Overview

Dataset statistics

Number of variables11
Number of observations5248
Missing cells20664
Missing cells (%)35.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory481.9 KiB
Average record size in memory94.0 B

Variable types

Numeric5
Categorical5
DateTime1

Dataset

Description부산광역시상수도사업본부_수용가정보시스템_물복지사업정보_20220131
Author부산광역시 상수도사업본부
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15100356

Alerts

직결급수공사종류 is highly overall correlated with 구분High correlation
교체대상여부 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
진단일자 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
구분 is highly overall correlated with 구경(mm) and 6 other fieldsHigh correlation
일련번호 is highly overall correlated with 구분High correlation
연번 is highly overall correlated with 교체대상여부 and 1 other fieldsHigh correlation
공사비 is highly overall correlated with 지원비 and 2 other fieldsHigh correlation
구경(mm) is highly overall correlated with 세대원수 and 1 other fieldsHigh correlation
지원비 is highly overall correlated with 공사비 and 1 other fieldsHigh correlation
세대원수 is highly overall correlated with 구경(mm) and 1 other fieldsHigh correlation
구분 is highly imbalanced (86.0%)Imbalance
교체대상여부 is highly imbalanced (92.4%)Imbalance
진단일자 is highly imbalanced (96.6%)Imbalance
일련번호 is highly imbalanced (83.0%)Imbalance
공사비 has 5092 (97.0%) missing valuesMissing
설치일자 has 74 (1.4%) missing valuesMissing
구경(mm) has 5166 (98.4%) missing valuesMissing
지원비 has 5166 (98.4%) missing valuesMissing
세대원수 has 5166 (98.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:20:46.623064
Analysis finished2023-12-10 16:20:50.599226
Duration3.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct5248
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2624.5
Minimum1
Maximum5248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2023-12-11T01:20:50.694259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile263.35
Q11312.75
median2624.5
Q33936.25
95-th percentile4985.65
Maximum5248
Range5247
Interquartile range (IQR)2623.5

Descriptive statistics

Standard deviation1515.1114
Coefficient of variation (CV)0.57729527
Kurtosis-1.2
Mean2624.5
Median Absolute Deviation (MAD)1312
Skewness0
Sum13773376
Variance2295562.7
MonotonicityStrictly increasing
2023-12-11T01:20:50.885081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3507 1
 
< 0.1%
3505 1
 
< 0.1%
3504 1
 
< 0.1%
3503 1
 
< 0.1%
3502 1
 
< 0.1%
3501 1
 
< 0.1%
3500 1
 
< 0.1%
3499 1
 
< 0.1%
3498 1
 
< 0.1%
Other values (5238) 5238
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
5248 1
< 0.1%
5247 1
< 0.1%
5246 1
< 0.1%
5245 1
< 0.1%
5244 1
< 0.1%
5243 1
< 0.1%
5242 1
< 0.1%
5241 1
< 0.1%
5240 1
< 0.1%
5239 1
< 0.1%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.1 KiB
물복지-직결급수공사
5092 
물복지-옥내노후관교체
 
82
물복지-내시경진단
 
74

Length

Max length11
Median length10
Mean length10.001524
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row물복지-내시경진단
2nd row물복지-내시경진단
3rd row물복지-내시경진단
4th row물복지-내시경진단
5th row물복지-내시경진단

Common Values

ValueCountFrequency (%)
물복지-직결급수공사 5092
97.0%
물복지-옥내노후관교체 82
 
1.6%
물복지-내시경진단 74
 
1.4%

Length

2023-12-11T01:20:51.040787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:51.491482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물복지-직결급수공사 5092
97.0%
물복지-옥내노후관교체 82
 
1.6%
물복지-내시경진단 74
 
1.4%

교체대상여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.1 KiB
<NA>
5174 
대상
 
50
비대상
 
24

Length

Max length4
Median length4
Mean length3.976372
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5174
98.6%
대상 50
 
1.0%
비대상 24
 
0.5%

Length

2023-12-11T01:20:51.619183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:51.736744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5174
98.6%
대상 50
 
1.0%
비대상 24
 
0.5%

공사비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct85
Distinct (%)54.5%
Missing5092
Missing (%)97.0%
Infinite0
Infinite (%)0.0%
Mean14882418
Minimum0
Maximum2.24 × 108
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2023-12-11T01:20:51.857809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35000
Q169520
median204000
Q34512500
95-th percentile96750000
Maximum2.24 × 108
Range2.24 × 108
Interquartile range (IQR)4442980

Descriptive statistics

Standard deviation35263211
Coefficient of variation (CV)2.3694544
Kurtosis11.76004
Mean14882418
Median Absolute Deviation (MAD)168000
Skewness3.2278413
Sum2.3216572 × 109
Variance1.2434941 × 1015
MonotonicityNot monotonic
2023-12-11T01:20:51.995828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69520 21
 
0.4%
175000 16
 
0.3%
2500000 11
 
0.2%
210000 9
 
0.2%
190000 8
 
0.2%
197000 7
 
0.1%
8000000 2
 
< 0.1%
0 2
 
< 0.1%
35000000 2
 
< 0.1%
40000000 2
 
< 0.1%
Other values (75) 76
 
1.4%
(Missing) 5092
97.0%
ValueCountFrequency (%)
0 2
< 0.1%
13152 1
< 0.1%
18000 1
< 0.1%
18800 1
< 0.1%
28000 1
< 0.1%
29870 1
< 0.1%
32000 1
< 0.1%
36000 2
< 0.1%
39000 1
< 0.1%
42800 1
< 0.1%
ValueCountFrequency (%)
224000000 1
< 0.1%
177650000 1
< 0.1%
129700000 1
< 0.1%
124960000 1
< 0.1%
115000000 1
< 0.1%
110209000 1
< 0.1%
108000000 1
< 0.1%
102000000 1
< 0.1%
95000000 1
< 0.1%
90400000 1
< 0.1%

진단일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct29
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size41.1 KiB
<NA>
5174 
2021-04-06
 
17
2021-12-10
 
13
2021-04-26
 
7
2021-09-06
 
4
Other values (24)
 
33

Length

Max length10
Median length4
Mean length4.0846037
Min length4

Unique

Unique17 ?
Unique (%)0.3%

Sample

1st row2021-12-10
2nd row2021-12-10
3rd row2021-12-10
4th row2021-04-26
5th row2021-04-28

Common Values

ValueCountFrequency (%)
<NA> 5174
98.6%
2021-04-06 17
 
0.3%
2021-12-10 13
 
0.2%
2021-04-26 7
 
0.1%
2021-09-06 4
 
0.1%
2021-08-05 3
 
0.1%
2021-07-09 3
 
0.1%
2021-04-28 2
 
< 0.1%
2021-04-19 2
 
< 0.1%
2021-07-21 2
 
< 0.1%
Other values (19) 21
 
0.4%

Length

2023-12-11T01:20:52.123832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5174
98.6%
2021-04-06 17
 
0.3%
2021-12-10 13
 
0.2%
2021-04-26 7
 
0.1%
2021-09-06 4
 
0.1%
2021-08-05 3
 
0.1%
2021-07-09 3
 
0.1%
2021-07-21 2
 
< 0.1%
2021-07-02 2
 
< 0.1%
2021-04-20 2
 
< 0.1%
Other values (19) 21
 
0.4%

설치일자
Date

MISSING 

Distinct362
Distinct (%)7.0%
Missing74
Missing (%)1.4%
Memory size41.1 KiB
Minimum2021-01-04 00:00:00
Maximum2022-05-17 00:00:00
2023-12-11T01:20:52.247487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:52.362086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구경(mm)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)7.3%
Missing5166
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean32.621951
Minimum15
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2023-12-11T01:20:52.447565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile15
Q115
median15
Q350
95-th percentile99
Maximum100
Range85
Interquartile range (IQR)35

Descriptive statistics

Standard deviation24.459914
Coefficient of variation (CV)0.74979925
Kurtosis1.484658
Mean32.621951
Median Absolute Deviation (MAD)0
Skewness1.459822
Sum2675
Variance598.28741
MonotonicityNot monotonic
2023-12-11T01:20:52.525629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
15 44
 
0.8%
50 15
 
0.3%
40 10
 
0.2%
100 5
 
0.1%
25 5
 
0.1%
80 3
 
0.1%
(Missing) 5166
98.4%
ValueCountFrequency (%)
15 44
0.8%
25 5
 
0.1%
40 10
 
0.2%
50 15
 
0.3%
80 3
 
0.1%
100 5
 
0.1%
ValueCountFrequency (%)
100 5
 
0.1%
80 3
 
0.1%
50 15
 
0.3%
40 10
 
0.2%
25 5
 
0.1%
15 44
0.8%

지원비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct64
Distinct (%)78.0%
Missing5166
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean26699840
Minimum9393
Maximum2.24 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2023-12-11T01:20:52.629847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9393
5-th percentile29976.5
Q1102500
median3000000
Q336000000
95-th percentile1.1465 × 108
Maximum2.24 × 108
Range2.2399061 × 108
Interquartile range (IQR)35897500

Descriptive statistics

Standard deviation43901449
Coefficient of variation (CV)1.6442589
Kurtosis5.347554
Mean26699840
Median Absolute Deviation (MAD)2969065
Skewness2.2059334
Sum2.1893869 × 109
Variance1.9273372 × 1015
MonotonicityNot monotonic
2023-12-11T01:20:52.744535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 7
 
0.1%
2000000 5
 
0.1%
1200000 3
 
0.1%
8000000 2
 
< 0.1%
50000000 2
 
< 0.1%
36000000 2
 
< 0.1%
40000000 2
 
< 0.1%
90000000 2
 
< 0.1%
35000000 2
 
< 0.1%
18000 1
 
< 0.1%
Other values (54) 54
 
1.0%
(Missing) 5166
98.4%
ValueCountFrequency (%)
9393 1
< 0.1%
18000 1
< 0.1%
18800 1
< 0.1%
28000 1
< 0.1%
29870 1
< 0.1%
32000 1
< 0.1%
33000 1
< 0.1%
36000 1
< 0.1%
39000 1
< 0.1%
42000 1
< 0.1%
ValueCountFrequency (%)
224000000 1
< 0.1%
170000000 1
< 0.1%
125000000 1
< 0.1%
124960000 1
< 0.1%
115000000 1
< 0.1%
108000000 1
< 0.1%
102000000 1
< 0.1%
95000000 1
< 0.1%
90000000 2
< 0.1%
84000000 1
< 0.1%

세대원수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct48
Distinct (%)58.5%
Missing5166
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean56.134146
Minimum0
Maximum1150
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size46.3 KiB
2023-12-11T01:20:52.856413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median33.5
Q357
95-th percentile131.65
Maximum1150
Range1150
Interquartile range (IQR)53

Descriptive statistics

Standard deviation130.94535
Coefficient of variation (CV)2.3327219
Kurtosis61.705801
Mean56.134146
Median Absolute Deviation (MAD)29.5
Skewness7.4120841
Sum4603
Variance17146.685
MonotonicityNot monotonic
2023-12-11T01:20:52.978691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
3 8
 
0.2%
1 5
 
0.1%
2 5
 
0.1%
36 4
 
0.1%
50 4
 
0.1%
90 2
 
< 0.1%
18 2
 
< 0.1%
12 2
 
< 0.1%
8 2
 
< 0.1%
20 2
 
< 0.1%
Other values (38) 46
 
0.9%
(Missing) 5166
98.4%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 5
0.1%
2 5
0.1%
3 8
0.2%
4 2
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
8 2
 
< 0.1%
11 1
 
< 0.1%
12 2
 
< 0.1%
ValueCountFrequency (%)
1150 1
< 0.1%
224 1
< 0.1%
198 1
< 0.1%
170 1
< 0.1%
132 1
< 0.1%
125 2
< 0.1%
120 1
< 0.1%
110 1
< 0.1%
108 1
< 0.1%
102 1
< 0.1%

일련번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.1 KiB
1
4983 
<NA>
 
156
2
 
108
3
 
1

Length

Max length4
Median length1
Mean length1.0891768
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 4983
95.0%
<NA> 156
 
3.0%
2 108
 
2.1%
3 1
 
< 0.1%

Length

2023-12-11T01:20:53.090924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:53.179575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4983
95.0%
na 156
 
3.0%
2 108
 
2.1%
3 1
 
< 0.1%

직결급수공사종류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size41.1 KiB
물탱크철거,감압변 설치
2413 
물탱크 철거
1315 
물탱크철거,감압보호통 설치
821 
감압변 설치(통내)
324 
<NA>
 
156
Other values (4)
 
219

Length

Max length14
Median length12
Mean length10.160442
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물탱크철거,감압변 설치 2413
46.0%
물탱크 철거 1315
25.1%
물탱크철거,감압보호통 설치 821
 
15.6%
감압변 설치(통내) 324
 
6.2%
<NA> 156
 
3.0%
직결연결 120
 
2.3%
감압보호통 설치 68
 
1.3%
기타 27
 
0.5%
감압변 설치(통외) 4
 
0.1%

Length

2023-12-11T01:20:53.303596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:53.420981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설치 3302
32.4%
물탱크철거,감압변 2413
23.7%
물탱크 1315
 
12.9%
철거 1315
 
12.9%
물탱크철거,감압보호통 821
 
8.1%
감압변 328
 
3.2%
설치(통내 324
 
3.2%
na 156
 
1.5%
직결연결 120
 
1.2%
감압보호통 68
 
0.7%
Other values (2) 31
 
0.3%

Interactions

2023-12-11T01:20:49.505345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:47.541769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.122502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.584867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.035703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.612402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:47.676528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.223601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.697825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.138591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.719621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:47.809216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.317468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.799669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.234025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.814749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:47.909212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.409483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.878048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.331566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.920303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:47.999548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.492856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:48.955325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:49.419443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:20:53.510158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분교체대상여부공사비진단일자구경(mm)지원비세대원수일련번호직결급수공사종류
연번1.0000.524NaNNaNNaNNaNNaNNaN0.0660.164
구분0.5241.000NaN0.515NaNNaNNaNNaNNaNNaN
교체대상여부NaNNaN1.000NaN0.915NaNNaNNaNNaNNaN
공사비NaN0.515NaN1.000NaN0.6351.0000.698NaNNaN
진단일자NaNNaN0.915NaN1.000NaNNaNNaNNaNNaN
구경(mm)NaNNaNNaN0.635NaN1.0000.6360.844NaNNaN
지원비NaNNaNNaN1.000NaN0.6361.0000.697NaNNaN
세대원수NaNNaNNaN0.698NaN0.8440.6971.000NaNNaN
일련번호0.066NaNNaNNaNNaNNaNNaNNaN1.0000.414
직결급수공사종류0.164NaNNaNNaNNaNNaNNaNNaN0.4141.000
2023-12-11T01:20:53.638659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직결급수공사종류교체대상여부진단일자구분일련번호
직결급수공사종류1.000NaNNaN1.0000.290
교체대상여부NaN1.0000.6291.000NaN
진단일자NaN0.6291.0001.000NaN
구분1.0001.0001.0001.0001.000
일련번호0.290NaNNaN1.0001.000
2023-12-11T01:20:53.767966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번공사비구경(mm)지원비세대원수구분교체대상여부진단일자일련번호직결급수공사종류
연번1.0000.3540.0410.023-0.0800.3691.0001.0000.0390.079
공사비0.3541.0000.4350.9950.2660.3801.0001.0000.0000.000
구경(mm)0.0410.4351.0000.4320.5411.0000.0000.0000.0000.000
지원비0.0230.9950.4321.0000.2701.0000.0000.0000.0000.000
세대원수-0.0800.2660.5410.2701.0001.0000.0000.0000.0000.000
구분0.3690.3801.0001.0001.0001.0001.0001.0001.0001.000
교체대상여부1.0001.0000.0000.0000.0001.0001.0000.6290.0000.000
진단일자1.0001.0000.0000.0000.0001.0000.6291.0000.0000.000
일련번호0.0390.0000.0000.0000.0001.0000.0000.0001.0000.290
직결급수공사종류0.0790.0000.0000.0000.0001.0000.0000.0000.2901.000

Missing values

2023-12-11T01:20:50.070840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:20:50.268913image/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.
2023-12-11T01:20:50.460974image/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

연번구분교체대상여부공사비진단일자설치일자구경(mm)지원비세대원수일련번호직결급수공사종류
01물복지-내시경진단대상25000002021-12-10<NA><NA><NA><NA><NA><NA>
12물복지-내시경진단대상25000002021-12-10<NA><NA><NA><NA><NA><NA>
23물복지-내시경진단대상02021-12-10<NA><NA><NA><NA><NA><NA>
34물복지-내시경진단대상1970002021-04-26<NA><NA><NA><NA><NA><NA>
45물복지-내시경진단대상1750002021-04-28<NA><NA><NA><NA><NA><NA>
56물복지-내시경진단대상1970002021-04-29<NA><NA><NA><NA><NA><NA>
67물복지-내시경진단대상1750002021-04-19<NA><NA><NA><NA><NA><NA>
78물복지-내시경진단대상1750002021-04-20<NA><NA><NA><NA><NA><NA>
89물복지-내시경진단대상1750002021-05-28<NA><NA><NA><NA><NA><NA>
910물복지-내시경진단대상1750002021-04-26<NA><NA><NA><NA><NA><NA>
연번구분교체대상여부공사비진단일자설치일자구경(mm)지원비세대원수일련번호직결급수공사종류
52385239물복지-직결급수공사<NA><NA><NA>2022-02-28<NA><NA><NA>1물탱크철거,감압변 설치
52395240물복지-직결급수공사<NA><NA><NA>2022-02-28<NA><NA><NA>1물탱크철거,감압변 설치
52405241물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
52415242물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압변 설치
52425243물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
52435244물복지-직결급수공사<NA><NA><NA>2022-02-25<NA><NA><NA>1물탱크철거,감압변 설치
52445245물복지-직결급수공사<NA><NA><NA>2022-02-25<NA><NA><NA>1직결연결
52455246물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
52465247물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
52475248물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크 철거