Overview

Dataset statistics

Number of variables7
Number of observations56
Missing cells33
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory59.4 B

Variable types

Numeric1
Categorical1
Text5

Dataset

Description인천광역시 서구의 사회적기업에 관한 데이터로 연번, 구분, 기업명, 사회적기업 주소, 연락처, 사업내용 항목을 제공합니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15105075&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번High correlation
연락처 has 33 (58.9%) missing valuesMissing
연번 has unique valuesUnique
기업명 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:59:48.536875
Analysis finished2024-01-28 17:59:49.311388
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.5
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-01-29T02:59:49.368276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.75
Q114.75
median28.5
Q342.25
95-th percentile53.25
Maximum56
Range55
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation16.309506
Coefficient of variation (CV)0.57226338
Kurtosis-1.2
Mean28.5
Median Absolute Deviation (MAD)14
Skewness0
Sum1596
Variance266
MonotonicityStrictly increasing
2024-01-29T02:59:49.481821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
30 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%
47 1
1.8%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
인증
33 
예비
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인증 33
58.9%
예비 23
41.1%

Length

2024-01-29T02:59:49.585933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:59:49.673948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인증 33
58.9%
예비 23
41.1%

기업명
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-01-29T02:59:49.875846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length14
Mean length9.125
Min length3

Characters and Unicode

Total characters511
Distinct characters192
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row㈜가까이한마음 사회서비스센터
2nd row㈜인성드림
3rd row(사)한국근로 장애인진흥회
4th row㈜장애인 장학사업장
5th row㈜유정피싱
ValueCountFrequency (%)
주식회사 9
 
10.3%
협동조합 4
 
4.6%
사회적협동조합 2
 
2.3%
사단법인 2
 
2.3%
대책협의회 1
 
1.1%
미세먼지공해예방 1
 
1.1%
사람들 1
 
1.1%
우리동네 1
 
1.1%
㈜와이지에프 1
 
1.1%
㈜바라봄 1
 
1.1%
Other values (64) 64
73.6%
2024-01-29T02:59:50.219474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 32
 
6.3%
31
 
6.1%
사 22
 
4.3%
회 18
 
3.5%
주 15
 
2.9%
동 10
 
2.0%
스 10
 
2.0%
식 10
 
2.0%
인 9
 
1.8%
이 9
 
1.8%
Other values (182) 345
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 420
82.2%
Other Symbol 32
 
6.3%
Space Separator 31
 
6.1%
Uppercase Letter 11
 
2.2%
Close Punctuation 7
 
1.4%
Open Punctuation 6
 
1.2%
Lowercase Letter 2
 
0.4%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 22
 
5.2%
회 18
 
4.3%
주 15
 
3.6%
동 10
 
2.4%
스 10
 
2.4%
식 10
 
2.4%
인 9
 
2.1%
이 9
 
2.1%
협 9
 
2.1%
합 8
 
1.9%
Other values (165) 300
71.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
18.2%
T 2
18.2%
L 1
9.1%
O 1
9.1%
C 1
9.1%
I 1
9.1%
R 1
9.1%
A 1
9.1%
M 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
d 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 32
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 452
88.5%
Common 46
 
9.0%
Latin 13
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 32
 
7.1%
사 22
 
4.9%
회 18
 
4.0%
주 15
 
3.3%
동 10
 
2.2%
스 10
 
2.2%
식 10
 
2.2%
인 9
 
2.0%
이 9
 
2.0%
협 9
 
2.0%
Other values (166) 308
68.1%
Latin
ValueCountFrequency (%)
E 2
15.4%
T 2
15.4%
t 1
7.7%
d 1
7.7%
L 1
7.7%
O 1
7.7%
C 1
7.7%
I 1
7.7%
R 1
7.7%
A 1
7.7%
Common
ValueCountFrequency (%)
31
67.4%
) 7
 
15.2%
( 6
 
13.0%
, 1
 
2.2%
. 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 420
82.2%
ASCII 59
 
11.5%
None 32
 
6.3%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 32
100.0%
ASCII
ValueCountFrequency (%)
31
52.5%
) 7
 
11.9%
( 6
 
10.2%
E 2
 
3.4%
T 2
 
3.4%
t 1
 
1.7%
d 1
 
1.7%
L 1
 
1.7%
, 1
 
1.7%
. 1
 
1.7%
Other values (6) 6
 
10.2%
Hangul
ValueCountFrequency (%)
사 22
 
5.2%
회 18
 
4.3%
주 15
 
3.6%
동 10
 
2.4%
스 10
 
2.4%
식 10
 
2.4%
인 9
 
2.1%
이 9
 
2.1%
협 9
 
2.1%
합 8
 
1.9%
Other values (165) 300
71.4%

대표자
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-01-29T02:59:50.437669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.1071429
Min length2

Characters and Unicode

Total characters174
Distinct characters80
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

Unique56 ?
Unique (%)100.0%

Sample

1st row한태영
2nd row정영호
3rd row윤기상
4th row김재필
5th row전경옥+최범
ValueCountFrequency (%)
한태영 1
 
1.8%
정영호 1
 
1.8%
안효진 1
 
1.8%
변영주 1
 
1.8%
박보민 1
 
1.8%
최홍열 1
 
1.8%
구혜은 1
 
1.8%
오현주 1
 
1.8%
김경욱 1
 
1.8%
김영구 1
 
1.8%
Other values (46) 46
82.1%
2024-01-29T02:59:50.775543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 10
 
5.7%
영 8
 
4.6%
정 6
 
3.4%
진 6
 
3.4%
윤 6
 
3.4%
호 5
 
2.9%
박 5
 
2.9%
임 5
 
2.9%
최 4
 
2.3%
경 4
 
2.3%
Other values (70) 115
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 172
98.9%
Math Symbol 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 10
 
5.8%
영 8
 
4.7%
정 6
 
3.5%
진 6
 
3.5%
윤 6
 
3.5%
호 5
 
2.9%
박 5
 
2.9%
임 5
 
2.9%
최 4
 
2.3%
경 4
 
2.3%
Other values (69) 113
65.7%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 172
98.9%
Common 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 10
 
5.8%
영 8
 
4.7%
정 6
 
3.5%
진 6
 
3.5%
윤 6
 
3.5%
호 5
 
2.9%
박 5
 
2.9%
임 5
 
2.9%
최 4
 
2.3%
경 4
 
2.3%
Other values (69) 113
65.7%
Common
ValueCountFrequency (%)
+ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 172
98.9%
ASCII 2
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 10
 
5.8%
영 8
 
4.7%
정 6
 
3.5%
진 6
 
3.5%
윤 6
 
3.5%
호 5
 
2.9%
박 5
 
2.9%
임 5
 
2.9%
최 4
 
2.3%
경 4
 
2.3%
Other values (69) 113
65.7%
ASCII
ValueCountFrequency (%)
+ 2
100.0%

주소
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-01-29T02:59:50.996584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length29.482143
Min length19

Characters and Unicode

Total characters1651
Distinct characters141
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)96.4%

Sample

1st row인천광역시 서구 길주로 63번길 25, 3층
2nd row인천광역시 서구 백범로 810번길 27
3rd row인천광역시 서구 원당대로 608번안길 9-18
4th row인천광역시 서구 서로3로 49(당하동, 인천검단LH 13단지)
5th row인천광역시 서구 염곡로 18(가좌동)
ValueCountFrequency (%)
인천광역시 56
 
18.0%
서구 56
 
18.0%
15 6
 
1.9%
염곡로 6
 
1.9%
염곡로464번길 5
 
1.6%
2층 4
 
1.3%
3층 4
 
1.3%
464번길 4
 
1.3%
미플존 3
 
1.0%
5 3
 
1.0%
Other values (141) 164
52.7%
2024-01-29T02:59:51.331851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
 
15.5%
1 78
 
4.7%
서 64
 
3.9%
천 60
 
3.6%
인 58
 
3.5%
구 57
 
3.5%
로 57
 
3.5%
시 56
 
3.4%
역 56
 
3.4%
광 56
 
3.4%
Other values (131) 853
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 914
55.4%
Decimal Number 352
 
21.3%
Space Separator 256
 
15.5%
Other Punctuation 46
 
2.8%
Open Punctuation 30
 
1.8%
Close Punctuation 30
 
1.8%
Dash Punctuation 17
 
1.0%
Uppercase Letter 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 64
 
7.0%
천 60
 
6.6%
인 58
 
6.3%
구 57
 
6.2%
로 57
 
6.2%
시 56
 
6.1%
역 56
 
6.1%
광 56
 
6.1%
동 37
 
4.0%
길 36
 
3.9%
Other values (111) 377
41.2%
Decimal Number
ValueCountFrequency (%)
1 78
22.2%
4 52
14.8%
2 46
13.1%
0 41
11.6%
8 32
9.1%
5 24
 
6.8%
6 24
 
6.8%
3 23
 
6.5%
9 17
 
4.8%
7 15
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
H 2
33.3%
L 2
33.3%
D 1
16.7%
A 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 45
97.8%
. 1
 
2.2%
Space Separator
ValueCountFrequency (%)
256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 914
55.4%
Common 731
44.3%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 64
 
7.0%
천 60
 
6.6%
인 58
 
6.3%
구 57
 
6.2%
로 57
 
6.2%
시 56
 
6.1%
역 56
 
6.1%
광 56
 
6.1%
동 37
 
4.0%
길 36
 
3.9%
Other values (111) 377
41.2%
Common
ValueCountFrequency (%)
256
35.0%
1 78
 
10.7%
4 52
 
7.1%
2 46
 
6.3%
, 45
 
6.2%
0 41
 
5.6%
8 32
 
4.4%
( 30
 
4.1%
) 30
 
4.1%
5 24
 
3.3%
Other values (6) 97
 
13.3%
Latin
ValueCountFrequency (%)
H 2
33.3%
L 2
33.3%
D 1
16.7%
A 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 914
55.4%
ASCII 737
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
34.7%
1 78
 
10.6%
4 52
 
7.1%
2 46
 
6.2%
, 45
 
6.1%
0 41
 
5.6%
8 32
 
4.3%
( 30
 
4.1%
) 30
 
4.1%
5 24
 
3.3%
Other values (10) 103
14.0%
Hangul
ValueCountFrequency (%)
서 64
 
7.0%
천 60
 
6.6%
인 58
 
6.3%
구 57
 
6.2%
로 57
 
6.2%
시 56
 
6.1%
역 56
 
6.1%
광 56
 
6.1%
동 37
 
4.0%
길 36
 
3.9%
Other values (111) 377
41.2%

연락처
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing33
Missing (%)58.9%
Memory size580.0 B
2024-01-29T02:59:51.514126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters276
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

Unique23 ?
Unique (%)100.0%

Sample

1st row032-584-4115
2nd row032-581-9369
3rd row032-435-8857
4th row032-330-5957
5th row032-574-7452
ValueCountFrequency (%)
032-584-4115 1
 
4.3%
032-577-1926 1
 
4.3%
032-577-0940 1
 
4.3%
032-574-7526 1
 
4.3%
032-832-0979 1
 
4.3%
032-565-5701 1
 
4.3%
032-434-9393 1
 
4.3%
032-572-8197 1
 
4.3%
032-568-1254 1
 
4.3%
032-566-1623 1
 
4.3%
Other values (13) 13
56.5%
2024-01-29T02:59:51.786172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 46
16.7%
3 42
15.2%
2 40
14.5%
0 32
11.6%
5 32
11.6%
7 20
7.2%
6 15
 
5.4%
4 14
 
5.1%
9 13
 
4.7%
8 12
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.3%
Dash Punctuation 46
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 42
18.3%
2 40
17.4%
0 32
13.9%
5 32
13.9%
7 20
8.7%
6 15
 
6.5%
4 14
 
6.1%
9 13
 
5.7%
8 12
 
5.2%
1 10
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 46
16.7%
3 42
15.2%
2 40
14.5%
0 32
11.6%
5 32
11.6%
7 20
7.2%
6 15
 
5.4%
4 14
 
5.1%
9 13
 
4.7%
8 12
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 46
16.7%
3 42
15.2%
2 40
14.5%
0 32
11.6%
5 32
11.6%
7 20
7.2%
6 15
 
5.4%
4 14
 
5.1%
9 13
 
4.7%
8 12
 
4.3%

사업내용
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-01-29T02:59:52.009341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length17.196429
Min length4

Characters and Unicode

Total characters963
Distinct characters212
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

Unique54 ?
Unique (%)96.4%

Sample

1st row재가장기요양, 노인돌봄
2nd row의료세탁물위탁처리
3rd row복사용지생산 및 판매
4th row건강식품 제조 및 화장지 도.소매
5th row낚싯대 제조 및 판매
ValueCountFrequency (%)
및 25
 
10.8%
제조 9
 
3.9%
판매 8
 
3.5%
등 7
 
3.0%
운영 4
 
1.7%
제조업 4
 
1.7%
강의 3
 
1.3%
컨설팅 3
 
1.3%
개발 3
 
1.3%
교육 3
 
1.3%
Other values (144) 162
70.1%
2024-01-29T02:59:52.360054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
 
18.2%
, 45
 
4.7%
제 30
 
3.1%
및 25
 
2.6%
업 23
 
2.4%
조 19
 
2.0%
매 15
 
1.6%
기 14
 
1.5%
스 13
 
1.3%
판 13
 
1.3%
Other values (202) 591
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 725
75.3%
Space Separator 175
 
18.2%
Other Punctuation 47
 
4.9%
Uppercase Letter 6
 
0.6%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 30
 
4.1%
및 25
 
3.4%
업 23
 
3.2%
조 19
 
2.6%
매 15
 
2.1%
기 14
 
1.9%
스 13
 
1.8%
판 13
 
1.8%
교 12
 
1.7%
가 12
 
1.7%
Other values (193) 549
75.7%
Other Punctuation
ValueCountFrequency (%)
, 45
95.7%
· 1
 
2.1%
. 1
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
L 2
33.3%
D 2
33.3%
E 2
33.3%
Space Separator
ValueCountFrequency (%)
175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 725
75.3%
Common 232
 
24.1%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 30
 
4.1%
및 25
 
3.4%
업 23
 
3.2%
조 19
 
2.6%
매 15
 
2.1%
기 14
 
1.9%
스 13
 
1.8%
판 13
 
1.8%
교 12
 
1.7%
가 12
 
1.7%
Other values (193) 549
75.7%
Common
ValueCountFrequency (%)
175
75.4%
, 45
 
19.4%
) 5
 
2.2%
( 5
 
2.2%
· 1
 
0.4%
. 1
 
0.4%
Latin
ValueCountFrequency (%)
L 2
33.3%
D 2
33.3%
E 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 725
75.3%
ASCII 237
 
24.6%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
73.8%
, 45
 
19.0%
) 5
 
2.1%
( 5
 
2.1%
L 2
 
0.8%
D 2
 
0.8%
E 2
 
0.8%
. 1
 
0.4%
Hangul
ValueCountFrequency (%)
제 30
 
4.1%
및 25
 
3.4%
업 23
 
3.2%
조 19
 
2.6%
매 15
 
2.1%
기 14
 
1.9%
스 13
 
1.8%
판 13
 
1.8%
교 12
 
1.7%
가 12
 
1.7%
Other values (193) 549
75.7%
None
ValueCountFrequency (%)
· 1
100.0%

Interactions

2024-01-29T02:59:49.077653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:59:52.460835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분기업명대표자주소연락처사업내용
연번1.0000.9981.0001.0001.0001.0001.000
구분0.9981.0001.0001.0001.0001.0001.000
기업명1.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0000.999
연락처1.0001.0001.0001.0001.0001.0001.000
사업내용1.0001.0001.0001.0000.9991.0001.000
2024-01-29T02:59:52.563062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분
연번1.0000.888
구분0.8881.000

Missing values

2024-01-29T02:59:49.176011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:59:49.274814image/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

연번구분기업명대표자주소연락처사업내용
01인증㈜가까이한마음 사회서비스센터한태영인천광역시 서구 길주로 63번길 25, 3층032-584-4115재가장기요양, 노인돌봄
12인증㈜인성드림정영호인천광역시 서구 백범로 810번길 27032-581-9369의료세탁물위탁처리
23인증(사)한국근로 장애인진흥회윤기상인천광역시 서구 원당대로 608번안길 9-18032-435-8857복사용지생산 및 판매
34인증㈜장애인 장학사업장김재필인천광역시 서구 서로3로 49(당하동, 인천검단LH 13단지)032-330-5957건강식품 제조 및 화장지 도.소매
45인증㈜유정피싱전경옥+최범인천광역시 서구 염곡로 18(가좌동)032-574-7452낚싯대 제조 및 판매
56인증사단법인 한국복지나눔(㈜씨드)박태성인천광역시 서구 서곶로315번길 15-1, 303,304호(심곡동)032-433-6973LED 사업 (가로등, 바닥신호등, 조명기구 등) 카페 교육사업
67인증㈜씨케이 크린앤환경김봉환인천광역시 서구 검단로 516 보현빌딩 308032-562-0233청소업 및 위생관리용역업
78인증예일종합목재㈜안윤호인천광역시 서구 북항로178번길 4032-589-2813목재 제조업
89인증뉴라이프재단임헌영인천광역시 서구 심곡로 86, A동 2층<NA>세탁공장, 커피판매점
910인증케일㈜김태신인천광역시 서구 가정로394번길 4, 2층(가정동)<NA>자동문,지하철안전문, 아파트홈네트워크 LED 조명 제조설치
연번구분기업명대표자주소연락처사업내용
4647예비공간사랑 협동조합홍상철인천광역시 서구 서달로137번길 12-7(석남동)<NA>그린리모델링, 태양광 설치, 집수리 등
4748예비미래채움교육 협동조합지윤정인천광역시 서구 염곡로 464번길 15, 8층 802호<NA>융합코딩 수업, 아트코딩교구 판매 및 강의, 디지털교실 운영
4849예비㈜한국스마트 치료협회허정문인천광역시 서구 보듬로158, 미플존 221호<NA>교육, 돌봄, 상담 등 전문가 연계 플래폼 구축
4950예비동네살이 협동조합백선희인천광역시 서구 연희로 14번길 10<NA>농수산물 유통
5051예비㈜라츄니여수진인천광역시 서구 보듬로 158 오류동 코코아 221호(블루텍, 미플존)<NA>친황경 요가제품 제조, 판매
5152예비㈜프린지이영근인천광역시 서구 보듬로 158 오류동 코코아 221호(블루텍, 미플존)<NA>플로깅 강의 및 프로그램 운영
5253예비해드림산업㈜이현경인천광역시 서구 염곡로 464번길 5, 809호032-567-7232플로깅 강의 및 프로그램 운영
5354예비주식회사 희망이룸연구소정문진인천광역시 서구 염곡로 464번길 5, 809호, 코워킹룸 12<NA>창업교육
5455예비㈜피플앤컬쳐유광훈인천광역시 서구 염곡로 311번길 18-1(석남동)<NA>커피 및 제과제빵교육
5556예비주식회사 에바댄스챌린지윤재훈인천광역시 서구 염곡로 464번길 15, 811호<NA>영상제작 및 배급, 이벤트 대행 및 기획, 공연기획 및 예술관련 서비스업