Overview

Dataset statistics

Number of variables15
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory124.7 B

Variable types

Categorical10
Boolean1
Text2
Numeric2

Dataset

Description인천광역시 남동구 비상급수시설 현황에 대한 데이터로 시도, 시군구, 읍면동, 시설종류, 용도, 개방유무, 시설명, 소재지주소, 비상발전기 보유수, 분기별 수질검사결과, 일일급수능력, 일일사용가능인원 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3077740&srcSe=7661IVAWM27C61E190

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
수질검사(1분기) has constant value ""Constant
수질검사(2분기) has constant value ""Constant
수질검사(3분기) has constant value ""Constant
시설종류 is highly overall correlated with 용도 and 1 other fieldsHigh correlation
비상발전기 보유 수 is highly overall correlated with 시설종류 and 1 other fieldsHigh correlation
급수능력(일일 생산능력_톤) is highly overall correlated with 일일 사용가능인원 High correlation
일일 사용가능인원 is highly overall correlated with 급수능력(일일 생산능력_톤) and 2 other fieldsHigh correlation
읍면동 is highly overall correlated with 개방유무High correlation
용도 is highly overall correlated with 일일 사용가능인원 and 2 other fieldsHigh correlation
개방유무 is highly overall correlated with 읍면동High correlation
수질검사(4분기) is highly overall correlated with 일일 사용가능인원 High correlation
시설종류 is highly imbalanced (55.4%)Imbalance
수질검사(4분기) is highly imbalanced (90.1%)Imbalance

Reproduction

Analysis started2024-01-28 12:50:46.296705
Analysis finished2024-01-28 12:50:47.534097
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
인천광역시
78 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 78
100.0%

Length

2024-01-28T21:50:47.579912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:47.651437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 78
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
남동구
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 78
100.0%

Length

2024-01-28T21:50:47.729559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:47.799426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 78
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size756.0 B
남촌도림동
24 
장수서창동
15 
논현고잔동
6 
구월4동
5 
논현1동
5 
Other values (9)
23 

Length

Max length5
Median length5
Mean length4.5769231
Min length4

Unique

Unique4 ?
Unique (%)5.1%

Sample

1st row구월2동
2nd row간석3동
3rd row만수1동
4th row만수1동
5th row장수서창동

Common Values

ValueCountFrequency (%)
남촌도림동 24
30.8%
장수서창동 15
19.2%
논현고잔동 6
 
7.7%
구월4동 5
 
6.4%
논현1동 5
 
6.4%
구월2동 4
 
5.1%
만수1동 4
 
5.1%
구월3동 4
 
5.1%
만수2동 4
 
5.1%
논현2동 3
 
3.8%
Other values (4) 4
 
5.1%

Length

2024-01-28T21:50:47.875375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남촌도림동 24
30.8%
장수서창동 15
19.2%
논현고잔동 6
 
7.7%
구월4동 5
 
6.4%
논현1동 5
 
6.4%
구월2동 4
 
5.1%
만수1동 4
 
5.1%
구월3동 4
 
5.1%
만수2동 4
 
5.1%
논현2동 3
 
3.8%
Other values (4) 4
 
5.1%

시설종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
공공용
67 
정부지원
8 
지자체
 
3

Length

Max length4
Median length3
Mean length3.1025641
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 67
85.9%
정부지원 8
 
10.3%
지자체 3
 
3.8%

Length

2024-01-28T21:50:47.973322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:48.060949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 67
85.9%
정부지원 8
 
10.3%
지자체 3
 
3.8%

용도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
생활용수
64 
음용수
14 

Length

Max length4
Median length4
Mean length3.8205128
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활용수 64
82.1%
음용수 14
 
17.9%

Length

2024-01-28T21:50:48.146674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:48.226843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활용수 64
82.1%
음용수 14
 
17.9%

개방유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size210.0 B
True
41 
False
37 
ValueCountFrequency (%)
True 41
52.6%
False 37
47.4%
2024-01-28T21:50:48.294185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

민방위 비상급수시설 명
Text

Distinct74
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-01-28T21:50:48.478078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.2435897
Min length2

Characters and Unicode

Total characters487
Distinct characters165
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)93.6%

Sample

1st row구월체육공원
2nd row신명여고
3rd row삼환아파트
4th row만성중
5th row만의골
ValueCountFrequency (%)
농축수산과 5
 
6.2%
㈜멘토티엔씨 1
 
1.2%
김정곤(세원플레이팅 1
 
1.2%
성진레미콘 1
 
1.2%
장정수(한진열처리 1
 
1.2%
최현식(아이플렉르사우나 1
 
1.2%
최현식(아이플렉스사우나 1
 
1.2%
김은자 1
 
1.2%
하나님교회 1
 
1.2%
천영천 1
 
1.2%
Other values (66) 66
82.5%
2024-01-28T21:50:48.784635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 26
 
5.3%
) 25
 
5.1%
원 14
 
2.9%
수 13
 
2.7%
김 13
 
2.7%
이 12
 
2.5%
농 10
 
2.1%
천 9
 
1.8%
산 8
 
1.6%
나 8
 
1.6%
Other values (155) 349
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 429
88.1%
Open Punctuation 26
 
5.3%
Close Punctuation 25
 
5.1%
Decimal Number 3
 
0.6%
Space Separator 2
 
0.4%
Other Symbol 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 14
 
3.3%
수 13
 
3.0%
김 13
 
3.0%
이 12
 
2.8%
농 10
 
2.3%
천 9
 
2.1%
산 8
 
1.9%
나 8
 
1.9%
현 8
 
1.9%
공 8
 
1.9%
Other values (149) 326
76.0%
Decimal Number
ValueCountFrequency (%)
9 2
66.7%
2 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 431
88.5%
Common 56
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 14
 
3.2%
수 13
 
3.0%
김 13
 
3.0%
이 12
 
2.8%
농 10
 
2.3%
천 9
 
2.1%
산 8
 
1.9%
나 8
 
1.9%
현 8
 
1.9%
공 8
 
1.9%
Other values (150) 328
76.1%
Common
ValueCountFrequency (%)
( 26
46.4%
) 25
44.6%
2
 
3.6%
9 2
 
3.6%
2 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 429
88.1%
ASCII 56
 
11.5%
None 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 26
46.4%
) 25
44.6%
2
 
3.6%
9 2
 
3.6%
2 1
 
1.8%
Hangul
ValueCountFrequency (%)
원 14
 
3.3%
수 13
 
3.0%
김 13
 
3.0%
이 12
 
2.8%
농 10
 
2.3%
천 9
 
2.1%
산 8
 
1.9%
나 8
 
1.9%
현 8
 
1.9%
공 8
 
1.9%
Other values (149) 326
76.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지 도로명 주소
Text

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-01-28T21:50:48.979351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length11.141026
Min length6

Characters and Unicode

Total characters869
Distinct characters79
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

Unique76 ?
Unique (%)97.4%

Sample

1st row구월2동 구월로251
2nd row간석3동 용천로205번길42
3rd row만수1동 인주대로857
4th row만수1동 인주대로899
5th row장수동727-2
ValueCountFrequency (%)
도림동 9
 
5.8%
논현고잔동 6
 
3.9%
남촌동 6
 
3.9%
운연동 4
 
2.6%
장수동 4
 
2.6%
만수1동 4
 
2.6%
구월4동 4
 
2.6%
구월2동 4
 
2.6%
논현1동 4
 
2.6%
구월3동 3
 
1.9%
Other values (99) 107
69.0%
2024-01-28T21:50:49.295423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
 
8.9%
동 73
 
8.4%
2 62
 
7.1%
1 56
 
6.4%
로 54
 
6.2%
5 33
 
3.8%
4 30
 
3.5%
- 23
 
2.6%
3 23
 
2.6%
7 23
 
2.6%
Other values (69) 415
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 464
53.4%
Decimal Number 303
34.9%
Space Separator 77
 
8.9%
Dash Punctuation 23
 
2.6%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 73
 
15.7%
로 54
 
11.6%
수 22
 
4.7%
번 22
 
4.7%
논 21
 
4.5%
구 20
 
4.3%
길 19
 
4.1%
현 18
 
3.9%
고 16
 
3.4%
남 14
 
3.0%
Other values (55) 185
39.9%
Decimal Number
ValueCountFrequency (%)
2 62
20.5%
1 56
18.5%
5 33
10.9%
4 30
9.9%
3 23
 
7.6%
7 23
 
7.6%
8 21
 
6.9%
0 20
 
6.6%
6 19
 
6.3%
9 16
 
5.3%
Space Separator
ValueCountFrequency (%)
77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 464
53.4%
Common 405
46.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 73
 
15.7%
로 54
 
11.6%
수 22
 
4.7%
번 22
 
4.7%
논 21
 
4.5%
구 20
 
4.3%
길 19
 
4.1%
현 18
 
3.9%
고 16
 
3.4%
남 14
 
3.0%
Other values (55) 185
39.9%
Common
ValueCountFrequency (%)
77
19.0%
2 62
15.3%
1 56
13.8%
5 33
8.1%
4 30
 
7.4%
- 23
 
5.7%
3 23
 
5.7%
7 23
 
5.7%
8 21
 
5.2%
0 20
 
4.9%
Other values (4) 37
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 464
53.4%
ASCII 405
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
19.0%
2 62
15.3%
1 56
13.8%
5 33
8.1%
4 30
 
7.4%
- 23
 
5.7%
3 23
 
5.7%
7 23
 
5.7%
8 21
 
5.2%
0 20
 
4.9%
Other values (4) 37
9.1%
Hangul
ValueCountFrequency (%)
동 73
 
15.7%
로 54
 
11.6%
수 22
 
4.7%
번 22
 
4.7%
논 21
 
4.5%
구 20
 
4.3%
길 19
 
4.1%
현 18
 
3.9%
고 16
 
3.4%
남 14
 
3.0%
Other values (55) 185
39.9%

비상발전기 보유 수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
0
66 
1
12 

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 (%)
0 66
84.6%
1 12
 
15.4%

Length

2024-01-28T21:50:49.665279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:49.738001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 66
84.6%
1 12
 
15.4%

수질검사(1분기)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
적합
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적합 78
100.0%

Length

2024-01-28T21:50:49.813679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:49.887092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 78
100.0%

수질검사(2분기)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
적합
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적합 78
100.0%

Length

2024-01-28T21:50:49.958915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:50.038032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 78
100.0%

수질검사(3분기)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
적합
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적합 78
100.0%

Length

2024-01-28T21:50:50.121680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:50.203096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 78
100.0%

수질검사(4분기)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
적합
77 
부적합
 
1

Length

Max length3
Median length2
Mean length2.0128205
Min length2

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row적합
2nd row적합
3rd row부적합
4th row적합
5th row적합

Common Values

ValueCountFrequency (%)
적합 77
98.7%
부적합 1
 
1.3%

Length

2024-01-28T21:50:50.291816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:50:50.371887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 77
98.7%
부적합 1
 
1.3%

급수능력(일일 생산능력_톤)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.92308
Minimum30
Maximum510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-01-28T21:50:50.451397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile42.75
Q170
median86
Q3100
95-th percentile208.7
Maximum510
Range480
Interquartile range (IQR)30

Descriptive statistics

Standard deviation68.438003
Coefficient of variation (CV)0.66494323
Kurtosis16.6509
Mean102.92308
Median Absolute Deviation (MAD)14
Skewness3.4796345
Sum8028
Variance4683.7602
MonotonicityNot monotonic
2024-01-28T21:50:50.545037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
100 13
16.7%
60 6
 
7.7%
90 6
 
7.7%
86 5
 
6.4%
80 4
 
5.1%
30 4
 
5.1%
150 4
 
5.1%
170 3
 
3.8%
55 3
 
3.8%
83 3
 
3.8%
Other values (22) 27
34.6%
ValueCountFrequency (%)
30 4
5.1%
45 1
 
1.3%
55 3
3.8%
58 1
 
1.3%
60 6
7.7%
61 2
 
2.6%
65 1
 
1.3%
67 1
 
1.3%
70 2
 
2.6%
72 1
 
1.3%
ValueCountFrequency (%)
510 1
 
1.3%
300 1
 
1.3%
280 1
 
1.3%
258 1
 
1.3%
200 1
 
1.3%
170 3
3.8%
160 1
 
1.3%
150 4
5.1%
135 1
 
1.3%
125 1
 
1.3%

일일 사용가능인원
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7296.3077
Minimum1875
Maximum31875
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-01-28T21:50:50.638771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1875
5-th percentile3333
Q14406.25
median5531
Q39375
95-th percentile17541.55
Maximum31875
Range30000
Interquartile range (IQR)4968.75

Descriptive statistics

Standard deviation4878.2046
Coefficient of variation (CV)0.66858538
Kurtosis7.9095912
Mean7296.3077
Median Absolute Deviation (MAD)1750
Skewness2.3938875
Sum569112
Variance23796881
MonotonicityNot monotonic
2024-01-28T21:50:50.737335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
11111 7
 
9.0%
6250 6
 
7.7%
5625 6
 
7.7%
3750 5
 
6.4%
5375 4
 
5.1%
5000 4
 
5.1%
5125 3
 
3.8%
9375 3
 
3.8%
3437 3
 
3.8%
5187 3
 
3.8%
Other values (28) 34
43.6%
ValueCountFrequency (%)
1875 2
 
2.6%
2812 1
 
1.3%
3333 2
 
2.6%
3437 3
3.8%
3625 1
 
1.3%
3750 5
6.4%
3812 2
 
2.6%
4062 1
 
1.3%
4187 1
 
1.3%
4375 2
 
2.6%
ValueCountFrequency (%)
31875 1
 
1.3%
18888 1
 
1.3%
18750 1
 
1.3%
17777 1
 
1.3%
17500 1
 
1.3%
16666 1
 
1.3%
16125 1
 
1.3%
12500 1
 
1.3%
11111 7
9.0%
10625 2
 
2.6%

Interactions

2024-01-28T21:50:47.140807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:50:47.022460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:50:47.202171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:50:47.077984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T21:50:50.813192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동시설종류용도개방유무민방위 비상급수시설 명소재지 도로명 주소비상발전기 보유 수수질검사(4분기)급수능력(일일 생산능력_톤)일일 사용가능인원
읍면동1.0000.6340.3980.8330.9841.0000.3830.3800.5260.443
시설종류0.6341.0000.3540.2171.0001.0000.7020.1830.0000.495
용도0.3980.3541.0000.1381.0001.0000.7900.0000.0000.607
개방유무0.8330.2170.1381.0001.0001.0000.4230.0000.1660.206
민방위 비상급수시설 명0.9841.0001.0001.0001.0000.9951.0001.0000.9860.983
소재지 도로명 주소1.0001.0001.0001.0000.9951.0001.0001.0000.0000.000
비상발전기 보유 수0.3830.7020.7900.4231.0001.0001.0000.0000.1930.469
수질검사(4분기)0.3800.1830.0000.0001.0001.0000.0001.0000.1460.623
급수능력(일일 생산능력_톤)0.5260.0000.0000.1660.9860.0000.1930.1461.0000.977
일일 사용가능인원0.4430.4950.6070.2060.9830.0000.4690.6230.9771.000
2024-01-28T21:50:50.922629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류읍면동용도비상발전기 보유 수개방유무수질검사(4분기)
시설종류1.0000.4120.5600.9430.3520.298
읍면동0.4121.0000.2830.2720.6240.269
용도0.5600.2831.0000.5800.0870.000
비상발전기 보유 수0.9430.2720.5801.0000.2780.000
개방유무0.3520.6240.0870.2781.0000.000
수질검사(4분기)0.2980.2690.0000.0000.0001.000
2024-01-28T21:50:51.015076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수능력(일일 생산능력_톤)일일 사용가능인원읍면동시설종류용도개방유무비상발전기 보유 수수질검사(4분기)
급수능력(일일 생산능력_톤)1.0000.9470.2110.0270.0000.1820.2090.148
일일 사용가능인원0.9471.0000.1690.3750.6340.2290.4910.649
읍면동0.2110.1691.0000.4120.2830.6240.2720.269
시설종류0.0270.3750.4121.0000.5600.3520.9430.298
용도0.0000.6340.2830.5601.0000.0870.5800.000
개방유무0.1820.2290.6240.3520.0871.0000.2780.000
비상발전기 보유 수0.2090.4910.2720.9430.5800.2781.0000.000
수질검사(4분기)0.1480.6490.2690.2980.0000.0000.0001.000

Missing values

2024-01-28T21:50:47.299938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T21:50:47.460356image/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

시도시군구읍면동시설종류용도개방유무민방위 비상급수시설 명소재지 도로명 주소비상발전기 보유 수수질검사(1분기)수질검사(2분기)수질검사(3분기)수질검사(4분기)급수능력(일일 생산능력_톤)일일 사용가능인원
0인천광역시남동구구월2동지자체음용수Y구월체육공원구월2동 구월로2511적합적합적합적합10011111
1인천광역시남동구간석3동정부지원음용수Y신명여고간석3동 용천로205번길421적합적합적합적합10011111
2인천광역시남동구만수1동정부지원음용수Y삼환아파트만수1동 인주대로8571적합적합적합부적합15016666
3인천광역시남동구만수1동정부지원음용수Y만성중만수1동 인주대로8991적합적합적합적합17018888
4인천광역시남동구장수서창동정부지원음용수Y만의골장수동727-21적합적합적합적합16017777
5인천광역시남동구남촌도림동정부지원음용수Y남촌공원남촌동 남촌동로26번길201적합적합적합적합10011111
6인천광역시남동구장수서창동정부지원음용수Y서창어린이공원 내서창동 552-41적합적합적합적합10011111
7인천광역시남동구장수서창동공공용음용수N김현환장수동 만의골로2041적합적합적합적합869555
8인천광역시남동구장수서창동공공용음용수Y9공수부대장수동52-20적합적합적합적합10011111
9인천광역시남동구장수서창동공공용음용수N김순철운연동 수인로35710적합적합적합적합606666
시도시군구읍면동시설종류용도개방유무민방위 비상급수시설 명소재지 도로명 주소비상발전기 보유 수수질검사(1분기)수질검사(2분기)수질검사(3분기)수질검사(4분기)급수능력(일일 생산능력_톤)일일 사용가능인원
68인천광역시남동구남촌도림동공공용생활용수Y남촌동 주말농장남촌동510-80적합적합적합적합1006250
69인천광역시남동구남촌도림동공공용생활용수N김용웅도림동 343번지5호0적합적합적합적합301875
70인천광역시남동구논현1동공공용생활용수N김번은봉로419번길 210적합적합적합적합583625
71인천광역시남동구남촌도림동공공용생활용수N이경미도림북로19번길 12-260적합적합적합적합301875
72인천광역시남동구장수서창동공공용생활용수Y정인상운연동 33번지 2호0적합적합적합적합452812
73인천광역시남동구남촌도림동공공용생활용수N안미영(메트로다솜주유소)논고개로 2530적합적합적합적합553437
74인천광역시남동구만수2동공공용생활용수N강종훈수현로 1170적합적합적합적합553437
75인천광역시남동구장수서창동공공용생활용수N배윤영(남원참추어탕)연락골로 320적합적합적합적합603750
76인천광역시남동구구월4동공공용생활용수N용석권경신상로 680적합적합적합적합805000
77인천광역시남동구장수서창동공공용생활용수N최영수운연동 850적합적합적합적합825125