Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells11846
Missing cells (%)10.8%
Duplicate rows1182
Duplicate rows (%)11.8%
Total size in memory937.5 KiB
Average record size in memory96.0 B

Variable types

Categorical7
Text3
DateTime1

Dataset

Description부산도시공간정보시스템 도로상하수도기반시설에 대한 하수 맨홀 정보입니다.(등록 구, 설치 일자, 뚜껑 형태, 행정동 등)
Author부산광역시
URLhttps://www.data.go.kr/data/15084501/fileData.do

Alerts

Dataset has 1182 (11.8%) 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 (71.1%)Imbalance
뚜껑형태 is highly imbalanced (77.0%)Imbalance
뚜껑재질 is highly imbalanced (80.7%)Imbalance
불량여부 is highly imbalanced (94.1%)Imbalance
맨홀종류 is highly imbalanced (76.4%)Imbalance
맨홀형식 is highly imbalanced (55.6%)Imbalance
설치일자 has 172 (1.7%) missing valuesMissing
최종준설일자 has 6597 (66.0%) missing valuesMissing
행정동 has 828 (8.3%) missing valuesMissing
측량일자 has 4249 (42.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:40:34.246268
Analysis finished2023-12-12 23:40:35.775670
Duration1.53 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
1251 
강서구
1240 
부산진구
1201 
사하구
851 
사상구
718 
Other values (13)
4739 

Length

Max length4
Median length3
Mean length3.0168
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기장군 1251
12.5%
강서구 1240
12.4%
부산진구 1201
12.0%
사하구 851
8.5%
사상구 718
7.2%
해운대구 686
6.9%
동래구 680
6.8%
금정구 668
6.7%
북구 592
 
5.9%
남구 531
 
5.3%
Other values (8) 1582
15.8%

Length

2023-12-13T08:40:35.858060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기장군 1251
12.5%
강서구 1240
12.4%
부산진구 1201
12.0%
사하구 851
8.5%
사상구 718
7.2%
해운대구 686
6.9%
동래구 680
6.8%
금정구 668
6.7%
북구 592
 
5.9%
남구 531
 
5.3%
Other values (8) 1582
15.8%

설치일자
Text

MISSING 

Distinct706
Distinct (%)7.2%
Missing172
Missing (%)1.7%
Memory size156.2 KiB
2023-12-13T08:40:36.150415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters98280
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

Unique238 ?
Unique (%)2.4%

Sample

1st row2002-12-10
2nd row2016-07-30
3rd row2015-11-19
4th row2019-12-31
5th row2017-12-30
ValueCountFrequency (%)
2019-12-31 672
 
6.8%
2020-01-01 406
 
4.1%
2018-11-14 313
 
3.2%
2016-07-22 303
 
3.1%
2015-11-19 298
 
3.0%
2013-12-31 269
 
2.7%
2017-12-30 249
 
2.5%
2010-02-16 210
 
2.1%
1983-01-01 203
 
2.1%
2018-05-31 194
 
2.0%
Other values (696) 6711
68.3%
2023-12-13T08:40:36.537029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22835
23.2%
- 19656
20.0%
1 19616
20.0%
2 17661
18.0%
3 5295
 
5.4%
9 3320
 
3.4%
8 2600
 
2.6%
6 2425
 
2.5%
7 1896
 
1.9%
5 1776
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78624
80.0%
Dash Punctuation 19656
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22835
29.0%
1 19616
24.9%
2 17661
22.5%
3 5295
 
6.7%
9 3320
 
4.2%
8 2600
 
3.3%
6 2425
 
3.1%
7 1896
 
2.4%
5 1776
 
2.3%
4 1200
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 19656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22835
23.2%
- 19656
20.0%
1 19616
20.0%
2 17661
18.0%
3 5295
 
5.4%
9 3320
 
3.4%
8 2600
 
2.6%
6 2425
 
2.5%
7 1896
 
1.9%
5 1776
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22835
23.2%
- 19656
20.0%
1 19616
20.0%
2 17661
18.0%
3 5295
 
5.4%
9 3320
 
3.4%
8 2600
 
2.6%
6 2425
 
2.5%
7 1896
 
1.9%
5 1776
 
1.8%

최종준설일자
Date

MISSING 

Distinct142
Distinct (%)4.2%
Missing6597
Missing (%)66.0%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2023-05-15 00:00:00
2023-12-13T08:40:36.685880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:36.816801image/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
8372 
우수
1460 
합류
 
74
집수
 
47
<NA>
 
38

Length

Max length4
Median length2
Mean length2.0094
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
오수 8372
83.7%
우수 1460
 
14.6%
합류 74
 
0.7%
집수 47
 
0.5%
<NA> 38
 
0.4%
차집시설 9
 
0.1%

Length

2023-12-13T08:40:36.953124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:37.088751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오수 8372
83.7%
우수 1460
 
14.6%
합류 74
 
0.7%
집수 47
 
0.5%
na 38
 
0.4%
차집시설 9
 
0.1%

뚜껑형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
원형뚜껑
9190 
각형뚜껑
 
707
미분류
 
59
<NA>
 
44

Length

Max length4
Median length4
Mean length3.9941
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원형뚜껑 9190
91.9%
각형뚜껑 707
 
7.1%
미분류 59
 
0.6%
<NA> 44
 
0.4%

Length

2023-12-13T08:40:37.211787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:37.300407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원형뚜껑 9190
91.9%
각형뚜껑 707
 
7.1%
미분류 59
 
0.6%
na 44
 
0.4%

뚜껑재질
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주철
9058 
칼라
 
616
스틸그리팅(SG)
 
145
미분류
 
65
<NA>
 
39
Other values (4)
 
77

Length

Max length9
Median length2
Mean length2.13
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주철 9058
90.6%
칼라 616
 
6.2%
스틸그리팅(SG) 145
 
1.5%
미분류 65
 
0.7%
<NA> 39
 
0.4%
콘크리트 33
 
0.3%
기타 21
 
0.2%
철판(ST) 19
 
0.2%
PE 4
 
< 0.1%

Length

2023-12-13T08:40:37.407344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:37.541369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주철 9058
90.6%
칼라 616
 
6.2%
스틸그리팅(sg 145
 
1.5%
미분류 65
 
0.7%
na 39
 
0.4%
콘크리트 33
 
0.3%
기타 21
 
0.2%
철판(st 19
 
0.2%
pe 4
 
< 0.1%

행정동
Text

MISSING 

Distinct203
Distinct (%)2.2%
Missing828
Missing (%)8.3%
Memory size156.2 KiB
2023-12-13T08:40:37.839707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5983428
Min length3

Characters and Unicode

Total characters33004
Distinct characters107
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

Unique8 ?
Unique (%)0.1%

Sample

1st row대저1동
2nd row학장동
3rd row수정5동
4th row대연5동
5th row남산동
ValueCountFrequency (%)
녹산동 712
 
7.8%
장안읍 315
 
3.4%
기장읍 280
 
3.1%
명지동 203
 
2.2%
대저1동 199
 
2.2%
철마면 186
 
2.0%
정관읍 183
 
2.0%
일광면 147
 
1.6%
남산동 138
 
1.5%
하단2동 129
 
1.4%
Other values (193) 6680
72.8%
2023-12-13T08:40:38.337519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 8231
24.9%
1 2246
 
6.8%
2 1863
 
5.6%
산 1202
 
3.6%
장 1055
 
3.2%
읍 866
 
2.6%
3 778
 
2.4%
녹 712
 
2.2%
대 646
 
2.0%
연 600
 
1.8%
Other values (97) 14805
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27415
83.1%
Decimal Number 5589
 
16.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8231
30.0%
산 1202
 
4.4%
장 1055
 
3.8%
읍 866
 
3.2%
녹 712
 
2.6%
대 646
 
2.4%
연 600
 
2.2%
안 558
 
2.0%
전 517
 
1.9%
천 466
 
1.7%
Other values (89) 12562
45.8%
Decimal Number
ValueCountFrequency (%)
1 2246
40.2%
2 1863
33.3%
3 778
 
13.9%
4 371
 
6.6%
5 105
 
1.9%
9 91
 
1.6%
6 81
 
1.4%
8 54
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27415
83.1%
Common 5589
 
16.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8231
30.0%
산 1202
 
4.4%
장 1055
 
3.8%
읍 866
 
3.2%
녹 712
 
2.6%
대 646
 
2.4%
연 600
 
2.2%
안 558
 
2.0%
전 517
 
1.9%
천 466
 
1.7%
Other values (89) 12562
45.8%
Common
ValueCountFrequency (%)
1 2246
40.2%
2 1863
33.3%
3 778
 
13.9%
4 371
 
6.6%
5 105
 
1.9%
9 91
 
1.6%
6 81
 
1.4%
8 54
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27415
83.1%
ASCII 5589
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 8231
30.0%
산 1202
 
4.4%
장 1055
 
3.8%
읍 866
 
3.2%
녹 712
 
2.6%
대 646
 
2.4%
연 600
 
2.2%
안 558
 
2.0%
전 517
 
1.9%
천 466
 
1.7%
Other values (89) 12562
45.8%
ASCII
ValueCountFrequency (%)
1 2246
40.2%
2 1863
33.3%
3 778
 
13.9%
4 371
 
6.6%
5 105
 
1.9%
9 91
 
1.6%
6 81
 
1.4%
8 54
 
1.0%

불량여부
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
양호
9830 
<NA>
 
140
불량
 
26
준설필요
 
3
폐쇄
 
1

Length

Max length4
Median length2
Mean length2.0286
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
양호 9830
98.3%
<NA> 140
 
1.4%
불량 26
 
0.3%
준설필요 3
 
< 0.1%
폐쇄 1
 
< 0.1%

Length

2023-12-13T08:40:38.484818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:38.587094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양호 9830
98.3%
na 140
 
1.4%
불량 26
 
0.3%
준설필요 3
 
< 0.1%
폐쇄 1
 
< 0.1%

맨홀종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
오수맨홀
8344 
우수맨홀
1428 
<NA>
 
144
합류맨홀
 
38
공기변맨홀
 
18
Other values (5)
 
28

Length

Max length5
Median length4
Mean length4.0002
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
오수맨홀 8344
83.4%
우수맨홀 1428
 
14.3%
<NA> 144
 
1.4%
합류맨홀 38
 
0.4%
공기변맨홀 18
 
0.2%
기타 13
 
0.1%
이토변맨홀 5
 
0.1%
제수변맨홀 5
 
0.1%
방류맨홀 4
 
< 0.1%
차집맨홀 1
 
< 0.1%

Length

2023-12-13T08:40:38.693705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:38.804361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오수맨홀 8344
83.4%
우수맨홀 1428
 
14.3%
na 144
 
1.4%
합류맨홀 38
 
0.4%
공기변맨홀 18
 
0.2%
기타 13
 
0.1%
이토변맨홀 5
 
< 0.1%
제수변맨홀 5
 
< 0.1%
방류맨홀 4
 
< 0.1%
차집맨홀 1
 
< 0.1%

맨홀형식
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
표준맨홀
6714 
소형맨홀
2342 
<NA>
 
345
특수맨홀
 
252
기타
 
182
Other values (4)
 
165

Length

Max length7
Median length4
Mean length3.9678
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
표준맨홀 6714
67.1%
소형맨홀 2342
 
23.4%
<NA> 345
 
3.5%
특수맨홀 252
 
2.5%
기타 182
 
1.8%
미분류 69
 
0.7%
부관맨홀 57
 
0.6%
소재구,점검구 37
 
0.4%
폐쇠맨홀 2
 
< 0.1%

Length

2023-12-13T08:40:38.923902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:39.278617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
표준맨홀 6714
67.1%
소형맨홀 2342
 
23.4%
na 345
 
3.5%
특수맨홀 252
 
2.5%
기타 182
 
1.8%
미분류 69
 
0.7%
부관맨홀 57
 
0.6%
소재구,점검구 37
 
0.4%
폐쇠맨홀 2
 
< 0.1%

측량일자
Text

MISSING 

Distinct423
Distinct (%)7.4%
Missing4249
Missing (%)42.5%
Memory size156.2 KiB
2023-12-13T08:40:39.588059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters57510
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

Unique123 ?
Unique (%)2.1%

Sample

1st row2015-11-19
2nd row2018-02-20
3rd row2021-05-21
4th row2020-01-01
5th row2021-09-01
ValueCountFrequency (%)
2020-01-01 339
 
5.9%
2018-11-14 313
 
5.4%
2015-11-19 297
 
5.2%
2020-05-24 247
 
4.3%
2018-02-20 204
 
3.5%
2018-08-10 194
 
3.4%
2020-12-18 170
 
3.0%
2022-03-16 151
 
2.6%
2014-10-30 146
 
2.5%
2017-10-20 125
 
2.2%
Other values (413) 3565
62.0%
2023-12-13T08:40:40.070768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13891
24.2%
2 11986
20.8%
- 11502
20.0%
1 10753
18.7%
8 2000
 
3.5%
4 1701
 
3.0%
3 1641
 
2.9%
9 1208
 
2.1%
5 1201
 
2.1%
6 956
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46008
80.0%
Dash Punctuation 11502
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13891
30.2%
2 11986
26.1%
1 10753
23.4%
8 2000
 
4.3%
4 1701
 
3.7%
3 1641
 
3.6%
9 1208
 
2.6%
5 1201
 
2.6%
6 956
 
2.1%
7 671
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 11502
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13891
24.2%
2 11986
20.8%
- 11502
20.0%
1 10753
18.7%
8 2000
 
3.5%
4 1701
 
3.0%
3 1641
 
2.9%
9 1208
 
2.1%
5 1201
 
2.1%
6 956
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13891
24.2%
2 11986
20.8%
- 11502
20.0%
1 10753
18.7%
8 2000
 
3.5%
4 1701
 
3.0%
3 1641
 
2.9%
9 1208
 
2.1%
5 1201
 
2.1%
6 956
 
1.7%

Correlations

2023-12-13T08:40:40.208021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록구우오수구분뚜껑형태뚜껑재질불량여부맨홀종류맨홀형식
등록구1.0000.3200.2140.2760.0000.2720.366
우오수구분0.3201.0000.5130.3390.0000.8390.417
뚜껑형태0.2140.5131.0000.8090.0920.7750.410
뚜껑재질0.2760.3390.8091.0000.1520.3420.368
불량여부0.0000.0000.0920.1521.0000.0210.324
맨홀종류0.2720.8390.7750.3420.0211.0000.453
맨홀형식0.3660.4170.4100.3680.3240.4531.000
2023-12-13T08:40:40.321857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록구불량여부맨홀종류맨홀형식뚜껑재질우오수구분뚜껑형태
등록구1.0000.0000.1110.1620.1190.1710.117
불량여부0.0001.0000.0130.1500.0690.0000.086
맨홀종류0.1110.0131.0000.2420.1750.6850.480
맨홀형식0.1620.1500.2421.0000.1300.2720.286
뚜껑재질0.1190.0690.1750.1301.0000.2160.738
우오수구분0.1710.0000.6850.2720.2161.0000.450
뚜껑형태0.1170.0860.4800.2860.7380.4501.000
2023-12-13T08:40:40.440112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록구우오수구분뚜껑형태뚜껑재질불량여부맨홀종류맨홀형식
등록구1.0000.1710.1170.1190.0000.1110.162
우오수구분0.1711.0000.4500.2160.0000.6850.272
뚜껑형태0.1170.4501.0000.7380.0860.4800.286
뚜껑재질0.1190.2160.7381.0000.0690.1750.130
불량여부0.0000.0000.0860.0691.0000.0130.150
맨홀종류0.1110.6850.4800.1750.0131.0000.242
맨홀형식0.1620.2720.2860.1300.1500.2421.000

Missing values

2023-12-13T08:40:35.283968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:40:35.446371image/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.
2023-12-13T08:40:35.647406image/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
775강서구2002-12-10<NA>오수원형뚜껑주철대저1동양호오수맨홀표준맨홀<NA>
10002부산진구2016-07-302016-07-30오수원형뚜껑주철<NA>양호오수맨홀표준맨홀<NA>
34253사상구2015-11-192015-11-19오수원형뚜껑주철학장동양호오수맨홀표준맨홀2015-11-19
76737동구2019-12-31<NA>오수미분류미분류수정5동양호오수맨홀표준맨홀<NA>
50354남구2017-12-302017-12-30오수원형뚜껑주철대연5동양호오수맨홀소형맨홀2018-02-20
81110금정구2021-01-01<NA>오수원형뚜껑주철남산동양호오수맨홀표준맨홀2021-05-21
62703기장군2019-12-31<NA>오수원형뚜껑주철장안읍양호오수맨홀표준맨홀<NA>
10675금정구<NA><NA>오수원형뚜껑주철선두구동양호오수맨홀<NA><NA>
17399사하구2012-02-29<NA>오수원형뚜껑주철하단2동양호오수맨홀표준맨홀<NA>
79845부산진구2020-01-012020-01-01오수원형뚜껑주철초읍동양호오수맨홀표준맨홀2020-01-01
등록구설치일자최종준설일자우오수구분뚜껑형태뚜껑재질행정동불량여부맨홀종류맨홀형식측량일자
38080사상구2015-11-192015-11-19오수원형뚜껑주철감전동양호오수맨홀표준맨홀2015-11-19
4799기장군2012-10-302012-10-30오수원형뚜껑주철장안읍양호오수맨홀표준맨홀2012-10-30
54368동래구2018-10-01<NA>오수원형뚜껑주철안락1동양호오수맨홀소형맨홀<NA>
86103연제구2022-03-16<NA>오수원형뚜껑주철연산8동양호오수맨홀소형맨홀2022-03-16
4460북구2015-02-19<NA>오수원형뚜껑주철금곡동양호오수맨홀소형맨홀2015-02-16
71772중구2021-04-13<NA>오수원형뚜껑주철광복동양호오수맨홀소형맨홀2021-04-13
55502수영구2018-05-31<NA>오수원형뚜껑주철광안2동양호오수맨홀소형맨홀2018-08-10
56447북구<NA><NA>우수각형뚜껑스틸그리팅(SG)<NA>양호우수맨홀표준맨홀<NA>
1666북구2014-12-31<NA>오수원형뚜껑주철만덕2동양호오수맨홀표준맨홀2014-12-31
41913영도구2005-12-01<NA>오수원형뚜껑주철영선2동양호오수맨홀표준맨홀<NA>

Duplicate rows

Most frequently occurring

등록구설치일자최종준설일자우오수구분뚜껑형태뚜껑재질행정동불량여부맨홀종류맨홀형식측량일자# duplicates
790사상구2016-07-222016-07-22오수원형뚜껑주철<NA>양호오수맨홀표준맨홀<NA>117
4강서구2001-08-182001-08-18오수원형뚜껑주철녹산동양호오수맨홀표준맨홀<NA>105
62강서구2013-12-31<NA>우수원형뚜껑주철녹산동양호우수맨홀표준맨홀2014-10-3089
209금정구2021-01-01<NA>오수원형뚜껑주철남산동양호오수맨홀표준맨홀2021-05-2187
852사하구2012-02-29<NA>오수원형뚜껑주철<NA>양호오수맨홀소형맨홀<NA>82
904사하구2020-12-18<NA>오수원형뚜껑주철하단2동양호오수맨홀소형맨홀2020-12-1875
958수영구2018-05-31<NA>오수원형뚜껑주철민락동양호오수맨홀소형맨홀2018-08-1074
604부산진구2016-07-302016-07-30오수원형뚜껑주철<NA>양호오수맨홀소형맨홀<NA>65
776사상구2015-11-192015-11-19오수원형뚜껑주철감전동양호오수맨홀표준맨홀2015-11-1961
1137해운대구2017-10-20<NA>오수원형뚜껑주철반여1동양호오수맨홀표준맨홀2017-10-2058