Overview

Dataset statistics

Number of variables8
Number of observations183
Missing cells10
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory65.7 B

Variable types

Categorical3
Text4
Numeric1

Dataset

Description전북특별자치도 시군별.관청별 모유수유실 설치 현황(시군구명, 소재기관명, 소재기관 주소, 시설 구분, 이용 대상, 기관 내 수유시설 위치 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/3081261/fileData.do

Alerts

시설 구분 is highly imbalanced (51.9%)Imbalance
기관 내 수유시설 위치 has 4 (2.2%) missing valuesMissing
비치 물품 has 6 (3.3%) missing valuesMissing
수유시설 면적(제곱미터) has 44 (24.0%) zerosZeros

Reproduction

Analysis started2024-03-15 00:57:42.801020
Analysis finished2024-03-15 00:57:44.757716
Duration1.96 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

Distinct14
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
전주시
93 
남원시
17 
익산시
15 
군산시
10 
고창군
 
8
Other values (9)
40 

Length

Max length4
Median length3
Mean length3.0273224
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 93
50.8%
남원시 17
 
9.3%
익산시 15
 
8.2%
군산시 10
 
5.5%
고창군 8
 
4.4%
정읍시 7
 
3.8%
순창군 7
 
3.8%
완주군 6
 
3.3%
김제시 5
 
2.7%
임실군 4
 
2.2%
Other values (4) 11
 
6.0%

Length

2024-03-15T09:57:44.901917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 93
50.8%
남원시 17
 
9.3%
익산시 15
 
8.2%
군산시 10
 
5.5%
고창군 8
 
4.4%
정읍시 7
 
3.8%
순창군 7
 
3.8%
완주군 6
 
3.3%
김제시 5
 
2.7%
임실군 4
 
2.2%
Other values (4) 11
 
6.0%

소재기관명
Text

Distinct181
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T09:57:45.883716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.0491803
Min length3

Characters and Unicode

Total characters1473
Distinct characters219
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)97.8%

Sample

1st row전북대학교
2nd row북전주세무서
3rd row전주시동물원
4th row팔복동주민센터
5th row조촌동주민센터
ValueCountFrequency (%)
보건소 4
 
1.9%
롯데마트 4
 
1.9%
홈플러스 4
 
1.9%
전주점 3
 
1.4%
휴게소 2
 
1.0%
행정복지센터 2
 
1.0%
육아종합지원센터 2
 
1.0%
남원점 2
 
1.0%
농업기술센터 2
 
1.0%
이마트 2
 
1.0%
Other values (181) 181
87.0%
2024-03-15T09:57:47.266783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 76
 
5.2%
관 55
 
3.7%
전 47
 
3.2%
터 41
 
2.8%
산 39
 
2.6%
센 39
 
2.6%
동 36
 
2.4%
민 35
 
2.4%
소 35
 
2.4%
서 34
 
2.3%
Other values (209) 1036
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1369
92.9%
Space Separator 30
 
2.0%
Open Punctuation 24
 
1.6%
Close Punctuation 24
 
1.6%
Decimal Number 19
 
1.3%
Uppercase Letter 6
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 76
 
5.6%
관 55
 
4.0%
전 47
 
3.4%
터 41
 
3.0%
산 39
 
2.8%
센 39
 
2.8%
동 36
 
2.6%
민 35
 
2.6%
소 35
 
2.6%
서 34
 
2.5%
Other values (195) 932
68.1%
Uppercase Letter
ValueCountFrequency (%)
J 1
16.7%
V 1
16.7%
T 1
16.7%
S 1
16.7%
B 1
16.7%
K 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 8
42.1%
2 7
36.8%
3 3
 
15.8%
5 1
 
5.3%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1369
92.9%
Common 98
 
6.7%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 76
 
5.6%
관 55
 
4.0%
전 47
 
3.4%
터 41
 
3.0%
산 39
 
2.8%
센 39
 
2.8%
동 36
 
2.6%
민 35
 
2.6%
소 35
 
2.6%
서 34
 
2.5%
Other values (195) 932
68.1%
Common
ValueCountFrequency (%)
30
30.6%
( 24
24.5%
) 24
24.5%
1 8
 
8.2%
2 7
 
7.1%
3 3
 
3.1%
5 1
 
1.0%
· 1
 
1.0%
Latin
ValueCountFrequency (%)
J 1
16.7%
V 1
16.7%
T 1
16.7%
S 1
16.7%
B 1
16.7%
K 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1369
92.9%
ASCII 103
 
7.0%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 76
 
5.6%
관 55
 
4.0%
전 47
 
3.4%
터 41
 
3.0%
산 39
 
2.8%
센 39
 
2.8%
동 36
 
2.6%
민 35
 
2.6%
소 35
 
2.6%
서 34
 
2.5%
Other values (195) 932
68.1%
ASCII
ValueCountFrequency (%)
30
29.1%
( 24
23.3%
) 24
23.3%
1 8
 
7.8%
2 7
 
6.8%
3 3
 
2.9%
J 1
 
1.0%
V 1
 
1.0%
T 1
 
1.0%
5 1
 
1.0%
Other values (3) 3
 
2.9%
None
ValueCountFrequency (%)
· 1
100.0%

소재기관 주소
Text

Distinct181
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T09:57:48.511428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length36
Mean length18.754098
Min length10

Characters and Unicode

Total characters3432
Distinct characters205
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

Unique179 ?
Unique (%)97.8%

Sample

1st row전북 전주시 덕진구 백제대로 567
2nd row전북 전주시 덕진구 벚꽃로 33
3rd row전북 전주시 덕진구 소리로 68
4th row전북 전주시 덕진구 신복5길 6
5th row전북 전주시 덕진구 쪽구름로 150
ValueCountFrequency (%)
전북 152
 
17.4%
전주시 92
 
10.6%
완산구 51
 
5.8%
덕진구 41
 
4.7%
전라북도 18
 
2.1%
남원시 17
 
1.9%
익산시 15
 
1.7%
군산시 10
 
1.1%
고창군 8
 
0.9%
순창군 7
 
0.8%
Other values (344) 461
52.9%
2024-03-15T09:57:50.202826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
692
20.2%
전 273
 
8.0%
북 177
 
5.2%
시 151
 
4.4%
로 132
 
3.8%
1 121
 
3.5%
주 114
 
3.3%
산 101
 
2.9%
구 98
 
2.9%
2 73
 
2.1%
Other values (195) 1500
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2153
62.7%
Space Separator 692
 
20.2%
Decimal Number 529
 
15.4%
Dash Punctuation 20
 
0.6%
Other Punctuation 13
 
0.4%
Close Punctuation 12
 
0.3%
Open Punctuation 12
 
0.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 273
 
12.7%
북 177
 
8.2%
시 151
 
7.0%
로 132
 
6.1%
주 114
 
5.3%
산 101
 
4.7%
구 98
 
4.6%
완 60
 
2.8%
길 51
 
2.4%
진 50
 
2.3%
Other values (178) 946
43.9%
Decimal Number
ValueCountFrequency (%)
1 121
22.9%
2 73
13.8%
3 58
11.0%
5 49
9.3%
4 49
9.3%
0 46
 
8.7%
7 39
 
7.4%
9 35
 
6.6%
6 33
 
6.2%
8 26
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 11
84.6%
. 2
 
15.4%
Space Separator
ValueCountFrequency (%)
692
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2153
62.7%
Common 1278
37.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 273
 
12.7%
북 177
 
8.2%
시 151
 
7.0%
로 132
 
6.1%
주 114
 
5.3%
산 101
 
4.7%
구 98
 
4.6%
완 60
 
2.8%
길 51
 
2.4%
진 50
 
2.3%
Other values (178) 946
43.9%
Common
ValueCountFrequency (%)
692
54.1%
1 121
 
9.5%
2 73
 
5.7%
3 58
 
4.5%
5 49
 
3.8%
4 49
 
3.8%
0 46
 
3.6%
7 39
 
3.1%
9 35
 
2.7%
6 33
 
2.6%
Other values (6) 83
 
6.5%
Latin
ValueCountFrequency (%)
E 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2153
62.7%
ASCII 1279
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
692
54.1%
1 121
 
9.5%
2 73
 
5.7%
3 58
 
4.5%
5 49
 
3.8%
4 49
 
3.8%
0 46
 
3.6%
7 39
 
3.0%
9 35
 
2.7%
6 33
 
2.6%
Other values (7) 84
 
6.6%
Hangul
ValueCountFrequency (%)
전 273
 
12.7%
북 177
 
8.2%
시 151
 
7.0%
로 132
 
6.1%
주 114
 
5.3%
산 101
 
4.7%
구 98
 
4.6%
완 60
 
2.8%
길 51
 
2.4%
진 50
 
2.3%
Other values (178) 946
43.9%

시설 구분
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
가족수유실
104 
모유수유실
72 
공공기관
 
3
공중(다중)시설
 
2
청사
 
1

Length

Max length8
Median length5
Mean length4.9945355
Min length2

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row모유수유실
2nd row모유수유실
3rd row가족수유실
4th row가족수유실
5th row가족수유실

Common Values

ValueCountFrequency (%)
가족수유실 104
56.8%
모유수유실 72
39.3%
공공기관 3
 
1.6%
공중(다중)시설 2
 
1.1%
청사 1
 
0.5%
교통시설 1
 
0.5%

Length

2024-03-15T09:57:50.651316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:57:51.048141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가족수유실 104
56.8%
모유수유실 72
39.3%
공공기관 3
 
1.6%
공중(다중)시설 2
 
1.1%
청사 1
 
0.5%
교통시설 1
 
0.5%

이용 대상
Categorical

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
외부인
100 
직원+외부인
69 
외부/직원용
12 
직원
 
2

Length

Max length6
Median length3
Mean length4.3169399
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row외부/직원용
2nd row외부/직원용
3rd row외부/직원용
4th row외부/직원용
5th row외부/직원용

Common Values

ValueCountFrequency (%)
외부인 100
54.6%
직원+외부인 69
37.7%
외부/직원용 12
 
6.6%
직원 2
 
1.1%

Length

2024-03-15T09:57:51.528631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:57:51.907632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외부인 100
54.6%
직원+외부인 69
37.7%
외부/직원용 12
 
6.6%
직원 2
 
1.1%

수유시설 면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct38
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.822896
Minimum0
Maximum52.9
Zeros44
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-03-15T09:57:52.487172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median9.9
Q316.5
95-th percentile26.4
Maximum52.9
Range52.9
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation9.5317933
Coefficient of variation (CV)0.88070634
Kurtosis2.1380038
Mean10.822896
Median Absolute Deviation (MAD)6.9
Skewness1.0509303
Sum1980.59
Variance90.855083
MonotonicityNot monotonic
2024-03-15T09:57:53.028886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.0 44
24.0%
13.2 23
12.6%
19.8 16
 
8.7%
6.6 16
 
8.7%
20.0 8
 
4.4%
26.4 7
 
3.8%
3.3 7
 
3.8%
15.0 6
 
3.3%
9.9 6
 
3.3%
23.1 6
 
3.3%
Other values (28) 44
24.0%
ValueCountFrequency (%)
0.0 44
24.0%
2.83 1
 
0.5%
3.0 2
 
1.1%
3.3 7
 
3.8%
3.6 1
 
0.5%
4.4 1
 
0.5%
5.0 4
 
2.2%
6.0 1
 
0.5%
6.21 1
 
0.5%
6.23 1
 
0.5%
ValueCountFrequency (%)
52.9 1
 
0.5%
49.6 1
 
0.5%
33.1 2
 
1.1%
31.0 1
 
0.5%
29.0 1
 
0.5%
26.4 7
3.8%
23.1 6
 
3.3%
20.0 8
4.4%
19.8 16
8.7%
18.7 1
 
0.5%

기관 내 수유시설 위치
Text

MISSING 

Distinct133
Distinct (%)74.3%
Missing4
Missing (%)2.2%
Memory size1.6 KiB
2024-03-15T09:57:54.095550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length10.832402
Min length4

Characters and Unicode

Total characters1939
Distinct characters171
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)63.1%

Sample

1st row 1층 지원과 앞
2nd row 동물원내 드림랜드 앞
3rd row 1층 회의실 내
4th row 1층 복지상담실 내
5th row 6층여직원휴게실 내
ValueCountFrequency (%)
1층 100
21.6%
내 57
 
12.3%
옆 34
 
7.3%
2층 21
 
4.5%
앞 13
 
2.8%
상담실 12
 
2.6%
수유실 10
 
2.2%
안쪽 9
 
1.9%
민원실 9
 
1.9%
어린이 7
 
1.5%
Other values (136) 191
41.3%
2024-03-15T09:57:55.416274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
658
33.9%
층 147
 
7.6%
1 115
 
5.9%
실 103
 
5.3%
내 84
 
4.3%
옆 40
 
2.1%
원 29
 
1.5%
2 26
 
1.3%
자 24
 
1.2%
장 23
 
1.2%
Other values (161) 690
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1119
57.7%
Space Separator 658
33.9%
Decimal Number 157
 
8.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 147
 
13.1%
실 103
 
9.2%
내 84
 
7.5%
옆 40
 
3.6%
원 29
 
2.6%
자 24
 
2.1%
장 23
 
2.1%
상 21
 
1.9%
담 21
 
1.9%
아 21
 
1.9%
Other values (149) 606
54.2%
Decimal Number
ValueCountFrequency (%)
1 115
73.2%
2 26
 
16.6%
3 6
 
3.8%
4 3
 
1.9%
0 2
 
1.3%
7 2
 
1.3%
6 2
 
1.3%
5 1
 
0.6%
Space Separator
ValueCountFrequency (%)
658
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1119
57.7%
Common 820
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 147
 
13.1%
실 103
 
9.2%
내 84
 
7.5%
옆 40
 
3.6%
원 29
 
2.6%
자 24
 
2.1%
장 23
 
2.1%
상 21
 
1.9%
담 21
 
1.9%
아 21
 
1.9%
Other values (149) 606
54.2%
Common
ValueCountFrequency (%)
658
80.2%
1 115
 
14.0%
2 26
 
3.2%
3 6
 
0.7%
4 3
 
0.4%
0 2
 
0.2%
7 2
 
0.2%
6 2
 
0.2%
) 2
 
0.2%
( 2
 
0.2%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1119
57.7%
ASCII 820
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
658
80.2%
1 115
 
14.0%
2 26
 
3.2%
3 6
 
0.7%
4 3
 
0.4%
0 2
 
0.2%
7 2
 
0.2%
6 2
 
0.2%
) 2
 
0.2%
( 2
 
0.2%
Other values (2) 2
 
0.2%
Hangul
ValueCountFrequency (%)
층 147
 
13.1%
실 103
 
9.2%
내 84
 
7.5%
옆 40
 
3.6%
원 29
 
2.6%
자 24
 
2.1%
장 23
 
2.1%
상 21
 
1.9%
담 21
 
1.9%
아 21
 
1.9%
Other values (149) 606
54.2%

비치 물품
Text

MISSING 

Distinct128
Distinct (%)72.3%
Missing6
Missing (%)3.3%
Memory size1.6 KiB
2024-03-15T09:57:56.274018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length34
Mean length15.446328
Min length4

Characters and Unicode

Total characters2734
Distinct characters125
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

Unique112 ?
Unique (%)63.3%

Sample

1st row 침대
2nd row 가림막/의자/테이블
3rd row 의자/테이블
4th row 쇼파/테이블
5th row 냉장고/수유쿠션/침대
ValueCountFrequency (%)
소파 62
 
16.0%
기저귀교환대 42
 
10.9%
테이블 41
 
10.6%
쇼파 13
 
3.4%
침대 12
 
3.1%
전자레인지 12
 
3.1%
등 10
 
2.6%
정수기 9
 
2.3%
아기침대 9
 
2.3%
싱크대 8
 
2.1%
Other values (116) 169
43.7%
2024-03-15T09:57:57.526860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
570
20.8%
/ 375
 
13.7%
파 134
 
4.9%
대 126
 
4.6%
기 121
 
4.4%
이 99
 
3.6%
테 92
 
3.4%
블 92
 
3.4%
소 85
 
3.1%
저 64
 
2.3%
Other values (115) 976
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1788
65.4%
Space Separator 570
 
20.8%
Other Punctuation 376
 
13.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 134
 
7.5%
대 126
 
7.0%
기 121
 
6.8%
이 99
 
5.5%
테 92
 
5.1%
블 92
 
5.1%
소 85
 
4.8%
저 64
 
3.6%
환 63
 
3.5%
교 63
 
3.5%
Other values (112) 849
47.5%
Other Punctuation
ValueCountFrequency (%)
/ 375
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
570
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1788
65.4%
Common 946
34.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 134
 
7.5%
대 126
 
7.0%
기 121
 
6.8%
이 99
 
5.5%
테 92
 
5.1%
블 92
 
5.1%
소 85
 
4.8%
저 64
 
3.6%
환 63
 
3.5%
교 63
 
3.5%
Other values (112) 849
47.5%
Common
ValueCountFrequency (%)
570
60.3%
/ 375
39.6%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1788
65.4%
ASCII 946
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
570
60.3%
/ 375
39.6%
. 1
 
0.1%
Hangul
ValueCountFrequency (%)
파 134
 
7.5%
대 126
 
7.0%
기 121
 
6.8%
이 99
 
5.5%
테 92
 
5.1%
블 92
 
5.1%
소 85
 
4.8%
저 64
 
3.6%
환 63
 
3.5%
교 63
 
3.5%
Other values (112) 849
47.5%

Interactions

2024-03-15T09:57:43.661165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:57:57.696425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명시설 구분이용 대상수유시설 면적(제곱미터)
시군구명1.0000.6780.5010.368
시설 구분0.6781.0000.3450.300
이용 대상0.5010.3451.0000.513
수유시설 면적(제곱미터)0.3680.3000.5131.000
2024-03-15T09:57:57.932404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명이용 대상시설 구분
시군구명1.0000.2970.407
이용 대상0.2971.0000.227
시설 구분0.4070.2271.000
2024-03-15T09:57:58.215151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수유시설 면적(제곱미터)시군구명시설 구분이용 대상
수유시설 면적(제곱미터)1.0000.1670.1700.246
시군구명0.1671.0000.4070.297
시설 구분0.1700.4071.0000.227
이용 대상0.2460.2970.2271.000

Missing values

2024-03-15T09:57:43.952699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:57:44.390522image/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.
2024-03-15T09:57:44.672956image/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

시군구명소재기관명소재기관 주소시설 구분이용 대상수유시설 면적(제곱미터)기관 내 수유시설 위치비치 물품
0전주시전북대학교전북 전주시 덕진구 백제대로 567모유수유실외부/직원용13.2<NA><NA>
1전주시북전주세무서전북 전주시 덕진구 벚꽃로 33모유수유실외부/직원용26.41층 지원과 앞침대
2전주시전주시동물원전북 전주시 덕진구 소리로 68가족수유실외부/직원용19.8동물원내 드림랜드 앞가림막/의자/테이블
3전주시팔복동주민센터전북 전주시 덕진구 신복5길 6가족수유실외부/직원용52.91층 회의실 내의자/테이블
4전주시조촌동주민센터전북 전주시 덕진구 쪽구름로 150가족수유실외부/직원용19.81층 복지상담실 내쇼파/테이블
5전주시전주시청전북 전주시 완산구 노송광장로 10가족수유실외부/직원용49.66층여직원휴게실 내냉장고/수유쿠션/침대
6전주시전주자연생태관전북 전주시 완산구 바람쐬는길 21가족수유실외부/직원용13.21층자연 생태관안내데스크 옆쿠션/쇼파/냉장고
7전주시건강보험공단전주남부지사전북 전주시 완산구 서신천변12길 9가족수유실외부/직원용19.81층의자/테이블/세면대/전자레인지/가림막
8전주시동서학동주민센터전북 전주시 완산구 서학로 26가족수유실외부/직원용19.8청사내 민원실 입구 앞가스레인지/화장실/
9전주시국민연금공단전주완주지사전북 전주시 완산구 온고을로 13모유수유실외부/직원용33.1<NA><NA>
시군구명소재기관명소재기관 주소시설 구분이용 대상수유시설 면적(제곱미터)기관 내 수유시설 위치비치 물품
173고창군고창휴게소(하)전북 고창군 신림면 서해안고속도로 81가족수유실외부인19.81층 편의점 옆소파/ 아기침대/ 기저귀교환대/ 젖병소독기/ 정수기/ 공기청정기/ 전자레인지
174고창군고인돌박물관전북 고창군 아산면 고인돌공원길 74모유수유실외부인6.211층 출입구 옆소파
175고창군육아종합지원센터전북 고창군 고창읍 월곡뉴타운2길 20모유수유실외부인5.01층 출입구 옆소파
176고창군고창군보건소전북 고창군 고창읍 전봉준로 90모유수유실직원+외부인5.01층 모자보건실 내소파/기저귀교환대/수유쿠션
177고창군청보리밭관광객 편의시설전북 고창군 공음면 학원농장길 142모유수유실외부인14.81층 여자화장실 옆소파/ 아기침대/ 개수대
178고창군해리면주민센터전북 고창군 해리면 청해2길 38.모유수유실외부인15.01층 맞춤형복지팀 옆소파/ 테디블
179고창군고창군청전북 고창군 고창읍 중앙로 200모유수유실외부인0.01층 여자화장실 옆소파
180부안군부안군청전북 부안군 부안읍 당산로 91가족수유실직원+외부인16.01층 화장실 옆소파/ 테이블/ 기저귀교환대
181부안군엔젤소아청소년과의원전북 부안군 부안읍 석정로 233가족수유실직원+외부인3.02층 병원 내소파/ 에어컨/ 의자
182부안군부안군 보건소전북 부안군 부안읍 오리정로 124가족수유실직원+외부인10.01층 모자보건실 내소파/ 기저귀교환대