Overview

Dataset statistics

Number of variables11
Number of observations3120
Missing cells15410
Missing cells (%)44.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory286.5 KiB
Average record size in memory94.0 B

Variable types

Numeric5
Categorical4
DateTime2

Dataset

Description부산광역시 상수도사업본부에서 상하수도 요금 계산 및 징수를 위해 운영하는 수용가정보시스템에 사용되는 물복지사업 정보 자료입니다.(구분, 교체대상여부, 공사비, 지원비 등)
Author부산광역시 상수도사업본부
URLhttps://www.data.go.kr/data/15100356/fileData.do

Alerts

구분 is highly overall correlated with 구경(mm) and 5 other fieldsHigh correlation
직결급수공사종류 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
교체대상여부 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
일련번호 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 교체대상여부High correlation
공사비 is highly overall correlated with 구경(mm) and 3 other fieldsHigh correlation
구경(mm) is highly overall correlated with 공사비 and 3 other fieldsHigh correlation
지원비 is highly overall correlated with 공사비 and 3 other fieldsHigh correlation
세대원수 is highly overall correlated with 공사비 and 3 other fieldsHigh correlation
구분 is highly imbalanced (91.2%)Imbalance
교체대상여부 is highly imbalanced (97.8%)Imbalance
일련번호 is highly imbalanced (53.1%)Imbalance
공사비 has 3065 (98.2%) missing valuesMissing
진단일자 has 3110 (99.7%) missing valuesMissing
구경(mm) has 3075 (98.6%) missing valuesMissing
지원비 has 3075 (98.6%) missing valuesMissing
세대원수 has 3075 (98.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:55:19.163369
Analysis finished2024-03-14 12:55:28.296567
Duration9.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1560.5
Minimum1
Maximum3120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.5 KiB
2024-03-14T21:55:28.532931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile156.95
Q1780.75
median1560.5
Q32340.25
95-th percentile2964.05
Maximum3120
Range3119
Interquartile range (IQR)1559.5

Descriptive statistics

Standard deviation900.81075
Coefficient of variation (CV)0.57725777
Kurtosis-1.2
Mean1560.5
Median Absolute Deviation (MAD)780
Skewness0
Sum4868760
Variance811460
MonotonicityStrictly increasing
2024-03-14T21:55:28.975467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2098 1
 
< 0.1%
2076 1
 
< 0.1%
2077 1
 
< 0.1%
2078 1
 
< 0.1%
2079 1
 
< 0.1%
2080 1
 
< 0.1%
2081 1
 
< 0.1%
2082 1
 
< 0.1%
2083 1
 
< 0.1%
Other values (3110) 3110
99.7%
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 (%)
3120 1
< 0.1%
3119 1
< 0.1%
3118 1
< 0.1%
3117 1
< 0.1%
3116 1
< 0.1%
3115 1
< 0.1%
3114 1
< 0.1%
3113 1
< 0.1%
3112 1
< 0.1%
3111 1
< 0.1%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.5 KiB
물복지-직결급수공사
3065 
물복지-옥내노후관교체
 
45
물복지-내시경진단
 
10

Length

Max length11
Median length10
Mean length10.011218
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 3065
98.2%
물복지-옥내노후관교체 45
 
1.4%
물복지-내시경진단 10
 
0.3%

Length

2024-03-14T21:55:29.443929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:55:29.737816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물복지-직결급수공사 3065
98.2%
물복지-옥내노후관교체 45
 
1.4%
물복지-내시경진단 10
 
0.3%

교체대상여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.5 KiB
<NA>
3110 
비대상
 
6
대상
 
4

Length

Max length4
Median length4
Mean length3.9955128
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3110
99.7%
비대상 6
 
0.2%
대상 4
 
0.1%

Length

2024-03-14T21:55:30.055825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:55:30.404243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3110
99.7%
비대상 6
 
0.2%
대상 4
 
0.1%

공사비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)81.8%
Missing3065
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean24825288
Minimum0
Maximum2.04 × 108
Zeros10
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size27.5 KiB
2024-03-14T21:55:30.706183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12850
median4000000
Q343000000
95-th percentile72236800
Maximum2.04 × 108
Range2.04 × 108
Interquartile range (IQR)42997150

Descriptive statistics

Standard deviation38891470
Coefficient of variation (CV)1.566607
Kurtosis9.4435442
Mean24825288
Median Absolute Deviation (MAD)4000000
Skewness2.7143462
Sum1.3653908 × 109
Variance1.5125464 × 1015
MonotonicityNot monotonic
2024-03-14T21:55:31.105180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 10
 
0.3%
48000000 2
 
0.1%
39000000 1
 
< 0.1%
50000000 1
 
< 0.1%
5830000 1
 
< 0.1%
17300000 1
 
< 0.1%
160000000 1
 
< 0.1%
30860000 1
 
< 0.1%
5500000 1
 
< 0.1%
52000000 1
 
< 0.1%
Other values (35) 35
 
1.1%
(Missing) 3065
98.2%
ValueCountFrequency (%)
0 10
0.3%
1616 1
 
< 0.1%
2100 1
 
< 0.1%
2310 1
 
< 0.1%
2730 1
 
< 0.1%
2970 1
 
< 0.1%
3350 1
 
< 0.1%
3466 1
 
< 0.1%
40800 1
 
< 0.1%
45500 1
 
< 0.1%
ValueCountFrequency (%)
204000000 1
< 0.1%
160000000 1
< 0.1%
76140000 1
< 0.1%
70564000 1
< 0.1%
70000000 1
< 0.1%
62200000 1
< 0.1%
52000000 1
< 0.1%
50700000 1
< 0.1%
50000000 1
< 0.1%
49000000 1
< 0.1%

진단일자
Date

MISSING 

Distinct7
Distinct (%)70.0%
Missing3110
Missing (%)99.7%
Memory size24.5 KiB
Minimum2023-01-09 00:00:00
Maximum2023-03-20 00:00:00
2024-03-14T21:55:31.407881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:31.682943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

설치일자
Date

Distinct256
Distinct (%)8.2%
Missing10
Missing (%)0.3%
Memory size24.5 KiB
Minimum2023-01-04 00:00:00
Maximum2023-12-28 00:00:00
2024-03-14T21:55:31.957053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:32.198049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구경(mm)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)15.6%
Missing3075
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean29.888889
Minimum15
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.5 KiB
2024-03-14T21:55:32.517653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile15
Q115
median15
Q340
95-th percentile74
Maximum150
Range135
Interquartile range (IQR)25

Descriptive statistics

Standard deviation25.214734
Coefficient of variation (CV)0.84361565
Kurtosis11.141348
Mean29.888889
Median Absolute Deviation (MAD)0
Skewness2.8789268
Sum1345
Variance635.78283
MonotonicityNot monotonic
2024-03-14T21:55:32.894279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
15 26
 
0.8%
40 10
 
0.3%
50 4
 
0.1%
80 2
 
0.1%
25 1
 
< 0.1%
20 1
 
< 0.1%
150 1
 
< 0.1%
(Missing) 3075
98.6%
ValueCountFrequency (%)
15 26
0.8%
20 1
 
< 0.1%
25 1
 
< 0.1%
40 10
 
0.3%
50 4
 
0.1%
80 2
 
0.1%
150 1
 
< 0.1%
ValueCountFrequency (%)
150 1
 
< 0.1%
80 2
 
0.1%
50 4
 
0.1%
40 10
 
0.3%
25 1
 
< 0.1%
20 1
 
< 0.1%
15 26
0.8%

지원비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)62.2%
Missing3075
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean29131683
Minimum1200
Maximum2.04 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.5 KiB
2024-03-14T21:55:33.263667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile1200
Q11200000
median16000000
Q348000000
95-th percentile69400000
Maximum2.04 × 108
Range2.039988 × 108
Interquartile range (IQR)46800000

Descriptive statistics

Standard deviation40724328
Coefficient of variation (CV)1.3979394
Kurtosis8.6126519
Mean29131683
Median Absolute Deviation (MAD)15998800
Skewness2.5871672
Sum1.3109257 × 109
Variance1.6584709 × 1015
MonotonicityNot monotonic
2024-03-14T21:55:33.681680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1200000 5
 
0.2%
1200 5
 
0.2%
2000000 3
 
0.1%
30000000 3
 
0.1%
3000000 3
 
0.1%
48000000 3
 
0.1%
49000000 2
 
0.1%
50000000 1
 
< 0.1%
52000000 1
 
< 0.1%
6000000 1
 
< 0.1%
Other values (18) 18
 
0.6%
(Missing) 3075
98.6%
ValueCountFrequency (%)
1200 5
0.2%
2000 1
 
< 0.1%
2731 1
 
< 0.1%
40000 1
 
< 0.1%
45000 1
 
< 0.1%
1200000 5
0.2%
2000000 3
0.1%
3000000 3
0.1%
5830000 1
 
< 0.1%
6000000 1
 
< 0.1%
ValueCountFrequency (%)
204000000 1
 
< 0.1%
160000000 1
 
< 0.1%
70000000 1
 
< 0.1%
67000000 1
 
< 0.1%
60000000 1
 
< 0.1%
54000000 1
 
< 0.1%
52000000 1
 
< 0.1%
50000000 1
 
< 0.1%
49000000 2
0.1%
48000000 3
0.1%

세대원수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)48.9%
Missing3075
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean28.133333
Minimum1
Maximum204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.5 KiB
2024-03-14T21:55:34.069967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median17
Q348
95-th percentile67.8
Maximum204
Range203
Interquartile range (IQR)46

Descriptive statistics

Standard deviation35.304262
Coefficient of variation (CV)1.2548908
Kurtosis13.152676
Mean28.133333
Median Absolute Deviation (MAD)16
Skewness2.9012958
Sum1266
Variance1246.3909
MonotonicityNot monotonic
2024-03-14T21:55:34.466250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 10
 
0.3%
3 5
 
0.2%
2 4
 
0.1%
30 3
 
0.1%
48 3
 
0.1%
40 2
 
0.1%
49 2
 
0.1%
16 2
 
0.1%
17 1
 
< 0.1%
204 1
 
< 0.1%
Other values (12) 12
 
0.4%
(Missing) 3075
98.6%
ValueCountFrequency (%)
1 10
0.3%
2 4
 
0.1%
3 5
0.2%
6 1
 
< 0.1%
16 2
 
0.1%
17 1
 
< 0.1%
30 3
 
0.1%
34 1
 
< 0.1%
37 1
 
< 0.1%
39 1
 
< 0.1%
ValueCountFrequency (%)
204 1
 
< 0.1%
70 1
 
< 0.1%
68 1
 
< 0.1%
67 1
 
< 0.1%
54 1
 
< 0.1%
52 1
 
< 0.1%
50 1
 
< 0.1%
49 2
0.1%
48 3
0.1%
46 1
 
< 0.1%

일련번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.5 KiB
1
2341 
2
708 
<NA>
 
55
3
 
16

Length

Max length4
Median length1
Mean length1.0528846
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2341
75.0%
2 708
 
22.7%
<NA> 55
 
1.8%
3 16
 
0.5%

Length

2024-03-14T21:55:34.896420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:55:35.239690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2341
75.0%
2 708
 
22.7%
na 55
 
1.8%
3 16
 
0.5%

직결급수공사종류
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size24.5 KiB
물탱크철거,감압변 설치
992 
물탱크 철거
857 
직결연결
509 
물탱크철거,감압보호통 설치
477 
감압변 설치(통내)
207 
Other values (3)
 
78

Length

Max length14
Median length12
Mean length9.0474359
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
물탱크철거,감압변 설치 992
31.8%
물탱크 철거 857
27.5%
직결연결 509
16.3%
물탱크철거,감압보호통 설치 477
15.3%
감압변 설치(통내) 207
 
6.6%
<NA> 55
 
1.8%
감압보호통 설치 22
 
0.7%
기타 1
 
< 0.1%

Length

2024-03-14T21:55:35.803544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:55:36.158376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설치 1491
26.3%
물탱크철거,감압변 992
17.5%
물탱크 857
15.1%
철거 857
15.1%
직결연결 509
 
9.0%
물탱크철거,감압보호통 477
 
8.4%
감압변 207
 
3.6%
설치(통내 207
 
3.6%
na 55
 
1.0%
감압보호통 22
 
0.4%

Interactions

2024-03-14T21:55:25.419262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:19.945236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:21.228070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:22.553583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:24.076445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:25.672878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:20.208224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:21.480163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:22.791964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:24.280878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:25.978272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:20.470642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:21.749750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:23.059546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:24.604497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:26.251279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:20.711098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:22.009050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:23.310676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:24.845795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:26.541647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:20.975154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:22.283159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:23.804022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:55:25.132669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:55:36.434009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분교체대상여부공사비진단일자구경(mm)지원비세대원수일련번호직결급수공사종류
연번1.0000.421NaNNaNNaNNaNNaNNaN0.0580.118
구분0.4211.000NaN0.314NaNNaNNaNNaNNaNNaN
교체대상여부NaNNaN1.000NaN0.642NaNNaNNaNNaNNaN
공사비NaN0.314NaN1.000NaN0.7650.9980.936NaNNaN
진단일자NaNNaN0.642NaN1.000NaNNaNNaNNaNNaN
구경(mm)NaNNaNNaN0.765NaN1.0000.7240.941NaNNaN
지원비NaNNaNNaN0.998NaN0.7241.0000.928NaNNaN
세대원수NaNNaNNaN0.936NaN0.9410.9281.000NaNNaN
일련번호0.058NaNNaNNaNNaNNaNNaNNaN1.0000.685
직결급수공사종류0.118NaNNaNNaNNaNNaNNaNNaN0.6851.000
2024-03-14T21:55:36.755552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분직결급수공사종류교체대상여부일련번호
구분1.0001.0001.0001.000
직결급수공사종류1.0001.000NaN0.595
교체대상여부1.000NaN1.000NaN
일련번호1.0000.595NaN1.000
2024-03-14T21:55:37.034736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번공사비구경(mm)지원비세대원수구분교체대상여부일련번호직결급수공사종류
연번1.0000.4890.0880.026-0.0350.2791.0000.0340.060
공사비0.4891.0000.7430.9890.8500.2131.0000.0000.000
구경(mm)0.0880.7431.0000.7300.6661.0000.0000.0000.000
지원비0.0260.9890.7301.0000.8661.0000.0000.0000.000
세대원수-0.0350.8500.6660.8661.0001.0000.0000.0000.000
구분0.2790.2131.0001.0001.0001.0001.0001.0001.000
교체대상여부1.0001.0000.0000.0000.0001.0001.0000.0000.000
일련번호0.0340.0000.0000.0000.0001.0000.0001.0000.595
직결급수공사종류0.0600.0000.0000.0000.0001.0000.0000.5951.000

Missing values

2024-03-14T21:55:26.975522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:55:27.502089image/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.
2024-03-14T21:55:27.927912image/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-내시경진단비대상02023-02-20<NA><NA><NA><NA><NA><NA>
12물복지-내시경진단비대상02023-02-16<NA><NA><NA><NA><NA><NA>
23물복지-내시경진단대상02023-03-10<NA><NA><NA><NA><NA><NA>
34물복지-내시경진단비대상02023-02-20<NA><NA><NA><NA><NA><NA>
45물복지-내시경진단대상02023-02-16<NA><NA><NA><NA><NA><NA>
56물복지-내시경진단대상02023-03-10<NA><NA><NA><NA><NA><NA>
67물복지-내시경진단비대상02023-03-20<NA><NA><NA><NA><NA><NA>
78물복지-내시경진단비대상02023-01-09<NA><NA><NA><NA><NA><NA>
89물복지-내시경진단비대상02023-02-14<NA><NA><NA><NA><NA><NA>
910물복지-내시경진단대상02023-03-17<NA><NA><NA><NA><NA><NA>
연번구분교체대상여부공사비진단일자설치일자구경(mm)지원비세대원수일련번호직결급수공사종류
31103111물복지-직결급수공사<NA><NA><NA>2023-11-28<NA><NA><NA>1물탱크철거,감압변 설치
31113112물복지-직결급수공사<NA><NA><NA>2023-11-27<NA><NA><NA>1물탱크철거,감압변 설치
31123113물복지-직결급수공사<NA><NA><NA>2023-11-27<NA><NA><NA>2물탱크철거,감압변 설치
31133114물복지-직결급수공사<NA><NA><NA>2023-11-27<NA><NA><NA>1물탱크철거,감압변 설치
31143115물복지-직결급수공사<NA><NA><NA>2023-11-17<NA><NA><NA>1물탱크철거,감압변 설치
31153116물복지-직결급수공사<NA><NA><NA>2023-11-17<NA><NA><NA>1물탱크철거,감압변 설치
31163117물복지-직결급수공사<NA><NA><NA>2023-11-21<NA><NA><NA>1물탱크철거,감압보호통 설치
31173118물복지-직결급수공사<NA><NA><NA>2023-11-29<NA><NA><NA>1물탱크철거,감압보호통 설치
31183119물복지-직결급수공사<NA><NA><NA>2023-11-29<NA><NA><NA>2직결연결
31193120물복지-직결급수공사<NA><NA><NA>2023-11-29<NA><NA><NA>1물탱크철거,감압보호통 설치