Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells11233
Missing cells (%)11.2%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory859.4 KiB
Average record size in memory88.0 B

Variable types

Text2
Categorical5
DateTime3

Dataset

Description국토안전관리원에서 제공하는 데이터이며 공공시설물의(공동주택 제외) 안전관리현황인 시설물명, 구분, 종류, 종별 등의 CSV형식의 파일데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15046036/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
시설물종류 is highly overall correlated with 시설물구분 and 1 other fieldsHigh correlation
시설물구분 is highly overall correlated with 시설물종류 and 1 other fieldsHigh correlation
종별 is highly overall correlated with 시설물구분 and 1 other fieldsHigh correlation
차기정기점검도래일 is highly imbalanced (72.9%)Imbalance
등급 is highly imbalanced (50.4%)Imbalance
차기정밀점검도래일 has 5346 (53.5%) missing valuesMissing
최종정기점검일 has 214 (2.1%) missing valuesMissing
최종정밀점검일 has 5673 (56.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 07:04:20.104281
Analysis finished2023-12-12 07:04:21.876466
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설물명
Text

Distinct9729
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T16:04:22.213226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length8.4974
Min length2

Characters and Unicode

Total characters84974
Distinct characters655
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9533 ?
Unique (%)95.3%

Sample

1st row대산하수종말처리장
2nd row4-026 혜화역
3rd row군산대학교 자연대3호관
4th row석보초등학교 교사(본관동)
5th row군위 고로 화수 (상)
ValueCountFrequency (%)
교사동 232
 
1.6%
본관동 175
 
1.2%
본관 130
 
0.9%
옹벽 117
 
0.8%
절토사면 104
 
0.7%
교사 63
 
0.4%
본관교사 42
 
0.3%
보강토옹벽 37
 
0.3%
교사1호동 37
 
0.3%
터널 36
 
0.3%
Other values (11107) 13330
93.2%
2023-12-12T16:04:22.825246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 6896
 
8.1%
4309
 
5.1%
( 2578
 
3.0%
) 2578
 
3.0%
동 2054
 
2.4%
1 2037
 
2.4%
학 1943
 
2.3%
2 1594
 
1.9%
수 1455
 
1.7%
사 1450
 
1.7%
Other values (645) 58080
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62512
73.6%
Decimal Number 8507
 
10.0%
Space Separator 4311
 
5.1%
Open Punctuation 2609
 
3.1%
Close Punctuation 2609
 
3.1%
Uppercase Letter 1959
 
2.3%
Other Punctuation 899
 
1.1%
Lowercase Letter 817
 
1.0%
Math Symbol 394
 
0.5%
Dash Punctuation 334
 
0.4%
Other values (6) 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 6896
 
11.0%
동 2054
 
3.3%
학 1943
 
3.1%
수 1455
 
2.3%
사 1450
 
2.3%
관 1298
 
2.1%
천 1283
 
2.1%
등 1250
 
2.0%
산 1036
 
1.7%
초 991
 
1.6%
Other values (564) 42856
68.6%
Uppercase Letter
ValueCountFrequency (%)
C 295
15.1%
I 241
12.3%
D 214
10.9%
A 181
9.2%
B 160
8.2%
T 142
 
7.2%
S 123
 
6.3%
U 118
 
6.0%
R 67
 
3.4%
J 59
 
3.0%
Other values (14) 359
18.3%
Lowercase Letter
ValueCountFrequency (%)
m 251
30.7%
k 235
28.8%
u 121
14.8%
y 109
13.3%
l 27
 
3.3%
a 16
 
2.0%
d 15
 
1.8%
p 14
 
1.7%
e 7
 
0.9%
t 5
 
0.6%
Other values (9) 17
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 2037
23.9%
2 1594
18.7%
0 1262
14.8%
3 886
10.4%
4 561
 
6.6%
5 521
 
6.1%
6 511
 
6.0%
7 423
 
5.0%
8 365
 
4.3%
9 347
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 704
78.3%
, 101
 
11.2%
/ 72
 
8.0%
# 11
 
1.2%
: 7
 
0.8%
· 3
 
0.3%
@ 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 8
57.1%
Ⅱ 3
 
21.4%
Ⅳ 1
 
7.1%
Ⅵ 1
 
7.1%
Ⅲ 1
 
7.1%
Math Symbol
ValueCountFrequency (%)
~ 196
49.7%
+ 159
40.4%
| 36
 
9.1%
∼ 3
 
0.8%
Space Separator
ValueCountFrequency (%)
4309
> 99.9%
　 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2578
98.8%
[ 31
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 2578
98.8%
] 31
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 334
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
㎞ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Number
ValueCountFrequency (%)
② 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62511
73.6%
Common 19672
 
23.2%
Latin 2790
 
3.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 6896
 
11.0%
동 2054
 
3.3%
학 1943
 
3.1%
수 1455
 
2.3%
사 1450
 
2.3%
관 1298
 
2.1%
천 1283
 
2.1%
등 1250
 
2.0%
산 1036
 
1.7%
초 991
 
1.6%
Other values (563) 42855
68.6%
Latin
ValueCountFrequency (%)
C 295
 
10.6%
m 251
 
9.0%
I 241
 
8.6%
k 235
 
8.4%
D 214
 
7.7%
A 181
 
6.5%
B 160
 
5.7%
T 142
 
5.1%
S 123
 
4.4%
u 121
 
4.3%
Other values (38) 827
29.6%
Common
ValueCountFrequency (%)
4309
21.9%
( 2578
13.1%
) 2578
13.1%
1 2037
10.4%
2 1594
 
8.1%
0 1262
 
6.4%
3 886
 
4.5%
. 704
 
3.6%
4 561
 
2.9%
5 521
 
2.6%
Other values (23) 2642
13.4%
Han
ValueCountFrequency (%)
舊 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62509
73.6%
ASCII 22437
 
26.4%
Number Forms 14
 
< 0.1%
None 5
 
< 0.1%
Math Operators 3
 
< 0.1%
CJK Compat 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 6896
 
11.0%
동 2054
 
3.3%
학 1943
 
3.1%
수 1455
 
2.3%
사 1450
 
2.3%
관 1298
 
2.1%
천 1283
 
2.1%
등 1250
 
2.0%
산 1036
 
1.7%
초 991
 
1.6%
Other values (562) 42853
68.6%
ASCII
ValueCountFrequency (%)
4309
19.2%
( 2578
11.5%
) 2578
11.5%
1 2037
 
9.1%
2 1594
 
7.1%
0 1262
 
5.6%
3 886
 
3.9%
. 704
 
3.1%
4 561
 
2.5%
5 521
 
2.3%
Other values (61) 5407
24.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 8
57.1%
Ⅱ 3
 
21.4%
Ⅳ 1
 
7.1%
Ⅵ 1
 
7.1%
Ⅲ 1
 
7.1%
Math Operators
ValueCountFrequency (%)
∼ 3
100.0%
None
ValueCountFrequency (%)
· 3
60.0%
　 2
40.0%
CJK Compat
ValueCountFrequency (%)
㎞ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 1
100.0%
CJK
ValueCountFrequency (%)
舊 1
100.0%

시설물구분
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
교량
4249 
건축물
2780 
하천
961 
터널
584 
절토사면
506 
Other values (6)
920 

Length

Max length4
Median length2
Mean length2.432
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상하수도
2nd row건축물
3rd row건축물
4th row건축물
5th row절토사면

Common Values

ValueCountFrequency (%)
교량 4249
42.5%
건축물 2780
27.8%
하천 961
 
9.6%
터널 584
 
5.8%
절토사면 506
 
5.1%
옹벽 381
 
3.8%
상하수도 311
 
3.1%
댐 100
 
1.0%
항만 67
 
0.7%
기타 55
 
0.5%

Length

2023-12-12T16:04:22.975585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교량 4249
42.5%
건축물 2780
27.8%
하천 961
 
9.6%
터널 584
 
5.8%
절토사면 506
 
5.1%
옹벽 381
 
3.8%
상하수도 311
 
3.1%
댐 100
 
1.0%
항만 67
 
0.7%
기타 55
 
0.5%

시설물종류
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
도로교량
3696 
다중이용건축물
1835 
대형건축물
640 
수문 및 통문
548 
도로사면
481 
Other values (37)
2800 

Length

Max length12
Median length4
Mean length4.7853
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row공공하수처리시설
2nd row철도역시설
3rd row다중이용건축물
4th row다중이용건축물
5th row도로사면

Common Values

ValueCountFrequency (%)
도로교량 3696
37.0%
다중이용건축물 1835
18.4%
대형건축물 640
 
6.4%
수문 및 통문 548
 
5.5%
도로사면 481
 
4.8%
철도교량 365
 
3.6%
도로터널 315
 
3.1%
기타 240
 
2.4%
제방 210
 
2.1%
지방상수도 193
 
1.9%
Other values (32) 1477
 
14.8%

Length

2023-12-12T16:04:23.138130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도로교량 3696
33.2%
다중이용건축물 1835
16.5%
대형건축물 640
 
5.8%
및 565
 
5.1%
수문 548
 
4.9%
통문 548
 
4.9%
도로사면 481
 
4.3%
철도교량 365
 
3.3%
도로터널 315
 
2.8%
기타 240
 
2.2%
Other values (35) 1897
17.0%

종별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3종
5343 
2종
3603 
1종
1054 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3종 5343
53.4%
2종 3603
36.0%
1종 1054
 
10.5%

Length

2023-12-12T16:04:23.290585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:04:23.408009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3종 5343
53.4%
2종 3603
36.0%
1종 1054
 
10.5%

주소
Text

Distinct272
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T16:04:23.968542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length7.6761
Min length6

Characters and Unicode

Total characters76761
Distinct characters152
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 row충청남도서산시
2nd row서울특별시종로구
3rd row전라북도군산시
4th row경상북도영양군
5th row대구광역시군위군
ValueCountFrequency (%)
충청북도청주시 162
 
1.5%
경상남도창원시 135
 
1.2%
경기도고양시 124
 
1.1%
경상남도진주시 116
 
1.1%
경상남도김해시 114
 
1.0%
경상북도경주시 111
 
1.0%
울산광역시울주군 110
 
1.0%
경상북도구미시 108
 
1.0%
강원특별자치도삼척시 105
 
1.0%
경기도용인시 104
 
1.0%
Other values (262) 9672
89.1%
2023-12-12T16:04:24.433845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 7770
 
10.1%
시 7224
 
9.4%
경 3995
 
5.2%
구 3345
 
4.4%
군 3199
 
4.2%
남 2982
 
3.9%
북 2869
 
3.7%
상 2226
 
2.9%
광 1902
 
2.5%
주 1847
 
2.4%
Other values (142) 39402
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75900
98.9%
Space Separator 861
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 7770
 
10.2%
시 7224
 
9.5%
경 3995
 
5.3%
구 3345
 
4.4%
군 3199
 
4.2%
남 2982
 
3.9%
북 2869
 
3.8%
상 2226
 
2.9%
광 1902
 
2.5%
주 1847
 
2.4%
Other values (141) 38541
50.8%
Space Separator
ValueCountFrequency (%)
861
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75900
98.9%
Common 861
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 7770
 
10.2%
시 7224
 
9.5%
경 3995
 
5.3%
구 3345
 
4.4%
군 3199
 
4.2%
남 2982
 
3.9%
북 2869
 
3.8%
상 2226
 
2.9%
광 1902
 
2.5%
주 1847
 
2.4%
Other values (141) 38541
50.8%
Common
ValueCountFrequency (%)
861
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75900
98.9%
ASCII 861
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 7770
 
10.2%
시 7224
 
9.5%
경 3995
 
5.3%
구 3345
 
4.4%
군 3199
 
4.2%
남 2982
 
3.9%
북 2869
 
3.8%
상 2226
 
2.9%
광 1902
 
2.5%
주 1847
 
2.4%
Other values (141) 38541
50.8%
ASCII
ValueCountFrequency (%)
861
100.0%

차기정기점검도래일
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-06-30
4897 
2023-12-31
4692 
2022-12-31
 
164
2018-12-31
 
63
2000-06-30
 
42
Other values (25)
 
142

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique8 ?
Unique (%)0.1%

Sample

1st row2023-06-30
2nd row2023-06-30
3rd row2023-06-30
4th row2023-06-30
5th row2023-12-31

Common Values

ValueCountFrequency (%)
2023-06-30 4897
49.0%
2023-12-31 4692
46.9%
2022-12-31 164
 
1.6%
2018-12-31 63
 
0.6%
2000-06-30 42
 
0.4%
2022-06-30 37
 
0.4%
2016-06-30 25
 
0.2%
2004-06-30 17
 
0.2%
2012-06-30 8
 
0.1%
2017-06-30 8
 
0.1%
Other values (20) 47
 
0.5%

Length

2023-12-12T16:04:24.623816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-06-30 4897
49.0%
2023-12-31 4692
46.9%
2022-12-31 164
 
1.6%
2018-12-31 63
 
0.6%
2000-06-30 42
 
0.4%
2022-06-30 37
 
0.4%
2016-06-30 25
 
0.2%
2004-06-30 17
 
0.2%
2012-06-30 8
 
0.1%
2017-06-30 8
 
0.1%
Other values (20) 47
 
0.5%

차기정밀점검도래일
Date

MISSING 

Distinct863
Distinct (%)18.5%
Missing5346
Missing (%)53.5%
Memory size156.2 KiB
Minimum1997-06-03 00:00:00
Maximum2027-06-09 00:00:00
2023-12-12T16:04:24.779730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:24.957301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등급
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
B등급
7066 
C등급
1390 
A등급
1279 
불명
 
239
D등급
 
24

Length

Max length3
Median length3
Mean length2.9761
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA등급
2nd rowB등급
3rd rowB등급
4th rowB등급
5th rowC등급

Common Values

ValueCountFrequency (%)
B등급 7066
70.7%
C등급 1390
 
13.9%
A등급 1279
 
12.8%
불명 239
 
2.4%
D등급 24
 
0.2%
E등급 2
 
< 0.1%

Length

2023-12-12T16:04:25.102269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:04:25.243356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b등급 7066
70.7%
c등급 1390
 
13.9%
a등급 1279
 
12.8%
불명 239
 
2.4%
d등급 24
 
0.2%
e등급 2
 
< 0.1%

최종정기점검일
Date

MISSING 

Distinct369
Distinct (%)3.8%
Missing214
Missing (%)2.1%
Memory size156.2 KiB
Minimum2018-11-30 00:00:00
Maximum2023-06-30 00:00:00
2023-12-12T16:04:25.385860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:25.546940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종정밀점검일
Date

MISSING 

Distinct787
Distinct (%)18.2%
Missing5673
Missing (%)56.7%
Memory size156.2 KiB
Minimum2018-11-26 00:00:00
Maximum2023-06-30 00:00:00
2023-12-12T16:04:25.718045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:25.896363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-12T16:04:26.022327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설물구분시설물종류종별차기정기점검도래일등급
시설물구분1.0000.9960.6750.3540.412
시설물종류0.9961.0000.8270.8280.583
종별0.6750.8271.0000.3210.333
차기정기점검도래일0.3540.8280.3211.0000.773
등급0.4120.5830.3330.7731.000
2023-12-12T16:04:26.122963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설물종류시설물구분종별차기정기점검도래일등급
시설물종류1.0000.9580.5790.3030.276
시설물구분0.9581.0000.5150.1280.226
종별0.5790.5151.0000.1570.146
차기정기점검도래일0.3030.1280.1571.0000.434
등급0.2760.2260.1460.4341.000
2023-12-12T16:04:26.222534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설물구분시설물종류종별차기정기점검도래일등급
시설물구분1.0000.9580.5150.1280.226
시설물종류0.9581.0000.5790.3030.276
종별0.5150.5791.0000.1570.146
차기정기점검도래일0.1280.3030.1571.0000.434
등급0.2260.2760.1460.4341.000

Missing values

2023-12-12T16:04:21.428911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:04:21.633821image/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.
2023-12-12T16:04:21.786291image/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

시설물명시설물구분시설물종류종별주소차기정기점검도래일차기정밀점검도래일등급최종정기점검일최종정밀점검일
53537대산하수종말처리장상하수도공공하수처리시설2종충청남도서산시2023-06-302024-05-26A등급2022-11-082021-05-26
337044-026 혜화역건축물철도역시설2종서울특별시종로구2023-06-302025-12-12B등급2022-12-122022-12-12
55332군산대학교 자연대3호관건축물다중이용건축물3종전라북도군산시2023-06-30<NA>B등급2022-12-21<NA>
67143석보초등학교 교사(본관동)건축물다중이용건축물3종경상북도영양군2023-06-30<NA>B등급2022-11-22<NA>
28375군위 고로 화수 (상)절토사면도로사면2종대구광역시군위군2023-12-312025-04-28C등급2023-04-282023-04-28
71776서재중학교 본관동|BU00045202건축물다중이용건축물3종대구광역시달성군2023-12-31<NA>B등급2023-06-20<NA>
11344진산교(하)교량도로교량3종경상남도거창군2023-06-30<NA>C등급2022-11-30<NA>
54389부강터널(상행)터널도로터널1종세종특별자치시2023-12-312024-04-28B등급2023-05-302022-04-28
336502-058 봉천역건축물철도역시설2종서울특별시관악구2023-06-302023-11-14B등급2022-12-312020-11-14
73238온마을아이맘센터건축물다중이용건축물3종대구광역시남구2023-12-31<NA>C등급2023-06-26<NA>
시설물명시설물구분시설물종류종별주소차기정기점검도래일차기정밀점검도래일등급최종정기점검일최종정밀점검일
29813새터교교량도로교량3종경기도가평군2023-12-31<NA>C등급2023-05-08<NA>
75199현북제하천제방2종충청남도부여군2023-12-312025-12-21A등급2023-06-022022-12-21
47173광탄교교량도로교량3종강원특별자치도정선군2023-12-31<NA>B등급2023-05-21<NA>
6095군자교(인천)교량도로교량1종경기도시흥시2023-12-312024-12-10B등급2023-06-232022-12-10
18937오이교차로 PEM옹벽옹벽도로옹벽2종경기도시흥시2023-12-312024-05-16A등급2023-06-042021-05-16
54097창원교도소 여사건축물기타3종경상남도창원시 마산회원구2023-12-31<NA>C등급2023-03-27<NA>
58111덕신고등학교 급식소/3동BU00209866건축물다중이용건축물3종인천광역시강화군2023-12-31<NA>B등급2023-05-31<NA>
24988신상교교량철도교량2종전라북도익산시2023-06-302025-12-05A등급2022-12-052022-12-05
31015반성철도육교(상)교량도로교량1종경상남도진주시2023-06-302023-12-26B등급2022-12-312021-12-26
37148갈전2교(평택)교량도로교량3종경기도안성시2023-12-31<NA>B등급2023-04-03<NA>

Duplicate rows

Most frequently occurring

시설물명시설물구분시설물종류종별주소차기정기점검도래일차기정밀점검도래일등급최종정기점검일최종정밀점검일# duplicates
0구수교교량도로교량3종경상북도안동시2023-12-31<NA>B등급2023-06-23<NA>2