Overview

Dataset statistics

Number of variables30
Number of observations1348
Missing cells7688
Missing cells (%)19.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory331.9 KiB
Average record size in memory252.1 B

Variable types

Text7
Categorical7
Numeric12
Boolean1
DateTime3

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15025444/standard.do

Alerts

부대시설종류 is highly imbalanced (60.7%)Imbalance
안전등급 is highly imbalanced (52.4%)Imbalance
사용제한구분 is highly imbalanced (96.0%)Imbalance
최종안전점검유형 is highly imbalanced (96.0%)Imbalance
도로노선번호 has 668 (49.6%) missing valuesMissing
육교연장 has 78 (5.8%) missing valuesMissing
육교높이 has 492 (36.5%) missing valuesMissing
허용통행하중 has 1138 (84.4%) missing valuesMissing
육교폭 has 138 (10.2%) missing valuesMissing
난간높이 has 786 (58.3%) missing valuesMissing
조명개수 has 998 (74.0%) missing valuesMissing
장애인편의시설수량 has 795 (59.0%) missing valuesMissing
부대시설수량 has 1015 (75.3%) missing valuesMissing
육교준공일자 has 480 (35.6%) missing valuesMissing
육교보수보강내역 has 1100 (81.6%) missing valuesMissing
육교폭 is highly skewed (γ1 = 34.74144478)Skewed
육교높이 has 33 (2.4%) zerosZeros
허용통행하중 has 69 (5.1%) zerosZeros
통행제한높이 has 35 (2.6%) zerosZeros
난간높이 has 47 (3.5%) zerosZeros
조명개수 has 92 (6.8%) zerosZeros
장애인편의시설수량 has 111 (8.2%) zerosZeros
부대시설수량 has 181 (13.4%) zerosZeros

Reproduction

Analysis started2024-05-04 08:09:45.878056
Analysis finished2024-05-04 08:09:48.226600
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

육교명
Text

Distinct1215
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
2024-05-04T08:09:48.582219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length6.8330861
Min length2

Characters and Unicode

Total characters9211
Distinct characters425
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1088 ?
Unique (%)80.7%

Sample

1st row여상육교
2nd row이수육교
3rd row조례육교2
4th row남산육교
5th row금당육교
ValueCountFrequency (%)
보도육교 157
 
8.5%
육교 115
 
6.2%
앞 104
 
5.6%
옆 6
 
0.3%
1육교 6
 
0.3%
2육교 6
 
0.3%
청북지구 6
 
0.3%
풍덕천 6
 
0.3%
보도육교(2 5
 
0.3%
보도육교(1 5
 
0.3%
Other values (1260) 1437
77.5%
2024-05-04T08:09:49.849212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 1424
 
15.5%
육 1226
 
13.3%
도 534
 
5.8%
505
 
5.5%
보 497
 
5.4%
앞 197
 
2.1%
초 128
 
1.4%
동 122
 
1.3%
리 88
 
1.0%
2 83
 
0.9%
Other values (415) 4407
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8247
89.5%
Space Separator 505
 
5.5%
Decimal Number 241
 
2.6%
Open Punctuation 66
 
0.7%
Close Punctuation 66
 
0.7%
Uppercase Letter 64
 
0.7%
Dash Punctuation 11
 
0.1%
Other Punctuation 5
 
0.1%
Lowercase Letter 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 1424
 
17.3%
육 1226
 
14.9%
도 534
 
6.5%
보 497
 
6.0%
앞 197
 
2.4%
초 128
 
1.6%
동 122
 
1.5%
리 88
 
1.1%
산 83
 
1.0%
신 82
 
1.0%
Other values (382) 3866
46.9%
Uppercase Letter
ValueCountFrequency (%)
T 13
20.3%
P 10
15.6%
C 9
14.1%
A 7
10.9%
E 5
 
7.8%
I 5
 
7.8%
Y 4
 
6.2%
G 3
 
4.7%
L 2
 
3.1%
O 2
 
3.1%
Other values (4) 4
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 83
34.4%
1 82
34.0%
3 27
 
11.2%
4 17
 
7.1%
5 9
 
3.7%
6 7
 
2.9%
0 5
 
2.1%
8 4
 
1.7%
9 4
 
1.7%
7 3
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
& 2
40.0%
Lowercase Letter
ValueCountFrequency (%)
k 3
75.0%
s 1
 
25.0%
Space Separator
ValueCountFrequency (%)
505
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8247
89.5%
Common 896
 
9.7%
Latin 68
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 1424
 
17.3%
육 1226
 
14.9%
도 534
 
6.5%
보 497
 
6.0%
앞 197
 
2.4%
초 128
 
1.6%
동 122
 
1.5%
리 88
 
1.1%
산 83
 
1.0%
신 82
 
1.0%
Other values (382) 3866
46.9%
Common
ValueCountFrequency (%)
505
56.4%
2 83
 
9.3%
1 82
 
9.2%
( 66
 
7.4%
) 66
 
7.4%
3 27
 
3.0%
4 17
 
1.9%
- 11
 
1.2%
5 9
 
1.0%
6 7
 
0.8%
Other values (7) 23
 
2.6%
Latin
ValueCountFrequency (%)
T 13
19.1%
P 10
14.7%
C 9
13.2%
A 7
10.3%
E 5
 
7.4%
I 5
 
7.4%
Y 4
 
5.9%
G 3
 
4.4%
k 3
 
4.4%
L 2
 
2.9%
Other values (6) 7
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8247
89.5%
ASCII 964
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 1424
 
17.3%
육 1226
 
14.9%
도 534
 
6.5%
보 497
 
6.0%
앞 197
 
2.4%
초 128
 
1.6%
동 122
 
1.5%
리 88
 
1.1%
산 83
 
1.0%
신 82
 
1.0%
Other values (382) 3866
46.9%
ASCII
ValueCountFrequency (%)
505
52.4%
2 83
 
8.6%
1 82
 
8.5%
( 66
 
6.8%
) 66
 
6.8%
3 27
 
2.8%
4 17
 
1.8%
T 13
 
1.3%
- 11
 
1.1%
P 10
 
1.0%
Other values (23) 84
 
8.7%

도로종류
Categorical

Distinct9
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
시도
683 
기타
241 
일반국도
174 
구도
124 
지방도
 
61
Other values (4)
 
65

Length

Max length7
Median length2
Mean length2.3864985
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row일반국도
2nd row시도
3rd row일반국도
4th row시도
5th row일반국도

Common Values

ValueCountFrequency (%)
시도 683
50.7%
기타 241
 
17.9%
일반국도 174
 
12.9%
구도 124
 
9.2%
지방도 61
 
4.5%
특별시도 50
 
3.7%
군도 12
 
0.9%
국가지원지방도 2
 
0.1%
고속국도 1
 
0.1%

Length

2024-05-04T08:09:50.344498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:09:50.858295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시도 683
50.7%
기타 241
 
17.9%
일반국도 174
 
12.9%
구도 124
 
9.2%
지방도 61
 
4.5%
특별시도 50
 
3.7%
군도 12
 
0.9%
국가지원지방도 2
 
0.1%
고속국도 1
 
0.1%

도로노선번호
Text

MISSING 

Distinct284
Distinct (%)41.8%
Missing668
Missing (%)49.6%
Memory size10.7 KiB
2024-05-04T08:09:51.531763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length3.9970588
Min length1

Characters and Unicode

Total characters2718
Distinct characters65
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)21.8%

Sample

1st row2번
2nd row2번
3rd row2번
4th row2번
5th row2번
ValueCountFrequency (%)
1번 35
 
5.0%
해당없음 20
 
2.8%
없음 19
 
2.7%
23번 18
 
2.5%
국도1호선 18
 
2.5%
대로 11
 
1.6%
71번 10
 
1.4%
25 8
 
1.1%
2 8
 
1.1%
3219073번 8
 
1.1%
Other values (283) 551
78.0%
2024-05-04T08:09:52.686864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 336
 
12.4%
2 239
 
8.8%
번 223
 
8.2%
3 223
 
8.2%
호 184
 
6.8%
선 164
 
6.0%
- 160
 
5.9%
로 119
 
4.4%
7 114
 
4.2%
5 112
 
4.1%
Other values (55) 844
31.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1374
50.6%
Other Letter 1142
42.0%
Dash Punctuation 160
 
5.9%
Space Separator 26
 
1.0%
Close Punctuation 8
 
0.3%
Open Punctuation 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 223
19.5%
호 184
16.1%
선 164
14.4%
로 119
10.4%
대 80
 
7.0%
도 55
 
4.8%
음 39
 
3.4%
없 39
 
3.4%
광 33
 
2.9%
국 33
 
2.9%
Other values (41) 173
15.1%
Decimal Number
ValueCountFrequency (%)
1 336
24.5%
2 239
17.4%
3 223
16.2%
7 114
 
8.3%
5 112
 
8.2%
4 92
 
6.7%
0 87
 
6.3%
9 73
 
5.3%
8 53
 
3.9%
6 45
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 160
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1576
58.0%
Hangul 1142
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 223
19.5%
호 184
16.1%
선 164
14.4%
로 119
10.4%
대 80
 
7.0%
도 55
 
4.8%
음 39
 
3.4%
없 39
 
3.4%
광 33
 
2.9%
국 33
 
2.9%
Other values (41) 173
15.1%
Common
ValueCountFrequency (%)
1 336
21.3%
2 239
15.2%
3 223
14.1%
- 160
10.2%
7 114
 
7.2%
5 112
 
7.1%
4 92
 
5.8%
0 87
 
5.5%
9 73
 
4.6%
8 53
 
3.4%
Other values (4) 87
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1576
58.0%
Hangul 1142
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 336
21.3%
2 239
15.2%
3 223
14.1%
- 160
10.2%
7 114
 
7.2%
5 112
 
7.1%
4 92
 
5.8%
0 87
 
5.5%
9 73
 
4.6%
8 53
 
3.4%
Other values (4) 87
 
5.5%
Hangul
ValueCountFrequency (%)
번 223
19.5%
호 184
16.1%
선 164
14.4%
로 119
10.4%
대 80
 
7.0%
도 55
 
4.8%
음 39
 
3.4%
없 39
 
3.4%
광 33
 
2.9%
국 33
 
2.9%
Other values (41) 173
15.1%

도로노선명
Text

Distinct708
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
2024-05-04T08:09:53.342271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length3.9176558
Min length2

Characters and Unicode

Total characters5281
Distinct characters319
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique407 ?
Unique (%)30.2%

Sample

1st row녹색로
2nd row이수로
3rd row순광로
4th row남산로
5th row백강로
ValueCountFrequency (%)
호남선 29
 
2.1%
경충대로 16
 
1.2%
한밭대로 14
 
1.0%
중앙로 11
 
0.8%
천안대로 11
 
0.8%
경기대로 11
 
0.8%
남부순환로 11
 
0.8%
경수대로 9
 
0.7%
무왕로 8
 
0.6%
덕영대로 8
 
0.6%
Other values (705) 1238
90.6%
2024-05-04T08:09:54.535396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 1217
 
23.0%
대 336
 
6.4%
길 98
 
1.9%
남 90
 
1.7%
천 89
 
1.7%
동 79
 
1.5%
선 76
 
1.4%
안 75
 
1.4%
도 74
 
1.4%
경 74
 
1.4%
Other values (309) 3073
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5063
95.9%
Decimal Number 170
 
3.2%
Space Separator 18
 
0.3%
Math Symbol 14
 
0.3%
Dash Punctuation 6
 
0.1%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1217
24.0%
대 336
 
6.6%
길 98
 
1.9%
남 90
 
1.8%
천 89
 
1.8%
동 79
 
1.6%
선 76
 
1.5%
안 75
 
1.5%
도 74
 
1.5%
경 74
 
1.5%
Other values (291) 2855
56.4%
Decimal Number
ValueCountFrequency (%)
1 45
26.5%
3 33
19.4%
4 25
14.7%
2 22
12.9%
5 13
 
7.6%
7 11
 
6.5%
6 10
 
5.9%
0 6
 
3.5%
9 3
 
1.8%
8 2
 
1.2%
Math Symbol
ValueCountFrequency (%)
~ 11
78.6%
+ 3
 
21.4%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5063
95.9%
Common 218
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1217
24.0%
대 336
 
6.6%
길 98
 
1.9%
남 90
 
1.8%
천 89
 
1.8%
동 79
 
1.6%
선 76
 
1.5%
안 75
 
1.5%
도 74
 
1.5%
경 74
 
1.5%
Other values (291) 2855
56.4%
Common
ValueCountFrequency (%)
1 45
20.6%
3 33
15.1%
4 25
11.5%
2 22
10.1%
18
 
8.3%
5 13
 
6.0%
7 11
 
5.0%
~ 11
 
5.0%
6 10
 
4.6%
- 6
 
2.8%
Other values (8) 24
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5063
95.9%
ASCII 218
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 1217
24.0%
대 336
 
6.6%
길 98
 
1.9%
남 90
 
1.8%
천 89
 
1.8%
동 79
 
1.6%
선 76
 
1.5%
안 75
 
1.5%
도 74
 
1.5%
경 74
 
1.5%
Other values (291) 2855
56.4%
ASCII
ValueCountFrequency (%)
1 45
20.6%
3 33
15.1%
4 25
11.5%
2 22
10.1%
18
 
8.3%
5 13
 
6.0%
7 11
 
5.0%
~ 11
 
5.0%
6 10
 
4.6%
- 6
 
2.8%
Other values (8) 24
11.0%

소재지도로명주소
Text

Distinct1198
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
2024-05-04T08:09:55.302874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length18.364243
Min length11

Characters and Unicode

Total characters24755
Distinct characters341
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1086 ?
Unique (%)80.6%

Sample

1st row전라남도 순천시 녹색로 1636 (덕월동)
2nd row전라남도 순천시 이수로 171-1 (생목동)
3rd row전라남도 순천시 순광로 17 (조례동)
4th row전라남도 순천시 남산로 59 (풍덕동)
5th row전라남도 순천시 백강로 206 (연향동)
ValueCountFrequency (%)
경기도 448
 
7.9%
서울특별시 137
 
2.4%
대전광역시 108
 
1.9%
서구 91
 
1.6%
부산광역시 79
 
1.4%
충청남도 73
 
1.3%
전라북도 73
 
1.3%
인천광역시 69
 
1.2%
광주광역시 62
 
1.1%
고양시 62
 
1.1%
Other values (1761) 4489
78.9%
2024-05-04T08:09:56.882528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4343
 
17.5%
시 1322
 
5.3%
로 1250
 
5.0%
구 919
 
3.7%
도 858
 
3.5%
1 756
 
3.1%
경 612
 
2.5%
대 512
 
2.1%
광 507
 
2.0%
2 506
 
2.0%
Other values (331) 13170
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16498
66.6%
Space Separator 4343
 
17.5%
Decimal Number 3624
 
14.6%
Dash Punctuation 155
 
0.6%
Close Punctuation 59
 
0.2%
Open Punctuation 59
 
0.2%
Other Punctuation 17
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1322
 
8.0%
로 1250
 
7.6%
구 919
 
5.6%
도 858
 
5.2%
경 612
 
3.7%
대 512
 
3.1%
광 507
 
3.1%
기 487
 
3.0%
산 418
 
2.5%
서 389
 
2.4%
Other values (315) 9224
55.9%
Decimal Number
ValueCountFrequency (%)
1 756
20.9%
2 506
14.0%
3 415
11.5%
4 344
9.5%
6 302
 
8.3%
0 297
 
8.2%
5 295
 
8.1%
7 290
 
8.0%
8 227
 
6.3%
9 192
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 16
94.1%
· 1
 
5.9%
Space Separator
ValueCountFrequency (%)
4343
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16498
66.6%
Common 8257
33.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1322
 
8.0%
로 1250
 
7.6%
구 919
 
5.6%
도 858
 
5.2%
경 612
 
3.7%
대 512
 
3.1%
광 507
 
3.1%
기 487
 
3.0%
산 418
 
2.5%
서 389
 
2.4%
Other values (315) 9224
55.9%
Common
ValueCountFrequency (%)
4343
52.6%
1 756
 
9.2%
2 506
 
6.1%
3 415
 
5.0%
4 344
 
4.2%
6 302
 
3.7%
0 297
 
3.6%
5 295
 
3.6%
7 290
 
3.5%
8 227
 
2.7%
Other values (6) 482
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16498
66.6%
ASCII 8256
33.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4343
52.6%
1 756
 
9.2%
2 506
 
6.1%
3 415
 
5.0%
4 344
 
4.2%
6 302
 
3.7%
0 297
 
3.6%
5 295
 
3.6%
7 290
 
3.5%
8 227
 
2.7%
Other values (5) 481
 
5.8%
Hangul
ValueCountFrequency (%)
시 1322
 
8.0%
로 1250
 
7.6%
구 919
 
5.6%
도 858
 
5.2%
경 612
 
3.7%
대 512
 
3.1%
광 507
 
3.1%
기 487
 
3.0%
산 418
 
2.5%
서 389
 
2.4%
Other values (315) 9224
55.9%
None
ValueCountFrequency (%)
· 1
100.0%

위도
Real number (ℝ)

Distinct1262
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.636477
Minimum33.289972
Maximum37.863336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:09:57.474000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.289972
5-th percentile35.069226
Q135.851484
median37.065572
Q337.467069
95-th percentile37.668258
Maximum37.863336
Range4.5733642
Interquartile range (IQR)1.6155853

Descriptive statistics

Standard deviation0.96028148
Coefficient of variation (CV)0.026211076
Kurtosis-1.1116964
Mean36.636477
Median Absolute Deviation (MAD)0.55673468
Skewness-0.58866472
Sum49385.971
Variance0.92214051
MonotonicityNot monotonic
2024-05-04T08:09:58.017517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.78071284 3
 
0.2%
37.65948674 3
 
0.2%
35.39784106 2
 
0.1%
36.78314975 2
 
0.1%
37.504812 2
 
0.1%
37.515011 2
 
0.1%
37.5413148 2
 
0.1%
37.527552 2
 
0.1%
37.863336 2
 
0.1%
35.32871572 2
 
0.1%
Other values (1252) 1326
98.4%
ValueCountFrequency (%)
33.28997179 1
0.1%
34.7271942 1
0.1%
34.736583 1
0.1%
34.73988317 1
0.1%
34.74108802 1
0.1%
34.74117121 1
0.1%
34.7428744 1
0.1%
34.74662228 1
0.1%
34.74853058 1
0.1%
34.75218956 1
0.1%
ValueCountFrequency (%)
37.863336 2
0.1%
37.843418 1
0.1%
37.840538 2
0.1%
37.797323 2
0.1%
37.76903806 1
0.1%
37.767951 2
0.1%
37.76635177 2
0.1%
37.76463753 2
0.1%
37.761237 1
0.1%
37.760358 1
0.1%

경도
Real number (ℝ)

Distinct1261
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.3697
Minimum126.28726
Maximum129.45296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:09:58.479230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.28726
5-th percentile126.64971
Q1126.8697
median127.07384
Q3127.47579
95-th percentile129.09231
Maximum129.45296
Range3.1656991
Interquartile range (IQR)0.60608504

Descriptive statistics

Standard deviation0.76416865
Coefficient of variation (CV)0.0059996112
Kurtosis0.4060161
Mean127.3697
Median Absolute Deviation (MAD)0.27369105
Skewness1.3014253
Sum171694.35
Variance0.58395373
MonotonicityNot monotonic
2024-05-04T08:09:58.968184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0911641 3
 
0.2%
126.7726989 3
 
0.2%
127.155221 2
 
0.1%
127.719436 2
 
0.1%
129.1041113 2
 
0.1%
129.102151 2
 
0.1%
129.105132 2
 
0.1%
127.0924082 2
 
0.1%
127.714284 2
 
0.1%
126.567824 2
 
0.1%
Other values (1251) 1326
98.4%
ValueCountFrequency (%)
126.2872649 1
0.1%
126.388415 1
0.1%
126.388639 1
0.1%
126.390636 1
0.1%
126.411395 1
0.1%
126.4178012 1
0.1%
126.417928 1
0.1%
126.418279 1
0.1%
126.4210149 1
0.1%
126.4232524 1
0.1%
ValueCountFrequency (%)
129.452964 1
0.1%
129.429991 1
0.1%
129.429451 1
0.1%
129.424415 1
0.1%
129.388553 1
0.1%
129.381231 1
0.1%
129.378216 2
0.1%
129.354123 1
0.1%
129.348251 1
0.1%
129.327709 1
0.1%

육교연장
Real number (ℝ)

MISSING 

Distinct412
Distinct (%)32.4%
Missing78
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean50.614157
Minimum5.3
Maximum693.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:09:59.385778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.3
5-th percentile20.445
Q130
median40
Q356
95-th percentile121.275
Maximum693.6
Range688.3
Interquartile range (IQR)26

Descriptive statistics

Standard deviation40.08704
Coefficient of variation (CV)0.79201238
Kurtosis59.189007
Mean50.614157
Median Absolute Deviation (MAD)11.25
Skewness5.3393354
Sum64279.98
Variance1606.9707
MonotonicityNot monotonic
2024-05-04T08:09:59.829139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 55
 
4.1%
40.0 50
 
3.7%
45.0 32
 
2.4%
28.0 31
 
2.3%
35.0 27
 
2.0%
38.0 26
 
1.9%
32.0 24
 
1.8%
33.0 22
 
1.6%
46.0 20
 
1.5%
34.0 20
 
1.5%
Other values (402) 963
71.4%
(Missing) 78
 
5.8%
ValueCountFrequency (%)
5.3 1
0.1%
6.5 1
0.1%
10.0 2
0.1%
11.0 1
0.1%
12.0 1
0.1%
12.2 1
0.1%
13.3 1
0.1%
13.58 2
0.1%
13.6 1
0.1%
14.0 1
0.1%
ValueCountFrequency (%)
693.6 1
0.1%
332.0 1
0.1%
315.0 1
0.1%
272.8 1
0.1%
266.0 1
0.1%
257.0 1
0.1%
250.0 1
0.1%
240.0 1
0.1%
236.0 1
0.1%
234.0 1
0.1%

육교높이
Real number (ℝ)

MISSING  ZEROS 

Distinct128
Distinct (%)15.0%
Missing492
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean8.5644521
Minimum0
Maximum150
Zeros33
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:00.520567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.375
Q14.5
median5
Q35.63325
95-th percentile37.55
Maximum150
Range150
Interquartile range (IQR)1.13325

Descriptive statistics

Standard deviation15.460258
Coefficient of variation (CV)1.805166
Kurtosis32.232751
Mean8.5644521
Median Absolute Deviation (MAD)0.5
Skewness5.305914
Sum7331.171
Variance239.01957
MonotonicityNot monotonic
2024-05-04T08:10:01.065612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 197
14.6%
4.5 145
 
10.8%
5.5 77
 
5.7%
6.0 55
 
4.1%
4.8 46
 
3.4%
0.0 33
 
2.4%
5.2 20
 
1.5%
4.0 18
 
1.3%
4.7 17
 
1.3%
5.1 16
 
1.2%
Other values (118) 232
17.2%
(Missing) 492
36.5%
ValueCountFrequency (%)
0.0 33
2.4%
0.6 1
 
0.1%
0.8 1
 
0.1%
1.0 3
 
0.2%
1.1 1
 
0.1%
1.2 3
 
0.2%
1.3 1
 
0.1%
1.4 1
 
0.1%
1.6 2
 
0.1%
1.8 1
 
0.1%
ValueCountFrequency (%)
150.0 1
0.1%
130.0 1
0.1%
125.0 1
0.1%
121.0 1
0.1%
119.3 1
0.1%
116.0 1
0.1%
111.0 1
0.1%
96.6 1
0.1%
92.0 1
0.1%
88.8 1
0.1%

허용통행하중
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)6.7%
Missing1138
Missing (%)84.4%
Infinite0
Infinite (%)0.0%
Mean9.9038429
Minimum0
Maximum225
Zeros69
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:01.488306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.5
Q37.5
95-th percentile43.2
Maximum225
Range225
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation20.74026
Coefficient of variation (CV)2.0941629
Kurtosis54.894819
Mean9.9038429
Median Absolute Deviation (MAD)3.5
Skewness5.9162958
Sum2079.807
Variance430.15838
MonotonicityNot monotonic
2024-05-04T08:10:01.894274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 69
 
5.1%
43.2 29
 
2.2%
5.0 26
 
1.9%
0.5 26
 
1.9%
3.5 24
 
1.8%
13.5 12
 
0.9%
7.5 11
 
0.8%
13.0 4
 
0.3%
15.0 3
 
0.2%
2.4 2
 
0.1%
Other values (4) 4
 
0.3%
(Missing) 1138
84.4%
ValueCountFrequency (%)
0.0 69
5.1%
0.34 1
 
0.1%
0.5 26
 
1.9%
2.4 2
 
0.1%
3.367 1
 
0.1%
3.5 24
 
1.8%
5.0 26
 
1.9%
7.5 11
 
0.8%
13.0 4
 
0.3%
13.5 12
 
0.9%
ValueCountFrequency (%)
225.0 1
 
0.1%
43.2 29
2.2%
25.0 1
 
0.1%
15.0 3
 
0.2%
13.5 12
0.9%
13.0 4
 
0.3%
7.5 11
 
0.8%
5.0 26
1.9%
3.5 24
1.8%
3.367 1
 
0.1%

통행제한높이
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7327077
Minimum0
Maximum45
Zeros35
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:02.441025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q14.5
median4.5
Q35
95-th percentile6.53
Maximum45
Range45
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation1.6430893
Coefficient of variation (CV)0.34717744
Kurtosis272.98872
Mean4.7327077
Median Absolute Deviation (MAD)0.3
Skewness11.29051
Sum6379.69
Variance2.6997426
MonotonicityNot monotonic
2024-05-04T08:10:02.886759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.5 529
39.2%
5.0 261
19.4%
4.8 125
 
9.3%
4.0 87
 
6.5%
0.0 35
 
2.6%
4.3 34
 
2.5%
4.7 34
 
2.5%
7.0 29
 
2.2%
4.2 22
 
1.6%
5.5 22
 
1.6%
Other values (42) 170
 
12.6%
ValueCountFrequency (%)
0.0 35
2.6%
1.4 1
 
0.1%
2.0 1
 
0.1%
2.5 5
 
0.4%
3.0 9
 
0.7%
3.1 1
 
0.1%
3.3 1
 
0.1%
3.5 1
 
0.1%
3.8 2
 
0.1%
3.9 1
 
0.1%
ValueCountFrequency (%)
45.0 1
 
0.1%
18.0 1
 
0.1%
13.3 1
 
0.1%
12.5 1
 
0.1%
10.0 8
0.6%
9.2 1
 
0.1%
9.0 2
 
0.1%
8.7 1
 
0.1%
8.5 4
0.3%
8.44 2
 
0.1%

육교폭
Real number (ℝ)

MISSING  SKEWED 

Distinct81
Distinct (%)6.7%
Missing138
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean7.0945372
Minimum1
Maximum3345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:03.436327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q13
median4
Q34.5
95-th percentile8
Maximum3345
Range3344
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation96.077644
Coefficient of variation (CV)13.542482
Kurtosis1207.9692
Mean7.0945372
Median Absolute Deviation (MAD)0.7
Skewness34.741445
Sum8584.39
Variance9230.9137
MonotonicityNot monotonic
2024-05-04T08:10:04.169477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0 390
28.9%
3.0 238
17.7%
3.5 70
 
5.2%
5.0 64
 
4.7%
6.0 47
 
3.5%
4.5 46
 
3.4%
2.0 34
 
2.5%
2.5 25
 
1.9%
8.0 22
 
1.6%
5.4 19
 
1.4%
Other values (71) 255
18.9%
(Missing) 138
 
10.2%
ValueCountFrequency (%)
1.0 3
 
0.2%
1.5 6
 
0.4%
1.8 3
 
0.2%
2.0 34
2.5%
2.1 2
 
0.1%
2.2 1
 
0.1%
2.3 6
 
0.4%
2.35 1
 
0.1%
2.4 7
 
0.5%
2.5 25
1.9%
ValueCountFrequency (%)
3345.0 1
0.1%
35.0 1
0.1%
33.0 1
0.1%
30.3 1
0.1%
30.0 2
0.1%
29.2 1
0.1%
26.0 1
0.1%
21.0 1
0.1%
20.0 2
0.1%
19.3 1
0.1%

난간높이
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)4.3%
Missing786
Missing (%)58.3%
Infinite0
Infinite (%)0.0%
Mean1.2044662
Minimum0
Maximum12
Zeros47
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:04.560445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1.2
Q31.5
95-th percentile1.8
Maximum12
Range12
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.67116613
Coefficient of variation (CV)0.55723119
Kurtosis121.67737
Mean1.2044662
Median Absolute Deviation (MAD)0.2
Skewness7.6721065
Sum676.91
Variance0.45046397
MonotonicityNot monotonic
2024-05-04T08:10:04.984225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1.2 147
 
10.9%
1.5 134
 
9.9%
1.0 107
 
7.9%
1.1 66
 
4.9%
0.0 47
 
3.5%
2.0 15
 
1.1%
1.3 13
 
1.0%
1.8 10
 
0.7%
1.4 5
 
0.4%
1.15 2
 
0.1%
Other values (14) 16
 
1.2%
(Missing) 786
58.3%
ValueCountFrequency (%)
0.0 47
 
3.5%
0.88 1
 
0.1%
0.9 1
 
0.1%
1.0 107
7.9%
1.05 1
 
0.1%
1.1 66
4.9%
1.15 2
 
0.1%
1.17 1
 
0.1%
1.2 147
10.9%
1.3 13
 
1.0%
ValueCountFrequency (%)
12.0 1
 
0.1%
5.0 1
 
0.1%
4.5 1
 
0.1%
3.0 2
 
0.1%
2.5 2
 
0.1%
2.3 1
 
0.1%
2.0 15
1.1%
1.95 1
 
0.1%
1.87 1
 
0.1%
1.8 10
0.7%

조명개수
Real number (ℝ)

MISSING  ZEROS 

Distinct50
Distinct (%)14.3%
Missing998
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean15.997143
Minimum0
Maximum398
Zeros92
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:05.397753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q310
95-th percentile73.15
Maximum398
Range398
Interquartile range (IQR)10

Descriptive statistics

Standard deviation42.619964
Coefficient of variation (CV)2.6642235
Kurtosis31.231808
Mean15.997143
Median Absolute Deviation (MAD)5
Skewness5.1482814
Sum5599
Variance1816.4613
MonotonicityNot monotonic
2024-05-04T08:10:05.963221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 92
 
6.8%
2 39
 
2.9%
4 28
 
2.1%
8 28
 
2.1%
6 23
 
1.7%
10 21
 
1.6%
7 13
 
1.0%
11 11
 
0.8%
5 10
 
0.7%
18 7
 
0.5%
Other values (40) 78
 
5.8%
(Missing) 998
74.0%
ValueCountFrequency (%)
0 92
6.8%
1 1
 
0.1%
2 39
2.9%
3 6
 
0.4%
4 28
 
2.1%
5 10
 
0.7%
6 23
 
1.7%
7 13
 
1.0%
8 28
 
2.1%
9 4
 
0.3%
ValueCountFrequency (%)
398 1
0.1%
291 1
0.1%
276 1
0.1%
208 1
0.1%
194 1
0.1%
189 1
0.1%
188 1
0.1%
186 2
0.1%
154 1
0.1%
141 1
0.1%

장애인편의시설설치여부
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
True
792 
False
556 
ValueCountFrequency (%)
True 792
58.8%
False 556
41.2%
2024-05-04T08:10:06.407335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

장애인편의시설종류
Categorical

Distinct37
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
없음
516 
경사로
300 
엘리베이터
222 
승강기
87 
N
 
36
Other values (32)
187 

Length

Max length14
Median length13
Mean length3.5400593
Min length1

Unique

Unique11 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
없음 516
38.3%
경사로 300
22.3%
엘리베이터 222
16.5%
승강기 87
 
6.5%
N 36
 
2.7%
점자블록 24
 
1.8%
점자블럭+경사로 23
 
1.7%
엘리베이터+경사로 20
 
1.5%
경사로+엘리베이터 19
 
1.4%
점자블록+경사로 12
 
0.9%
Other values (27) 89
 
6.6%

Length

2024-05-04T08:10:06.826577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
없음 516
37.8%
경사로 307
22.5%
엘리베이터 229
16.8%
승강기 87
 
6.4%
n 36
 
2.6%
점자블록 24
 
1.8%
점자블럭+경사로 23
 
1.7%
엘리베이터+경사로 20
 
1.5%
경사로+엘리베이터 19
 
1.4%
점자블록+경사로 12
 
0.9%
Other values (29) 91
 
6.7%

장애인편의시설수량
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.3%
Missing795
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean1.477396
Minimum0
Maximum24
Zeros111
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:07.193433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile3
Maximum24
Range24
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3686232
Coefficient of variation (CV)0.92637531
Kurtosis132.83722
Mean1.477396
Median Absolute Deviation (MAD)1
Skewness8.2773385
Sum817
Variance1.8731294
MonotonicityNot monotonic
2024-05-04T08:10:07.681144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 262
 
19.4%
1 143
 
10.6%
0 111
 
8.2%
3 24
 
1.8%
4 10
 
0.7%
7 2
 
0.1%
24 1
 
0.1%
(Missing) 795
59.0%
ValueCountFrequency (%)
0 111
8.2%
1 143
10.6%
2 262
19.4%
3 24
 
1.8%
4 10
 
0.7%
7 2
 
0.1%
24 1
 
0.1%
ValueCountFrequency (%)
24 1
 
0.1%
7 2
 
0.1%
4 10
 
0.7%
3 24
 
1.8%
2 262
19.4%
1 143
10.6%
0 111
8.2%

부대시설종류
Categorical

IMBALANCE 

Distinct17
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
<NA>
892 
없음
282 
엘리베이터
 
82
캐노피
 
23
엘리베이터+캐노피
 
12
Other values (12)
 
57

Length

Max length12
Median length4
Mean length3.6951039
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 892
66.2%
없음 282
 
20.9%
엘리베이터 82
 
6.1%
캐노피 23
 
1.7%
엘리베이터+캐노피 12
 
0.9%
0 9
 
0.7%
N 8
 
0.6%
교량 8
 
0.6%
엘리베이터+케노피 7
 
0.5%
난간+가로등 6
 
0.4%
Other values (7) 19
 
1.4%

Length

2024-05-04T08:10:08.057234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 892
66.0%
없음 282
 
20.9%
엘리베이터 84
 
6.2%
캐노피 25
 
1.8%
엘리베이터+캐노피 12
 
0.9%
0 9
 
0.7%
n 8
 
0.6%
교량 8
 
0.6%
엘리베이터+케노피 7
 
0.5%
난간+가로등 6
 
0.4%
Other values (7) 19
 
1.4%

부대시설수량
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)3.6%
Missing1015
Missing (%)75.3%
Infinite0
Infinite (%)0.0%
Mean1.003003
Minimum0
Maximum14
Zeros181
Zeros (%)13.4%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:08.300380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum14
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7329175
Coefficient of variation (CV)1.7277291
Kurtosis19.385197
Mean1.003003
Median Absolute Deviation (MAD)0
Skewness3.6882793
Sum334
Variance3.003003
MonotonicityNot monotonic
2024-05-04T08:10:08.665040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 181
 
13.4%
2 64
 
4.7%
1 60
 
4.5%
3 14
 
1.0%
5 4
 
0.3%
7 3
 
0.2%
9 2
 
0.1%
14 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
Other values (2) 2
 
0.1%
(Missing) 1015
75.3%
ValueCountFrequency (%)
0 181
13.4%
1 60
 
4.5%
2 64
 
4.7%
3 14
 
1.0%
4 1
 
0.1%
5 4
 
0.3%
6 1
 
0.1%
7 3
 
0.2%
8 1
 
0.1%
9 2
 
0.1%
ValueCountFrequency (%)
14 1
 
0.1%
13 1
 
0.1%
9 2
 
0.1%
8 1
 
0.1%
7 3
 
0.2%
6 1
 
0.1%
5 4
 
0.3%
4 1
 
0.1%
3 14
 
1.0%
2 64
4.7%

육교준공일자
Date

MISSING 

Distinct394
Distinct (%)45.4%
Missing480
Missing (%)35.6%
Memory size10.7 KiB
Minimum1968-01-01 00:00:00
Maximum2023-08-25 00:00:00
2024-05-04T08:10:09.145534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:10:09.618993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

내진설계적용여부
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
N
777 
358 
Y
213 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 777
57.6%
358
26.6%
Y 213
 
15.8%

Length

2024-05-04T08:10:10.416199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:10:10.824923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 777
78.5%
y 213
 
21.5%

안전등급
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
양호
891 
보통
416 
미흡
 
26
우수
 
14
불량
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
양호 891
66.1%
보통 416
30.9%
미흡 26
 
1.9%
우수 14
 
1.0%
불량 1
 
0.1%

Length

2024-05-04T08:10:11.225502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:10:11.689302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양호 891
66.1%
보통 416
30.9%
미흡 26
 
1.9%
우수 14
 
1.0%
불량 1
 
0.1%

사용제한구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
제한없음
1339 
사용제한
 
6
철거
 
3

Length

Max length4
Median length4
Mean length3.995549
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제한없음 1339
99.3%
사용제한 6
 
0.4%
철거 3
 
0.2%

Length

2024-05-04T08:10:12.086763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:10:12.590227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제한없음 1339
99.3%
사용제한 6
 
0.4%
철거 3
 
0.2%

육교보수보강내역
Text

MISSING 

Distinct104
Distinct (%)41.9%
Missing1100
Missing (%)81.6%
Memory size10.7 KiB
2024-05-04T08:10:13.272707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length50
Mean length8.3669355
Min length1

Characters and Unicode

Total characters2075
Distinct characters163
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

Unique74 ?
Unique (%)29.8%

Sample

1st row2023-02-17
2nd row화강석판석+ 하부도장 + 배수관교체
3rd row화강석판석+ 하부도장 + 배수관 교체
4th row세척
5th row기둥+거더+계단 보수
ValueCountFrequency (%)
n 37
 
7.6%
없음 25
 
5.1%
보수 24
 
4.9%
도색 21
 
4.3%
및 19
 
3.9%
교체 16
 
3.3%
일상유지보수 14
 
2.9%
계단 14
 
2.9%
논슬립 11
 
2.2%
해당없음 11
 
2.2%
Other values (159) 298
60.8%
2024-05-04T08:10:14.640300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245
 
11.8%
2 106
 
5.1%
도 95
 
4.6%
보 93
 
4.5%
수 90
 
4.3%
0 80
 
3.9%
장 52
 
2.5%
1 45
 
2.2%
교 45
 
2.2%
+ 41
 
2.0%
Other values (153) 1183
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1350
65.1%
Decimal Number 282
 
13.6%
Space Separator 245
 
11.8%
Other Punctuation 50
 
2.4%
Math Symbol 43
 
2.1%
Uppercase Letter 40
 
1.9%
Close Punctuation 23
 
1.1%
Open Punctuation 23
 
1.1%
Dash Punctuation 10
 
0.5%
Other Symbol 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 95
 
7.0%
보 93
 
6.9%
수 90
 
6.7%
장 52
 
3.9%
교 45
 
3.3%
음 36
 
2.7%
없 36
 
2.7%
비 36
 
2.7%
색 34
 
2.5%
재 34
 
2.5%
Other values (130) 799
59.2%
Decimal Number
ValueCountFrequency (%)
2 106
37.6%
0 80
28.4%
1 45
16.0%
7 10
 
3.5%
9 10
 
3.5%
3 10
 
3.5%
5 7
 
2.5%
8 6
 
2.1%
4 5
 
1.8%
6 3
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 37
92.5%
A 2
 
5.0%
X 1
 
2.5%
Math Symbol
ValueCountFrequency (%)
+ 41
95.3%
= 2
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 34
68.0%
, 16
32.0%
Space Separator
ValueCountFrequency (%)
245
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1350
65.1%
Common 683
32.9%
Latin 42
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 95
 
7.0%
보 93
 
6.9%
수 90
 
6.7%
장 52
 
3.9%
교 45
 
3.3%
음 36
 
2.7%
없 36
 
2.7%
비 36
 
2.7%
색 34
 
2.5%
재 34
 
2.5%
Other values (130) 799
59.2%
Common
ValueCountFrequency (%)
245
35.9%
2 106
15.5%
0 80
 
11.7%
1 45
 
6.6%
+ 41
 
6.0%
. 34
 
5.0%
) 23
 
3.4%
( 23
 
3.4%
, 16
 
2.3%
7 10
 
1.5%
Other values (9) 60
 
8.8%
Latin
ValueCountFrequency (%)
N 37
88.1%
m 2
 
4.8%
A 2
 
4.8%
X 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1350
65.1%
ASCII 718
34.6%
CJK Compat 7
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245
34.1%
2 106
14.8%
0 80
 
11.1%
1 45
 
6.3%
+ 41
 
5.7%
N 37
 
5.2%
. 34
 
4.7%
) 23
 
3.2%
( 23
 
3.2%
, 16
 
2.2%
Other values (12) 68
 
9.5%
Hangul
ValueCountFrequency (%)
도 95
 
7.0%
보 93
 
6.9%
수 90
 
6.7%
장 52
 
3.9%
교 45
 
3.3%
음 36
 
2.7%
없 36
 
2.7%
비 36
 
2.7%
색 34
 
2.5%
재 34
 
2.5%
Other values (130) 799
59.2%
CJK Compat
ValueCountFrequency (%)
㎡ 7
100.0%

최종안전점검유형
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
정기점검
1339 
정밀점검
 
6
정밀안전진단
 
3

Length

Max length6
Median length4
Mean length4.004451
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기점검 1339
99.3%
정밀점검 6
 
0.4%
정밀안전진단 3
 
0.2%

Length

2024-05-04T08:10:15.287846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:10:15.753659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기점검 1339
99.3%
정밀점검 6
 
0.4%
정밀안전진단 3
 
0.2%

최종안전점검일자
Date

Distinct170
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
Minimum1900-01-01 00:00:00
Maximum2023-12-31 00:00:00
2024-05-04T08:10:16.303133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:10:16.751539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관명
Text

Distinct163
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
2024-05-04T08:10:17.282242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length9.8026706
Min length3

Characters and Unicode

Total characters13214
Distinct characters125
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

Unique16 ?
Unique (%)1.2%

Sample

1st row전라남도 순천시청 도로과
2nd row전라남도 순천시청 도로과
3rd row전라남도 순천시청 도로과
4th row전라남도 순천시청 도로과
5th row전라남도 순천시청 도로과
ValueCountFrequency (%)
경기도 448
 
15.0%
서울특별시 138
 
4.6%
대전광역시 108
 
3.6%
부산광역시 79
 
2.7%
충청남도 72
 
2.4%
전라북도 69
 
2.3%
인천광역시 69
 
2.3%
고양시청 62
 
2.1%
전라남도 58
 
1.9%
경상남도 53
 
1.8%
Other values (168) 1825
61.2%
2024-05-04T08:10:18.325624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1633
 
12.4%
시 1295
 
9.8%
청 1076
 
8.1%
도 905
 
6.8%
구 747
 
5.7%
경 559
 
4.2%
광 486
 
3.7%
기 458
 
3.5%
역 374
 
2.8%
남 305
 
2.3%
Other values (115) 5376
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11581
87.6%
Space Separator 1633
 
12.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1295
 
11.2%
청 1076
 
9.3%
도 905
 
7.8%
구 747
 
6.5%
경 559
 
4.8%
광 486
 
4.2%
기 458
 
4.0%
역 374
 
3.2%
남 305
 
2.6%
전 286
 
2.5%
Other values (114) 5090
44.0%
Space Separator
ValueCountFrequency (%)
1633
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11581
87.6%
Common 1633
 
12.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1295
 
11.2%
청 1076
 
9.3%
도 905
 
7.8%
구 747
 
6.5%
경 559
 
4.8%
광 486
 
4.2%
기 458
 
4.0%
역 374
 
3.2%
남 305
 
2.6%
전 286
 
2.5%
Other values (114) 5090
44.0%
Common
ValueCountFrequency (%)
1633
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11581
87.6%
ASCII 1633
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1633
100.0%
Hangul
ValueCountFrequency (%)
시 1295
 
11.2%
청 1076
 
9.3%
도 905
 
7.8%
구 747
 
6.5%
경 559
 
4.8%
광 486
 
4.2%
기 458
 
4.0%
역 374
 
3.2%
남 305
 
2.6%
전 286
 
2.5%
Other values (114) 5090
44.0%

데이터기준일자
Date

Distinct107
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
Minimum2020-07-17 00:00:00
Maximum2024-04-03 00:00:00
2024-05-04T08:10:18.681504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:10:19.057162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct152
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4197884.6
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2024-05-04T08:10:19.538707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3150000
Q13600000
median3940000
Q34721000
95-th percentile6300000
Maximum6520000
Range3520000
Interquartile range (IQR)1121000

Descriptive statistics

Standard deviation855115.61
Coefficient of variation (CV)0.20370155
Kurtosis0.076158839
Mean4197884.6
Median Absolute Deviation (MAD)510000
Skewness0.92260594
Sum5.6587485 × 109
Variance7.3122271 × 1011
MonotonicityNot monotonic
2024-05-04T08:10:20.011039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6300000 65
 
4.8%
3940000 62
 
4.6%
3740000 46
 
3.4%
3780000 37
 
2.7%
3930000 27
 
2.0%
4490000 27
 
2.0%
3830000 27
 
2.0%
4520000 25
 
1.9%
3660000 25
 
1.9%
4810000 24
 
1.8%
Other values (142) 983
72.9%
ValueCountFrequency (%)
3000000 3
 
0.2%
3010000 2
 
0.1%
3020000 13
1.0%
3030000 4
 
0.3%
3050000 7
0.5%
3060000 6
0.4%
3070000 5
 
0.4%
3080000 1
 
0.1%
3100000 5
 
0.4%
3120000 7
0.5%
ValueCountFrequency (%)
6520000 1
 
0.1%
6310000 8
 
0.6%
6300000 65
4.8%
5710000 12
 
0.9%
5700000 4
 
0.3%
5690000 9
 
0.7%
5680000 9
 
0.7%
5670000 21
 
1.6%
5580000 1
 
0.1%
5540000 13
 
1.0%

제공기관명
Text

Distinct152
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
2024-05-04T08:10:20.829321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.8820475
Min length5

Characters and Unicode

Total characters10625
Distinct characters104
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

Unique20 ?
Unique (%)1.5%

Sample

1st row전라남도 순천시
2nd row전라남도 순천시
3rd row전라남도 순천시
4th row전라남도 순천시
5th row전라남도 순천시
ValueCountFrequency (%)
경기도 449
 
17.2%
서울특별시 138
 
5.3%
대전광역시 108
 
4.1%
부산광역시 79
 
3.0%
충청남도 73
 
2.8%
인천광역시 69
 
2.6%
서구 67
 
2.6%
광주광역시 62
 
2.4%
고양시 62
 
2.4%
전라남도 58
 
2.2%
Other values (127) 1449
55.4%
2024-05-04T08:10:21.970076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 1301
 
12.2%
1266
 
11.9%
도 830
 
7.8%
경 560
 
5.3%
구 492
 
4.6%
광 486
 
4.6%
기 459
 
4.3%
역 371
 
3.5%
남 290
 
2.7%
전 270
 
2.5%
Other values (94) 4300
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9359
88.1%
Space Separator 1266
 
11.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1301
 
13.9%
도 830
 
8.9%
경 560
 
6.0%
구 492
 
5.3%
광 486
 
5.2%
기 459
 
4.9%
역 371
 
4.0%
남 290
 
3.1%
전 270
 
2.9%
서 252
 
2.7%
Other values (93) 4048
43.3%
Space Separator
ValueCountFrequency (%)
1266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9359
88.1%
Common 1266
 
11.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1301
 
13.9%
도 830
 
8.9%
경 560
 
6.0%
구 492
 
5.3%
광 486
 
5.2%
기 459
 
4.9%
역 371
 
4.0%
남 290
 
3.1%
전 270
 
2.9%
서 252
 
2.7%
Other values (93) 4048
43.3%
Common
ValueCountFrequency (%)
1266
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9359
88.1%
ASCII 1266
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 1301
 
13.9%
도 830
 
8.9%
경 560
 
6.0%
구 492
 
5.3%
광 486
 
5.2%
기 459
 
4.9%
역 371
 
4.0%
남 290
 
3.1%
전 270
 
2.9%
서 252
 
2.7%
Other values (93) 4048
43.3%
ASCII
ValueCountFrequency (%)
1266
100.0%

Sample

육교명도로종류도로노선번호도로노선명소재지도로명주소위도경도육교연장육교높이허용통행하중통행제한높이육교폭난간높이조명개수장애인편의시설설치여부장애인편의시설종류장애인편의시설수량부대시설종류부대시설수량육교준공일자내진설계적용여부안전등급사용제한구분육교보수보강내역최종안전점검유형최종안전점검일자관리기관명데이터기준일자제공기관코드제공기관명
0여상육교일반국도2번녹색로전라남도 순천시 녹색로 1636 (덕월동)34.926486127.49090345.7<NA><NA>4.44.1<NA><NA>N없음<NA><NA><NA>1991-01-01N보통제한없음2023-02-17정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
1이수육교시도<NA>이수로전라남도 순천시 이수로 171-1 (생목동)34.949072127.50461422.8<NA><NA>4.53.1<NA><NA>N없음<NA><NA><NA>1991-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
2조례육교2일반국도2번순광로전라남도 순천시 순광로 17 (조례동)34.955124127.52298232.6<NA><NA>4.13.8<NA><NA>N없음<NA><NA><NA>1992-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
3남산육교시도<NA>남산로전라남도 순천시 남산로 59 (풍덕동)34.939879127.49491221.2<NA><NA>4.34.0<NA><NA>N없음<NA><NA><NA>1993-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
4금당육교일반국도2번백강로전라남도 순천시 백강로 206 (연향동)34.95169127.52251834.2<NA><NA>4.53.0<NA><NA>N없음<NA><NA><NA>1995-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
5풍전육교일반국도2번순광로전라남도 순천시 순광로34.957017127.52819531.0<NA><NA>5.03.0<NA><NA>N없음<NA><NA><NA>1997-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
6강변육교시도<NA>강변로전라남도 순천시 강변로34.930748127.51160719.9<NA><NA>4.52.0<NA><NA>N없음<NA><NA><NA>1998-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
7송촌육교일반국도2번순광로전라남도 순천시 순광로 111 (조례동)34.95912127.53181934.0<NA><NA>5.53.5<NA><NA>N없음<NA><NA><NA>1999-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
8연향철도육교시도<NA>연향로전라남도 순천시 율산3길 112 (연향동)34.941517127.52812436.4<NA><NA>4.53.4<NA><NA>Y경사로2<NA><NA>2000-01-01N보통제한없음<NA>정기점검2022-09-27전라남도 순천시청 도로과2023-08-214820000전라남도 순천시
9갈현보도육교시도2-61드림로인천광역시 계양구 드림로 790번길 237.575638126.72118929.0<NA><NA>5.04.0<NA><NA>N없음<NA><NA><NA>1997-01-01N보통제한없음<NA>정기점검2023-07-17인천광역시 계양구청2023-12-043550000인천광역시 계양구
육교명도로종류도로노선번호도로노선명소재지도로명주소위도경도육교연장육교높이허용통행하중통행제한높이육교폭난간높이조명개수장애인편의시설설치여부장애인편의시설종류장애인편의시설수량부대시설종류부대시설수량육교준공일자내진설계적용여부안전등급사용제한구분육교보수보강내역최종안전점검유형최종안전점검일자관리기관명데이터기준일자제공기관코드제공기관명
1338장평육교일반국도58호선장평3로경상남도 거제시 장평3로 1034.889442128.609402104.5<NA><NA>4.52.5<NA><NA>Y엘리베이터<NA><NA><NA>2008-01-01보통제한없음<NA>정기점검2022-10-11경상남도 거제시청 도로과2023-11-275370000경상남도 거제시
1339중곡동육교일반국도58호선거제대로경상남도 거제시 중곡로 334.893034128.6302843.7<NA><NA>4.74.0<NA><NA>Y엘리베이터<NA><NA><NA>1998-01-01보통제한없음<NA>정기점검2022-10-11경상남도 거제시청 도로과2023-11-275370000경상남도 거제시
1340청마교기타<NA>거제남서로경상남도 거제시 둔덕면 거제남서로 462434.835678128.50467665.0<NA><NA>4.03.0<NA><NA>N없음<NA><NA><NA>2004-12-29양호제한없음<NA>정기점검2022-10-08경상남도 거제시청 도로과2023-11-275370000경상남도 거제시
1341산방보도교기타<NA>산방2길경상남도 거제시 둔덕면 산방2길 7-1734.856585128.51461425.0<NA><NA>3.13.9<NA><NA>N없음<NA><NA><NA>2008-04-25양호제한없음<NA>정기점검2022-10-08경상남도 거제시청 도로과2023-11-275370000경상남도 거제시
1342민락초등학교 앞 육교시도광역시도2003광남로부산광역시 수영구 광남로 27135.160662129.12833556.0<NA><NA>4.93.0<NA><NA>Y승강기3<NA><NA><NA>N보통제한없음<NA>정기점검2023-06-07부산광역시 수영구청2023-11-213380000부산광역시 수영구
1343민락교 접속육교시도광역시도2401광안해변로부산광역시 수영구 광안해변로 41835.159986129.1315185.3<NA><NA>8.72.0<NA><NA>N없음0<NA><NA><NA>N보통제한없음<NA>정기점검2023-06-07부산광역시 수영구청2023-11-213380000부산광역시 수영구
1344남천동 자유한국당사 앞 육교시도광역시도24황령대로부산광역시 수영구 황령대로 49335.138288129.10791329.8<NA><NA>4.53.0<NA><NA>Y승강기2<NA><NA><NA>N보통제한없음<NA>정기점검2023-06-07부산광역시 수영구청2023-11-213380000부산광역시 수영구
1345송도곡각지 앞 육교시도1-8호선충무대로부산광역시 서구 충무대로 5635.078649129.01830166.56.0<NA>5.53.01.26Y승강기2<NA><NA>1995-12-31양호제한없음2020.08.(재도장 완료)정기점검2023-10-04부산광역시 서구청2023-11-043260000부산광역시 서구
1346동신초등학교 앞 육교시도3-7호선보수대로부산광역시 서구 보수대로 219-135.114451129.01947335.05.0<NA>4.53.01.26Y승강기2<NA><NA>1986-12-31양호제한없음2021.07.(재도장 완료)정기점검2023-10-04부산광역시 서구청2023-11-043260000부산광역시 서구
1347구덕야구장 앞 육교시도3-7호선보수대로부산광역시 서구 보수대로 25035.116255129.01728950.55.0<NA>4.53.51.24Y승강기2<NA><NA>1986-12-31양호제한없음2022.01.(재도장 완료)정기점검2023-10-04부산광역시 서구청2023-11-043260000부산광역시 서구