Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)< 0.1%
Total size in memory546.9 KiB
Average record size in memory56.0 B

Variable types

Text3
Categorical3

Dataset

Description국토안전관리원에서 제공하는 데이터이며 시설물의안전관리에관한특별법에 의거하여 국토안전관리원에서 운영중인 시설물정보관리종합시스템 내 등록된 공공시설물(공동주택 제외)의 시설물명, 시설물구분, 시설물소재지, 시설물안전관리부서명(취합기관) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15017292/fileData.do

Alerts

Dataset has 4 (< 0.1%) duplicate rowsDuplicates
시설물구분 is highly overall correlated with 종별High correlation
종별 is highly overall correlated with 시설물구분High correlation

Reproduction

Analysis started2023-12-12 16:50:49.221845
Analysis finished2023-12-12 16:50:50.430816
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설물명
Text

Distinct9726
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:50:50.701988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length8.629
Min length2

Characters and Unicode

Total characters86290
Distinct characters649
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9527 ?
Unique (%)95.3%

Sample

1st row송정교(함안)
2nd row마련제2교
3rd row문상초등학교 후관교사
4th row대복2교(울산)
5th row돈내교
ValueCountFrequency (%)
교사동 220
 
1.5%
본관동 168
 
1.2%
옹벽 131
 
0.9%
절토사면 131
 
0.9%
본관 126
 
0.9%
교사 56
 
0.4%
본관교사 56
 
0.4%
보강토옹벽 40
 
0.3%
터널 38
 
0.3%
교사1호동 36
 
0.2%
Other values (11141) 13419
93.1%
2023-12-13T01:50:51.239834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 7000
 
8.1%
4423
 
5.1%
) 2616
 
3.0%
( 2615
 
3.0%
동 2134
 
2.5%
1 2088
 
2.4%
학 1972
 
2.3%
2 1708
 
2.0%
사 1541
 
1.8%
수 1455
 
1.7%
Other values (639) 58738
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63659
73.8%
Decimal Number 8889
 
10.3%
Space Separator 4428
 
5.1%
Close Punctuation 2651
 
3.1%
Open Punctuation 2650
 
3.1%
Uppercase Letter 1992
 
2.3%
Other Punctuation 768
 
0.9%
Math Symbol 455
 
0.5%
Lowercase Letter 428
 
0.5%
Dash Punctuation 359
 
0.4%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 7000
 
11.0%
동 2134
 
3.4%
학 1972
 
3.1%
사 1541
 
2.4%
수 1455
 
2.3%
관 1367
 
2.1%
천 1347
 
2.1%
등 1258
 
2.0%
산 1102
 
1.7%
초 992
 
1.6%
Other values (567) 43491
68.3%
Uppercase Letter
ValueCountFrequency (%)
C 354
17.8%
I 265
13.3%
A 188
9.4%
T 168
8.4%
B 164
8.2%
D 139
 
7.0%
S 134
 
6.7%
U 112
 
5.6%
J 81
 
4.1%
R 79
 
4.0%
Other values (15) 308
15.5%
Lowercase Letter
ValueCountFrequency (%)
k 296
69.2%
m 54
 
12.6%
a 24
 
5.6%
p 18
 
4.2%
t 8
 
1.9%
e 6
 
1.4%
l 5
 
1.2%
n 4
 
0.9%
i 4
 
0.9%
s 4
 
0.9%
Other values (5) 5
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 2088
23.5%
2 1708
19.2%
0 1294
14.6%
3 860
9.7%
4 638
 
7.2%
5 516
 
5.8%
6 494
 
5.6%
7 490
 
5.5%
8 421
 
4.7%
9 380
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 579
75.4%
, 87
 
11.3%
/ 80
 
10.4%
# 15
 
2.0%
: 5
 
0.7%
· 2
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 233
51.2%
+ 177
38.9%
| 38
 
8.4%
∼ 7
 
1.5%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
44.4%
Ⅱ 3
33.3%
Ⅲ 2
22.2%
Space Separator
ValueCountFrequency (%)
4423
99.9%
　 5
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 2616
98.7%
] 35
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 2615
98.7%
[ 35
 
1.3%
Other Number
ValueCountFrequency (%)
③ 1
50.0%
① 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 359
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63658
73.8%
Common 20202
 
23.4%
Latin 2427
 
2.8%
Greek 2
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 7000
 
11.0%
동 2134
 
3.4%
학 1972
 
3.1%
사 1541
 
2.4%
수 1455
 
2.3%
관 1367
 
2.1%
천 1347
 
2.1%
등 1258
 
2.0%
산 1102
 
1.7%
초 992
 
1.6%
Other values (566) 43490
68.3%
Latin
ValueCountFrequency (%)
C 354
14.6%
k 296
12.2%
I 265
10.9%
A 188
 
7.7%
T 168
 
6.9%
B 164
 
6.8%
D 139
 
5.7%
S 134
 
5.5%
U 112
 
4.6%
J 81
 
3.3%
Other values (32) 526
21.7%
Common
ValueCountFrequency (%)
4423
21.9%
) 2616
12.9%
( 2615
12.9%
1 2088
10.3%
2 1708
 
8.5%
0 1294
 
6.4%
3 860
 
4.3%
4 638
 
3.2%
. 579
 
2.9%
5 516
 
2.6%
Other values (19) 2865
14.2%
Greek
ValueCountFrequency (%)
Ι 2
100.0%
Han
ValueCountFrequency (%)
舊 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63657
73.8%
ASCII 22604
 
26.2%
None 9
 
< 0.1%
Number Forms 9
 
< 0.1%
Math Operators 7
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 7000
 
11.0%
동 2134
 
3.4%
학 1972
 
3.1%
사 1541
 
2.4%
수 1455
 
2.3%
관 1367
 
2.1%
천 1347
 
2.1%
등 1258
 
2.0%
산 1102
 
1.7%
초 992
 
1.6%
Other values (565) 43489
68.3%
ASCII
ValueCountFrequency (%)
4423
19.6%
) 2616
11.6%
( 2615
11.6%
1 2088
 
9.2%
2 1708
 
7.6%
0 1294
 
5.7%
3 860
 
3.8%
4 638
 
2.8%
. 579
 
2.6%
5 516
 
2.3%
Other values (53) 5267
23.3%
Math Operators
ValueCountFrequency (%)
∼ 7
100.0%
None
ValueCountFrequency (%)
　 5
55.6%
Ι 2
 
22.2%
· 2
 
22.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
44.4%
Ⅱ 3
33.3%
Ⅲ 2
22.2%
CJK
ValueCountFrequency (%)
舊 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
③ 1
50.0%
① 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

시설물구분
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
교량
4245 
건축물
2829 
하천
939 
터널
577 
절토사면
527 
Other values (6)
883 

Length

Max length4
Median length2
Mean length2.4347
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교량
2nd row교량
3rd row건축물
4th row교량
5th row교량

Common Values

ValueCountFrequency (%)
교량 4245
42.4%
건축물 2829
28.3%
하천 939
 
9.4%
터널 577
 
5.8%
절토사면 527
 
5.3%
옹벽 392
 
3.9%
상하수도 275
 
2.8%
댐 92
 
0.9%
기타 84
 
0.8%
항만 34
 
0.3%

Length

2023-12-13T01:50:51.396405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교량 4245
42.4%
건축물 2829
28.3%
하천 939
 
9.4%
터널 577
 
5.8%
절토사면 527
 
5.3%
옹벽 392
 
3.9%
상하수도 275
 
2.8%
댐 92
 
0.9%
기타 84
 
0.8%
항만 34
 
0.3%

시설물소재지
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
1782 
경상북도
1182 
강원특별자치도
898 
경상남도
869 
충청남도
799 
Other values (12)
4470 

Length

Max length7
Median length5
Mean length4.3565
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도
2nd row충청북도
3rd row충청북도
4th row울산광역시
5th row경상북도

Common Values

ValueCountFrequency (%)
경기도 1782
17.8%
경상북도 1182
11.8%
강원특별자치도 898
9.0%
경상남도 869
8.7%
충청남도 799
8.0%
전라남도 747
7.5%
전라북도 713
7.1%
서울특별시 684
 
6.8%
충청북도 667
 
6.7%
부산광역시 366
 
3.7%
Other values (7) 1293
12.9%

Length

2023-12-13T01:50:51.592330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 1782
17.8%
경상북도 1182
11.8%
강원특별자치도 898
9.0%
경상남도 869
8.7%
충청남도 799
8.0%
전라남도 747
7.5%
전라북도 713
7.1%
서울특별시 684
 
6.8%
충청북도 667
 
6.7%
부산광역시 366
 
3.7%
Other values (7) 1293
12.9%

관리주체
Text

Distinct2932
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:50:51.916481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length9.9827
Min length3

Characters and Unicode

Total characters99827
Distinct characters414
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2020 ?
Unique (%)20.2%

Sample

1st row경상남도 도로안전과
2nd row충청본부
3rd row문상초등학교
4th row한국도로공사 서울산지사 밀양울산팀
5th row포항시 북구청 건설교통과
ValueCountFrequency (%)
한국도로공사 1278
 
7.7%
건설과 609
 
3.7%
한국철도공사 404
 
2.4%
도로과 362
 
2.2%
도로관리사업소 191
 
1.2%
한국농어촌공사 171
 
1.0%
도로안전팀 158
 
1.0%
안전건설과 131
 
0.8%
도로관리과 123
 
0.7%
시설처 97
 
0.6%
Other values (2972) 13020
78.7%
2023-12-13T01:50:52.386201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6559
 
6.6%
사 5390
 
5.4%
도 4333
 
4.3%
국 3164
 
3.2%
청 3138
 
3.1%
시 2969
 
3.0%
과 2933
 
2.9%
로 2836
 
2.8%
공 2388
 
2.4%
관 2363
 
2.4%
Other values (404) 63754
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91655
91.8%
Space Separator 6559
 
6.6%
Open Punctuation 645
 
0.6%
Close Punctuation 645
 
0.6%
Decimal Number 226
 
0.2%
Math Symbol 43
 
< 0.1%
Other Punctuation 27
 
< 0.1%
Uppercase Letter 12
 
< 0.1%
Dash Punctuation 10
 
< 0.1%
Other Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 5390
 
5.9%
도 4333
 
4.7%
국 3164
 
3.5%
청 3138
 
3.4%
시 2969
 
3.2%
과 2933
 
3.2%
로 2836
 
3.1%
공 2388
 
2.6%
관 2363
 
2.6%
교 2313
 
2.5%
Other values (377) 59828
65.3%
Decimal Number
ValueCountFrequency (%)
2 70
31.0%
1 52
23.0%
5 28
 
12.4%
8 26
 
11.5%
3 21
 
9.3%
4 20
 
8.8%
9 5
 
2.2%
6 3
 
1.3%
0 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
H 4
33.3%
L 2
16.7%
S 2
16.7%
D 1
 
8.3%
R 1
 
8.3%
E 1
 
8.3%
G 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 17
63.0%
/ 9
33.3%
. 1
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
6559
100.0%
Open Punctuation
ValueCountFrequency (%)
( 645
100.0%
Close Punctuation
ValueCountFrequency (%)
) 645
100.0%
Math Symbol
ValueCountFrequency (%)
~ 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91658
91.8%
Common 8155
 
8.2%
Latin 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 5390
 
5.9%
도 4333
 
4.7%
국 3164
 
3.5%
청 3138
 
3.4%
시 2969
 
3.2%
과 2933
 
3.2%
로 2836
 
3.1%
공 2388
 
2.6%
관 2363
 
2.6%
교 2313
 
2.5%
Other values (378) 59831
65.3%
Common
ValueCountFrequency (%)
6559
80.4%
( 645
 
7.9%
) 645
 
7.9%
2 70
 
0.9%
1 52
 
0.6%
~ 43
 
0.5%
5 28
 
0.3%
8 26
 
0.3%
3 21
 
0.3%
4 20
 
0.2%
Other values (7) 46
 
0.6%
Latin
ValueCountFrequency (%)
H 4
28.6%
L 2
14.3%
S 2
14.3%
D 1
 
7.1%
R 1
 
7.1%
E 1
 
7.1%
c 1
 
7.1%
o 1
 
7.1%
G 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91655
91.8%
ASCII 8169
 
8.2%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6559
80.3%
( 645
 
7.9%
) 645
 
7.9%
2 70
 
0.9%
1 52
 
0.6%
~ 43
 
0.5%
5 28
 
0.3%
8 26
 
0.3%
3 21
 
0.3%
4 20
 
0.2%
Other values (16) 60
 
0.7%
Hangul
ValueCountFrequency (%)
사 5390
 
5.9%
도 4333
 
4.7%
국 3164
 
3.5%
청 3138
 
3.4%
시 2969
 
3.2%
과 2933
 
3.2%
로 2836
 
3.1%
공 2388
 
2.6%
관 2363
 
2.6%
교 2313
 
2.5%
Other values (377) 59828
65.3%
None
ValueCountFrequency (%)
㈜ 3
100.0%

취합기관
Text

Distinct321
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:50:52.711557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.4618
Min length3

Characters and Unicode

Total characters74618
Distinct characters184
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.4%

Sample

1st row경상남도청
2nd row국가철도공단
3rd row충청북도교육청
4th row한국도로공사
5th row경상북도 포항시청
ValueCountFrequency (%)
한국도로공사 1278
 
9.7%
경기도 813
 
6.2%
한국철도공사 477
 
3.6%
경상남도 395
 
3.0%
경상북도 379
 
2.9%
경기도교육청 355
 
2.7%
강원특별자치도 346
 
2.6%
부산지방국토관리청 312
 
2.4%
충청남도 261
 
2.0%
서울특별시교육청 247
 
1.9%
Other values (313) 8267
63.0%
2023-12-13T01:50:53.171737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 8215
 
11.0%
도 6277
 
8.4%
시 3607
 
4.8%
3130
 
4.2%
국 3107
 
4.2%
경 2644
 
3.5%
공 2297
 
3.1%
사 2228
 
3.0%
교 2035
 
2.7%
한 2026
 
2.7%
Other values (174) 39052
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71366
95.6%
Space Separator 3130
 
4.2%
Open Punctuation 49
 
0.1%
Close Punctuation 49
 
0.1%
Uppercase Letter 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 8215
 
11.5%
도 6277
 
8.8%
시 3607
 
5.1%
국 3107
 
4.4%
경 2644
 
3.7%
공 2297
 
3.2%
사 2228
 
3.1%
교 2035
 
2.9%
한 2026
 
2.8%
육 1902
 
2.7%
Other values (169) 37028
51.9%
Uppercase Letter
ValueCountFrequency (%)
H 12
50.0%
L 12
50.0%
Space Separator
ValueCountFrequency (%)
3130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71366
95.6%
Common 3228
 
4.3%
Latin 24
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 8215
 
11.5%
도 6277
 
8.8%
시 3607
 
5.1%
국 3107
 
4.4%
경 2644
 
3.7%
공 2297
 
3.2%
사 2228
 
3.1%
교 2035
 
2.9%
한 2026
 
2.8%
육 1902
 
2.7%
Other values (169) 37028
51.9%
Common
ValueCountFrequency (%)
3130
97.0%
( 49
 
1.5%
) 49
 
1.5%
Latin
ValueCountFrequency (%)
H 12
50.0%
L 12
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71366
95.6%
ASCII 3252
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 8215
 
11.5%
도 6277
 
8.8%
시 3607
 
5.1%
국 3107
 
4.4%
경 2644
 
3.7%
공 2297
 
3.2%
사 2228
 
3.1%
교 2035
 
2.9%
한 2026
 
2.8%
육 1902
 
2.7%
Other values (169) 37028
51.9%
ASCII
ValueCountFrequency (%)
3130
96.2%
( 49
 
1.5%
) 49
 
1.5%
H 12
 
0.4%
L 12
 
0.4%

종별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3종
5434 
2종
3582 
1종
984 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3종
2nd row2종
3rd row3종
4th row2종
5th row3종

Common Values

ValueCountFrequency (%)
3종 5434
54.3%
2종 3582
35.8%
1종 984
 
9.8%

Length

2023-12-13T01:50:53.363626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:50:53.476678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3종 5434
54.3%
2종 3582
35.8%
1종 984
 
9.8%

Correlations

2023-12-13T01:50:53.563411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설물구분시설물소재지종별
시설물구분1.0000.3510.668
시설물소재지0.3511.0000.221
종별0.6680.2211.000
2023-12-13T01:50:53.688293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별시설물구분시설물소재지
종별1.0000.5060.121
시설물구분0.5061.0000.138
시설물소재지0.1210.1381.000
2023-12-13T01:50:53.837229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설물구분시설물소재지종별
시설물구분1.0000.1380.506
시설물소재지0.1381.0000.121
종별0.5060.1211.000

Missing values

2023-12-13T01:50:50.231714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:50:50.365372image/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.

Sample

시설물명시설물구분시설물소재지관리주체취합기관종별
33858송정교(함안)교량경상남도경상남도 도로안전과경상남도청3종
19637마련제2교교량충청북도충청본부국가철도공단2종
42957문상초등학교 후관교사건축물충청북도문상초등학교충청북도교육청3종
10019대복2교(울산)교량울산광역시한국도로공사 서울산지사 밀양울산팀한국도로공사2종
37395돈내교교량경상북도포항시 북구청 건설교통과경상북도 포항시청3종
10785상우1교(양평)교량충청북도한국도로공사 충주지사한국도로공사2종
57301구외초소건축물경상남도밀양구치소법무부3종
11290노근2교(부산0)교량충청북도한국도로공사 영동지사한국도로공사3종
19732강동대교(구리0)교량서울특별시한국도로공사 동서울지사한국도로공사1종
10883상직3교(상주)교량경상북도한국도로공사 청송지사한국도로공사2종
시설물명시설물구분시설물소재지관리주체취합기관종별
50668광주우산초등학교 교사(본관동)건축물광주광역시광주우산초등학교광주광역시교육청3종
29410탄천2지하보도터널경기도성남시 도로과경기도 성남시청3종
32202검암1제하천경상남도함안군청 안전총괄과경상남도 함안군청2종
59894대림2빗물펌프장하천서울특별시영등포구 치수과 기전팀서울특별시청2종
15756두릉1교(양평)교량경상북도한국도로공사 상주지사한국도로공사3종
64690남산교교량전라남도여수시청 도로시설관리과전라남도 여수시청3종
65197기룡교교량전라남도강진군청 건설과 도로관리팀2전라남도 강진군청3종
33401구룡교(구만교)교량경상남도함양군청 도로담당경상남도 함양군청3종
40580경수초등학교 교사동건축물경기도경수초등학교경기도교육청3종
20132수척교교량대전광역시고속시설사업단(오송고속광역2)한국철도공사1종

Duplicate rows

Most frequently occurring

시설물명시설물구분시설물소재지관리주체취합기관종별# duplicates
0대천교교량경상남도도로관리사업소 진주지소경상남도청3종2
1장평천교교량충청북도한국철도공사 충북지역관리단 시설처한국철도공사2종2
2창암교교량강원특별자치도강원도 도로관리사업소 북부지소강원특별자치도청3종2
3하촌교교량경상남도진주시경상남도 진주시청3종2