Overview

Dataset statistics

Number of variables11
Number of observations3220
Missing cells15877
Missing cells (%)44.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory295.7 KiB
Average record size in memory94.0 B

Variable types

Numeric5
Categorical4
DateTime2

Dataset

Description부산광역시상수도사업본부_수용가정보시스템_물복지사업정보_20230125
Author부산광역시 상수도사업본부
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15100356

Alerts

직결급수공사종류 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 구경(mm) and 5 other fieldsHigh correlation
일련번호 is highly overall correlated with 구분High correlation
교체대상여부 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 공사비 and 1 other fieldsHigh correlation
공사비 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
구경(mm) is highly overall correlated with 구분High correlation
지원비 is highly overall correlated with 공사비 and 2 other fieldsHigh correlation
세대원수 is highly overall correlated with 공사비 and 2 other fieldsHigh correlation
구분 is highly imbalanced (90.3%)Imbalance
교체대상여부 is highly imbalanced (97.8%)Imbalance
일련번호 is highly imbalanced (76.8%)Imbalance
공사비 has 3156 (98.0%) missing valuesMissing
진단일자 has 3209 (99.7%) missing valuesMissing
구경(mm) has 3167 (98.4%) missing valuesMissing
지원비 has 3167 (98.4%) missing valuesMissing
세대원수 has 3167 (98.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:20:33.865229
Analysis finished2023-12-10 16:20:39.145961
Duration5.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3220
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1610.5
Minimum1
Maximum3220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-12-11T01:20:39.291041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile161.95
Q1805.75
median1610.5
Q32415.25
95-th percentile3059.05
Maximum3220
Range3219
Interquartile range (IQR)1609.5

Descriptive statistics

Standard deviation929.67826
Coefficient of variation (CV)0.57726064
Kurtosis-1.2
Mean1610.5
Median Absolute Deviation (MAD)805
Skewness0
Sum5185810
Variance864301.67
MonotonicityStrictly increasing
2023-12-11T01:20:39.517104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2153 1
 
< 0.1%
2143 1
 
< 0.1%
2144 1
 
< 0.1%
2145 1
 
< 0.1%
2146 1
 
< 0.1%
2147 1
 
< 0.1%
2148 1
 
< 0.1%
2149 1
 
< 0.1%
2150 1
 
< 0.1%
Other values (3210) 3210
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 (%)
3220 1
< 0.1%
3219 1
< 0.1%
3218 1
< 0.1%
3217 1
< 0.1%
3216 1
< 0.1%
3215 1
< 0.1%
3214 1
< 0.1%
3213 1
< 0.1%
3212 1
< 0.1%
3211 1
< 0.1%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
물복지-직결급수공사
3156 
물복지-옥내노후관교체
 
53
물복지-내시경진단
 
11

Length

Max length11
Median length10
Mean length10.013043
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 3156
98.0%
물복지-옥내노후관교체 53
 
1.6%
물복지-내시경진단 11
 
0.3%

Length

2023-12-11T01:20:39.769145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:39.978432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물복지-직결급수공사 3156
98.0%
물복지-옥내노후관교체 53
 
1.6%
물복지-내시경진단 11
 
0.3%

교체대상여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
<NA>
3209 
대상
 
9
비대상
 
2

Length

Max length4
Median length4
Mean length3.9937888
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3209
99.7%
대상 9
 
0.3%
비대상 2
 
0.1%

Length

2023-12-11T01:20:40.206847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:40.429131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3209
99.7%
대상 9
 
0.3%
비대상 2
 
0.1%

공사비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)71.9%
Missing3156
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean27100758
Minimum0
Maximum1.75 × 108
Zeros11
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-12-11T01:20:40.647523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120680.5
median4763000
Q340910750
95-th percentile1.1755 × 108
Maximum1.75 × 108
Range1.75 × 108
Interquartile range (IQR)40890070

Descriptive statistics

Standard deviation43238059
Coefficient of variation (CV)1.5954557
Kurtosis4.4256847
Mean27100758
Median Absolute Deviation (MAD)4763000
Skewness2.1586912
Sum1.7344485 × 109
Variance1.8695297 × 1015
MonotonicityNot monotonic
2023-12-11T01:20:40.904135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 11
 
0.3%
19000000 3
 
0.1%
50600 2
 
0.1%
40000 2
 
0.1%
24000000 2
 
0.1%
175000000 2
 
0.1%
36000 2
 
0.1%
45000000 2
 
0.1%
3000 1
 
< 0.1%
115000000 1
 
< 0.1%
Other values (36) 36
 
1.1%
(Missing) 3156
98.0%
ValueCountFrequency (%)
0 11
0.3%
1350 1
 
< 0.1%
3000 1
 
< 0.1%
4059 1
 
< 0.1%
4300 1
 
< 0.1%
16722 1
 
< 0.1%
22000 1
 
< 0.1%
24000 1
 
< 0.1%
28000 1
 
< 0.1%
31000 1
 
< 0.1%
ValueCountFrequency (%)
175000000 2
0.1%
165000000 1
< 0.1%
118000000 1
< 0.1%
115000000 1
< 0.1%
108000000 1
< 0.1%
73062000 1
< 0.1%
71400000 1
< 0.1%
51000000 1
< 0.1%
49000000 1
< 0.1%
47000000 1
< 0.1%

진단일자
Date

MISSING 

Distinct10
Distinct (%)90.9%
Missing3209
Missing (%)99.7%
Memory size25.3 KiB
Minimum2022-03-24 00:00:00
Maximum2022-10-25 00:00:00
2023-12-11T01:20:41.112976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:41.300997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

설치일자
Date

Distinct267
Distinct (%)8.3%
Missing11
Missing (%)0.3%
Memory size25.3 KiB
Minimum2022-01-03 00:00:00
Maximum2022-12-30 00:00:00
2023-12-11T01:20:41.557724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:42.257878image/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 (%)11.3%
Missing3167
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean29.056604
Minimum15
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-12-11T01:20:42.550216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile15
Q115
median15
Q340
95-th percentile80
Maximum100
Range85
Interquartile range (IQR)25

Descriptive statistics

Standard deviation21.123643
Coefficient of variation (CV)0.7269825
Kurtosis2.0491376
Mean29.056604
Median Absolute Deviation (MAD)0
Skewness1.5678781
Sum1540
Variance446.20827
MonotonicityNot monotonic
2023-12-11T01:20:42.736469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
15 32
 
1.0%
40 8
 
0.2%
50 7
 
0.2%
80 3
 
0.1%
25 2
 
0.1%
100 1
 
< 0.1%
(Missing) 3167
98.4%
ValueCountFrequency (%)
15 32
1.0%
25 2
 
0.1%
40 8
 
0.2%
50 7
 
0.2%
80 3
 
0.1%
100 1
 
< 0.1%
ValueCountFrequency (%)
100 1
 
< 0.1%
80 3
 
0.1%
50 7
 
0.2%
40 8
 
0.2%
25 2
 
0.1%
15 32
1.0%

지원비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)67.9%
Missing3167
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean31966991
Minimum1200
Maximum1.75 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-12-11T01:20:42.918346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile3000
Q140000
median18000000
Q344000000
95-th percentile1.348 × 108
Maximum1.75 × 108
Range1.749988 × 108
Interquartile range (IQR)43960000

Descriptive statistics

Standard deviation45333852
Coefficient of variation (CV)1.4181457
Kurtosis3.2958048
Mean31966991
Median Absolute Deviation (MAD)17972000
Skewness1.9188896
Sum1.6942505 × 109
Variance2.0551582 × 1015
MonotonicityNot monotonic
2023-12-11T01:20:43.168532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
40000000 5
 
0.2%
3000000 3
 
0.1%
19000000 3
 
0.1%
40000 3
 
0.1%
45000000 2
 
0.1%
24000000 2
 
0.1%
3000 2
 
0.1%
36000 2
 
0.1%
49000 2
 
0.1%
70000000 2
 
0.1%
Other values (26) 27
 
0.8%
(Missing) 3167
98.4%
ValueCountFrequency (%)
1200 1
< 0.1%
2000 1
< 0.1%
3000 2
0.1%
12000 1
< 0.1%
22000 1
< 0.1%
24000 1
< 0.1%
28000 1
< 0.1%
31000 1
< 0.1%
36000 2
0.1%
37000 1
< 0.1%
ValueCountFrequency (%)
175000000 2
0.1%
160000000 1
< 0.1%
118000000 1
< 0.1%
114000000 1
< 0.1%
108000000 1
< 0.1%
70000000 2
0.1%
49000000 1
< 0.1%
48000000 1
< 0.1%
47000000 1
< 0.1%
45000000 2
0.1%

세대원수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct29
Distinct (%)54.7%
Missing3167
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean45.584906
Minimum1
Maximum216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-12-11T01:20:43.405727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q119
median37
Q347
95-th percentile166
Maximum216
Range215
Interquartile range (IQR)28

Descriptive statistics

Standard deviation47.3215
Coefficient of variation (CV)1.0380958
Kurtosis4.0395156
Mean45.584906
Median Absolute Deviation (MAD)13
Skewness2.0394794
Sum2416
Variance2239.3244
MonotonicityNot monotonic
2023-12-11T01:20:43.596713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
40 8
 
0.2%
3 5
 
0.2%
49 3
 
0.1%
36 3
 
0.1%
24 3
 
0.1%
19 3
 
0.1%
70 2
 
0.1%
175 2
 
0.1%
1 2
 
0.1%
12 2
 
0.1%
Other values (19) 20
 
0.6%
(Missing) 3167
98.4%
ValueCountFrequency (%)
1 2
 
0.1%
2 1
 
< 0.1%
3 5
0.2%
10 1
 
< 0.1%
12 2
 
0.1%
13 1
 
< 0.1%
18 1
 
< 0.1%
19 3
0.1%
22 1
 
< 0.1%
24 3
0.1%
ValueCountFrequency (%)
216 1
 
< 0.1%
175 2
0.1%
160 1
 
< 0.1%
118 1
 
< 0.1%
114 1
 
< 0.1%
108 1
 
< 0.1%
70 2
0.1%
49 3
0.1%
48 1
 
< 0.1%
47 1
 
< 0.1%

일련번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
1
2969 
2
 
185
<NA>
 
64
3
 
2

Length

Max length4
Median length1
Mean length1.0596273
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 2969
92.2%
2 185
 
5.7%
<NA> 64
 
2.0%
3 2
 
0.1%

Length

2023-12-11T01:20:43.807502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:44.015739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2969
92.2%
2 185
 
5.7%
na 64
 
2.0%
3 2
 
0.1%

직결급수공사종류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
물탱크철거,감압변 설치
1352 
물탱크 철거
883 
물탱크철거,감압보호통 설치
415 
감압변 설치(통내)
312 
직결연결
153 
Other values (4)
 
105

Length

Max length14
Median length12
Mean length9.8167702
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 1352
42.0%
물탱크 철거 883
27.4%
물탱크철거,감압보호통 설치 415
 
12.9%
감압변 설치(통내) 312
 
9.7%
직결연결 153
 
4.8%
<NA> 64
 
2.0%
감압보호통 설치 32
 
1.0%
기타 7
 
0.2%
감압변 설치(통외) 2
 
0.1%

Length

2023-12-11T01:20:44.199368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:20:44.389058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설치 1799
28.9%
물탱크철거,감압변 1352
21.8%
물탱크 883
14.2%
철거 883
14.2%
물탱크철거,감압보호통 415
 
6.7%
감압변 314
 
5.1%
설치(통내 312
 
5.0%
직결연결 153
 
2.5%
na 64
 
1.0%
감압보호통 32
 
0.5%
Other values (2) 9
 
0.1%

Interactions

2023-12-11T01:20:37.609859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:34.698233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:35.403423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:36.163808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:36.958840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:37.768010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:34.859096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:35.544555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:36.312425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:37.081770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:37.913659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:34.995305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:35.708455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:36.454537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:37.207194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:38.034728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:35.108982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:35.842051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:36.611999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:37.336613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:38.202718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:35.288645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:36.025010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:36.834886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:20:37.477748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:20:44.552319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분교체대상여부공사비진단일자구경(mm)지원비세대원수일련번호직결급수공사종류
연번1.0000.443NaNNaNNaNNaNNaNNaN0.0700.129
구분0.4431.000NaN0.392NaNNaNNaNNaNNaNNaN
교체대상여부NaNNaN1.000NaN1.000NaNNaNNaNNaNNaN
공사비NaN0.392NaN1.000NaN0.3221.0000.937NaNNaN
진단일자NaNNaN1.000NaN1.000NaNNaNNaNNaNNaN
구경(mm)NaNNaNNaN0.322NaN1.0000.3040.711NaNNaN
지원비NaNNaNNaN1.000NaN0.3041.0000.936NaNNaN
세대원수NaNNaNNaN0.937NaN0.7110.9361.000NaNNaN
일련번호0.070NaNNaNNaNNaNNaNNaNNaN1.0000.536
직결급수공사종류0.129NaNNaNNaNNaNNaNNaNNaN0.5361.000
2023-12-11T01:20:44.749381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직결급수공사종류구분일련번호교체대상여부
직결급수공사종류1.0001.0000.401NaN
구분1.0001.0001.0001.000
일련번호0.4011.0001.000NaN
교체대상여부NaN1.000NaN1.000
2023-12-11T01:20:44.895041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번공사비구경(mm)지원비세대원수구분교체대상여부일련번호직결급수공사종류
연번1.0000.510-0.0120.146-0.0970.2981.0000.0410.062
공사비0.5101.0000.0890.9990.6550.2711.0000.0000.000
구경(mm)-0.0120.0891.0000.0880.3631.0000.0000.0000.000
지원비0.1460.9990.0881.0000.6561.0000.0000.0000.000
세대원수-0.0970.6550.3630.6561.0001.0000.0000.0000.000
구분0.2980.2711.0001.0001.0001.0001.0001.0001.000
교체대상여부1.0001.0000.0000.0000.0001.0001.0000.0000.000
일련번호0.0410.0000.0000.0000.0001.0000.0001.0000.401
직결급수공사종류0.0620.0000.0000.0000.0001.0000.0000.4011.000

Missing values

2023-12-11T01:20:38.379933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:20:38.688530image/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.
2023-12-11T01:20:38.961840image/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-내시경진단비대상02022-06-22<NA><NA><NA><NA><NA><NA>
12물복지-내시경진단대상02022-06-28<NA><NA><NA><NA><NA><NA>
23물복지-내시경진단대상02022-07-26<NA><NA><NA><NA><NA><NA>
34물복지-내시경진단대상02022-07-28<NA><NA><NA><NA><NA><NA>
45물복지-내시경진단대상02022-10-11<NA><NA><NA><NA><NA><NA>
56물복지-내시경진단대상02022-10-25<NA><NA><NA><NA><NA><NA>
67물복지-내시경진단대상02022-06-16<NA><NA><NA><NA><NA><NA>
78물복지-내시경진단대상02022-03-24<NA><NA><NA><NA><NA><NA>
89물복지-내시경진단대상02022-07-21<NA><NA><NA><NA><NA><NA>
910물복지-내시경진단대상02022-07-26<NA><NA><NA><NA><NA><NA>
연번구분교체대상여부공사비진단일자설치일자구경(mm)지원비세대원수일련번호직결급수공사종류
32103211물복지-직결급수공사<NA><NA><NA>2022-02-28<NA><NA><NA>1물탱크철거,감압변 설치
32113212물복지-직결급수공사<NA><NA><NA>2022-02-28<NA><NA><NA>1물탱크철거,감압변 설치
32123213물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
32133214물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압변 설치
32143215물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
32153216물복지-직결급수공사<NA><NA><NA>2022-02-25<NA><NA><NA>1물탱크철거,감압변 설치
32163217물복지-직결급수공사<NA><NA><NA>2022-02-25<NA><NA><NA>1직결연결
32173218물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
32183219물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크철거,감압보호통 설치
32193220물복지-직결급수공사<NA><NA><NA>2022-03-02<NA><NA><NA>1물탱크 철거