
 
7.7%
제조업(c 76
 
5.4%
도매 60
 
4.3%
소매업(g 60
 
4.3%
출판 56
 
4.0%
영상 56
 
4.0%
방송통신 56
 
4.0%
정보서비스업(j 56
 
4.0%
Other values (33) 503
35.9%

사회적목적유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
기타(창의ㆍ혁신)형
450 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타(창의ㆍ혁신)형
2nd row기타(창의ㆍ혁신)형
3rd row기타(창의ㆍ혁신)형
4th row기타(창의ㆍ혁신)형
5th row기타(창의ㆍ혁신)형

Common Values

ValueCountFrequency (%)
기타(창의ㆍ혁신)형 450
100.0%

Length

2023-12-13T09:05:56.864409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:56.938700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타(창의ㆍ혁신)형 450
100.0%

조직형태
Categorical

IMBALANCE 

Distinct9
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
상법에 따른 회사
299 
민법에 따른 법인
88 
협동조합 기본법에 따른 협동조합
39 
사회적협동조합
 
9
농업회사법인
 
9
Other values (4)
 
6

Length

Max length26
Median length9
Mean length9.6177778
Min length2

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row민법에 따른 법인
2nd row상법에 따른 회사
3rd row사회적협동조합
4th row상법에 따른 회사
5th row상법에 따른 회사

Common Values

ValueCountFrequency (%)
상법에 따른 회사 299
66.4%
민법에 따른 법인 88
 
19.6%
협동조합 기본법에 따른 협동조합 39
 
8.7%
사회적협동조합 9
 
2.0%
농업회사법인 9
 
2.0%
기타 3
 
0.7%
영농(어)조합법인 1
 
0.2%
그 밖에 다른 법률에 따른 법인 또는 비영리단체 1
 
0.2%
「비영리민간단체지원법」에 따른 비영리민간단체 1
 
0.2%

Length

2023-12-13T09:05:57.011462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:57.100805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
따른 428
31.7%
상법에 299
22.1%
회사 299
22.1%
법인 89
 
6.6%
민법에 88
 
6.5%
협동조합 78
 
5.8%
기본법에 39
 
2.9%
사회적협동조합 9
 
0.7%
농업회사법인 9
 
0.7%
기타 3
 
0.2%
Other values (9) 9
 
0.7%

대표자
Text

Distinct443
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T09:05:57.365660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.1466667
Min length2

Characters and Unicode

Total characters1416
Distinct characters182
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique436 ?
Unique (%)96.9%

Sample

1st row정남득
2nd row오지영
3rd row박숙경
4th row이재진
5th row김영욱
ValueCountFrequency (%)
김정현 2
 
0.4%
정세윤 2
 
0.4%
김미경 2
 
0.4%
장윤석 2
 
0.4%
김영미 2
 
0.4%
박은경 2
 
0.4%
김현주 2
 
0.4%
김도형 1
 
0.2%
호기헌 1
 
0.2%
김진성 1
 
0.2%
Other values (446) 446
96.3%
2023-12-13T09:05:57.721264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 98
 
6.9%
이 71
 
5.0%
정 62
 
4.4%
박 48
 
3.4%
현 43
 
3.0%
영 37
 
2.6%
수 36
 
2.5%
은 35
 
2.5%
진 31
 
2.2%
성 29
 
2.0%
Other values (172) 926
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1378
97.3%
Space Separator 13
 
0.9%
Other Punctuation 12
 
0.8%
Lowercase Letter 10
 
0.7%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 98
 
7.1%
이 71
 
5.2%
정 62
 
4.5%
박 48
 
3.5%
현 43
 
3.1%
영 37
 
2.7%
수 36
 
2.6%
은 35
 
2.5%
진 31
 
2.2%
성 29
 
2.1%
Other values (160) 888
64.4%
Lowercase Letter
ValueCountFrequency (%)
e 3
30.0%
l 2
20.0%
h 1
 
10.0%
p 1
 
10.0%
s 1
 
10.0%
o 1
 
10.0%
i 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
33.3%
H 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1378
97.3%
Common 25
 
1.8%
Latin 13
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 98
 
7.1%
이 71
 
5.2%
정 62
 
4.5%
박 48
 
3.5%
현 43
 
3.1%
영 37
 
2.7%
수 36
 
2.6%
은 35
 
2.5%
진 31
 
2.2%
성 29
 
2.1%
Other values (160) 888
64.4%
Latin
ValueCountFrequency (%)
e 3
23.1%
l 2
15.4%
h 1
 
7.7%
p 1
 
7.7%
s 1
 
7.7%
o 1
 
7.7%
J 1
 
7.7%
i 1
 
7.7%
H 1
 
7.7%
L 1
 
7.7%
Common
ValueCountFrequency (%)
13
52.0%
, 12
48.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1378
97.3%
ASCII 38
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 98
 
7.1%
이 71
 
5.2%
정 62
 
4.5%
박 48
 
3.5%
현 43
 
3.1%
영 37
 
2.7%
수 36
 
2.6%
은 35
 
2.5%
진 31
 
2.2%
성 29
 
2.1%
Other values (160) 888
64.4%
ASCII
ValueCountFrequency (%)
13
34.2%
, 12
31.6%
e 3
 
7.9%
l 2
 
5.3%
h 1
 
2.6%
p 1
 
2.6%
s 1
 
2.6%
o 1
 
2.6%
J 1
 
2.6%
i 1
 
2.6%
Other values (2) 2
 
5.3%

소재지
Text

Distinct441
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T09:05:57.995785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length50
Mean length32.42
Min length18

Characters and Unicode

Total characters14589
Distinct characters442
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

Unique433 ?
Unique (%)96.2%

Sample

1st row충청북도 청주시 청원구 우암로 67-1 내덕동
2nd row광주광역시 동구 중앙로196번길 29 대의동 , 2층
3rd row충청북도 청주시 청원구 오창읍 중심상업로 14 , 307호
4th row서울특별시 동대문구 경희대로 26 회기동 , 네오르상스관 B114-A2호
5th row서울특별시 종로구 청계천로 159 장사동 , 663호
ValueCountFrequency (%)
215
 
7.1%
서울특별시 150
 
4.9%
1층 66
 
2.2%
2층 57
 
1.9%
부산광역시 53
 
1.7%
경기도 47
 
1.5%
경상남도 37
 
1.2%
3층 30
 
1.0%
광주광역시 28
 
0.9%
북구 24
 
0.8%
Other values (1443) 2335
76.8%
2023-12-13T09:05:58.383758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2706
 
18.5%
1 598
 
4.1%
시 443
 
3.0%
로 437
 
3.0%
2 408
 
2.8%
동 407
 
2.8%
구 386
 
2.6%
0 277
 
1.9%
, 271
 
1.9%
3 271
 
1.9%
Other values (432) 8385
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8457
58.0%
Space Separator 2706
 
18.5%
Decimal Number 2543
 
17.4%
Other Punctuation 273
 
1.9%
Open Punctuation 222
 
1.5%
Close Punctuation 222
 
1.5%
Dash Punctuation 94
 
0.6%
Uppercase Letter 61
 
0.4%
Lowercase Letter 9
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 443
 
5.2%
로 437
 
5.2%
동 407
 
4.8%
구 386
 
4.6%
층 268
 
3.2%
서 230
 
2.7%
호 223
 
2.6%
길 212
 
2.5%
도 199
 
2.4%
울 187
 
2.2%
Other values (387) 5465
64.6%
Uppercase Letter
ValueCountFrequency (%)
B 13
21.3%
A 9
14.8%
I 5
 
8.2%
S 4
 
6.6%
L 4
 
6.6%
K 4
 
6.6%
D 3
 
4.9%
T 3
 
4.9%
R 2
 
3.3%
E 2
 
3.3%
Other values (9) 12
19.7%
Decimal Number
ValueCountFrequency (%)
1 598
23.5%
2 408
16.0%
0 277
10.9%
3 271
10.7%
5 236
 
9.3%
4 211
 
8.3%
6 160
 
6.3%
7 155
 
6.1%
8 119
 
4.7%
9 108
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
l 2
22.2%
i 1
11.1%
h 1
11.1%
g 1
11.1%
b 1
11.1%
a 1
11.1%
e 1
11.1%
v 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 271
99.3%
& 1
 
0.4%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
2706
100.0%
Open Punctuation
ValueCountFrequency (%)
( 222
100.0%
Close Punctuation
ValueCountFrequency (%)
) 222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8457
58.0%
Common 6062
41.6%
Latin 70
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 443
 
5.2%
로 437
 
5.2%
동 407
 
4.8%
구 386
 
4.6%
층 268
 
3.2%
서 230
 
2.7%
호 223
 
2.6%
길 212
 
2.5%
도 199
 
2.4%
울 187
 
2.2%
Other values (387) 5465
64.6%
Latin
ValueCountFrequency (%)
B 13
18.6%
A 9
12.9%
I 5
 
7.1%
S 4
 
5.7%
L 4
 
5.7%
K 4
 
5.7%
D 3
 
4.3%
T 3
 
4.3%
R 2
 
2.9%
E 2
 
2.9%
Other values (17) 21
30.0%
Common
ValueCountFrequency (%)
2706
44.6%
1 598
 
9.9%
2 408
 
6.7%
0 277
 
4.6%
, 271
 
4.5%
3 271
 
4.5%
5 236
 
3.9%
( 222
 
3.7%
) 222
 
3.7%
4 211
 
3.5%
Other values (8) 640
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8457
58.0%
ASCII 6132
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2706
44.1%
1 598
 
9.8%
2 408
 
6.7%
0 277
 
4.5%
, 271
 
4.4%
3 271
 
4.4%
5 236
 
3.8%
( 222
 
3.6%
) 222
 
3.6%
4 211
 
3.4%
Other values (35) 710
 
11.6%
Hangul
ValueCountFrequency (%)
시 443
 
5.2%
로 437
 
5.2%
동 407
 
4.8%
구 386
 
4.6%
층 268
 
3.2%
서 230
 
2.7%
호 223
 
2.6%
길 212
 
2.5%
도 199
 
2.4%
울 187
 
2.2%
Other values (387) 5465
64.6%

설립연도
Real number (ℝ)

Distinct15
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.7467
Minimum1979
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-13T09:05:58.498519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1979
5-th percentile2017
Q12018
median2019
Q32020
95-th percentile2021
Maximum2021
Range42
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.9306686
Coefficient of variation (CV)0.0019470837
Kurtosis70.446042
Mean2018.7467
Median Absolute Deviation (MAD)1
Skewness-7.9031849
Sum908436
Variance15.450156
MonotonicityNot monotonic
2023-12-13T09:05:58.579992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2019 142
31.6%
2020 136
30.2%
2018 76
16.9%
2021 54
 
12.0%
2017 25
 
5.6%
2016 5
 
1.1%
2014 2
 
0.4%
2015 2
 
0.4%
2013 2
 
0.4%
1979 1
 
0.2%
Other values (5) 5
 
1.1%
ValueCountFrequency (%)
1979 1
 
0.2%
1980 1
 
0.2%
1981 1
 
0.2%
1991 1
 
0.2%
1996 1
 
0.2%
2000 1
 
0.2%
2013 2
 
0.4%
2014 2
 
0.4%
2015 2
 
0.4%
2016 5
1.1%
ValueCountFrequency (%)
2021 54
 
12.0%
2020 136
30.2%
2019 142
31.6%
2018 76
16.9%
2017 25
 
5.6%
2016 5
 
1.1%
2015 2
 
0.4%
2014 2
 
0.4%
2013 2
 
0.4%
2000 1
 
0.2%

회차
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2020년 02차수
151 
2021년 02차수
110 
2019년 03차수
95 
2020년 01차수
35 
2019년 01차수
25 
Other values (2)
34 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021년 02차수
2nd row2021년 02차수
3rd row2021년 02차수
4th row2021년 02차수
5th row2021년 02차수

Common Values

ValueCountFrequency (%)
2020년 02차수 151
33.6%
2021년 02차수 110
24.4%
2019년 03차수 95
21.1%
2020년 01차수 35
 
7.8%
2019년 01차수 25
 
5.6%
2021년 01차수 24
 
5.3%
2019년 02차수 10
 
2.2%

Length

2023-12-13T09:05:58.671182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:58.772863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02차수 271
30.1%
2020년 186
20.7%
2021년 134
14.9%
2019년 130
14.4%
03차수 95
 
10.6%
01차수 84
 
9.3%

회사메일
Text

MISSING 

Distinct68
Distinct (%)100.0%
Missing382
Missing (%)84.9%
Memory size3.6 KiB
2023-12-13T09:05:58.962028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19.205882
Min length13

Characters and Unicode

Total characters1306
Distinct characters39
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st rowgnhugnhu@gmail.com
2nd rowpone4211@hanmail.net
3rd rowbusanchimaex@naver.com
4th roweverbam@nate.com
5th rowkjy3677@gmail.com
ValueCountFrequency (%)
master@fivesenses.co.kr 1
 
1.5%
huntshin@gmail.com 1
 
1.5%
chukbae@naver.com 1
 
1.5%
loty.ruby@gmail.com 1
 
1.5%
jeon1082@gmail.com 1
 
1.5%
upgradlee@naver.com 1
 
1.5%
bnbs_co@naver.com 1
 
1.5%
bmk501@naver.com 1
 
1.5%
happy5771@hanmail.net 1
 
1.5%
pone4211@hanmail.net 1
 
1.5%
Other values (58) 58
85.3%
2023-12-13T09:05:59.260704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 110
 
8.4%
a 109
 
8.3%
e 106
 
8.1%
m 95
 
7.3%
n 91
 
7.0%
c 76
 
5.8%
. 75
 
5.7%
r 73
 
5.6%
@ 69
 
5.3%
i 53
 
4.1%
Other values (29) 449
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1074
82.2%
Other Punctuation 144
 
11.0%
Decimal Number 76
 
5.8%
Connector Punctuation 6
 
0.5%
Dash Punctuation 5
 
0.4%
Space Separator 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 110
10.2%
a 109
10.1%
e 106
 
9.9%
m 95
 
8.8%
n 91
 
8.5%
c 76
 
7.1%
r 73
 
6.8%
i 53
 
4.9%
l 48
 
4.5%
t 43
 
4.0%
Other values (14) 270
25.1%
Decimal Number
ValueCountFrequency (%)
0 13
17.1%
1 11
14.5%
7 9
11.8%
3 8
10.5%
6 7
9.2%
2 7
9.2%
5 6
7.9%
8 5
 
6.6%
4 5
 
6.6%
9 5
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 75
52.1%
@ 69
47.9%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1074
82.2%
Common 232
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 110
10.2%
a 109
10.1%
e 106
 
9.9%
m 95
 
8.8%
n 91
 
8.5%
c 76
 
7.1%
r 73
 
6.8%
i 53
 
4.9%
l 48
 
4.5%
t 43
 
4.0%
Other values (14) 270
25.1%
Common
ValueCountFrequency (%)
. 75
32.3%
@ 69
29.7%
0 13
 
5.6%
1 11
 
4.7%
7 9
 
3.9%
3 8
 
3.4%
6 7
 
3.0%
2 7
 
3.0%
_ 6
 
2.6%
5 6
 
2.6%
Other values (5) 21
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 110
 
8.4%
a 109
 
8.3%
e 106
 
8.1%
m 95
 
7.3%
n 91
 
7.0%
c 76
 
5.8%
. 75
 
5.7%
r 73
 
5.6%
@ 69
 
5.3%
i 53
 
4.1%
Other values (29) 449
34.4%

Interactions

2023-12-13T09:05:53.618325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:05:59.341336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정일관할행정관서(시도)관할행정관서(고용관서)업종조직형태설립연도회차회사메일
지정일1.0000.4850.5650.0530.3170.1520.9921.000
관할행정관서(시도)0.4851.0000.9910.3570.2310.0000.2411.000
관할행정관서(고용관서)0.5650.9911.0000.6040.2210.0000.4581.000
업종0.0530.3570.6041.0000.4010.0000.0631.000
조직형태0.3170.2310.2210.4011.0000.0000.2611.000
설립연도0.1520.0000.0000.0000.0001.0000.1751.000
회차0.9920.2410.4580.0630.2610.1751.0001.000
회사메일1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T09:05:59.428778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종관할행정관서(시도)조직형태회차관할행정관서(고용관서)지정일
업종1.0000.1260.1740.0270.2040.020
관할행정관서(시도)0.1261.0000.0930.1090.8450.215
조직형태0.1740.0931.0000.1400.0760.106
회차0.0270.1090.1401.0000.1930.990
관할행정관서(고용관서)0.2040.8450.0760.1931.0000.229
지정일0.0200.2150.1060.9900.2291.000
2023-12-13T09:05:59.510726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립연도지정일관할행정관서(시도)관할행정관서(고용관서)업종조직형태회차
설립연도1.0000.0940.0000.0230.0000.0000.117
지정일0.0941.0000.2150.2290.0200.1060.990
관할행정관서(시도)0.0000.2151.0000.8450.1260.0930.109
관할행정관서(고용관서)0.0230.2290.8451.0000.2040.0760.193
업종0.0000.0200.1260.2041.0000.1740.027
조직형태0.0000.1060.0930.0760.1741.0000.140
회차0.1170.9900.1090.1930.0270.1401.000

Missing values

2023-12-13T09:05:53.733281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:05:53.891712image/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.
2023-12-13T09:05:53.994356image/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

지정번호지정일관할행정관서(시도)관할 행정관서(시군)관할행정관서(고용관서)기업명사업내용업종사회적목적유형조직형태대표자소재지설립연도회차회사메일
0제2021-069호2021-12-30충북청주시청주지청주식회사 나너드림인형극, 학술연구용역, 교육컨설팅교육 서비스업(P)기타(창의ㆍ혁신)형민법에 따른 법인정남득충청북도 청주시 청원구 우암로 67-1 내덕동20202021년 02차수<NA>
1제2021-107호2021-12-30광주동구광주고용센터주식회사 이리바<NA>예술, 스포츠 및 여가관련 서비스업(R)기타(창의ㆍ혁신)형상법에 따른 회사오지영광주광역시 동구 중앙로196번길 29 대의동 , 2층20212021년 02차수<NA>
2제2021-068호2021-12-30충북청주시청주지청다빈사회적협동조합<NA>교육 서비스업(P)기타(창의ㆍ혁신)형사회적협동조합박숙경충청북도 청주시 청원구 오창읍 중심상업로 14 , 307호20202021년 02차수<NA>
3제2021-094호2021-12-30서울동대문구서울고용센터(주)시프트미러제조업, 과학 및 기술서비스업제조업(C)기타(창의ㆍ혁신)형상법에 따른 회사이재진서울특별시 동대문구 경희대로 26 회기동 , 네오르상스관 B114-A2호20212021년 02차수<NA>
4제2021-053호2021-12-30서울종로구서울고용센터주식회사청년비스튜디오<NA>출판, 영상, 방송통신 및 정보서비스업(J)기타(창의ㆍ혁신)형상법에 따른 회사김영욱서울특별시 종로구 청계천로 159 장사동 , 663호20192021년 02차수<NA>
5제2021-115호2021-12-30서울구로구서울관악고용센터주식회사 더치스토어<NA>전문, 과학 및 기술 서비스업(M)기타(창의ㆍ혁신)형상법에 따른 회사박대성서울특별시 구로구 신도림로13길 51 신도림동 , 2층20202021년 02차수<NA>
6제2021-095호2021-12-30경기화성시수원고용센터(주)알에스건재<NA>제조업(C)기타(창의ㆍ혁신)형민법에 따른 법인임재성경기도 화성시 정남면 정남동로 302 주건물 3동 1층20202021년 02차수<NA>
7제2021-133호2021-12-30서울강동구서울동부고용센터소셜브릿지협동조합소프트웨어 개발 및 공급전문, 과학 및 기술 서비스업(M)기타(창의ㆍ혁신)형협동조합 기본법에 따른 협동조합나현홍서울특별시 강동구 올림픽로 651 천호동 , 9층 945호20192021년 02차수<NA>
8제2021-114호2021-12-30서울구로구서울관악고용센터주식회사 슬로아이정보통신업전문, 과학 및 기술 서비스업(M)기타(창의ㆍ혁신)형상법에 따른 회사조오윤서울특별시 구로구 신도림로13길 51 신도림동 , 2층20212021년 02차수<NA>
9제2021-108호2021-12-30광주동구광주고용센터주식회사 비제로스튜디오광고대행업출판, 영상, 방송통신 및 정보서비스업(J)기타(창의ㆍ혁신)형상법에 따른 회사정세윤광주광역시 동구 동계로 16-1 산수동 , 2층20212021년 02차수<NA>
지정번호지정일관할행정관서(시도)관할 행정관서(시군)관할행정관서(고용관서)기업명사업내용업종사회적목적유형조직형태대표자소재지설립연도회차회사메일
440제2019-017호2019-06-21경기수정구성남고용센터애프터레인주식회사제조업제조업(C)기타(창의ㆍ혁신)형민법에 따른 법인이윤희, 박중현경기도 성남시 수정구 창업로 54 , 엘에이치 기업성장센터 1층 135호(시흥동, 판교제2테크노밸리기업성장센터)20182019년 01차수afterainkorea@gmail.com
441제2019-41호2019-08-07대구중구대구고용센터(주)컬처팩토리아지트도소매업예술, 스포츠 및 여가관련 서비스업(R)기타(창의ㆍ혁신)형상법에 따른 회사최남욱대구광역시 중구 태평로 160 소셜캠퍼스온 1101호20172019년 02차수mk_noriyuki@naver.com
442제2019-133호2019-12-26서울서대문구서울서부고용센터(주)질링스서비스출판, 영상, 방송통신 및 정보서비스업(J)기타(창의ㆍ혁신)형상법에 따른 회사양홍석서울특별시 강남구 봉은사로 320(역삼동) 9층 905호20172019년 03차수<NA>
443제2019-023호2019-06-21충남천안시천안고용센터주식회사주긍정(Joopositiveco.,Ltd)서비스업사업시설관리 및 사업지원 서비스업(N)기타(창의ㆍ혁신)형상법에 따른 회사주상현충청남도 천안시 동남구 다가10길 31, 1층(다가동)20132019년 01차수<NA>
444제2019-119호2019-12-26서울중구서울남부고용센터주식회사굿임팩트서비스출판, 영상, 방송통신 및 정보서비스업(J)기타(창의ㆍ혁신)형상법에 따른 회사이준수서울특별시 중구 청계천로 40(다동) 한국관광공사 서울센터 1206호20172019년 03차수<NA>
445제2020-130호2020-12-28서울구로구서울관악고용센터주식회사쉐어러스기타통신판매업출판, 영상, 방송통신 및 정보서비스업(J)기타(창의ㆍ혁신)형민법에 따른 법인이병훈서울특별시 구로구 개봉로23길 10(개봉동) 서울개봉지구 임대산업시설 , 5층 505호20172020년 02차수<NA>
446제2020-148호2020-12-28인천연수구중부청주식회사나인와트전문, 과학 및 기술 서비스업 전문, 과학 및 기술서비스업 사업시설관리 및 사업지원서비스업전문, 과학 및 기술 서비스업(M)기타(창의ㆍ혁신)형상법에 따른 회사김영록인천광역시 연수구 컨벤시아대로 204(송도동) , 104호(인스타2)20172020년 02차수<NA>
447제2021-010호2021-10-18서울송파구서울동부고용센터합명회사 인토피아서비스업교육 서비스업(P)기타(창의ㆍ혁신)형민법에 따른 법인정현호서울특별시 송파구 중대로 135(가락동) 아이티벤처타워 , 서관 10층20172021년 02차수<NA>
448제2019-008호2019-06-21서울성동구서울동부고용센터주식회사그로잉맘정보서비스교육 서비스업(P)기타(창의ㆍ혁신)형상법에 따른 회사이다랑서울특별시 성동구 뚝섬로1나길 5 709호20172019년 01차수<NA>
449제2020-036호2020-08-27경기중원구성남고용센터히어로앤컴퍼니 주식회사서비스업교육 서비스업(P)기타(창의ㆍ혁신)형상법에 따른 회사정부현경기도 성남시 중원구 둔촌대로 287 (하대원동, B02)20142020년 01차수<NA>