Overview

Dataset statistics

Number of variables8
Number of observations445
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.9 KiB
Average record size in memory64.3 B

Variable types

Categorical3
Text5

Dataset

Description야간보육어린이집현황201507
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202397

Alerts

2015 야간보육 어린이집 현황 is highly overall correlated with Unnamed: 3High correlation
Unnamed: 2 is highly overall correlated with Unnamed: 3High correlation
Unnamed: 3 is highly overall correlated with 2015 야간보육 어린이집 현황 and 1 other fieldsHigh correlation
Unnamed: 3 is highly imbalanced (82.6%)Imbalance

Reproduction

Analysis started2024-03-14 01:51:33.079326
Analysis finished2024-03-14 01:51:33.759700
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2015 야간보육 어린이집 현황
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
전주시 완산구
96 
익산시
95 
군산시
48 
남원시
47 
정읍시
40 
Other values (10)
119 

Length

Max length7
Median length3
Mean length4.2067416
Min length3

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row시군구
3rd row전주시 완산구
4th row전주시 완산구
5th row전주시 완산구

Common Values

ValueCountFrequency (%)
전주시 완산구 96
21.6%
익산시 95
21.3%
군산시 48
10.8%
남원시 47
10.6%
정읍시 40
9.0%
전주시 덕진구 38
 
8.5%
김제시 26
 
5.8%
완주군 26
 
5.8%
고창군 11
 
2.5%
부안군 8
 
1.8%
Other values (5) 10
 
2.2%

Length

2024-03-14T10:51:33.819256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 134
23.1%
완산구 96
16.6%
익산시 95
16.4%
군산시 48
 
8.3%
남원시 47
 
8.1%
정읍시 40
 
6.9%
덕진구 38
 
6.6%
김제시 26
 
4.5%
완주군 26
 
4.5%
고창군 11
 
1.9%
Other values (6) 18
 
3.1%

Unnamed: 1
Text

Distinct398
Distinct (%)89.6%
Missing1
Missing (%)0.2%
Memory size3.6 KiB
2024-03-14T10:51:33.985125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.4009009
Min length5

Characters and Unicode

Total characters3286
Distinct characters311
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)81.1%

Sample

1st row어린이집명
2nd row키즈클럽어린이집
3rd row상원어린이집
4th row중산어린이집
5th rowECG우미어린이집
ValueCountFrequency (%)
어린이집 22
 
4.7%
아이사랑어린이집 3
 
0.6%
아이들세상어린이집 3
 
0.6%
꼬마천사어린이집 3
 
0.6%
이화어린이집 3
 
0.6%
큰별어린이집 3
 
0.6%
솔로몬어린이집 3
 
0.6%
꿈나래어린이집 3
 
0.6%
해바라기어린이집 3
 
0.6%
자람터어린이집 2
 
0.4%
Other values (392) 421
89.8%
2024-03-14T10:51:34.264914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 502
15.3%
린 447
 
13.6%
어 447
 
13.6%
집 444
 
13.5%
아 62
 
1.9%
나 36
 
1.1%
사 36
 
1.1%
마 32
 
1.0%
랑 30
 
0.9%
가 30
 
0.9%
Other values (301) 1220
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3248
98.8%
Space Separator 25
 
0.8%
Uppercase Letter 9
 
0.3%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 502
15.5%
린 447
 
13.8%
어 447
 
13.8%
집 444
 
13.7%
아 62
 
1.9%
나 36
 
1.1%
사 36
 
1.1%
마 32
 
1.0%
랑 30
 
0.9%
가 30
 
0.9%
Other values (291) 1182
36.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
22.2%
C 2
22.2%
G 1
11.1%
A 1
11.1%
Q 1
11.1%
B 1
11.1%
Y 1
11.1%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3248
98.8%
Common 29
 
0.9%
Latin 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 502
15.5%
린 447
 
13.8%
어 447
 
13.8%
집 444
 
13.7%
아 62
 
1.9%
나 36
 
1.1%
사 36
 
1.1%
마 32
 
1.0%
랑 30
 
0.9%
가 30
 
0.9%
Other values (291) 1182
36.4%
Latin
ValueCountFrequency (%)
E 2
22.2%
C 2
22.2%
G 1
11.1%
A 1
11.1%
Q 1
11.1%
B 1
11.1%
Y 1
11.1%
Common
ValueCountFrequency (%)
25
86.2%
4 2
 
6.9%
2 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3248
98.8%
ASCII 38
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 502
15.5%
린 447
 
13.8%
어 447
 
13.8%
집 444
 
13.7%
아 62
 
1.9%
나 36
 
1.1%
사 36
 
1.1%
마 32
 
1.0%
랑 30
 
0.9%
가 30
 
0.9%
Other values (291) 1182
36.4%
ASCII
ValueCountFrequency (%)
25
65.8%
4 2
 
5.3%
2 2
 
5.3%
E 2
 
5.3%
C 2
 
5.3%
G 1
 
2.6%
A 1
 
2.6%
Q 1
 
2.6%
B 1
 
2.6%
Y 1
 
2.6%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
가정
229 
민간
120 
국공립
34 
사회복지법인
33 
법인·단체등
26 
Other values (3)
 
3

Length

Max length6
Median length2
Mean length2.6202247
Min length2

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row어린이집유형
3rd row가정
4th row사회복지법인
5th row사회복지법인

Common Values

ValueCountFrequency (%)
가정 229
51.5%
민간 120
27.0%
국공립 34
 
7.6%
사회복지법인 33
 
7.4%
법인·단체등 26
 
5.8%
<NA> 1
 
0.2%
어린이집유형 1
 
0.2%
직장 1
 
0.2%

Length

2024-03-14T10:51:34.424758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:51:34.556137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가정 229
51.5%
민간 120
27.0%
국공립 34
 
7.6%
사회복지법인 33
 
7.4%
법인·단체등 26
 
5.8%
na 1
 
0.2%
어린이집유형 1
 
0.2%
직장 1
 
0.2%

Unnamed: 3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Y
419 
N
 
24
<NA>
 
1
평가인증여부
 
1

Length

Max length6
Median length1
Mean length1.0179775
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row평가인증여부
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
Y 419
94.2%
N 24
 
5.4%
<NA> 1
 
0.2%
평가인증여부 1
 
0.2%

Length

2024-03-14T10:51:34.667827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:51:34.754229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 419
94.2%
n 24
 
5.4%
na 1
 
0.2%
평가인증여부 1
 
0.2%

Unnamed: 4
Text

Distinct102
Distinct (%)23.0%
Missing1
Missing (%)0.2%
Memory size3.6 KiB
2024-03-14T10:51:34.939830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.0675676
Min length2

Characters and Unicode

Total characters918
Distinct characters13
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

Unique41 ?
Unique (%)9.2%

Sample

1st row정원수
2nd row19
3rd row66
4th row157
5th row32
ValueCountFrequency (%)
20 89
20.0%
19 58
 
13.1%
13 24
 
5.4%
99 17
 
3.8%
17 12
 
2.7%
16 11
 
2.5%
14 9
 
2.0%
11 8
 
1.8%
39 8
 
1.8%
18 8
 
1.8%
Other values (92) 200
45.0%
2024-03-14T10:51:35.254718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 197
21.5%
9 152
16.6%
2 129
14.1%
0 125
13.6%
3 69
 
7.5%
4 53
 
5.8%
7 52
 
5.7%
6 52
 
5.7%
8 49
 
5.3%
5 37
 
4.0%
Other values (3) 3
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 915
99.7%
Other Letter 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 197
21.5%
9 152
16.6%
2 129
14.1%
0 125
13.7%
3 69
 
7.5%
4 53
 
5.8%
7 52
 
5.7%
6 52
 
5.7%
8 49
 
5.4%
5 37
 
4.0%
Other Letter
ValueCountFrequency (%)
정 1
33.3%
원 1
33.3%
수 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 915
99.7%
Hangul 3
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 197
21.5%
9 152
16.6%
2 129
14.1%
0 125
13.7%
3 69
 
7.5%
4 53
 
5.8%
7 52
 
5.7%
6 52
 
5.7%
8 49
 
5.4%
5 37
 
4.0%
Hangul
ValueCountFrequency (%)
정 1
33.3%
원 1
33.3%
수 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 915
99.7%
Hangul 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 197
21.5%
9 152
16.6%
2 129
14.1%
0 125
13.7%
3 69
 
7.5%
4 53
 
5.8%
7 52
 
5.7%
6 52
 
5.7%
8 49
 
5.4%
5 37
 
4.0%
Hangul
ValueCountFrequency (%)
정 1
33.3%
원 1
33.3%
수 1
33.3%

Unnamed: 5
Text

Distinct102
Distinct (%)23.0%
Missing1
Missing (%)0.2%
Memory size3.6 KiB
2024-03-14T10:51:35.507456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.9234234
Min length1

Characters and Unicode

Total characters854
Distinct characters13
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

Unique33 ?
Unique (%)7.4%

Sample

1st row현원수
2nd row13
3rd row66
4th row76
5th row20
ValueCountFrequency (%)
20 24
 
5.4%
13 23
 
5.2%
19 21
 
4.7%
11 20
 
4.5%
12 20
 
4.5%
18 18
 
4.1%
16 18
 
4.1%
14 16
 
3.6%
15 15
 
3.4%
17 15
 
3.4%
Other values (92) 254
57.2%
2024-03-14T10:51:35.863760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 225
26.3%
2 89
 
10.4%
3 82
 
9.6%
6 76
 
8.9%
4 71
 
8.3%
5 67
 
7.8%
0 64
 
7.5%
9 61
 
7.1%
7 61
 
7.1%
8 55
 
6.4%
Other values (3) 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 851
99.6%
Other Letter 3
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 225
26.4%
2 89
 
10.5%
3 82
 
9.6%
6 76
 
8.9%
4 71
 
8.3%
5 67
 
7.9%
0 64
 
7.5%
9 61
 
7.2%
7 61
 
7.2%
8 55
 
6.5%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
수 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 851
99.6%
Hangul 3
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 225
26.4%
2 89
 
10.5%
3 82
 
9.6%
6 76
 
8.9%
4 71
 
8.3%
5 67
 
7.9%
0 64
 
7.5%
9 61
 
7.2%
7 61
 
7.2%
8 55
 
6.5%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
수 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 851
99.6%
Hangul 3
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 225
26.4%
2 89
 
10.5%
3 82
 
9.6%
6 76
 
8.9%
4 71
 
8.3%
5 67
 
7.9%
0 64
 
7.5%
9 61
 
7.2%
7 61
 
7.2%
8 55
 
6.5%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
수 1
33.3%

Unnamed: 6
Text

Distinct444
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size3.6 KiB
2024-03-14T10:51:36.071055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.986486
Min length4

Characters and Unicode

Total characters5322
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique444 ?
Unique (%)100.0%

Sample

1st row전화번호
2nd row063-255-8380
3rd row063-253-3138
4th row063-283-6667
5th row063-228-1834
ValueCountFrequency (%)
063-228-6111 1
 
0.2%
063-533-1912 1
 
0.2%
063-533-6255 1
 
0.2%
063-538-2091 1
 
0.2%
063-537-2031 1
 
0.2%
063-532-7428 1
 
0.2%
063-537-2735 1
 
0.2%
063-536-8765 1
 
0.2%
063-538-0224 1
 
0.2%
063-535-8889 1
 
0.2%
Other values (434) 434
97.7%
2024-03-14T10:51:36.363911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 886
16.6%
3 825
15.5%
6 758
14.2%
0 683
12.8%
2 487
9.2%
5 405
7.6%
8 300
 
5.6%
4 293
 
5.5%
1 278
 
5.2%
7 235
 
4.4%
Other values (5) 172
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4432
83.3%
Dash Punctuation 886
 
16.6%
Other Letter 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 825
18.6%
6 758
17.1%
0 683
15.4%
2 487
11.0%
5 405
9.1%
8 300
 
6.8%
4 293
 
6.6%
1 278
 
6.3%
7 235
 
5.3%
9 168
 
3.8%
Other Letter
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 886
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5318
99.9%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 886
16.7%
3 825
15.5%
6 758
14.3%
0 683
12.8%
2 487
9.2%
5 405
7.6%
8 300
 
5.6%
4 293
 
5.5%
1 278
 
5.2%
7 235
 
4.4%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5318
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 886
16.7%
3 825
15.5%
6 758
14.3%
0 683
12.8%
2 487
9.2%
5 405
7.6%
8 300
 
5.6%
4 293
 
5.5%
1 278
 
5.2%
7 235
 
4.4%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 7
Text

Distinct389
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-03-14T10:51:36.705240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length19.096629
Min length2

Characters and Unicode

Total characters8498
Distinct characters234
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)78.0%

Sample

1st row2015.07.31 기준
2nd row주소
3rd row전라북도 전주시 완산구 당산로 43
4th row전라북도 전주시 완산구 천잠로 545-7
5th row전라북도 전주시 완산구 서원로 334
ValueCountFrequency (%)
전라북도 443
22.0%
전주시 134
 
6.7%
완산구 96
 
4.8%
익산시 95
 
4.7%
군산시 48
 
2.4%
남원시 47
 
2.3%
정읍시 40
 
2.0%
덕진구 38
 
1.9%
김제시 26
 
1.3%
완주군 26
 
1.3%
Other values (608) 1022
50.7%
2024-03-14T10:51:37.114942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1571
18.5%
전 583
 
6.9%
도 457
 
5.4%
북 454
 
5.3%
라 443
 
5.2%
시 394
 
4.6%
1 336
 
4.0%
산 287
 
3.4%
로 279
 
3.3%
2 233
 
2.7%
Other values (224) 3461
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5393
63.5%
Space Separator 1571
 
18.5%
Decimal Number 1418
 
16.7%
Dash Punctuation 114
 
1.3%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 583
 
10.8%
도 457
 
8.5%
북 454
 
8.4%
라 443
 
8.2%
시 394
 
7.3%
산 287
 
5.3%
로 279
 
5.2%
길 221
 
4.1%
주 171
 
3.2%
구 137
 
2.5%
Other values (211) 1967
36.5%
Decimal Number
ValueCountFrequency (%)
1 336
23.7%
2 233
16.4%
3 180
12.7%
5 119
 
8.4%
0 105
 
7.4%
4 105
 
7.4%
9 97
 
6.8%
6 90
 
6.3%
7 83
 
5.9%
8 70
 
4.9%
Space Separator
ValueCountFrequency (%)
1571
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5393
63.5%
Common 3105
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 583
 
10.8%
도 457
 
8.5%
북 454
 
8.4%
라 443
 
8.2%
시 394
 
7.3%
산 287
 
5.3%
로 279
 
5.2%
길 221
 
4.1%
주 171
 
3.2%
구 137
 
2.5%
Other values (211) 1967
36.5%
Common
ValueCountFrequency (%)
1571
50.6%
1 336
 
10.8%
2 233
 
7.5%
3 180
 
5.8%
5 119
 
3.8%
- 114
 
3.7%
0 105
 
3.4%
4 105
 
3.4%
9 97
 
3.1%
6 90
 
2.9%
Other values (3) 155
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5393
63.5%
ASCII 3105
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1571
50.6%
1 336
 
10.8%
2 233
 
7.5%
3 180
 
5.8%
5 119
 
3.8%
- 114
 
3.7%
0 105
 
3.4%
4 105
 
3.4%
9 97
 
3.1%
6 90
 
2.9%
Other values (3) 155
 
5.0%
Hangul
ValueCountFrequency (%)
전 583
 
10.8%
도 457
 
8.5%
북 454
 
8.4%
라 443
 
8.2%
시 394
 
7.3%
산 287
 
5.3%
로 279
 
5.2%
길 221
 
4.1%
주 171
 
3.2%
구 137
 
2.5%
Other values (211) 1967
36.5%

Correlations

2024-03-14T10:51:37.202277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2015 야간보육 어린이집 현황Unnamed: 2Unnamed: 3
2015 야간보육 어린이집 현황1.0000.8030.848
Unnamed: 20.8031.0000.768
Unnamed: 30.8480.7681.000
2024-03-14T10:51:37.300457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2015 야간보육 어린이집 현황Unnamed: 2Unnamed: 3
2015 야간보육 어린이집 현황1.0000.4290.710
Unnamed: 20.4291.0000.704
Unnamed: 30.7100.7041.000
2024-03-14T10:51:37.372337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2015 야간보육 어린이집 현황Unnamed: 2Unnamed: 3
2015 야간보육 어린이집 현황1.0000.4290.710
Unnamed: 20.4291.0000.704
Unnamed: 30.7100.7041.000

Missing values

2024-03-14T10:51:33.456792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:51:33.565166image/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.
2024-03-14T10:51:33.691167image/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

2015 야간보육 어린이집 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0<NA><NA><NA><NA><NA><NA><NA>2015.07.31 기준
1시군구어린이집명어린이집유형평가인증여부정원수현원수전화번호주소
2전주시 완산구키즈클럽어린이집가정Y1913063-255-8380전라북도 전주시 완산구 당산로 43
3전주시 완산구상원어린이집사회복지법인Y6666063-253-3138전라북도 전주시 완산구 천잠로 545-7
4전주시 완산구중산어린이집사회복지법인Y15776063-283-6667전라북도 전주시 완산구 서원로 334
5전주시 완산구ECG우미어린이집민간Y3220063-228-1834전라북도 전주시 완산구 모악로 4685
6전주시 완산구신동어린이집민간Y9939063-237-0022전라북도 전주시 완산구 맏내로 158-11
7전주시 완산구빛나라어린이집민간Y3111063-227-0801전라북도 전주시 완산구 중산9길 7-5
8전주시 완산구미래어린이집민간Y5542063-271-5330전라북도 전주시 완산구 서신천변1길 16
9전주시 완산구우람어린이집사회복지법인Y7710063-222-1144전라북도 전주시 완산구 구이로 2041-1
2015 야간보육 어린이집 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
435고창군아이세상어린이집사회복지법인Y6663063-564-5240전라북도 고창군 고창읍 동리로 126-9
436고창군고창보듬이나눔이어린이집국공립Y9978063-564-0506전라북도 고창군 고창읍 월곡뉴타운2길 20
437부안군백산교회부설샬롬어린이집법인·단체등Y5530063-581-1513전라북도 부안군 백산면 시기길 18
438부안군하늘숲어린이집민간Y9791063-581-5599전라북도 부안군 부안읍 선은2길 2-1
439부안군아기별어린이집가정Y2019063-584-0579전라북도 부안군 부안읍 부풍로 26
440부안군하얀어린이집가정Y2020063-582-2777전라북도 부안군 부안읍 오리정로 172 하이안아파트 101동 109호
441부안군해랑어린이집민간Y10967063-582-2879전라북도 부안군 변산면 격포윗길 7
442부안군언덕위어린이집민간Y8376063-581-2595전라북도 부안군 부안읍 석정로 49-6
443부안군자연보물어린이집국공립Y6765063-584-8778전라북도 부안군 부안읍 봉두길 52
444부안군함께하는어린이집민간Y2323063-582-0391전라북도 부안군 백산면 임현로 8