Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells11767
Missing cells (%)10.7%
Duplicate rows1170
Duplicate rows (%)11.7%
Total size in memory937.5 KiB
Average record size in memory96.0 B

Variable types

Categorical7
Text2
DateTime2

Dataset

Description부산광역시_부산도시공간정보시스템_도로상하수도기반시설물_하수맨홀_20231013
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15084501

Alerts

Dataset has 1170 (11.7%) duplicate rowsDuplicates
우오수구분 is highly overall correlated with 맨홀종류High correlation
뚜껑형태 is highly overall correlated with 뚜껑재질High correlation
뚜껑재질 is highly overall correlated with 뚜껑형태High correlation
맨홀종류 is highly overall correlated with 우오수구분High correlation
우오수구분 is highly imbalanced (70.6%)Imbalance
뚜껑형태 is highly imbalanced (76.0%)Imbalance
뚜껑재질 is highly imbalanced (80.6%)Imbalance
불량여부 is highly imbalanced (93.7%)Imbalance
맨홀종류 is highly imbalanced (74.9%)Imbalance
맨홀형식 is highly imbalanced (55.6%)Imbalance
설치일자 has 154 (1.5%) missing valuesMissing
최종준설일자 has 6483 (64.8%) missing valuesMissing
행정동 has 821 (8.2%) missing valuesMissing
측량일자 has 4309 (43.1%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:51:46.831315
Analysis finished2023-12-10 16:51:48.491623
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록구
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기장군
1309 
강서구
1217 
부산진구
1172 
사하구
870 
사상구
756 
Other values (13)
4676 

Length

Max length4
Median length3
Mean length3.0167
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row부산진구
2nd row강서구
3rd row강서구
4th row부산진구
5th row동구

Common Values

ValueCountFrequency (%)
기장군 1309
13.1%
강서구 1217
12.2%
부산진구 1172
11.7%
사하구 870
8.7%
사상구 756
7.6%
동래구 694
6.9%
해운대구 689
6.9%
금정구 624
6.2%
북구 604
 
6.0%
연제구 510
 
5.1%
Other values (8) 1555
15.6%

Length

2023-12-11T01:51:48.567505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기장군 1309
13.1%
강서구 1217
12.2%
부산진구 1172
11.7%
사하구 870
8.7%
사상구 756
7.6%
동래구 694
6.9%
해운대구 689
6.9%
금정구 624
6.2%
북구 604
 
6.0%
연제구 510
 
5.1%
Other values (8) 1555
15.6%

설치일자
Text

MISSING 

Distinct703
Distinct (%)7.1%
Missing154
Missing (%)1.5%
Memory size156.2 KiB
2023-12-11T01:51:48.840904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters98460
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique239 ?
Unique (%)2.4%

Sample

1st row2013-06-10
2nd row2015-10-30
3rd row2005-12-15
4th row2017-12-31
5th row2022-10-06
ValueCountFrequency (%)
2019-12-31 626
 
6.4%
2020-01-01 418
 
4.2%
2015-11-19 340
 
3.5%
2016-07-22 334
 
3.4%
2018-11-14 318
 
3.2%
2013-12-31 248
 
2.5%
2017-12-30 244
 
2.5%
1983-01-01 218
 
2.2%
2010-02-16 194
 
2.0%
2018-05-31 183
 
1.9%
Other values (693) 6723
68.3%
2023-12-11T01:51:49.363336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22953
23.3%
- 19692
20.0%
1 19557
19.9%
2 17705
18.0%
3 5224
 
5.3%
9 3328
 
3.4%
8 2665
 
2.7%
6 2432
 
2.5%
7 1911
 
1.9%
5 1753
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78768
80.0%
Dash Punctuation 19692
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22953
29.1%
1 19557
24.8%
2 17705
22.5%
3 5224
 
6.6%
9 3328
 
4.2%
8 2665
 
3.4%
6 2432
 
3.1%
7 1911
 
2.4%
5 1753
 
2.2%
4 1240
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 19692
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98460
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22953
23.3%
- 19692
20.0%
1 19557
19.9%
2 17705
18.0%
3 5224
 
5.3%
9 3328
 
3.4%
8 2665
 
2.7%
6 2432
 
2.5%
7 1911
 
1.9%
5 1753
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22953
23.3%
- 19692
20.0%
1 19557
19.9%
2 17705
18.0%
3 5224
 
5.3%
9 3328
 
3.4%
8 2665
 
2.7%
6 2432
 
2.5%
7 1911
 
1.9%
5 1753
 
1.8%

최종준설일자
Date

MISSING 

Distinct131
Distinct (%)3.7%
Missing6483
Missing (%)64.8%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2023-07-08 00:00:00
2023-12-11T01:51:49.557979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:49.753098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

우오수구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
오수
8329 
우수
1500 
합류
 
83
집수
 
40
<NA>
 
38

Length

Max length4
Median length2
Mean length2.0096
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row오수
2nd row우수
3rd row오수
4th row오수
5th row오수

Common Values

ValueCountFrequency (%)
오수 8329
83.3%
우수 1500
 
15.0%
합류 83
 
0.8%
집수 40
 
0.4%
<NA> 38
 
0.4%
차집시설 10
 
0.1%

Length

2023-12-11T01:51:49.970647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:50.119426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오수 8329
83.3%
우수 1500
 
15.0%
합류 83
 
0.8%
집수 40
 
0.4%
na 38
 
0.4%
차집시설 10
 
0.1%

뚜껑형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
원형뚜껑
9144 
각형뚜껑
 
746
미분류
 
62
<NA>
 
48

Length

Max length4
Median length4
Mean length3.9938
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원형뚜껑 9144
91.4%
각형뚜껑 746
 
7.5%
미분류 62
 
0.6%
<NA> 48
 
0.5%

Length

2023-12-11T01:51:50.312290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:50.453369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원형뚜껑 9144
91.4%
각형뚜껑 746
 
7.5%
미분류 62
 
0.6%
na 48
 
0.5%

뚜껑재질
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주철
9034 
칼라
 
654
스틸그리팅(SG)
 
133
미분류
 
65
<NA>
 
51
Other values (4)
 
63

Length

Max length9
Median length2
Mean length2.124
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주철 9034
90.3%
칼라 654
 
6.5%
스틸그리팅(SG) 133
 
1.3%
미분류 65
 
0.7%
<NA> 51
 
0.5%
콘크리트 31
 
0.3%
철판(ST) 20
 
0.2%
기타 9
 
0.1%
PE 3
 
< 0.1%

Length

2023-12-11T01:51:50.598728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:50.752943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주철 9034
90.3%
칼라 654
 
6.5%
스틸그리팅(sg 133
 
1.3%
미분류 65
 
0.7%
na 51
 
0.5%
콘크리트 31
 
0.3%
철판(st 20
 
0.2%
기타 9
 
0.1%
pe 3
 
< 0.1%

행정동
Text

MISSING 

Distinct202
Distinct (%)2.2%
Missing821
Missing (%)8.2%
Memory size156.2 KiB
2023-12-11T01:51:51.145027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5981044
Min length3

Characters and Unicode

Total characters33027
Distinct characters106
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

Unique7 ?
Unique (%)0.1%

Sample

1st row범천2동
2nd row명지동
3rd row녹산동
4th row부전2동
5th row초량2동
ValueCountFrequency (%)
녹산동 669
 
7.3%
기장읍 326
 
3.6%
장안읍 314
 
3.4%
명지동 224
 
2.4%
대저1동 187
 
2.0%
철마면 173
 
1.9%
일광면 169
 
1.8%
정관읍 155
 
1.7%
감전동 133
 
1.4%
하단2동 131
 
1.4%
Other values (192) 6698
73.0%
2023-12-11T01:51:51.666421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 8216
24.9%
1 2195
 
6.6%
2 1989
 
6.0%
산 1178
 
3.6%
장 1152
 
3.5%
읍 881
 
2.7%
3 731
 
2.2%
녹 669
 
2.0%
대 660
 
2.0%
연 652
 
2.0%
Other values (96) 14704
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27423
83.0%
Decimal Number 5604
 
17.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8216
30.0%
산 1178
 
4.3%
장 1152
 
4.2%
읍 881
 
3.2%
녹 669
 
2.4%
대 660
 
2.4%
연 652
 
2.4%
안 577
 
2.1%
전 506
 
1.8%
포 500
 
1.8%
Other values (88) 12432
45.3%
Decimal Number
ValueCountFrequency (%)
1 2195
39.2%
2 1989
35.5%
3 731
 
13.0%
4 356
 
6.4%
5 122
 
2.2%
9 101
 
1.8%
8 61
 
1.1%
6 49
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27423
83.0%
Common 5604
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8216
30.0%
산 1178
 
4.3%
장 1152
 
4.2%
읍 881
 
3.2%
녹 669
 
2.4%
대 660
 
2.4%
연 652
 
2.4%
안 577
 
2.1%
전 506
 
1.8%
포 500
 
1.8%
Other values (88) 12432
45.3%
Common
ValueCountFrequency (%)
1 2195
39.2%
2 1989
35.5%
3 731
 
13.0%
4 356
 
6.4%
5 122
 
2.2%
9 101
 
1.8%
8 61
 
1.1%
6 49
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27423
83.0%
ASCII 5604
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 8216
30.0%
산 1178
 
4.3%
장 1152
 
4.2%
읍 881
 
3.2%
녹 669
 
2.4%
대 660
 
2.4%
연 652
 
2.4%
안 577
 
2.1%
전 506
 
1.8%
포 500
 
1.8%
Other values (88) 12432
45.3%
ASCII
ValueCountFrequency (%)
1 2195
39.2%
2 1989
35.5%
3 731
 
13.0%
4 356
 
6.4%
5 122
 
2.2%
9 101
 
1.8%
8 61
 
1.1%
6 49
 
0.9%

불량여부
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
양호
9813 
<NA>
 
162
불량
 
21
불량/준설필요
 
2
준설필요
 
2

Length

Max length7
Median length2
Mean length2.0338
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양호 9813
98.1%
<NA> 162
 
1.6%
불량 21
 
0.2%
불량/준설필요 2
 
< 0.1%
준설필요 2
 
< 0.1%

Length

2023-12-11T01:51:51.818812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:52.253637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양호 9813
98.1%
na 162
 
1.6%
불량 21
 
0.2%
불량/준설필요 2
 
< 0.1%
준설필요 2
 
< 0.1%

맨홀종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
오수맨홀
8304 
우수맨홀
1455 
<NA>
 
153
합류맨홀
 
46
기타
 
15
Other values (4)
 
27

Length

Max length5
Median length4
Mean length3.9988
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row오수맨홀
2nd row우수맨홀
3rd row오수맨홀
4th row오수맨홀
5th row오수맨홀

Common Values

ValueCountFrequency (%)
오수맨홀 8304
83.0%
우수맨홀 1455
 
14.5%
<NA> 153
 
1.5%
합류맨홀 46
 
0.5%
기타 15
 
0.1%
공기변맨홀 13
 
0.1%
방류맨홀 9
 
0.1%
이토변맨홀 4
 
< 0.1%
제수변맨홀 1
 
< 0.1%

Length

2023-12-11T01:51:52.406656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:52.536785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오수맨홀 8304
83.0%
우수맨홀 1455
 
14.5%
na 153
 
1.5%
합류맨홀 46
 
0.5%
기타 15
 
0.1%
공기변맨홀 13
 
0.1%
방류맨홀 9
 
0.1%
이토변맨홀 4
 
< 0.1%
제수변맨홀 1
 
< 0.1%

맨홀형식
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
표준맨홀
6750 
소형맨홀
2296 
<NA>
 
357
특수맨홀
 
230
기타
 
201
Other values (4)
 
166

Length

Max length7
Median length4
Mean length3.9698
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소형맨홀
2nd row표준맨홀
3rd row표준맨홀
4th row표준맨홀
5th row표준맨홀

Common Values

ValueCountFrequency (%)
표준맨홀 6750
67.5%
소형맨홀 2296
 
23.0%
<NA> 357
 
3.6%
특수맨홀 230
 
2.3%
기타 201
 
2.0%
미분류 59
 
0.6%
소재구,점검구 53
 
0.5%
부관맨홀 52
 
0.5%
폐쇠맨홀 2
 
< 0.1%

Length

2023-12-11T01:51:52.691395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:52.822505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
표준맨홀 6750
67.5%
소형맨홀 2296
 
23.0%
na 357
 
3.6%
특수맨홀 230
 
2.3%
기타 201
 
2.0%
미분류 59
 
0.6%
소재구,점검구 53
 
0.5%
부관맨홀 52
 
0.5%
폐쇠맨홀 2
 
< 0.1%

측량일자
Date

MISSING 

Distinct413
Distinct (%)7.3%
Missing4309
Missing (%)43.1%
Memory size156.2 KiB
Minimum1983-01-01 00:00:00
Maximum2023-07-24 00:00:00
2023-12-11T01:51:52.970011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:53.136642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-11T01:51:53.319969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록구우오수구분뚜껑형태뚜껑재질불량여부맨홀종류맨홀형식
등록구1.0000.3300.2150.2980.0630.2810.371
우오수구분0.3301.0000.4970.3120.0000.7950.421
뚜껑형태0.2150.4971.0000.8020.2050.5870.437
뚜껑재질0.2980.3120.8021.0000.3360.4350.351
불량여부0.0630.0000.2050.3361.0000.2410.274
맨홀종류0.2810.7950.5870.4350.2411.0000.653
맨홀형식0.3710.4210.4370.3510.2740.6531.000
2023-12-11T01:51:53.471109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
맨홀종류맨홀형식불량여부우오수구분등록구뚜껑재질뚜껑형태
맨홀종류1.0000.2690.1100.6510.1210.1580.455
맨홀형식0.2691.0000.1260.2740.1650.1240.310
불량여부0.1100.1261.0000.0000.0350.1550.195
우오수구분0.6510.2740.0001.0000.1760.1970.432
등록구0.1210.1650.0350.1761.0000.1290.118
뚜껑재질0.1580.1240.1550.1970.1291.0000.728
뚜껑형태0.4550.3100.1950.4320.1180.7281.000
2023-12-11T01:51:53.639414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록구우오수구분뚜껑형태뚜껑재질불량여부맨홀종류맨홀형식
등록구1.0000.1760.1180.1290.0350.1210.165
우오수구분0.1761.0000.4320.1970.0000.6510.274
뚜껑형태0.1180.4321.0000.7280.1950.4550.310
뚜껑재질0.1290.1970.7281.0000.1550.1580.124
불량여부0.0350.0000.1950.1551.0000.1100.126
맨홀종류0.1210.6510.4550.1580.1101.0000.269
맨홀형식0.1650.2740.3100.1240.1260.2691.000

Missing values

2023-12-11T01:51:47.990401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:51:48.173950image/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.
2023-12-11T01:51:48.347761image/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

등록구설치일자최종준설일자우오수구분뚜껑형태뚜껑재질행정동불량여부맨홀종류맨홀형식측량일자
36734부산진구2013-06-102013-06-10오수원형뚜껑주철범천2동양호오수맨홀소형맨홀2012-04-20
42204강서구2015-10-302015-10-30우수원형뚜껑주철명지동양호우수맨홀표준맨홀<NA>
87386강서구2005-12-15<NA>오수원형뚜껑주철녹산동양호오수맨홀표준맨홀2005-12-15
64508부산진구2017-12-31<NA>오수원형뚜껑주철부전2동양호오수맨홀표준맨홀2020-06-01
55430동구2022-10-06<NA>오수원형뚜껑주철초량2동양호오수맨홀표준맨홀2022-10-06
39122연제구2013-12-31<NA>오수원형뚜껑주철거제1동양호오수맨홀소형맨홀2014-08-29
54927수영구2018-05-31<NA>오수원형뚜껑주철민락동양호오수맨홀소형맨홀2018-08-10
24887기장군2012-10-302012-10-30오수원형뚜껑칼라장안읍양호오수맨홀표준맨홀2012-10-30
63381북구2020-08-28<NA>오수원형뚜껑주철구포3동양호오수맨홀소형맨홀<NA>
32741사하구2012-06-08<NA>오수원형뚜껑주철<NA>양호오수맨홀표준맨홀<NA>
등록구설치일자최종준설일자우오수구분뚜껑형태뚜껑재질행정동불량여부맨홀종류맨홀형식측량일자
39363부산진구2010-08-06<NA>오수원형뚜껑주철가야1동양호오수맨홀표준맨홀<NA>
48254기장군2018-04-302018-04-30오수원형뚜껑칼라장안읍양호오수맨홀표준맨홀2018-04-30
84487기장군2022-06-15<NA>오수원형뚜껑주철<NA>양호오수맨홀표준맨홀2022-06-15
54116강서구2007-01-01<NA>오수원형뚜껑주철명지동양호오수맨홀특수맨홀2007-01-01
53297남구2017-12-302017-12-30오수원형뚜껑주철대연3동양호오수맨홀소형맨홀2018-02-20
11495사상구2016-07-222016-07-22우수각형뚜껑스틸그리팅(SG)<NA>양호우수맨홀표준맨홀<NA>
68885부산진구2021-04-12<NA>오수원형뚜껑주철전포2동양호오수맨홀소형맨홀<NA>
12931북구2016-07-222016-07-22오수원형뚜껑주철덕천1동양호오수맨홀표준맨홀<NA>
84595부산진구2017-12-30<NA>오수원형뚜껑주철가야2동양호오수맨홀소형맨홀2022-01-12
9691해운대구1996-09-01<NA>오수원형뚜껑주철좌3동양호오수맨홀표준맨홀<NA>

Duplicate rows

Most frequently occurring

등록구설치일자최종준설일자우오수구분뚜껑형태뚜껑재질행정동불량여부맨홀종류맨홀형식측량일자# duplicates
781사상구2016-07-222016-07-22오수원형뚜껑주철<NA>양호오수맨홀표준맨홀<NA>127
4강서구2001-08-182001-08-18오수원형뚜껑주철녹산동양호오수맨홀표준맨홀<NA>106
200금정구2021-01-01<NA>오수원형뚜껑주철남산동양호오수맨홀표준맨홀2021-05-2184
890사하구2020-12-18<NA>오수원형뚜껑주철하단2동양호오수맨홀소형맨홀2020-12-1883
780사상구2015-11-192015-11-19오수원형뚜껑주철학장동양호오수맨홀표준맨홀2015-11-1978
769사상구2015-11-192015-11-19오수원형뚜껑주철감전동양호오수맨홀표준맨홀2015-11-1975
61강서구2013-12-31<NA>우수원형뚜껑주철녹산동양호우수맨홀표준맨홀2014-10-3070
598부산진구2016-07-302016-07-30오수원형뚜껑주철<NA>양호오수맨홀소형맨홀<NA>67
207기장군1983-01-011983-01-01오수원형뚜껑주철기장읍양호오수맨홀<NA><NA>64
844사하구2012-02-29<NA>오수원형뚜껑주철<NA>양호오수맨홀소형맨홀<NA>62