Overview

Dataset statistics

Number of variables9
Number of observations130
Missing cells222
Missing cells (%)19.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory74.0 B

Variable types

Numeric1
Categorical2
Text5
DateTime1

Dataset

Description인천광역시 부평구 직업소개소의 명칭, 소재지, 전화번호 데이터입니다.ex) 행복공인중개사사무소,김길자,대표,032-508-2455,인천광역시 부평구 경인로 959(부평동),2021-09-28
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3080299&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 유료/무료High correlation
유료/무료 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
운영 is highly overall correlated with 유료/무료High correlation
유료/무료 is highly imbalanced (66.6%)Imbalance
운영 is highly imbalanced (50.4%)Imbalance
등록일자 has 6 (4.6%) missing valuesMissing
전화번호 has 37 (28.5%) missing valuesMissing
fax has 52 (40.0%) missing valuesMissing
비 고 has 127 (97.7%) missing valuesMissing
연번 has unique valuesUnique
직업소개소 명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 15:26:39.670761
Analysis finished2024-01-28 15:26:40.495090
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.5
Minimum1
Maximum130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-29T00:26:40.554894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.45
Q133.25
median65.5
Q397.75
95-th percentile123.55
Maximum130
Range129
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation37.671829
Coefficient of variation (CV)0.57514242
Kurtosis-1.2
Mean65.5
Median Absolute Deviation (MAD)32.5
Skewness0
Sum8515
Variance1419.1667
MonotonicityStrictly increasing
2024-01-29T00:26:40.675996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
99 1
 
0.8%
97 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
Other values (120) 120
92.3%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%

유료/무료
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
유료
122 
무료
 
8

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 122
93.8%
무료 8
 
6.2%

Length

2024-01-29T00:26:40.788575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:26:40.861808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 122
93.8%
무료 8
 
6.2%

운영
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
개인
108 
법인
17 
<NA>
 
5

Length

Max length4
Median length2
Mean length2.0769231
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 108
83.1%
법인 17
 
13.1%
<NA> 5
 
3.8%

Length

2024-01-29T00:26:40.949021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:26:41.037956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 108
83.1%
법인 17
 
13.1%
na 5
 
3.8%

직업소개소 명
Text

UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-29T00:26:41.198972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length7.1769231
Min length2

Characters and Unicode

Total characters933
Distinct characters202
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)100.0%

Sample

1st row갈산인력
2nd row거금인력
3rd row건우인력개발
4th row경인건축인력
5th row경인인력개발공사
ValueCountFrequency (%)
무료직업소개소 4
 
2.6%
에스엠파워 3
 
2.0%
㈜현대인력개발 3
 
2.0%
금화인력 2
 
1.3%
만나파출직업소개소 2
 
1.3%
일터와사람들 2
 
1.3%
사회적협동조합 2
 
1.3%
동부직업소개소 2
 
1.3%
㈜상록건축인력 2
 
1.3%
㈜하이엔드코리아 1
 
0.7%
Other values (128) 128
84.8%
2024-01-29T00:26:41.505275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 91
 
9.8%
력 77
 
8.3%
소 48
 
5.1%
개 42
 
4.5%
업 28
 
3.0%
직 22
 
2.4%
21
 
2.3%
발 20
 
2.1%
사 17
 
1.8%
동 15
 
1.6%
Other values (192) 552
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 889
95.3%
Space Separator 21
 
2.3%
Other Symbol 9
 
1.0%
Open Punctuation 7
 
0.8%
Close Punctuation 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 91
 
10.2%
력 77
 
8.7%
소 48
 
5.4%
개 42
 
4.7%
업 28
 
3.1%
직 22
 
2.5%
발 20
 
2.2%
사 17
 
1.9%
동 15
 
1.7%
파 14
 
1.6%
Other values (188) 515
57.9%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 898
96.2%
Common 35
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 91
 
10.1%
력 77
 
8.6%
소 48
 
5.3%
개 42
 
4.7%
업 28
 
3.1%
직 22
 
2.4%
발 20
 
2.2%
사 17
 
1.9%
동 15
 
1.7%
파 14
 
1.6%
Other values (189) 524
58.4%
Common
ValueCountFrequency (%)
21
60.0%
( 7
 
20.0%
) 7
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 889
95.3%
ASCII 35
 
3.8%
None 9
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 91
 
10.2%
력 77
 
8.7%
소 48
 
5.4%
개 42
 
4.7%
업 28
 
3.1%
직 22
 
2.5%
발 20
 
2.2%
사 17
 
1.9%
동 15
 
1.7%
파 14
 
1.6%
Other values (188) 515
57.9%
ASCII
ValueCountFrequency (%)
21
60.0%
( 7
 
20.0%
) 7
 
20.0%
None
ValueCountFrequency (%)
㈜ 9
100.0%

등록일자
Date

MISSING 

Distinct117
Distinct (%)94.4%
Missing6
Missing (%)4.6%
Memory size1.1 KiB
Minimum1993-03-19 00:00:00
Maximum2020-08-05 00:00:00
2024-01-29T00:26:41.621758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:26:41.723870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct92
Distinct (%)98.9%
Missing37
Missing (%)28.5%
Memory size1.1 KiB
2024-01-29T00:26:41.925091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021505
Min length12

Characters and Unicode

Total characters1118
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

Unique91 ?
Unique (%)97.8%

Sample

1st row032-523-6492
2nd row032-528-0001
3rd row032-205-0333
4th row032-425-1233
5th row032-521-1282
ValueCountFrequency (%)
032-469-3575 2
 
2.2%
032-362-2811 1
 
1.1%
032-523-6492 1
 
1.1%
032-421-2231 1
 
1.1%
032-422-2159 1
 
1.1%
032-438-1415 1
 
1.1%
032-429-0644 1
 
1.1%
032-529-1882 1
 
1.1%
032-269-8275 1
 
1.1%
032-526-0307 1
 
1.1%
Other values (82) 82
88.2%
2024-01-29T00:26:42.222118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 186
16.6%
0 179
16.0%
2 178
15.9%
3 158
14.1%
5 94
8.4%
1 94
8.4%
4 62
 
5.5%
8 57
 
5.1%
6 43
 
3.8%
7 35
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 932
83.4%
Dash Punctuation 186
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 179
19.2%
2 178
19.1%
3 158
17.0%
5 94
10.1%
1 94
10.1%
4 62
 
6.7%
8 57
 
6.1%
6 43
 
4.6%
7 35
 
3.8%
9 32
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1118
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 186
16.6%
0 179
16.0%
2 178
15.9%
3 158
14.1%
5 94
8.4%
1 94
8.4%
4 62
 
5.5%
8 57
 
5.1%
6 43
 
3.8%
7 35
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 186
16.6%
0 179
16.0%
2 178
15.9%
3 158
14.1%
5 94
8.4%
1 94
8.4%
4 62
 
5.5%
8 57
 
5.1%
6 43
 
3.8%
7 35
 
3.1%

fax
Text

MISSING 

Distinct77
Distinct (%)98.7%
Missing52
Missing (%)40.0%
Memory size1.1 KiB
2024-01-29T00:26:42.428071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.141026
Min length12

Characters and Unicode

Total characters947
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

Unique76 ?
Unique (%)97.4%

Sample

1st row050-4253-6492
2nd row032-772-9889
3rd row032-361-0333
4th row032-438-3555
5th row032-521-1283
ValueCountFrequency (%)
032-438-3555 2
 
2.6%
050-4316-2020 1
 
1.3%
050-4253-6492 1
 
1.3%
032-362-2810 1
 
1.3%
032-521-3420 1
 
1.3%
032-433-2827 1
 
1.3%
032-0952-4700 1
 
1.3%
032-429-4894 1
 
1.3%
032-518-1882 1
 
1.3%
032-299-8275 1
 
1.3%
Other values (67) 67
85.9%
2024-01-29T00:26:42.724373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 156
16.5%
0 153
16.2%
3 139
14.7%
2 137
14.5%
5 90
9.5%
1 68
7.2%
4 58
 
6.1%
8 48
 
5.1%
9 34
 
3.6%
7 33
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 791
83.5%
Dash Punctuation 156
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 153
19.3%
3 139
17.6%
2 137
17.3%
5 90
11.4%
1 68
8.6%
4 58
 
7.3%
8 48
 
6.1%
9 34
 
4.3%
7 33
 
4.2%
6 31
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 947
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 156
16.5%
0 153
16.2%
3 139
14.7%
2 137
14.5%
5 90
9.5%
1 68
7.2%
4 58
 
6.1%
8 48
 
5.1%
9 34
 
3.6%
7 33
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 947
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 156
16.5%
0 153
16.2%
3 139
14.7%
2 137
14.5%
5 90
9.5%
1 68
7.2%
4 58
 
6.1%
8 48
 
5.1%
9 34
 
3.6%
7 33
 
3.5%

소재지(도로명주소)
Text

Distinct129
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-29T00:26:42.951176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length30
Mean length24.107692
Min length14

Characters and Unicode

Total characters3134
Distinct characters181
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

Unique128 ?
Unique (%)98.5%

Sample

1st row부평구 주부토로 183, 501호(갈산동)
2nd row부평구 경인로1104번길 14-7 2층(부개동)
3rd row부평구 마장로 41(십정동, 2층)
4th row인천광역시 부평구 열우물로 43-1(4층, 십정1동)
5th row부평구 부평대로 74 (부평동)
ValueCountFrequency (%)
부평구 117
 
21.3%
부평대로 22
 
4.0%
경인로 12
 
2.2%
인천광역시 7
 
1.3%
열우물로 6
 
1.1%
마장로 6
 
1.1%
장제로 6
 
1.1%
3층(부평동 5
 
0.9%
4 4
 
0.7%
4층(부평동 4
 
0.7%
Other values (295) 361
65.6%
2024-01-29T00:26:43.278626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
420
 
13.4%
부 205
 
6.5%
평 196
 
6.3%
동 150
 
4.8%
로 133
 
4.2%
구 128
 
4.1%
) 127
 
4.1%
( 126
 
4.0%
, 106
 
3.4%
1 101
 
3.2%
Other values (171) 1442
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1736
55.4%
Decimal Number 592
 
18.9%
Space Separator 420
 
13.4%
Close Punctuation 127
 
4.1%
Open Punctuation 126
 
4.0%
Other Punctuation 106
 
3.4%
Dash Punctuation 21
 
0.7%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 205
 
11.8%
평 196
 
11.3%
동 150
 
8.6%
로 133
 
7.7%
구 128
 
7.4%
층 55
 
3.2%
정 48
 
2.8%
호 45
 
2.6%
십 40
 
2.3%
대 39
 
2.2%
Other values (150) 697
40.1%
Decimal Number
ValueCountFrequency (%)
1 101
17.1%
3 87
14.7%
2 86
14.5%
0 70
11.8%
4 65
11.0%
6 47
7.9%
7 40
 
6.8%
8 38
 
6.4%
5 33
 
5.6%
9 25
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
H 1
16.7%
Y 1
16.7%
O 1
16.7%
L 1
16.7%
A 1
16.7%
F 1
16.7%
Space Separator
ValueCountFrequency (%)
420
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Other Punctuation
ValueCountFrequency (%)
, 106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1736
55.4%
Common 1392
44.4%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 205
 
11.8%
평 196
 
11.3%
동 150
 
8.6%
로 133
 
7.7%
구 128
 
7.4%
층 55
 
3.2%
정 48
 
2.8%
호 45
 
2.6%
십 40
 
2.3%
대 39
 
2.2%
Other values (150) 697
40.1%
Common
ValueCountFrequency (%)
420
30.2%
) 127
 
9.1%
( 126
 
9.1%
, 106
 
7.6%
1 101
 
7.3%
3 87
 
6.2%
2 86
 
6.2%
0 70
 
5.0%
4 65
 
4.7%
6 47
 
3.4%
Other values (5) 157
 
11.3%
Latin
ValueCountFrequency (%)
H 1
16.7%
Y 1
16.7%
O 1
16.7%
L 1
16.7%
A 1
16.7%
F 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1736
55.4%
ASCII 1398
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
420
30.0%
) 127
 
9.1%
( 126
 
9.0%
, 106
 
7.6%
1 101
 
7.2%
3 87
 
6.2%
2 86
 
6.2%
0 70
 
5.0%
4 65
 
4.6%
6 47
 
3.4%
Other values (11) 163
 
11.7%
Hangul
ValueCountFrequency (%)
부 205
 
11.8%
평 196
 
11.3%
동 150
 
8.6%
로 133
 
7.7%
구 128
 
7.4%
층 55
 
3.2%
정 48
 
2.8%
호 45
 
2.6%
십 40
 
2.3%
대 39
 
2.2%
Other values (150) 697
40.1%

비 고
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing127
Missing (%)97.7%
Memory size1.1 KiB
2024-01-29T00:26:43.395479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length6
Mean length8.3333333
Min length6

Characters and Unicode

Total characters25
Distinct characters14
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

Unique1 ?
Unique (%)33.3%

Sample

1st row해피케어직업소개소 이메일
2nd row이메일 오류
3rd row이메일 오류
ValueCountFrequency (%)
이메일 3
50.0%
오류 2
33.3%
해피케어직업소개소 1
 
16.7%
2024-01-29T00:26:43.599938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 3
12.0%
메 3
12.0%
일 3
12.0%
3
12.0%
오 2
8.0%
류 2
8.0%
소 2
8.0%
해 1
 
4.0%
피 1
 
4.0%
케 1
 
4.0%
Other values (4) 4
16.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
88.0%
Space Separator 3
 
12.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3
13.6%
메 3
13.6%
일 3
13.6%
오 2
9.1%
류 2
9.1%
소 2
9.1%
해 1
 
4.5%
피 1
 
4.5%
케 1
 
4.5%
어 1
 
4.5%
Other values (3) 3
13.6%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
88.0%
Common 3
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3
13.6%
메 3
13.6%
일 3
13.6%
오 2
9.1%
류 2
9.1%
소 2
9.1%
해 1
 
4.5%
피 1
 
4.5%
케 1
 
4.5%
어 1
 
4.5%
Other values (3) 3
13.6%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
88.0%
ASCII 3
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 3
13.6%
메 3
13.6%
일 3
13.6%
오 2
9.1%
류 2
9.1%
소 2
9.1%
해 1
 
4.5%
피 1
 
4.5%
케 1
 
4.5%
어 1
 
4.5%
Other values (3) 3
13.6%
ASCII
ValueCountFrequency (%)
3
100.0%

Interactions

2024-01-29T00:26:40.112105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:26:43.673312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유료/무료운영전화번호fax비 고
연번1.0000.9080.5970.9391.0000.000
유료/무료0.9081.0000.7131.0001.000NaN
운영0.5970.7131.0000.0001.000NaN
전화번호0.9391.0000.0001.0001.000NaN
fax1.0001.0001.0001.0001.000NaN
비 고0.000NaNNaNNaNNaN1.000
2024-01-29T00:26:43.763412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영유료/무료
운영1.0000.505
유료/무료0.5051.000
2024-01-29T00:26:43.829004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유료/무료운영
연번1.0000.7240.446
유료/무료0.7241.0000.505
운영0.4460.5051.000

Missing values

2024-01-29T00:26:40.221730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:26:40.336663image/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.
2024-01-29T00:26:40.437089image/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

연번유료/무료운영직업소개소 명등록일자전화번호fax소재지(도로명주소)비 고
01유료개인갈산인력2019-05-03032-523-6492050-4253-6492부평구 주부토로 183, 501호(갈산동)<NA>
12유료개인거금인력2009-05-13032-528-0001032-772-9889부평구 경인로1104번길 14-7 2층(부개동)<NA>
23유료개인건우인력개발2007-03-02032-205-0333032-361-0333부평구 마장로 41(십정동, 2층)<NA>
34유료개인경인건축인력2016-12-13032-425-1233032-438-3555인천광역시 부평구 열우물로 43-1(4층, 십정1동)<NA>
45유료개인경인인력개발공사2010-05-12032-521-1282032-521-1283부평구 부평대로 74 (부평동)<NA>
56유료개인경인파출넷2006-02-07032-433-1133032-438-3555인천광역시 부평구 열우물로 43-1(4층, 십정1동)<NA>
67유료개인공영인력직업소개소2010-01-19032-423-3630032-423-3339부평구 동암남로 21, 2층(십정동)<NA>
78유료개인광장직업소개소2012-06-28032-431-9010032-431-9013부평구 동암남로4, 리치프라자 701호 (십정동)<NA>
89유료개인그린라이프2019-05-27<NA><NA>부평대로 158-1 3층 2호(부평동)<NA>
910유료개인그린종합건축인력개발2020-08-05<NA><NA>부평구 수변로85번길 2(부개동)<NA>
연번유료/무료운영직업소개소 명등록일자전화번호fax소재지(도로명주소)비 고
120121유료개인힘쎈인력2019-10-25032-442-1214070-4007-0138부평구 열우물로 36(십정동)<NA>
121122유료개인힘찬인력2002-06-20032-665-1800<NA>부평구 마장로 49, 비02호(십정동, 인천부평대주파크빌)<NA>
122123무료법인(사)인천여성노동자회 무료직업소개소2003-05-26032-524-8830032-5065-1318부평구 마장로 39-4 3층(십정동)<NA>
123124무료<NA>인천여성노동자회(부평자활센터)2014-10-15032-525-1982032-525-1052부평구 후정동로 6, 부평구자활센터 3층(삼산동)<NA>
124125무료법인(사)한국사회교육원(무료취업센터)2010-08-20032-362-4300<NA>부평구 부평대로 55, 9층(부평동, 국천빌딩)<NA>
125126무료법인(재)로이교육재단 중앙직업전문학교 무료직업소개소2015-01-05032-456-8080032-439-3957부평구 부평대로 147, LOY문화예술실용전문학교(부평동)<NA>
126127무료법인사회적협동조합 일터와사람들 무료직업소개소2015-01-12032-432-1986<NA>부평구 부평대로 59, 성창빌딩 6층(부평동)<NA>
127128무료<NA>사회적협동조합 일터와사람들 무료직업소개소(서구사무소)2015-10-20<NA><NA>서구 서곶로301번길 7, 6층(심곡동)<NA>
128129무료법인인천광역시여성가족재단 무료직업소개소2013-03-08032-511-3161032-511-3164부평구 길주로 539(갈산동)<NA>
129130무료법인전국건설노동자무료취업알선센터인천지부2002-10-16<NA><NA>부평구 대정로 80, 인천북부근로자종합복지관(부평동)<NA>