Overview

Dataset statistics

Number of variables7
Number of observations68
Missing cells15
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory58.9 B

Variable types

Numeric1
Categorical2
Text4

Dataset

Description해당 데이터는 인천광역시 남동구의 사회적기업 현황에 관련된 자료로서, 인천광역시 남동구 사회적기업 현황의 연번, 분류, 분야, 기업명, 대표전화, 사업내용, 주소의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15104352&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 분류High correlation
분류 is highly overall correlated with 연번High correlation
대표전화 has 15 (22.1%) missing valuesMissing
연번 has unique valuesUnique
기업명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 10:31:40.097071
Analysis finished2024-01-28 10:31:41.120693
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.5
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-01-28T19:31:41.174970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.35
Q117.75
median34.5
Q351.25
95-th percentile64.65
Maximum68
Range67
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation19.77372
Coefficient of variation (CV)0.5731513
Kurtosis-1.2
Mean34.5
Median Absolute Deviation (MAD)17
Skewness0
Sum2346
Variance391
MonotonicityStrictly increasing
2024-01-28T19:31:41.278798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
45 1
 
1.5%
51 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
44 1
 
1.5%
36 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
68 1
1.5%
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%

분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
인증 사회적기업
44 
인천형 예비사회적기업
17 
부처형 예비사회적기업
7 

Length

Max length11
Median length8
Mean length9.0588235
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인증 사회적기업
2nd row인증 사회적기업
3rd row인증 사회적기업
4th row인증 사회적기업
5th row인증 사회적기업

Common Values

ValueCountFrequency (%)
인증 사회적기업 44
64.7%
인천형 예비사회적기업 17
 
25.0%
부처형 예비사회적기업 7
 
10.3%

Length

2024-01-28T19:31:41.383373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:31:41.461006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인증 44
32.4%
사회적기업 44
32.4%
예비사회적기업 24
17.6%
인천형 17
 
12.5%
부처형 7
 
5.1%

분야
Categorical

Distinct10
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size676.0 B
제조업
30 
교육
12 
기타
10 
청소
6 
도소매업
 
3
Other values (5)
7 

Length

Max length4
Median length3
Mean length2.6764706
Min length2

Unique

Unique3 ?
Unique (%)4.4%

Sample

1st row교육
2nd row가사간병
3rd row가사간병
4th row청소
5th row공연

Common Values

ValueCountFrequency (%)
제조업 30
44.1%
교육 12
 
17.6%
기타 10
 
14.7%
청소 6
 
8.8%
도소매업 3
 
4.4%
가사간병 2
 
2.9%
서비스업 2
 
2.9%
공연 1
 
1.5%
<NA> 1
 
1.5%
예술 1
 
1.5%

Length

2024-01-28T19:31:41.550847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:31:41.646734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조업 30
44.1%
교육 12
 
17.6%
기타 10
 
14.7%
청소 6
 
8.8%
도소매업 3
 
4.4%
가사간병 2
 
2.9%
서비스업 2
 
2.9%
공연 1
 
1.5%
na 1
 
1.5%
예술 1
 
1.5%

기업명
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-01-28T19:31:41.829732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length14
Mean length7.75
Min length3

Characters and Unicode

Total characters527
Distinct characters197
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row㈜위더스함께걸음
2nd row청솔돌봄사회적협동조합
3rd row(주)아가페
4th row선문그린존(주)
5th row(주)엘림엔터테인먼트
ValueCountFrequency (%)
협동조합 3
 
3.9%
㈜위더스함께걸음 1
 
1.3%
주)청솔기획 1
 
1.3%
협동조합마중물문화광장 1
 
1.3%
㈜농업회사법인풀내음밤나무숲 1
 
1.3%
주)수작떡공방 1
 
1.3%
월드종합관리(주 1
 
1.3%
청솔돌봄사회적협동조합 1
 
1.3%
㈜신우종합상사 1
 
1.3%
주)두손식품 1
 
1.3%
Other values (64) 64
84.2%
2024-01-28T19:31:42.128324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 28
 
5.3%
( 27
 
5.1%
) 27
 
5.1%
주 26
 
4.9%
합 13
 
2.5%
동 13
 
2.5%
조 13
 
2.5%
이 12
 
2.3%
스 12
 
2.3%
협 11
 
2.1%
Other values (187) 345
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 424
80.5%
Other Symbol 28
 
5.3%
Open Punctuation 27
 
5.1%
Close Punctuation 27
 
5.1%
Lowercase Letter 13
 
2.5%
Space Separator 8
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 26
 
6.1%
합 13
 
3.1%
동 13
 
3.1%
조 13
 
3.1%
이 12
 
2.8%
스 12
 
2.8%
협 11
 
2.6%
사 11
 
2.6%
아 8
 
1.9%
인 7
 
1.7%
Other values (175) 298
70.3%
Lowercase Letter
ValueCountFrequency (%)
a 3
23.1%
s 2
15.4%
e 2
15.4%
n 2
15.4%
d 1
 
7.7%
r 1
 
7.7%
g 1
 
7.7%
v 1
 
7.7%
Other Symbol
ValueCountFrequency (%)
㈜ 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 452
85.8%
Common 62
 
11.8%
Latin 13
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 28
 
6.2%
주 26
 
5.8%
합 13
 
2.9%
동 13
 
2.9%
조 13
 
2.9%
이 12
 
2.7%
스 12
 
2.7%
협 11
 
2.4%
사 11
 
2.4%
아 8
 
1.8%
Other values (176) 305
67.5%
Latin
ValueCountFrequency (%)
a 3
23.1%
s 2
15.4%
e 2
15.4%
n 2
15.4%
d 1
 
7.7%
r 1
 
7.7%
g 1
 
7.7%
v 1
 
7.7%
Common
ValueCountFrequency (%)
( 27
43.5%
) 27
43.5%
8
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 424
80.5%
ASCII 75
 
14.2%
None 28
 
5.3%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 28
100.0%
ASCII
ValueCountFrequency (%)
( 27
36.0%
) 27
36.0%
8
 
10.7%
a 3
 
4.0%
s 2
 
2.7%
e 2
 
2.7%
n 2
 
2.7%
d 1
 
1.3%
r 1
 
1.3%
g 1
 
1.3%
Hangul
ValueCountFrequency (%)
주 26
 
6.1%
합 13
 
3.1%
동 13
 
3.1%
조 13
 
3.1%
이 12
 
2.8%
스 12
 
2.8%
협 11
 
2.6%
사 11
 
2.6%
아 8
 
1.9%
인 7
 
1.7%
Other values (175) 298
70.3%

대표전화
Text

MISSING 

Distinct53
Distinct (%)100.0%
Missing15
Missing (%)22.1%
Memory size676.0 B
2024-01-28T19:31:42.328943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.981132
Min length8

Characters and Unicode

Total characters635
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

Unique53 ?
Unique (%)100.0%

Sample

1st row032-465-5379
2nd row032-425-0630
3rd row032-434-3798
4th row032-461-1323
5th row032-434-6989
ValueCountFrequency (%)
032-423-0033 1
 
1.9%
032-550-1555 1
 
1.9%
032-812-3334 1
 
1.9%
032-472-4534 1
 
1.9%
032-468-4318 1
 
1.9%
032-422-9404 1
 
1.9%
032-815-5835 1
 
1.9%
032-432-9480 1
 
1.9%
032-461-1992 1
 
1.9%
070-8810-9088 1
 
1.9%
Other values (43) 43
81.1%
2024-01-28T19:31:42.619612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.4%
2 101
15.9%
0 95
15.0%
3 85
13.4%
4 67
10.6%
8 38
 
6.0%
5 37
 
5.8%
1 31
 
4.9%
7 30
 
4.7%
6 29
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 531
83.6%
Dash Punctuation 104
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 101
19.0%
0 95
17.9%
3 85
16.0%
4 67
12.6%
8 38
 
7.2%
5 37
 
7.0%
1 31
 
5.8%
7 30
 
5.6%
6 29
 
5.5%
9 18
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 635
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.4%
2 101
15.9%
0 95
15.0%
3 85
13.4%
4 67
10.6%
8 38
 
6.0%
5 37
 
5.8%
1 31
 
4.9%
7 30
 
4.7%
6 29
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 635
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.4%
2 101
15.9%
0 95
15.0%
3 85
13.4%
4 67
10.6%
8 38
 
6.0%
5 37
 
5.8%
1 31
 
4.9%
7 30
 
4.7%
6 29
 
4.6%

사업내용
Text

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-01-28T19:31:42.800401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length26.5
Mean length15.955882
Min length2

Characters and Unicode

Total characters1085
Distinct characters214
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)97.1%

Sample

1st row장애아동 직업전환교육사업(바리스타, 제과제빵), 원두 및 수제쿠키 판매
2nd row가사간병 서비스
3rd row가사간병 서비스 및 비누판매
4th row청소위생관리,방역(소독),경비업
5th row공연, 행사기획, 방송장비 대여
ValueCountFrequency (%)
및 17
 
7.4%
등 8
 
3.5%
판매 7
 
3.0%
제조업 5
 
2.2%
제조판매 4
 
1.7%
제조 4
 
1.7%
공사업 3
 
1.3%
서비스 3
 
1.3%
교육 3
 
1.3%
판촉물 3
 
1.3%
Other values (161) 174
75.3%
2024-01-28T19:31:43.086450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
164
 
15.1%
, 58
 
5.3%
업 37
 
3.4%
제 33
 
3.0%
조 26
 
2.4%
사 24
 
2.2%
및 23
 
2.1%
매 22
 
2.0%
판 20
 
1.8%
품 19
 
1.8%
Other values (204) 659
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 830
76.5%
Space Separator 164
 
15.1%
Other Punctuation 62
 
5.7%
Close Punctuation 10
 
0.9%
Open Punctuation 10
 
0.9%
Uppercase Letter 9
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 37
 
4.5%
제 33
 
4.0%
조 26
 
3.1%
사 24
 
2.9%
및 23
 
2.8%
매 22
 
2.7%
판 20
 
2.4%
품 19
 
2.3%
소 17
 
2.0%
교 15
 
1.8%
Other values (194) 594
71.6%
Other Punctuation
ValueCountFrequency (%)
, 58
93.5%
& 2
 
3.2%
· 1
 
1.6%
/ 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
L 3
33.3%
D 3
33.3%
E 3
33.3%
Space Separator
ValueCountFrequency (%)
164
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 830
76.5%
Common 246
 
22.7%
Latin 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 37
 
4.5%
제 33
 
4.0%
조 26
 
3.1%
사 24
 
2.9%
및 23
 
2.8%
매 22
 
2.7%
판 20
 
2.4%
품 19
 
2.3%
소 17
 
2.0%
교 15
 
1.8%
Other values (194) 594
71.6%
Common
ValueCountFrequency (%)
164
66.7%
, 58
 
23.6%
) 10
 
4.1%
( 10
 
4.1%
& 2
 
0.8%
· 1
 
0.4%
/ 1
 
0.4%
Latin
ValueCountFrequency (%)
L 3
33.3%
D 3
33.3%
E 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 830
76.5%
ASCII 254
 
23.4%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
164
64.6%
, 58
 
22.8%
) 10
 
3.9%
( 10
 
3.9%
L 3
 
1.2%
D 3
 
1.2%
E 3
 
1.2%
& 2
 
0.8%
/ 1
 
0.4%
Hangul
ValueCountFrequency (%)
업 37
 
4.5%
제 33
 
4.0%
조 26
 
3.1%
사 24
 
2.9%
및 23
 
2.8%
매 22
 
2.7%
판 20
 
2.4%
품 19
 
2.3%
소 17
 
2.0%
교 15
 
1.8%
Other values (194) 594
71.6%
None
ValueCountFrequency (%)
· 1
100.0%

주소
Text

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-01-28T19:31:43.326841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length36
Mean length32.338235
Min length18

Characters and Unicode

Total characters2199
Distinct characters150
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

Unique66 ?
Unique (%)97.1%

Sample

1st row인천광역시 남동구 소래로 500, 1층 123호(수산동, 남동체육관)
2nd row인천광역시 남동구 서창남순환로 215번길 35, 506호(서창동, 승민프라자)
3rd row인천광역시 남동구 남동대로 906, 2층(간석동)
4th row인천광역시 남동구 남촌동로 45번길3, 3층(남촌동)
5th row인천광역시 남동구 논고개로 393(도림동)
ValueCountFrequency (%)
인천광역시 68
 
18.3%
남동구 68
 
18.3%
앵고개로 5
 
1.3%
3층 5
 
1.3%
1층 4
 
1.1%
928 4
 
1.1%
남동대로 3
 
0.8%
은봉로 3
 
0.8%
2층 3
 
0.8%
297 3
 
0.8%
Other values (188) 206
55.4%
2024-01-28T19:31:43.681659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
306
 
13.9%
동 156
 
7.1%
남 96
 
4.4%
구 88
 
4.0%
1 83
 
3.8%
역 71
 
3.2%
시 71
 
3.2%
인 70
 
3.2%
2 70
 
3.2%
천 70
 
3.2%
Other values (140) 1118
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1291
58.7%
Decimal Number 401
 
18.2%
Space Separator 306
 
13.9%
Other Punctuation 67
 
3.0%
Close Punctuation 55
 
2.5%
Open Punctuation 55
 
2.5%
Dash Punctuation 15
 
0.7%
Uppercase Letter 7
 
0.3%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 156
 
12.1%
남 96
 
7.4%
구 88
 
6.8%
역 71
 
5.5%
시 71
 
5.5%
인 70
 
5.4%
천 70
 
5.4%
광 68
 
5.3%
로 67
 
5.2%
호 36
 
2.8%
Other values (118) 498
38.6%
Decimal Number
ValueCountFrequency (%)
1 83
20.7%
2 70
17.5%
3 58
14.5%
0 46
11.5%
5 43
10.7%
4 23
 
5.7%
9 20
 
5.0%
8 20
 
5.0%
7 19
 
4.7%
6 19
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
B 2
28.6%
H 1
14.3%
L 1
14.3%
E 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
n 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
306
100.0%
Other Punctuation
ValueCountFrequency (%)
, 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1291
58.7%
Common 899
40.9%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 156
 
12.1%
남 96
 
7.4%
구 88
 
6.8%
역 71
 
5.5%
시 71
 
5.5%
인 70
 
5.4%
천 70
 
5.4%
광 68
 
5.3%
로 67
 
5.2%
호 36
 
2.8%
Other values (118) 498
38.6%
Common
ValueCountFrequency (%)
306
34.0%
1 83
 
9.2%
2 70
 
7.8%
, 67
 
7.5%
3 58
 
6.5%
) 55
 
6.1%
( 55
 
6.1%
0 46
 
5.1%
5 43
 
4.8%
4 23
 
2.6%
Other values (5) 93
 
10.3%
Latin
ValueCountFrequency (%)
C 2
22.2%
B 2
22.2%
n 1
11.1%
o 1
11.1%
H 1
11.1%
L 1
11.1%
E 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1291
58.7%
ASCII 908
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
306
33.7%
1 83
 
9.1%
2 70
 
7.7%
, 67
 
7.4%
3 58
 
6.4%
) 55
 
6.1%
( 55
 
6.1%
0 46
 
5.1%
5 43
 
4.7%
4 23
 
2.5%
Other values (12) 102
 
11.2%
Hangul
ValueCountFrequency (%)
동 156
 
12.1%
남 96
 
7.4%
구 88
 
6.8%
역 71
 
5.5%
시 71
 
5.5%
인 70
 
5.4%
천 70
 
5.4%
광 68
 
5.3%
로 67
 
5.2%
호 36
 
2.8%
Other values (118) 498
38.6%

Interactions

2024-01-28T19:31:40.916599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T19:31:43.763311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분류분야기업명대표전화사업내용주소
연번1.0000.8760.4391.0001.0000.9400.940
분류0.8761.0000.4571.0001.0001.0001.000
분야0.4390.4571.0001.0001.0000.9850.985
기업명1.0001.0001.0001.0001.0001.0001.000
대표전화1.0001.0001.0001.0001.0001.0001.000
사업내용0.9401.0000.9851.0001.0001.0000.998
주소0.9401.0000.9851.0001.0000.9981.000
2024-01-28T19:31:43.841812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분야분류
분야1.0000.212
분류0.2121.000
2024-01-28T19:31:43.902939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분류분야
연번1.0000.7660.210
분류0.7661.0000.212
분야0.2100.2121.000

Missing values

2024-01-28T19:31:41.005368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T19:31:41.087751image/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

연번분류분야기업명대표전화사업내용주소
01인증 사회적기업교육㈜위더스함께걸음032-465-5379장애아동 직업전환교육사업(바리스타, 제과제빵), 원두 및 수제쿠키 판매인천광역시 남동구 소래로 500, 1층 123호(수산동, 남동체육관)
12인증 사회적기업가사간병청솔돌봄사회적협동조합032-425-0630가사간병 서비스인천광역시 남동구 서창남순환로 215번길 35, 506호(서창동, 승민프라자)
23인증 사회적기업가사간병(주)아가페032-434-3798가사간병 서비스 및 비누판매인천광역시 남동구 남동대로 906, 2층(간석동)
34인증 사회적기업청소선문그린존(주)032-461-1323청소위생관리,방역(소독),경비업인천광역시 남동구 남촌동로 45번길3, 3층(남촌동)
45인증 사회적기업공연(주)엘림엔터테인먼트032-434-6989공연, 행사기획, 방송장비 대여인천광역시 남동구 논고개로 393(도림동)
56인증 사회적기업교육(주)반디숲032-434-0557숲 체험 프로그램 운영, 친환경자연교구 및 교재 제작판매인천광역시 남동구 도림북로 19번길 12-26(도림동)
67인증 사회적기업제조업(주)이레인텍032-434-3616LED조명기구 제조 판매, 사무용품, 판촉물 제작인천광역시 남동구 남동동로 293(논현동, 1층일부)
78인증 사회적기업청소(주)하얀나라032-442-5005병원세탁물(침대시트, 환자복, 이불 등) 전문 세탁업인천광역시 남동구 청능대로 534번길 34-2(논현동)
89인증 사회적기업교육(주)채움에이치알디032-822-7073교육컨설팅, 교육사업(고용노동부사업), 유료직업소개소 운영인천광역시 남동구 백범로 376, 601호(간석동, 도시타워)
910인증 사회적기업청소네모클린사회적협동조합032-428-3700위생관리용역/소독업, 청소용품인천광역시 남동구 구월말 91번길 18-2 가동 102호(만수동)
연번분류분야기업명대표전화사업내용주소
5859인천형 예비사회적기업제조업(주)비앤제이글로벌<NA>친환경 무독성 살균수 제조판매인천광역시 남동구 선수촌 공원로 5, 구월테크노밸리 C동 청년창업지원센터 205호
5960인천형 예비사회적기업제조업(주)유브레스032-822-2040미세먼지 흡착 필터 직조 및 임가공업인천광역시 남동구 남동동로 84, 206호(고잔동)
6061인천형 예비사회적기업제조업(주)워나스<NA>향수 제조판매인천광역시 남동구 앵고개로 928
6162인천형 예비사회적기업교육글로벌미래교육원(주)032-772-2450출판, 영상, 방송통신 및 정보서비스업인천광역시 남동구 앵고개로 928
6263인천형 예비사회적기업교육㈜놀이동무토왕성<NA>놀이프로그램개발및 운영,놀잇감제조인천광역시 남동구 남동대로 353(남촌동)
6364인천형 예비사회적기업도소매업㈜소래바다070-7778-8366빵류, 기념품인천광역시 남동구 만수로 120, 201호(만수동)
6465인천형 예비사회적기업교육㈜조이쿠킹아트<NA>떡, 빵및과자류, 강사육성및파견인천광역시 남동구 서창남순환로215번길 27(서창동)
6566인천형 예비사회적기업제조업㈜케이지셀틱에너지<NA>기타 가죽제품 제조업인천광역시 남동구 앵고개로 928(논현동) 3층
6667인천형 예비사회적기업서비스업㈜힐링아트<NA>심리상담인천광역시 남동구 은봉로 297, 별동3층 남동구청년창업지원센터 310호
6768인천형 예비사회적기업교육이센티<NA>교육서비스업인천광역시 남동구 은봉로 297 (LH 16단지) 내 남동구청년창업지원센터 312호