Overview

Dataset statistics

Number of variables11
Number of observations79
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory91.6 B

Variable types

Numeric1
Categorical5
Text4
Boolean1

Dataset

Description전북특별자치도 시군별 청소년 시설 현황(시군명, 구분, 기관명, 도로명주소, 전화번호, 대표자, 자료출처, 공개여부, 작성일 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055544/fileData.do

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기(년) has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:42:02.389858
Analysis finished2024-03-14 08:42:04.425201
Duration2.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40
Minimum1
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size839.0 B
2024-03-14T17:42:04.629017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.9
Q120.5
median40
Q359.5
95-th percentile75.1
Maximum79
Range78
Interquartile range (IQR)39

Descriptive statistics

Standard deviation22.949219
Coefficient of variation (CV)0.57373048
Kurtosis-1.2
Mean40
Median Absolute Deviation (MAD)20
Skewness0
Sum3160
Variance526.66667
MonotonicityStrictly increasing
2024-03-14T17:42:05.087127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
2 1
 
1.3%
59 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
79 1
1.3%
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Memory size760.0 B
전주시
13 
김제시
9 
익산시
7 
무주군
7 
완주군
6 
Other values (9)
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row순창군
2nd row순창군
3rd row완주군
4th row완주군
5th row완주군

Common Values

ValueCountFrequency (%)
전주시 13
16.5%
김제시 9
11.4%
익산시 7
8.9%
무주군 7
8.9%
완주군 6
7.6%
부안군 6
7.6%
정읍시 5
 
6.3%
군산시 5
 
6.3%
고창군 5
 
6.3%
진안군 4
 
5.1%
Other values (4) 12
15.2%

Length

2024-03-14T17:42:05.503283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 13
16.5%
김제시 9
11.4%
익산시 7
8.9%
무주군 7
8.9%
완주군 6
7.6%
부안군 6
7.6%
정읍시 5
 
6.3%
군산시 5
 
6.3%
고창군 5
 
6.3%
진안군 4
 
5.1%
Other values (4) 12
15.2%

구분
Categorical

Distinct9
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size760.0 B
청소 문화의집
18 
청소 상담복지 센터
15 
청소수련원
13 
청소수련관
11 
유스호스텔
9 
Other values (4)
13 

Length

Max length10
Median length5
Mean length6.5949367
Min length5

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row청소 상담복지 센터
2nd row청소수련관
3rd row청소야영장
4th row유스호스텔
5th row청소 상담복지 센터

Common Values

ValueCountFrequency (%)
청소 문화의집 18
22.8%
청소 상담복지 센터 15
19.0%
청소수련원 13
16.5%
청소수련관 11
13.9%
유스호스텔 9
11.4%
청소 쉼터 5
 
6.3%
청소 성문화센터 4
 
5.1%
청소야영장 3
 
3.8%
청소활동진흥센터 1
 
1.3%

Length

2024-03-14T17:42:05.868480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:42:06.165717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청소 42
30.9%
문화의집 18
13.2%
상담복지 15
 
11.0%
센터 15
 
11.0%
청소수련원 13
 
9.6%
청소수련관 11
 
8.1%
유스호스텔 9
 
6.6%
쉼터 5
 
3.7%
성문화센터 4
 
2.9%
청소야영장 3
 
2.2%

기관명
Text

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size760.0 B
2024-03-14T17:42:06.918285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length10.164557
Min length5

Characters and Unicode

Total characters803
Distinct characters122
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)100.0%

Sample

1st row순창군 청소상담복지센터
2nd row순창군 청소센터
3rd row한국스카우트송광훈련장
4th row상관 유스호스텔
5th row완주군 청소상담복지센터
ValueCountFrequency (%)
청소문화의집 17
 
11.6%
청소상담복지센터 15
 
10.3%
청소수련관 9
 
6.2%
청소수련원 5
 
3.4%
유스호스텔 5
 
3.4%
군산시 5
 
3.4%
익산시 4
 
2.7%
부안군 4
 
2.7%
정읍시 4
 
2.7%
무주군 4
 
2.7%
Other values (55) 74
50.7%
2024-03-14T17:42:08.015280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 69
 
8.6%
67
 
8.3%
소 66
 
8.2%
터 29
 
3.6%
군 27
 
3.4%
수 24
 
3.0%
센 23
 
2.9%
시 23
 
2.9%
문 22
 
2.7%
련 22
 
2.7%
Other values (112) 431
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 727
90.5%
Space Separator 67
 
8.3%
Open Punctuation 4
 
0.5%
Close Punctuation 3
 
0.4%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 69
 
9.5%
소 66
 
9.1%
터 29
 
4.0%
군 27
 
3.7%
수 24
 
3.3%
센 23
 
3.2%
시 23
 
3.2%
문 22
 
3.0%
련 22
 
3.0%
화 22
 
3.0%
Other values (107) 400
55.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 727
90.5%
Common 74
 
9.2%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 69
 
9.5%
소 66
 
9.1%
터 29
 
4.0%
군 27
 
3.7%
수 24
 
3.3%
센 23
 
3.2%
시 23
 
3.2%
문 22
 
3.0%
련 22
 
3.0%
화 22
 
3.0%
Other values (107) 400
55.0%
Common
ValueCountFrequency (%)
67
90.5%
( 4
 
5.4%
) 3
 
4.1%
Latin
ValueCountFrequency (%)
K 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 727
90.5%
ASCII 76
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 69
 
9.5%
소 66
 
9.1%
터 29
 
4.0%
군 27
 
3.7%
수 24
 
3.3%
센 23
 
3.2%
시 23
 
3.2%
문 22
 
3.0%
련 22
 
3.0%
화 22
 
3.0%
Other values (107) 400
55.0%
ASCII
ValueCountFrequency (%)
67
88.2%
( 4
 
5.3%
) 3
 
3.9%
K 1
 
1.3%
J 1
 
1.3%

도로명주소
Text

Distinct74
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size760.0 B
2024-03-14T17:42:09.258045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length16.721519
Min length10

Characters and Unicode

Total characters1321
Distinct characters158
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)87.3%

Sample

1st row순창군 장류로 192
2nd row순창군 순창읍 장류로 192
3rd row완주군 소양면 신지송광로 879-32
4th row완주군 상관면 죽림편백길 118-38
5th row완주군 삼례읍 삼봉로 125
ValueCountFrequency (%)
전주시 13
 
4.2%
김제시 9
 
2.9%
익산시 7
 
2.3%
무주군 7
 
2.3%
부안군 6
 
1.9%
완주군 6
 
1.9%
덕진구 6
 
1.9%
완산구 6
 
1.9%
고창군 5
 
1.6%
군산시 5
 
1.6%
Other values (178) 241
77.5%
2024-03-14T17:42:10.988621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
236
 
17.9%
로 55
 
4.2%
1 50
 
3.8%
3 45
 
3.4%
시 44
 
3.3%
군 41
 
3.1%
2 40
 
3.0%
4 33
 
2.5%
주 32
 
2.4%
산 29
 
2.2%
Other values (148) 716
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 765
57.9%
Decimal Number 280
 
21.2%
Space Separator 236
 
17.9%
Dash Punctuation 27
 
2.0%
Close Punctuation 6
 
0.5%
Open Punctuation 6
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 55
 
7.2%
시 44
 
5.8%
군 41
 
5.4%
주 32
 
4.2%
산 29
 
3.8%
면 26
 
3.4%
길 25
 
3.3%
읍 24
 
3.1%
안 19
 
2.5%
전 18
 
2.4%
Other values (133) 452
59.1%
Decimal Number
ValueCountFrequency (%)
1 50
17.9%
3 45
16.1%
2 40
14.3%
4 33
11.8%
5 25
8.9%
6 23
8.2%
7 21
7.5%
0 18
 
6.4%
9 13
 
4.6%
8 12
 
4.3%
Space Separator
ValueCountFrequency (%)
236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 765
57.9%
Common 556
42.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 55
 
7.2%
시 44
 
5.8%
군 41
 
5.4%
주 32
 
4.2%
산 29
 
3.8%
면 26
 
3.4%
길 25
 
3.3%
읍 24
 
3.1%
안 19
 
2.5%
전 18
 
2.4%
Other values (133) 452
59.1%
Common
ValueCountFrequency (%)
236
42.4%
1 50
 
9.0%
3 45
 
8.1%
2 40
 
7.2%
4 33
 
5.9%
- 27
 
4.9%
5 25
 
4.5%
6 23
 
4.1%
7 21
 
3.8%
0 18
 
3.2%
Other values (5) 38
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 765
57.9%
ASCII 556
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
236
42.4%
1 50
 
9.0%
3 45
 
8.1%
2 40
 
7.2%
4 33
 
5.9%
- 27
 
4.9%
5 25
 
4.5%
6 23
 
4.1%
7 21
 
3.8%
0 18
 
3.2%
Other values (5) 38
 
6.8%
Hangul
ValueCountFrequency (%)
로 55
 
7.2%
시 44
 
5.8%
군 41
 
5.4%
주 32
 
4.2%
산 29
 
3.8%
면 26
 
3.4%
길 25
 
3.3%
읍 24
 
3.1%
안 19
 
2.5%
전 18
 
2.4%
Other values (133) 452
59.1%

전화번호
Text

Distinct76
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size760.0 B
2024-03-14T17:42:11.950025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters948
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

Unique73 ?
Unique (%)92.4%

Sample

1st row063-650-1278
2nd row063-650-1318
3rd row063-232-8100
4th row063-250-4216
5th row063-291-3303
ValueCountFrequency (%)
063-320-5642 2
 
2.5%
063-548-4401 2
 
2.5%
063-630-1000 2
 
2.5%
063-644-2000 1
 
1.3%
063-560-8915 1
 
1.3%
063-278-8588 1
 
1.3%
063-903-1091 1
 
1.3%
063-227-1005 1
 
1.3%
063-232-0479 1
 
1.3%
063-273-5501 1
 
1.3%
Other values (66) 66
83.5%
2024-03-14T17:42:13.208790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 158
16.7%
0 152
16.0%
3 152
16.0%
6 112
11.8%
2 73
7.7%
5 65
6.9%
1 58
 
6.1%
8 58
 
6.1%
4 57
 
6.0%
7 32
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 790
83.3%
Dash Punctuation 158
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 152
19.2%
3 152
19.2%
6 112
14.2%
2 73
9.2%
5 65
8.2%
1 58
 
7.3%
8 58
 
7.3%
4 57
 
7.2%
7 32
 
4.1%
9 31
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 948
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 158
16.7%
0 152
16.0%
3 152
16.0%
6 112
11.8%
2 73
7.7%
5 65
6.9%
1 58
 
6.1%
8 58
 
6.1%
4 57
 
6.0%
7 32
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 158
16.7%
0 152
16.0%
3 152
16.0%
6 112
11.8%
2 73
7.7%
5 65
6.9%
1 58
 
6.1%
8 58
 
6.1%
4 57
 
6.0%
7 32
 
3.4%

대표자
Text

Distinct72
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size760.0 B
2024-03-14T17:42:14.251942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.3544304
Min length2

Characters and Unicode

Total characters265
Distinct characters88
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

Unique67 ?
Unique (%)84.8%

Sample

1st row이*효
2nd row이*신
3rd row조*식
4th row정*신
5th row임*평
ValueCountFrequency (%)
김제시장 4
 
5.0%
김*기 2
 
2.5%
송*평 2
 
2.5%
정 2
 
2.5%
송*승 2
 
2.5%
이*희 2
 
2.5%
김*구 1
 
1.2%
최*승 1
 
1.2%
한국청소활동진흥 1
 
1.2%
김*진 1
 
1.2%
Other values (62) 62
77.5%
2024-03-14T17:42:15.658840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 72
27.2%
이 18
 
6.8%
김 15
 
5.7%
정 8
 
3.0%
장 7
 
2.6%
시 6
 
2.3%
송 6
 
2.3%
서 5
 
1.9%
희 4
 
1.5%
제 4
 
1.5%
Other values (78) 120
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
71.3%
Other Punctuation 73
 
27.5%
Space Separator 1
 
0.4%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 18
 
9.5%
김 15
 
7.9%
정 8
 
4.2%
장 7
 
3.7%
시 6
 
3.2%
송 6
 
3.2%
서 5
 
2.6%
희 4
 
2.1%
제 4
 
2.1%
기 4
 
2.1%
Other values (73) 112
59.3%
Other Punctuation
ValueCountFrequency (%)
* 72
98.6%
, 1
 
1.4%
Space Separator
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189
71.3%
Common 76
28.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 18
 
9.5%
김 15
 
7.9%
정 8
 
4.2%
장 7
 
3.7%
시 6
 
3.2%
송 6
 
3.2%
서 5
 
2.6%
희 4
 
2.1%
제 4
 
2.1%
기 4
 
2.1%
Other values (73) 112
59.3%
Common
ValueCountFrequency (%)
* 72
94.7%
1
 
1.3%
, 1
 
1.3%
( 1
 
1.3%
) 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189
71.3%
ASCII 76
28.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 72
94.7%
1
 
1.3%
, 1
 
1.3%
( 1
 
1.3%
) 1
 
1.3%
Hangul
ValueCountFrequency (%)
이 18
 
9.5%
김 15
 
7.9%
정 8
 
4.2%
장 7
 
3.7%
시 6
 
3.2%
송 6
 
3.2%
서 5
 
2.6%
희 4
 
2.1%
제 4
 
2.1%
기 4
 
2.1%
Other values (73) 112
59.3%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size760.0 B
여성청소과
79 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여성청소과 79
100.0%

Length

2024-03-14T17:42:15.901843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:42:16.207325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여성청소과 79
100.0%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size207.0 B
True
79 
ValueCountFrequency (%)
True 79
100.0%
2024-03-14T17:42:16.471171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size760.0 B
04-01
79 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row04-01
2nd row04-01
3rd row04-01
4th row04-01
5th row04-01

Common Values

ValueCountFrequency (%)
04-01 79
100.0%

Length

2024-03-14T17:42:16.781676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:42:17.084492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
04-01 79
100.0%

갱신주기(년)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size760.0 B
1
79 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 79
100.0%

Length

2024-03-14T17:42:17.401040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:42:17.706799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 79
100.0%

Interactions

2024-03-14T17:42:03.347221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:42:17.892948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명구분기관명도로명주소전화번호대표자
순번1.0000.9590.0001.0000.9710.9340.974
시군명0.9591.0000.0001.0001.0001.0001.000
구분0.0000.0001.0001.0000.0000.4440.936
기관명1.0001.0001.0001.0001.0001.0001.000
도로명주소0.9711.0000.0001.0001.0001.0000.987
전화번호0.9341.0000.4441.0001.0001.0000.994
대표자0.9741.0000.9361.0000.9870.9941.000
2024-03-14T17:42:18.367375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군명
구분1.0000.000
시군명0.0001.000
2024-03-14T17:42:18.599524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명구분
순번1.0000.8050.000
시군명0.8051.0000.000
구분0.0000.0001.000

Missing values

2024-03-14T17:42:03.726205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:42:04.230834image/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

순번시군명구분기관명도로명주소전화번호대표자자료출처공개여부작성일갱신주기(년)
01순창군청소 상담복지 센터순창군 청소상담복지센터순창군 장류로 192063-650-1278이*효여성청소과Y04-011
12순창군청소수련관순창군 청소센터순창군 순창읍 장류로 192063-650-1318이*신여성청소과Y04-011
23완주군청소야영장한국스카우트송광훈련장완주군 소양면 신지송광로 879-32063-232-8100조*식여성청소과Y04-011
34완주군유스호스텔상관 유스호스텔완주군 상관면 죽림편백길 118-38063-250-4216정*신여성청소과Y04-011
45완주군청소 상담복지 센터완주군 청소상담복지센터완주군 삼례읍 삼봉로 125063-291-3303임*평여성청소과Y04-011
56완주군청소수련관완주군 청소수련관완주군 삼례읍 삼봉로 125063-291-1350완주군수여성청소과Y04-011
67완주군청소 문화의집완주군 청소문화의집완주군 봉동읍 하보상길 18-9063-262-7942이*하여성청소과Y04-011
78완주군청소수련원청정테마센터(청정인성수련원)완주군 구이면 장미로 31063-222-7754이*휘여성청소과Y04-011
89익산시청소 상담복지 센터익산시 청소상담복지센터익산시 인북로 200 (남중동, 전북은행 2층)063-853-1388송*승여성청소과Y04-011
910익산시청소 쉼터익산 청소일시쉼터익산시 인북로 32길 17063-838-1091박*수여성청소과Y04-011
순번시군명구분기관명도로명주소전화번호대표자자료출처공개여부작성일갱신주기(년)
6970장수군청소 문화의집장수군 청소문화의집장수읍 한누리로 393 한누리전당 가람관 3층063-351-7942최*득여성청소과Y04-011
7071장수군청소수련원우석수련원장수군 번암면 방화동로 448063-353-3368송*섭여성청소과Y04-011
7172장수군유스호스텔(주)나봄리조트(구 장수힐스리조장수군 천천면 승마로 1005-24063-353-8880이*서여성청소과Y04-011
7273고창군청소 문화의집흥덕 청소문화의집고창군 흥덕면 선운대로 3774063-560-8927이*희여성청소과Y04-011
7374고창군청소 문화의집성내 청소문화의집고창군 성내면 시기2길 18063-560-8928김*숙여성청소과Y04-011
7475고창군유스호스텔선운산 유스호스텔고창군 아산면 선운사로 158-36063-560-8953안*효여성청소과Y04-011
7576고창군청소 상담복지 센터고창군 청소상담복지센터고창군 고창읍 운동장길 36 고창청소수련관(2층)063-560-8925진*표여성청소과Y04-011
7677고창군청소수련관고창군 청소수련관고창군 운동장길 36063-560-8915이*희여성청소과Y04-011
7778임실군청소 상담복지 센터임실군 청소상담복지센터임실군 임실읍 봉황로 159-7063-644-2000김*배여성청소과Y04-011
7879임실군청소수련원임실군 청소수련원임실군 관촌면 사선2길 96-24063-644-2526강*묵여성청소과Y04-011