Overview

Dataset statistics

Number of variables15
Number of observations232
Missing cells62
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.2 KiB
Average record size in memory124.6 B

Variable types

Numeric3
Categorical6
Text4
DateTime2

Dataset

Description전북특별자치도 민방위 급수시설 현황(시군구, 읍면동, 지정 운영 여부, 급수시설명 등)우리기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055713/fileData.do

Alerts

연번 is highly overall correlated with 시군구 and 2 other fieldsHigh correlation
급수능력 is highly overall correlated with 사용가능인원High correlation
사용가능인원 is highly overall correlated with 급수능력High correlation
시군구 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
개방여부 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
비상발전기 보유 대수 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
지정 운영 여부 is highly imbalanced (74.4%)Imbalance
도로명 주소 has 8 (3.4%) missing valuesMissing
지번 주소 has 3 (1.3%) missing valuesMissing
건축연도 has 4 (1.7%) missing valuesMissing
지정연도 (정부지원 제외) has 47 (20.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:02:08.934368
Analysis finished2024-03-14 09:02:13.829448
Duration4.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct232
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.5
Minimum1
Maximum232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-14T18:02:14.049118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.55
Q158.75
median116.5
Q3174.25
95-th percentile220.45
Maximum232
Range231
Interquartile range (IQR)115.5

Descriptive statistics

Standard deviation67.116814
Coefficient of variation (CV)0.57610999
Kurtosis-1.2
Mean116.5
Median Absolute Deviation (MAD)58
Skewness0
Sum27028
Variance4504.6667
MonotonicityStrictly increasing
2024-03-14T18:02:14.473589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
161 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
153 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
Other values (222) 222
95.7%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
232 1
0.4%
231 1
0.4%
230 1
0.4%
229 1
0.4%
228 1
0.4%
227 1
0.4%
226 1
0.4%
225 1
0.4%
224 1
0.4%
223 1
0.4%

시군구
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
전주시
67 
군산시
51 
익산시
43 
남원시
12 
김제시
12 
Other values (9)
47 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 67
28.9%
군산시 51
22.0%
익산시 43
18.5%
남원시 12
 
5.2%
김제시 12
 
5.2%
완주군 11
 
4.7%
정읍시 8
 
3.4%
무주군 7
 
3.0%
순창군 5
 
2.2%
임실군 4
 
1.7%
Other values (4) 12
 
5.2%

Length

2024-03-14T18:02:14.870563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 67
28.9%
군산시 51
22.0%
익산시 43
18.5%
남원시 12
 
5.2%
김제시 12
 
5.2%
완주군 11
 
4.7%
정읍시 8
 
3.4%
무주군 7
 
3.0%
순창군 5
 
2.2%
임실군 4
 
1.7%
Other values (4) 12
 
5.2%

읍면동
Text

Distinct94
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-03-14T18:02:15.906507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.2931034
Min length2

Characters and Unicode

Total characters764
Distinct characters97
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

Unique37 ?
Unique (%)15.9%

Sample

1st row중앙동
2nd row풍남동
3rd row풍남동
4th row노송동
5th row동서학동
ValueCountFrequency (%)
나운3동 10
 
4.3%
조촌동 8
 
3.4%
신풍동 8
 
3.4%
월명동 7
 
3.0%
봉동읍 7
 
3.0%
마동 6
 
2.6%
신동 5
 
2.2%
영등1동 5
 
2.2%
모현동 5
 
2.2%
삼성동 5
 
2.2%
Other values (84) 166
71.6%
2024-03-14T18:02:17.614187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 191
25.0%
읍 33
 
4.3%
1 25
 
3.3%
2 19
 
2.5%
면 17
 
2.2%
3 16
 
2.1%
신 16
 
2.1%
운 16
 
2.1%
삼 16
 
2.1%
나 15
 
2.0%
Other values (87) 400
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 696
91.1%
Decimal Number 68
 
8.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 191
27.4%
읍 33
 
4.7%
면 17
 
2.4%
신 16
 
2.3%
운 16
 
2.3%
삼 16
 
2.3%
나 15
 
2.2%
산 15
 
2.2%
화 15
 
2.2%
천 13
 
1.9%
Other values (82) 349
50.1%
Decimal Number
ValueCountFrequency (%)
1 25
36.8%
2 19
27.9%
3 16
23.5%
5 5
 
7.4%
4 3
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 696
91.1%
Common 68
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 191
27.4%
읍 33
 
4.7%
면 17
 
2.4%
신 16
 
2.3%
운 16
 
2.3%
삼 16
 
2.3%
나 15
 
2.2%
산 15
 
2.2%
화 15
 
2.2%
천 13
 
1.9%
Other values (82) 349
50.1%
Common
ValueCountFrequency (%)
1 25
36.8%
2 19
27.9%
3 16
23.5%
5 5
 
7.4%
4 3
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 696
91.1%
ASCII 68
 
8.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 191
27.4%
읍 33
 
4.7%
면 17
 
2.4%
신 16
 
2.3%
운 16
 
2.3%
삼 16
 
2.3%
나 15
 
2.2%
산 15
 
2.2%
화 15
 
2.2%
천 13
 
1.9%
Other values (82) 349
50.1%
ASCII
ValueCountFrequency (%)
1 25
36.8%
2 19
27.9%
3 16
23.5%
5 5
 
7.4%
4 3
 
4.4%

지정 운영 여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
지정운영
222 
신규지정
 
10

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정운영 222
95.7%
신규지정 10
 
4.3%

Length

2024-03-14T18:02:18.019273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:02:18.288865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정운영 222
95.7%
신규지정 10
 
4.3%

급수시설명
Text

Distinct229
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-03-14T18:02:18.992772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length7.0258621
Min length3

Characters and Unicode

Total characters1630
Distinct characters261
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

Unique226 ?
Unique (%)97.4%

Sample

1st row거북탕
2nd row한벽문화관
3rd row동부화재
4th row기린연립
5th row전주교육대학교
ValueCountFrequency (%)
급수시설 20
 
7.4%
삼성아파트 2
 
0.7%
보건소 2
 
0.7%
화이트사우나(화이트목욕탕 2
 
0.7%
공설운동장 2
 
0.7%
체육공원 2
 
0.7%
비상급수시설 2
 
0.7%
지곡초등학교 2
 
0.7%
수정사우나 2
 
0.7%
달님약수 1
 
0.4%
Other values (232) 232
86.2%
2024-03-14T18:02:20.293134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 85
 
5.2%
학 78
 
4.8%
등 53
 
3.3%
원 38
 
2.3%
주 38
 
2.3%
37
 
2.3%
공 35
 
2.1%
수 35
 
2.1%
산 32
 
2.0%
초 31
 
1.9%
Other values (251) 1168
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1518
93.1%
Space Separator 37
 
2.3%
Decimal Number 30
 
1.8%
Open Punctuation 18
 
1.1%
Close Punctuation 18
 
1.1%
Other Symbol 4
 
0.2%
Dash Punctuation 3
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 85
 
5.6%
학 78
 
5.1%
등 53
 
3.5%
원 38
 
2.5%
주 38
 
2.5%
공 35
 
2.3%
수 35
 
2.3%
산 32
 
2.1%
초 31
 
2.0%
고 30
 
2.0%
Other values (237) 1063
70.0%
Decimal Number
ValueCountFrequency (%)
1 12
40.0%
2 6
20.0%
3 5
16.7%
6 2
 
6.7%
4 2
 
6.7%
5 2
 
6.7%
9 1
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1522
93.4%
Common 106
 
6.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 85
 
5.6%
학 78
 
5.1%
등 53
 
3.5%
원 38
 
2.5%
주 38
 
2.5%
공 35
 
2.3%
수 35
 
2.3%
산 32
 
2.1%
초 31
 
2.0%
고 30
 
2.0%
Other values (238) 1067
70.1%
Common
ValueCountFrequency (%)
37
34.9%
( 18
17.0%
) 18
17.0%
1 12
 
11.3%
2 6
 
5.7%
3 5
 
4.7%
- 3
 
2.8%
6 2
 
1.9%
4 2
 
1.9%
5 2
 
1.9%
Latin
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1518
93.1%
ASCII 108
 
6.6%
None 4
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 85
 
5.6%
학 78
 
5.1%
등 53
 
3.5%
원 38
 
2.5%
주 38
 
2.5%
공 35
 
2.3%
수 35
 
2.3%
산 32
 
2.1%
초 31
 
2.0%
고 30
 
2.0%
Other values (237) 1063
70.0%
ASCII
ValueCountFrequency (%)
37
34.3%
( 18
16.7%
) 18
16.7%
1 12
 
11.1%
2 6
 
5.6%
3 5
 
4.6%
- 3
 
2.8%
6 2
 
1.9%
4 2
 
1.9%
5 2
 
1.9%
Other values (3) 3
 
2.8%
None
ValueCountFrequency (%)
㈜ 4
100.0%

시설종류
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
공공용
163 
정부지원
57 
지자체
 
12

Length

Max length4
Median length3
Mean length3.2456897
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공용
2nd row지자체
3rd row공공용
4th row정부지원
5th row공공용

Common Values

ValueCountFrequency (%)
공공용 163
70.3%
정부지원 57
 
24.6%
지자체 12
 
5.2%

Length

2024-03-14T18:02:20.718742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:02:21.037215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 163
70.3%
정부지원 57
 
24.6%
지자체 12
 
5.2%

용도
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
생활용수
123 
음용수
109 

Length

Max length4
Median length4
Mean length3.5301724
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음용수
2nd row생활용수
3rd row음용수
4th row음용수
5th row생활용수

Common Values

ValueCountFrequency (%)
생활용수 123
53.0%
음용수 109
47.0%

Length

2024-03-14T18:02:21.439485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:02:21.788968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활용수 123
53.0%
음용수 109
47.0%

개방여부
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
미개방
133 
개방
96 
<NA>
 
3

Length

Max length4
Median length3
Mean length2.5991379
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미개방
2nd row미개방
3rd row미개방
4th row개방
5th row미개방

Common Values

ValueCountFrequency (%)
미개방 133
57.3%
개방 96
41.4%
<NA> 3
 
1.3%

Length

2024-03-14T18:02:22.161080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:02:22.511662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미개방 133
57.3%
개방 96
41.4%
na 3
 
1.3%

도로명 주소
Text

MISSING 

Distinct215
Distinct (%)96.0%
Missing8
Missing (%)3.4%
Memory size1.9 KiB
2024-03-14T18:02:23.809959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length20
Mean length13.553571
Min length4

Characters and Unicode

Total characters3036
Distinct characters193
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

Unique210 ?
Unique (%)93.8%

Sample

1st row전주시 완산구 대동로 653
2nd row전주시 완산구 전주천동로 20
3rd row전주시 완산구 전라감영5길 10
4th row전주시 완산구 견훤로 10010
5th row전주시 완산구 서학로 50
ValueCountFrequency (%)
전주시 67
 
8.5%
군산시 43
 
5.5%
익산시 42
 
5.3%
완산구 40
 
5.1%
덕진구 26
 
3.3%
김제시 12
 
1.5%
완주군 11
 
1.4%
전북 10
 
1.3%
남원시 10
 
1.3%
20 8
 
1.0%
Other values (372) 519
65.9%
2024-03-14T18:02:25.543747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
568
18.7%
시 182
 
6.0%
산 145
 
4.8%
로 141
 
4.6%
1 139
 
4.6%
길 101
 
3.3%
2 97
 
3.2%
주 91
 
3.0%
전 88
 
2.9%
군 83
 
2.7%
Other values (183) 1401
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1818
59.9%
Decimal Number 648
 
21.3%
Space Separator 568
 
18.7%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 182
 
10.0%
산 145
 
8.0%
로 141
 
7.8%
길 101
 
5.6%
주 91
 
5.0%
전 88
 
4.8%
군 83
 
4.6%
구 71
 
3.9%
완 53
 
2.9%
익 44
 
2.4%
Other values (170) 819
45.0%
Decimal Number
ValueCountFrequency (%)
1 139
21.5%
2 97
15.0%
3 74
11.4%
5 58
9.0%
4 56
8.6%
9 52
 
8.0%
7 48
 
7.4%
6 47
 
7.3%
0 47
 
7.3%
8 30
 
4.6%
Space Separator
ValueCountFrequency (%)
568
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1818
59.9%
Common 1218
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 182
 
10.0%
산 145
 
8.0%
로 141
 
7.8%
길 101
 
5.6%
주 91
 
5.0%
전 88
 
4.8%
군 83
 
4.6%
구 71
 
3.9%
완 53
 
2.9%
익 44
 
2.4%
Other values (170) 819
45.0%
Common
ValueCountFrequency (%)
568
46.6%
1 139
 
11.4%
2 97
 
8.0%
3 74
 
6.1%
5 58
 
4.8%
4 56
 
4.6%
9 52
 
4.3%
7 48
 
3.9%
6 47
 
3.9%
0 47
 
3.9%
Other values (3) 32
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1818
59.9%
ASCII 1218
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
568
46.6%
1 139
 
11.4%
2 97
 
8.0%
3 74
 
6.1%
5 58
 
4.8%
4 56
 
4.6%
9 52
 
4.3%
7 48
 
3.9%
6 47
 
3.9%
0 47
 
3.9%
Other values (3) 32
 
2.6%
Hangul
ValueCountFrequency (%)
시 182
 
10.0%
산 145
 
8.0%
로 141
 
7.8%
길 101
 
5.6%
주 91
 
5.0%
전 88
 
4.8%
군 83
 
4.6%
구 71
 
3.9%
완 53
 
2.9%
익 44
 
2.4%
Other values (170) 819
45.0%

지번 주소
Text

MISSING 

Distinct219
Distinct (%)95.6%
Missing3
Missing (%)1.3%
Memory size1.9 KiB
2024-03-14T18:02:27.119806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length15.611354
Min length9

Characters and Unicode

Total characters3575
Distinct characters138
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

Unique213 ?
Unique (%)93.0%

Sample

1st row전주시 완산구 태평동 497
2nd row전주시 완산구 교동 71
3rd row전주시 완산구 경원동1가 10432
4th row전주시 완산구 중노송동 27번지 3호
5th row전주시 완산구 동서학동 128번지
ValueCountFrequency (%)
전주시 67
 
7.6%
군산시 51
 
5.8%
익산시 42
 
4.8%
완산구 41
 
4.7%
덕진구 26
 
3.0%
1호 20
 
2.3%
전북 12
 
1.4%
김제시 12
 
1.4%
남원시 12
 
1.4%
완주군 9
 
1.0%
Other values (397) 584
66.7%
2024-03-14T18:02:29.169096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
648
 
18.1%
시 193
 
5.4%
동 188
 
5.3%
1 179
 
5.0%
산 165
 
4.6%
2 132
 
3.7%
5 98
 
2.7%
지 91
 
2.5%
번 90
 
2.5%
군 89
 
2.5%
Other values (128) 1702
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2034
56.9%
Decimal Number 891
24.9%
Space Separator 648
 
18.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 193
 
9.5%
동 188
 
9.2%
산 165
 
8.1%
지 91
 
4.5%
번 90
 
4.4%
군 89
 
4.4%
주 86
 
4.2%
전 86
 
4.2%
구 70
 
3.4%
호 58
 
2.9%
Other values (115) 918
45.1%
Decimal Number
ValueCountFrequency (%)
1 179
20.1%
2 132
14.8%
5 98
11.0%
4 86
9.7%
3 86
9.7%
7 77
8.6%
8 70
 
7.9%
0 59
 
6.6%
9 52
 
5.8%
6 52
 
5.8%
Space Separator
ValueCountFrequency (%)
648
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2034
56.9%
Common 1541
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 193
 
9.5%
동 188
 
9.2%
산 165
 
8.1%
지 91
 
4.5%
번 90
 
4.4%
군 89
 
4.4%
주 86
 
4.2%
전 86
 
4.2%
구 70
 
3.4%
호 58
 
2.9%
Other values (115) 918
45.1%
Common
ValueCountFrequency (%)
648
42.1%
1 179
 
11.6%
2 132
 
8.6%
5 98
 
6.4%
4 86
 
5.6%
3 86
 
5.6%
7 77
 
5.0%
8 70
 
4.5%
0 59
 
3.8%
9 52
 
3.4%
Other values (3) 54
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2034
56.9%
ASCII 1541
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
648
42.1%
1 179
 
11.6%
2 132
 
8.6%
5 98
 
6.4%
4 86
 
5.6%
3 86
 
5.6%
7 77
 
5.0%
8 70
 
4.5%
0 59
 
3.8%
9 52
 
3.4%
Other values (3) 54
 
3.5%
Hangul
ValueCountFrequency (%)
시 193
 
9.5%
동 188
 
9.2%
산 165
 
8.1%
지 91
 
4.5%
번 90
 
4.4%
군 89
 
4.4%
주 86
 
4.2%
전 86
 
4.2%
구 70
 
3.4%
호 58
 
2.9%
Other values (115) 918
45.1%

건축연도
Date

MISSING 

Distinct183
Distinct (%)80.3%
Missing4
Missing (%)1.7%
Memory size1.9 KiB
Minimum1973-08-21 00:00:00
Maximum2020-05-28 00:00:00
2024-03-14T18:02:29.515269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:29.939705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지정연도 (정부지원 제외)
Date

MISSING 

Distinct101
Distinct (%)54.6%
Missing47
Missing (%)20.3%
Memory size1.9 KiB
Minimum1982-01-01 00:00:00
Maximum2020-08-18 00:00:00
2024-03-14T18:02:30.349757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:30.785777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

급수능력
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.56897
Minimum50
Maximum2184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-14T18:02:31.201407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile70
Q190
median120
Q3175
95-th percentile321.8
Maximum2184
Range2134
Interquartile range (IQR)85

Descriptive statistics

Standard deviation167.8322
Coefficient of variation (CV)1.0517848
Kurtosis94.166365
Mean159.56897
Median Absolute Deviation (MAD)30
Skewness8.4644082
Sum37020
Variance28167.649
MonotonicityNot monotonic
2024-03-14T18:02:31.626452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 33
14.2%
150 31
13.4%
90 30
12.9%
200 20
 
8.6%
120 13
 
5.6%
80 13
 
5.6%
110 9
 
3.9%
70 7
 
3.0%
170 6
 
2.6%
140 5
 
2.2%
Other values (45) 65
28.0%
ValueCountFrequency (%)
50 2
 
0.9%
55 1
 
0.4%
60 3
 
1.3%
70 7
 
3.0%
75 1
 
0.4%
78 1
 
0.4%
80 13
5.6%
82 2
 
0.9%
90 30
12.9%
95 1
 
0.4%
ValueCountFrequency (%)
2184 1
0.4%
939 1
0.4%
752 1
0.4%
550 1
0.4%
500 1
0.4%
483 1
0.4%
427 1
0.4%
410 1
0.4%
400 2
0.9%
325 1
0.4%

사용가능인원
Real number (ℝ)

HIGH CORRELATION 

Distinct69
Distinct (%)29.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13322.431
Minimum3125
Maximum136500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-14T18:02:32.037205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3125
5-th percentile4943.75
Q16250
median11111
Q316667
95-th percentile27716.95
Maximum136500
Range133375
Interquartile range (IQR)10417

Descriptive statistics

Standard deviation11358.959
Coefficient of variation (CV)0.85261912
Kurtosis60.335496
Mean13322.431
Median Absolute Deviation (MAD)4861
Skewness6.114264
Sum3090804
Variance1.2902596 × 108
MonotonicityNot monotonic
2024-03-14T18:02:32.494455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6250 20
 
8.6%
9375 16
 
6.9%
5625 16
 
6.9%
16667 15
 
6.5%
10000 14
 
6.0%
11111 13
 
5.6%
22222 11
 
4.7%
5000 11
 
4.7%
12500 9
 
3.9%
13333 9
 
3.9%
Other values (59) 98
42.2%
ValueCountFrequency (%)
3125 2
 
0.9%
3438 1
 
0.4%
3750 2
 
0.9%
4375 5
 
2.2%
4688 1
 
0.4%
4875 1
 
0.4%
5000 11
4.7%
5125 2
 
0.9%
5625 16
6.9%
6250 20
8.6%
ValueCountFrequency (%)
136500 1
 
0.4%
58688 1
 
0.4%
47000 1
 
0.4%
36111 1
 
0.4%
34375 1
 
0.4%
33333 2
0.9%
31250 1
 
0.4%
30188 1
 
0.4%
27778 3
1.3%
27667 1
 
0.4%

비상발전기 보유 대수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
197 
0
35 

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 (%)
1 197
84.9%
0 35
 
15.1%

Length

2024-03-14T18:02:32.906444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:02:33.198118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 197
84.9%
0 35
 
15.1%

Interactions

2024-03-14T18:02:11.738986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:10.311289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:11.025982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:11.984379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:10.540594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:11.258281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:12.232990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:10.772374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:02:11.486946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:02:33.390093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구읍면동지정 운영 여부시설종류용도개방여부급수능력사용가능인원비상발전기 보유 대수
연번1.0000.9090.9940.1680.5420.4450.8390.1580.1620.736
시군구0.9091.0000.9990.2380.6030.3920.8930.0000.2080.671
읍면동0.9940.9991.0000.9870.6990.6170.8530.9180.9390.877
지정 운영 여부0.1680.2380.9871.0000.0510.1560.0000.3920.4100.673
시설종류0.5420.6030.6990.0511.0000.1810.2270.0000.3630.136
용도0.4450.3920.6170.1560.1811.0000.0000.1650.6130.000
개방여부0.8390.8930.8530.0000.2270.0001.0000.0000.1010.000
급수능력0.1580.0000.9180.3920.0000.1650.0001.0000.9910.125
사용가능인원0.1620.2080.9390.4100.3630.6130.1010.9911.0000.281
비상발전기 보유 대수0.7360.6710.8770.6730.1360.0000.0000.1250.2811.000
2024-03-14T18:02:33.708820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정 운영 여부시군구시설종류개방여부용도비상발전기 보유 대수
지정 운영 여부1.0000.1800.0830.0000.1000.470
시군구0.1801.0000.4060.7240.2980.519
시설종류0.0830.4061.0000.3700.2970.223
개방여부0.0000.7240.3701.0000.0000.000
용도0.1000.2980.2970.0001.0000.000
비상발전기 보유 대수0.4700.5190.2230.0000.0001.000
2024-03-14T18:02:33.995137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번급수능력사용가능인원시군구지정 운영 여부시설종류용도개방여부비상발전기 보유 대수
연번1.000-0.0300.0100.6730.1260.3800.3360.6600.567
급수능력-0.0301.0000.8670.0000.2790.0000.1170.0000.089
사용가능인원0.0100.8671.0000.1040.2930.1630.4440.1180.198
시군구0.6730.0000.1041.0000.1800.4060.2980.7240.519
지정 운영 여부0.1260.2790.2930.1801.0000.0830.1000.0000.470
시설종류0.3800.0000.1630.4060.0831.0000.2970.3700.223
용도0.3360.1170.4440.2980.1000.2971.0000.0000.000
개방여부0.6600.0000.1180.7240.0000.3700.0001.0000.000
비상발전기 보유 대수0.5670.0890.1980.5190.4700.2230.0000.0001.000

Missing values

2024-03-14T18:02:12.623324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:02:13.236951image/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.
2024-03-14T18:02:13.639626image/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

연번시군구읍면동지정 운영 여부급수시설명시설종류용도개방여부도로명 주소지번 주소건축연도지정연도 (정부지원 제외)급수능력사용가능인원비상발전기 보유 대수
01전주시중앙동지정운영거북탕공공용음용수미개방전주시 완산구 대동로 653전주시 완산구 태평동 4971995-01-011995-01-01150166671
12전주시풍남동지정운영한벽문화관지자체생활용수미개방전주시 완산구 전주천동로 20전주시 완산구 교동 712003-02-072003-02-0715093751
23전주시풍남동지정운영동부화재공공용음용수미개방전주시 완산구 전라감영5길 10전주시 완산구 경원동1가 104321995-01-011995-01-01120133331
34전주시노송동지정운영기린연립정부지원음용수개방전주시 완산구 견훤로 10010전주시 완산구 중노송동 27번지 3호1986-12-201996-12-20160177781
45전주시동서학동지정운영전주교육대학교공공용생활용수미개방전주시 완산구 서학로 50전주시 완산구 동서학동 128번지2016-12-222016-12-2221841365001
56전주시서서학동지정운영전주남초등학교공공용음용수미개방전주시 완산구 장승배기로376전주시 완산구 서서학동 2771995-01-012000-03-02151167781
67전주시서서학동지정운영삼성아파트공공용생활용수미개방전주시 완산구 장승배기7길18전주시 완산구 서서학동 산2111996-01-012007-06-0515093751
78전주시중화산1동지정운영전주영상미디어고교공공용음용수미개방전주시 완산구 따박골2길 21전주시 완산구 중화산동2가 5462004-01-012004-01-01114126671
89전주시중화산1동지정운영신흥고교공공용생활용수미개방전주시 완산구 서원로 399전주시 완산구 중화산동1가 1882006-05-012006-05-0110062501
910전주시중화산1동지정운영우석대한방병원지자체생활용수미개방전주시 완산구 어은로 46전주시 완산구 중화산동2가 52006-05-012006-05-0111068751
연번시군구읍면동지정 운영 여부급수시설명시설종류용도개방여부도로명 주소지번 주소건축연도지정연도 (정부지원 제외)급수능력사용가능인원비상발전기 보유 대수
222223순창군복흥면지정운영복흥면 급수시설정부지원음용수미개방순창군 복흥면 추령로 1170순창군 복흥면 정산리 8531996-12-23<NA>250277781
223224순창군적성면지정운영적성면 급수시설정부지원음용수미개방순창군 적성면 적성로 121순창군 적성면 고원리 844141998-09-16<NA>145161111
224225고창군고창읍지정운영고창읍성정부지원음용수개방고창군 무장읍성길 45고창군 고창읍 읍내리 산91997-02-01<NA>105116671
225226고창군고창읍지정운영구동초등학교정부지원음용수개방고창군 월산길 6고창군 고창읍 월산리 5022000-10-06<NA>157174441
226227고창군고창읍지정운영복지회관정부지원음용수개방고창군 월곡14길 19고창군 고창읍 월곡리 6202002-11-06<NA>220244441
227228고창군고창읍지정운영보건소지자체음용수개방전라북도 고창군 고창읍 전봉준로 80고창군 고창읍 율계리 9612019-11-20<NA>200222220
228229부안군부안읍지정운영여성회관 급수시설정부지원음용수미개방부안군 부안읍 매창로 127부안군 부안읍 봉덕리 643651997-01-27<NA>120133331
229230부안군부안읍지정운영예술회관 급수시설정부지원생활용수미개방부안군 부안읍 예술회관길 11부안군 부안읍 서외리 455511998-01-18<NA>15093751
230231부안군부안읍지정운영(구)수도사업소 급수시설정부지원음용수미개방부안군 부안읍 수정길 98부안군 부안읍 봉덕리 58581999-01-18<NA>150166671
231232부안군부안읍지정운영스포츠파크 급수시설정부지원음용수미개방부안군 행안면 체육공원길 31부안군 부안읍 진동리 9332007-11-23<NA>140155561