Overview

Dataset statistics

Number of variables35
Number of observations2176
Missing cells17216
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory627.0 KiB
Average record size in memory295.1 B

Variable types

Text6
Categorical13
DateTime2
Numeric14

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/15025443/standard.do

Alerts

관리점검결과 has constant value ""Constant
운영방식구분 is highly imbalanced (87.6%)Imbalance
평일운영시작시각 is highly imbalanced (89.2%)Imbalance
평일운영종료시각 is highly imbalanced (78.7%)Imbalance
주말운영시작시각 is highly imbalanced (89.2%)Imbalance
주말운영종료시각 is highly imbalanced (78.8%)Imbalance
지정목적 is highly imbalanced (88.4%)Imbalance
유지보수내용 is highly imbalanced (90.6%)Imbalance
영상정보기처리기기설치개수 is highly imbalanced (87.4%)Imbalance
지정일자 has 1507 (69.3%) missing valuesMissing
보안등설치개수 has 1958 (90.0%) missing valuesMissing
횡단보도설치개수 has 1964 (90.3%) missing valuesMissing
방호울타리설치개수 has 1976 (90.8%) missing valuesMissing
차량진입억제용말뚝설치개수 has 1946 (89.4%) missing valuesMissing
속도저감시설설치개수 has 1964 (90.3%) missing valuesMissing
교통표지판설치개수 has 1963 (90.2%) missing valuesMissing
이정표설치개수 has 1964 (90.3%) missing valuesMissing
점자블럭설치개수 has 1970 (90.5%) missing valuesMissing
보안등설치개수 has 86 (4.0%) zerosZeros
횡단보도설치개수 has 129 (5.9%) zerosZeros
방호울타리설치개수 has 171 (7.9%) zerosZeros
차량진입억제용말뚝설치개수 has 188 (8.6%) zerosZeros
속도저감시설설치개수 has 206 (9.5%) zerosZeros
교통표지판설치개수 has 106 (4.9%) zerosZeros
이정표설치개수 has 143 (6.6%) zerosZeros
점자블럭설치개수 has 144 (6.6%) zerosZeros

Reproduction

Analysis started2024-05-11 07:51:17.608275
Analysis finished2024-05-11 07:51:19.515672
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

보행자전용도로명
Text

Distinct1996
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-05-11T16:51:20.051838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length9.7201287
Min length2

Characters and Unicode

Total characters21151
Distinct characters223
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1888 ?
Unique (%)86.8%

Sample

1st row합정동 소로 3-385
2nd row합정동 소로 3-386
3rd row합정동 소로 3-387
4th row죽백동 소로 2-40
5th row죽백동 소로 2-41
ValueCountFrequency (%)
소로 264
 
7.4%
이서면 110
 
3.1%
보행자전용도로 107
 
3.0%
비전동 71
 
2.0%
용이동 65
 
1.8%
운중동 64
 
1.8%
판교동 53
 
1.5%
없음 46
 
1.3%
구미동 45
 
1.3%
동삭동 37
 
1.0%
Other values (1741) 2725
76.0%
2024-05-11T16:51:21.370674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 2100
 
9.9%
- 1659
 
7.8%
3 1642
 
7.8%
소 1478
 
7.0%
1411
 
6.7%
1 1123
 
5.3%
2 931
 
4.4%
동 741
 
3.5%
4 513
 
2.4%
6 460
 
2.2%
Other values (213) 9093
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10665
50.4%
Decimal Number 6554
31.0%
Dash Punctuation 1659
 
7.8%
Space Separator 1411
 
6.7%
Close Punctuation 430
 
2.0%
Open Punctuation 430
 
2.0%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 2100
19.7%
소 1478
 
13.9%
동 741
 
6.9%
도 332
 
3.1%
길 262
 
2.5%
자 252
 
2.4%
신 223
 
2.1%
산 208
 
2.0%
행 201
 
1.9%
보 201
 
1.9%
Other values (198) 4667
43.8%
Decimal Number
ValueCountFrequency (%)
3 1642
25.1%
1 1123
17.1%
2 931
14.2%
4 513
 
7.8%
6 460
 
7.0%
5 433
 
6.6%
0 415
 
6.3%
7 377
 
5.8%
8 349
 
5.3%
9 311
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 1659
100.0%
Space Separator
ValueCountFrequency (%)
1411
100.0%
Close Punctuation
ValueCountFrequency (%)
) 430
100.0%
Open Punctuation
ValueCountFrequency (%)
( 430
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10665
50.4%
Common 10486
49.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 2100
19.7%
소 1478
 
13.9%
동 741
 
6.9%
도 332
 
3.1%
길 262
 
2.5%
자 252
 
2.4%
신 223
 
2.1%
산 208
 
2.0%
행 201
 
1.9%
보 201
 
1.9%
Other values (198) 4667
43.8%
Common
ValueCountFrequency (%)
- 1659
15.8%
3 1642
15.7%
1411
13.5%
1 1123
10.7%
2 931
8.9%
4 513
 
4.9%
6 460
 
4.4%
5 433
 
4.1%
) 430
 
4.1%
( 430
 
4.1%
Other values (5) 1454
13.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10665
50.4%
ASCII 10486
49.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 2100
19.7%
소 1478
 
13.9%
동 741
 
6.9%
도 332
 
3.1%
길 262
 
2.5%
자 252
 
2.4%
신 223
 
2.1%
산 208
 
2.0%
행 201
 
1.9%
보 201
 
1.9%
Other values (198) 4667
43.8%
ASCII
ValueCountFrequency (%)
- 1659
15.8%
3 1642
15.7%
1411
13.5%
1 1123
10.7%
2 931
8.9%
4 513
 
4.9%
6 460
 
4.4%
5 433
 
4.1%
) 430
 
4.1%
( 430
 
4.1%
Other values (5) 1454
13.9%

시도명
Categorical

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
경기도
848 
충청북도
505 
대전광역시
369 
인천광역시
170 
서울특별시
91 
Other values (9)
193 

Length

Max length7
Median length5
Mean length3.9972426
Min length3

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 848
39.0%
충청북도 505
23.2%
대전광역시 369
17.0%
인천광역시 170
 
7.8%
서울특별시 91
 
4.2%
전북특별자치도 62
 
2.8%
전라북도 62
 
2.8%
경상북도 25
 
1.1%
전라남도 22
 
1.0%
울산광역시 11
 
0.5%
Other values (4) 11
 
0.5%

Length

2024-05-11T16:51:21.853399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 848
39.0%
충청북도 505
23.2%
대전광역시 369
17.0%
인천광역시 170
 
7.8%
서울특별시 91
 
4.2%
전북특별자치도 62
 
2.8%
전라북도 62
 
2.8%
경상북도 25
 
1.1%
전라남도 22
 
1.0%
울산광역시 11
 
0.5%
Other values (4) 11
 
0.5%

시군구명
Text

Distinct53
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-05-11T16:51:22.370858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.8759191
Min length2

Characters and Unicode

Total characters6258
Distinct characters59
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.3%

Sample

1st row평택시
2nd row평택시
3rd row평택시
4th row평택시
5th row평택시
ValueCountFrequency (%)
성남시 418
19.2%
평택시 246
11.3%
서구 189
 
8.7%
서원구 158
 
7.2%
청주시 136
 
6.2%
완주군 124
 
5.7%
청원구 107
 
4.9%
남동구 106
 
4.9%
오산시 91
 
4.2%
동구 73
 
3.3%
Other values (44) 533
24.4%
2024-05-11T16:51:23.044467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 1048
16.7%
구 923
14.7%
남 582
 
9.3%
성 446
 
7.1%
서 361
 
5.8%
주 333
 
5.3%
원 274
 
4.4%
평 251
 
4.0%
택 246
 
3.9%
청 243
 
3.9%
Other values (49) 1551
24.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6253
99.9%
Space Separator 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1048
16.8%
구 923
14.8%
남 582
 
9.3%
성 446
 
7.1%
서 361
 
5.8%
주 333
 
5.3%
원 274
 
4.4%
평 251
 
4.0%
택 246
 
3.9%
청 243
 
3.9%
Other values (48) 1546
24.7%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6253
99.9%
Common 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1048
16.8%
구 923
14.8%
남 582
 
9.3%
성 446
 
7.1%
서 361
 
5.8%
주 333
 
5.3%
원 274
 
4.4%
평 251
 
4.0%
택 246
 
3.9%
청 243
 
3.9%
Other values (48) 1546
24.7%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6253
99.9%
ASCII 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 1048
16.8%
구 923
14.8%
남 582
 
9.3%
성 446
 
7.1%
서 361
 
5.8%
주 333
 
5.3%
원 274
 
4.4%
평 251
 
4.0%
택 246
 
3.9%
청 243
 
3.9%
Other values (48) 1546
24.7%
ASCII
ValueCountFrequency (%)
5
100.0%

법정동명
Text

Distinct237
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-05-11T16:51:23.691926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.1263787
Min length2

Characters and Unicode

Total characters6803
Distinct characters170
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)3.9%

Sample

1st row합정동
2nd row합정동
3rd row합정동
4th row죽백동
5th row죽백동
ValueCountFrequency (%)
이서면 110
 
5.0%
비전동 71
 
3.2%
용이동 65
 
3.0%
운중동 64
 
2.9%
덕산읍 62
 
2.8%
논현동 59
 
2.7%
판교동 53
 
2.4%
둔산동 53
 
2.4%
성화동 50
 
2.3%
산남동 49
 
2.2%
Other values (230) 1560
71.0%
2024-05-11T16:51:24.880128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 1949
28.6%
산 194
 
2.9%
이 183
 
2.7%
서 155
 
2.3%
수 134
 
2.0%
면 120
 
1.8%
리 118
 
1.7%
읍 110
 
1.6%
운 105
 
1.5%
현 104
 
1.5%
Other values (160) 3631
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6608
97.1%
Decimal Number 169
 
2.5%
Space Separator 20
 
0.3%
Math Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1949
29.5%
산 194
 
2.9%
이 183
 
2.8%
서 155
 
2.3%
수 134
 
2.0%
면 120
 
1.8%
리 118
 
1.8%
읍 110
 
1.7%
운 105
 
1.6%
현 104
 
1.6%
Other values (152) 3436
52.0%
Decimal Number
ValueCountFrequency (%)
3 57
33.7%
1 50
29.6%
2 40
23.7%
5 18
 
10.7%
4 3
 
1.8%
6 1
 
0.6%
Space Separator
ValueCountFrequency (%)
20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6608
97.1%
Common 195
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1949
29.5%
산 194
 
2.9%
이 183
 
2.8%
서 155
 
2.3%
수 134
 
2.0%
면 120
 
1.8%
리 118
 
1.8%
읍 110
 
1.7%
운 105
 
1.6%
현 104
 
1.6%
Other values (152) 3436
52.0%
Common
ValueCountFrequency (%)
3 57
29.2%
1 50
25.6%
2 40
20.5%
20
 
10.3%
5 18
 
9.2%
+ 6
 
3.1%
4 3
 
1.5%
6 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6608
97.1%
ASCII 195
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 1949
29.5%
산 194
 
2.9%
이 183
 
2.8%
서 155
 
2.3%
수 134
 
2.0%
면 120
 
1.8%
리 118
 
1.8%
읍 110
 
1.7%
운 105
 
1.6%
현 104
 
1.6%
Other values (152) 3436
52.0%
ASCII
ValueCountFrequency (%)
3 57
29.2%
1 50
25.6%
2 40
20.5%
20
 
10.3%
5 18
 
9.2%
+ 6
 
3.1%
4 3
 
1.5%
6 1
 
0.5%

지정일자
Date

MISSING 

Distinct131
Distinct (%)19.6%
Missing1507
Missing (%)69.3%
Memory size17.1 KiB
Minimum1969-04-11 00:00:00
Maximum2023-06-26 00:00:00
2024-05-11T16:51:25.367373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:25.845796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

운영방식구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
전일제
2120 
시간제
 
37
주말제
 
19

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전일제 2120
97.4%
시간제 37
 
1.7%
주말제 19
 
0.9%

Length

2024-05-11T16:51:26.387446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:51:26.612808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전일제 2120
97.4%
시간제 37
 
1.7%
주말제 19
 
0.9%

평일운영시작시각
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
00:00
2066 
12:00
 
70
10:00
 
15
16:00
 
5
01:00
 
5
Other values (7)
 
15

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row00:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 2066
94.9%
12:00 70
 
3.2%
10:00 15
 
0.7%
16:00 5
 
0.2%
01:00 5
 
0.2%
08:00 4
 
0.2%
07:30 3
 
0.1%
18:00 2
 
0.1%
00:01 2
 
0.1%
08:20 2
 
0.1%
Other values (2) 2
 
0.1%

Length

2024-05-11T16:51:26.864630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00 2066
94.9%
12:00 70
 
3.2%
10:00 15
 
0.7%
16:00 5
 
0.2%
01:00 5
 
0.2%
08:00 4
 
0.2%
07:30 3
 
0.1%
18:00 2
 
0.1%
00:01 2
 
0.1%
08:20 2
 
0.1%
Other values (2) 2
 
0.1%

평일운영종료시각
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
23:59
1862 
00:00
226 
24:00
 
51
23:00
 
7
09:00
 
6
Other values (9)
 
24

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row23:59
2nd row23:59
3rd row23:59
4th row23:59
5th row23:59

Common Values

ValueCountFrequency (%)
23:59 1862
85.6%
00:00 226
 
10.4%
24:00 51
 
2.3%
23:00 7
 
0.3%
09:00 6
 
0.3%
22:00 6
 
0.3%
15:00 5
 
0.2%
17:00 4
 
0.2%
21:00 4
 
0.2%
05:00 1
 
< 0.1%
Other values (4) 4
 
0.2%

Length

2024-05-11T16:51:27.111726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59 1862
85.6%
00:00 226
 
10.4%
24:00 51
 
2.3%
23:00 7
 
0.3%
09:00 6
 
0.3%
22:00 6
 
0.3%
15:00 5
 
0.2%
17:00 4
 
0.2%
21:00 4
 
0.2%
05:00 1
 
< 0.1%
Other values (4) 4
 
0.2%

주말운영시작시각
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
00:00
2057 
12:00
 
71
10:00
 
21
16:00
 
5
01:00
 
5
Other values (10)
 
17

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st row00:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 2057
94.5%
12:00 71
 
3.3%
10:00 21
 
1.0%
16:00 5
 
0.2%
01:00 5
 
0.2%
14:00 3
 
0.1%
18:00 2
 
0.1%
08:00 2
 
0.1%
00:01 2
 
0.1%
06:00 2
 
0.1%
Other values (5) 6
 
0.3%

Length

2024-05-11T16:51:27.338888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00 2057
94.5%
12:00 71
 
3.3%
10:00 21
 
1.0%
16:00 5
 
0.2%
01:00 5
 
0.2%
14:00 3
 
0.1%
18:00 2
 
0.1%
08:00 2
 
0.1%
00:01 2
 
0.1%
06:00 2
 
0.1%
Other values (5) 6
 
0.3%

주말운영종료시각
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
23:59
1873 
00:00
208 
24:00
 
52
22:00
 
14
23:00
 
9
Other values (9)
 
20

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row23:59
2nd row23:59
3rd row23:59
4th row23:59
5th row23:59

Common Values

ValueCountFrequency (%)
23:59 1873
86.1%
00:00 208
 
9.6%
24:00 52
 
2.4%
22:00 14
 
0.6%
23:00 9
 
0.4%
21:00 5
 
0.2%
17:00 4
 
0.2%
18:00 4
 
0.2%
09:00 2
 
0.1%
05:00 1
 
< 0.1%
Other values (4) 4
 
0.2%

Length

2024-05-11T16:51:27.640959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59 1873
86.1%
00:00 208
 
9.6%
24:00 52
 
2.4%
22:00 14
 
0.6%
23:00 9
 
0.4%
21:00 5
 
0.2%
17:00 4
 
0.2%
18:00 4
 
0.2%
09:00 2
 
0.1%
05:00 1
 
< 0.1%
Other values (4) 4
 
0.2%

보행자전용도로시작점위도
Real number (ℝ)

Distinct1966
Distinct (%)90.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean36.85003
Minimum32.709611
Maximum39.98806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:28.024492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.709611
5-th percentile35.831836
Q136.584048
median36.98951
Q337.386701
95-th percentile37.508647
Maximum39.98806
Range7.278449
Interquartile range (IQR)0.80265223

Descriptive statistics

Standard deviation0.61394689
Coefficient of variation (CV)0.016660689
Kurtosis5.2784531
Mean36.85003
Median Absolute Deviation (MAD)0.39864811
Skewness-1.4643946
Sum80148.816
Variance0.37693078
MonotonicityNot monotonic
2024-05-11T16:51:28.401983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.326999 73
 
3.4%
36.2819047 16
 
0.7%
36.2873081 9
 
0.4%
35.832594 8
 
0.4%
35.830951 6
 
0.3%
35.830717 6
 
0.3%
35.830953 4
 
0.2%
35.833403 4
 
0.2%
35.830956 4
 
0.2%
35.837148 4
 
0.2%
Other values (1956) 2041
93.8%
ValueCountFrequency (%)
32.709611 1
< 0.1%
33.462693 1
< 0.1%
33.464517 1
< 0.1%
33.469016 1
< 0.1%
33.46913 1
< 0.1%
33.469936 1
< 0.1%
33.470242 1
< 0.1%
33.4705 1
< 0.1%
33.470648 1
< 0.1%
33.476766 1
< 0.1%
ValueCountFrequency (%)
39.98806 1
< 0.1%
37.913956 1
< 0.1%
37.913843 1
< 0.1%
37.895635 1
< 0.1%
37.832141 1
< 0.1%
37.822291 1
< 0.1%
37.813291 1
< 0.1%
37.811631 1
< 0.1%
37.803181 1
< 0.1%
37.797621 1
< 0.1%

보행자전용도로시작점경도
Real number (ℝ)

Distinct1965
Distinct (%)90.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean127.23302
Minimum126.4604
Maximum129.37046
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:28.785788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.4604
5-th percentile126.7126
Q1127.07262
median127.12783
Q3127.43268
95-th percentile127.53462
Maximum129.37046
Range2.9100564
Interquartile range (IQR)0.360061

Descriptive statistics

Standard deviation0.35235263
Coefficient of variation (CV)0.0027693488
Kurtosis9.4559358
Mean127.23302
Median Absolute Deviation (MAD)0.2226329
Skewness2.0132335
Sum276731.83
Variance0.12415237
MonotonicityNot monotonic
2024-05-11T16:51:29.115744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.432683 73
 
3.4%
127.378031 16
 
0.7%
127.379181 9
 
0.4%
126.711682 4
 
0.2%
127.024241 4
 
0.2%
127.020611 4
 
0.2%
127.022519 4
 
0.2%
128.5406302 3
 
0.1%
126.752566 3
 
0.1%
127.378 3
 
0.1%
Other values (1955) 2052
94.3%
ValueCountFrequency (%)
126.460404 1
< 0.1%
126.461498 1
< 0.1%
126.461541 1
< 0.1%
126.461549 1
< 0.1%
126.462163 1
< 0.1%
126.463623 1
< 0.1%
126.464669 1
< 0.1%
126.464674 2
0.1%
126.464695 1
< 0.1%
126.490746 1
< 0.1%
ValueCountFrequency (%)
129.3704604 1
< 0.1%
129.369211 1
< 0.1%
129.368811 1
< 0.1%
129.3672922 1
< 0.1%
129.366578 1
< 0.1%
129.3660713 1
< 0.1%
129.3658451 1
< 0.1%
129.360006 1
< 0.1%
129.359311 1
< 0.1%
129.358234 1
< 0.1%

보행자전용도로종료점위도
Real number (ℝ)

Distinct1973
Distinct (%)90.7%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean36.848646
Minimum33.462408
Maximum39.999225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:29.454798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.462408
5-th percentile35.831787
Q136.583877
median36.98905
Q337.387642
95-th percentile37.510641
Maximum39.999225
Range6.536817
Interquartile range (IQR)0.8037655

Descriptive statistics

Standard deviation0.61757206
Coefficient of variation (CV)0.016759695
Kurtosis5.0023269
Mean36.848646
Median Absolute Deviation (MAD)0.399585
Skewness-1.4499284
Sum80145.805
Variance0.38139525
MonotonicityNot monotonic
2024-05-11T16:51:29.817789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.326999 73
 
3.4%
36.2819047 15
 
0.7%
36.2873081 9
 
0.4%
35.830953 8
 
0.4%
35.830951 6
 
0.3%
35.837148 4
 
0.2%
35.830722 4
 
0.2%
35.833407 4
 
0.2%
35.832594 4
 
0.2%
35.831735 4
 
0.2%
Other values (1963) 2044
93.9%
ValueCountFrequency (%)
33.462408 1
< 0.1%
33.4642 1
< 0.1%
33.464726 1
< 0.1%
33.464806 1
< 0.1%
33.469016 1
< 0.1%
33.470242 1
< 0.1%
33.470422 1
< 0.1%
33.470537 1
< 0.1%
33.472558 1
< 0.1%
33.472816 1
< 0.1%
ValueCountFrequency (%)
39.999225 1
< 0.1%
37.917827 1
< 0.1%
37.915284 1
< 0.1%
37.893552 1
< 0.1%
37.841251 1
< 0.1%
37.838161 1
< 0.1%
37.821861 1
< 0.1%
37.821231 1
< 0.1%
37.808981 1
< 0.1%
37.805301 1
< 0.1%

보행자전용도로종료점경도
Real number (ℝ)

Distinct1974
Distinct (%)90.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean127.23065
Minimum126.46092
Maximum129.37034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:30.762435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.46092
5-th percentile126.71148
Q1127.06934
median127.12719
Q3127.43268
95-th percentile127.5347
Maximum129.37034
Range2.909422
Interquartile range (IQR)0.3633395

Descriptive statistics

Standard deviation0.34964324
Coefficient of variation (CV)0.0027481055
Kurtosis9.2804835
Mean127.23065
Median Absolute Deviation (MAD)0.222306
Skewness1.9643794
Sum276726.66
Variance0.1222504
MonotonicityNot monotonic
2024-05-11T16:51:31.073830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.432683 73
 
3.4%
127.378031 15
 
0.7%
127.379181 9
 
0.4%
127.381 5
 
0.2%
127.024241 4
 
0.2%
127.110919 4
 
0.2%
127.022393 4
 
0.2%
127.39 4
 
0.2%
127.381256 3
 
0.1%
126.753838 3
 
0.1%
Other values (1964) 2051
94.3%
ValueCountFrequency (%)
126.460919 1
< 0.1%
126.461506 1
< 0.1%
126.461541 1
< 0.1%
126.461549 1
< 0.1%
126.462566 1
< 0.1%
126.464014 1
< 0.1%
126.464655 1
< 0.1%
126.464658 1
< 0.1%
126.464671 1
< 0.1%
126.464677 1
< 0.1%
ValueCountFrequency (%)
129.370341 1
< 0.1%
129.369494 1
< 0.1%
129.369082 1
< 0.1%
129.368022 1
< 0.1%
129.3672504 1
< 0.1%
129.3661237 1
< 0.1%
129.3659874 1
< 0.1%
129.365805 1
< 0.1%
129.360471 1
< 0.1%
129.360364 1
< 0.1%

자전거보행자겸용도로구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1682 
전용
426 
겸용
 
68

Length

Max length4
Median length4
Mean length3.5459559
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1682
77.3%
전용 426
 
19.6%
겸용 68
 
3.1%

Length

2024-05-11T16:51:31.478873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:51:31.836233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1682
77.3%
전용 426
 
19.6%
겸용 68
 
3.1%

보행자전용도로폭
Real number (ℝ)

Distinct42
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.859237
Minimum1.2
Maximum2030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:32.231837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile3
Q15
median6
Q38
95-th percentile15
Maximum2030
Range2028.8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation83.66574
Coefficient of variation (CV)6.5062755
Kurtosis355.05281
Mean12.859237
Median Absolute Deviation (MAD)2
Skewness17.413665
Sum27981.7
Variance6999.956
MonotonicityNot monotonic
2024-05-11T16:51:32.592813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
6.0 752
34.6%
4.0 345
15.9%
8.0 328
15.1%
10.0 200
 
9.2%
3.0 144
 
6.6%
5.0 139
 
6.4%
15.0 123
 
5.7%
2.0 39
 
1.8%
20.0 25
 
1.1%
12.0 16
 
0.7%
Other values (32) 65
 
3.0%
ValueCountFrequency (%)
1.2 1
 
< 0.1%
1.5 1
 
< 0.1%
2.0 39
 
1.8%
2.2 3
 
0.1%
3.0 144
6.6%
3.1 1
 
< 0.1%
3.2 1
 
< 0.1%
3.5 1
 
< 0.1%
4.0 345
15.9%
4.2 1
 
< 0.1%
ValueCountFrequency (%)
2030.0 2
0.1%
1030.0 1
 
< 0.1%
1015.0 1
 
< 0.1%
1014.0 1
 
< 0.1%
816.0 1
 
< 0.1%
715.0 4
0.2%
710.0 1
 
< 0.1%
556.0 2
0.1%
510.0 1
 
< 0.1%
46.0 1
 
< 0.1%

보차분리여부
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
1578 
N
313 
Y
285 

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 (%)
1578
72.5%
N 313
 
14.4%
Y 285
 
13.1%

Length

2024-05-11T16:51:32.911161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:51:33.164126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 313
52.3%
y 285
47.7%

지정목적
Categorical

IMBALANCE 

Distinct21
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
보행환경개선
2054 
안전한 보행로 확보
 
26
주거지
 
22
보행자 안전
 
16
보행편의증진
 
11
Other values (16)
 
47

Length

Max length35
Median length6
Mean length6.0808824
Min length2

Unique

Unique7 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
보행환경개선 2054
94.4%
안전한 보행로 확보 26
 
1.2%
주거지 22
 
1.0%
보행자 안전 16
 
0.7%
보행편의증진 11
 
0.5%
보행안전+편의증진 10
 
0.5%
문화 8
 
0.4%
지역상권활성화+보행환경개선 5
 
0.2%
시장방문 보행자 편의 3
 
0.1%
관광지내 보행자전용도로 확보 3
 
0.1%
Other values (11) 18
 
0.8%

Length

2024-05-11T16:51:33.513894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
보행환경개선 2054
90.6%
확보 29
 
1.3%
보행로 26
 
1.1%
안전한 26
 
1.1%
주거지 22
 
1.0%
보행자 19
 
0.8%
안전 16
 
0.7%
보행편의증진 11
 
0.5%
보행안전+편의증진 10
 
0.4%
문화 8
 
0.4%
Other values (24) 45
 
2.0%

관리점검일자
Date

Distinct74
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
Minimum2011-10-28 00:00:00
Maximum2023-11-13 00:00:00
2024-05-11T16:51:33.900596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:34.262223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리점검결과
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
합격
2176 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합격 2176
100.0%

Length

2024-05-11T16:51:34.591859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:51:34.829410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합격 2176
100.0%

유지보수내용
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
2091 
없음
 
53
N
 
11
시설물 양호(미보수)
 
10
노면표시 도색
 
3
Other values (5)
 
8

Length

Max length19
Median length4
Mean length3.9931066
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2091
96.1%
없음 53
 
2.4%
N 11
 
0.5%
시설물 양호(미보수) 10
 
0.5%
노면표시 도색 3
 
0.1%
디자인포장 실시 2
 
0.1%
도로 전면 재포장 2
 
0.1%
바닥안내판 정비 2
 
0.1%
조형물세척 및 보수+아크릴판문자교체 1
 
< 0.1%
탄성포장재 보수 1
 
< 0.1%

Length

2024-05-11T16:51:35.093719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:51:35.433268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2091
95.0%
없음 53
 
2.4%
n 11
 
0.5%
시설물 10
 
0.5%
양호(미보수 10
 
0.5%
노면표시 3
 
0.1%
도색 3
 
0.1%
재포장 2
 
0.1%
정비 2
 
0.1%
바닥안내판 2
 
0.1%
Other values (9) 13
 
0.6%

영상정보기처리기기설치개수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
2073 
0
 
97
1
 
4
13
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.8584559
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2073
95.3%
0 97
 
4.5%
1 4
 
0.2%
13 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-05-11T16:51:35.804991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:51:36.524780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2073
95.3%
0 97
 
4.5%
1 4
 
0.2%
13 1
 
< 0.1%
3 1
 
< 0.1%

보안등설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)8.7%
Missing1958
Missing (%)90.0%
Infinite0
Infinite (%)0.0%
Mean4.8853211
Minimum0
Maximum108
Zeros86
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:36.770949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q36
95-th percentile11.15
Maximum108
Range108
Interquartile range (IQR)6

Descriptive statistics

Standard deviation11.227052
Coefficient of variation (CV)2.2981196
Kurtosis46.203728
Mean4.8853211
Median Absolute Deviation (MAD)3
Skewness6.2937959
Sum1065
Variance126.0467
MonotonicityNot monotonic
2024-05-11T16:51:37.030030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 86
 
4.0%
3 26
 
1.2%
4 21
 
1.0%
8 17
 
0.8%
5 16
 
0.7%
6 10
 
0.5%
7 10
 
0.5%
10 9
 
0.4%
2 7
 
0.3%
1 4
 
0.2%
Other values (9) 12
 
0.6%
(Missing) 1958
90.0%
ValueCountFrequency (%)
0 86
4.0%
1 4
 
0.2%
2 7
 
0.3%
3 26
 
1.2%
4 21
 
1.0%
5 16
 
0.7%
6 10
 
0.5%
7 10
 
0.5%
8 17
 
0.8%
10 9
 
0.4%
ValueCountFrequency (%)
108 1
 
< 0.1%
78 1
 
< 0.1%
66 1
 
< 0.1%
52 1
 
< 0.1%
51 1
 
< 0.1%
19 1
 
< 0.1%
14 2
 
0.1%
12 3
 
0.1%
11 1
 
< 0.1%
10 9
0.4%

횡단보도설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)4.2%
Missing1964
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean0.89622642
Minimum0
Maximum20
Zeros129
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:37.258710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.9901618
Coefficient of variation (CV)2.2206016
Kurtosis51.176104
Mean0.89622642
Median Absolute Deviation (MAD)0
Skewness6.1610207
Sum190
Variance3.960744
MonotonicityNot monotonic
2024-05-11T16:51:37.514279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 129
 
5.9%
1 33
 
1.5%
2 31
 
1.4%
3 11
 
0.5%
4 4
 
0.2%
6 1
 
< 0.1%
20 1
 
< 0.1%
5 1
 
< 0.1%
15 1
 
< 0.1%
(Missing) 1964
90.3%
ValueCountFrequency (%)
0 129
5.9%
1 33
 
1.5%
2 31
 
1.4%
3 11
 
0.5%
4 4
 
0.2%
5 1
 
< 0.1%
6 1
 
< 0.1%
15 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
15 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 4
 
0.2%
3 11
 
0.5%
2 31
 
1.4%
1 33
 
1.5%
0 129
5.9%

방호울타리설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)3.5%
Missing1976
Missing (%)90.8%
Infinite0
Infinite (%)0.0%
Mean2.37
Minimum0
Maximum330
Zeros171
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:37.740031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum330
Range330
Interquartile range (IQR)0

Descriptive statistics

Standard deviation23.768209
Coefficient of variation (CV)10.02878
Kurtosis184.07079
Mean2.37
Median Absolute Deviation (MAD)0
Skewness13.361502
Sum474
Variance564.92774
MonotonicityNot monotonic
2024-05-11T16:51:37.941204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 171
 
7.9%
1 18
 
0.8%
2 6
 
0.3%
28 2
 
0.1%
3 1
 
< 0.1%
330 1
 
< 0.1%
55 1
 
< 0.1%
(Missing) 1976
90.8%
ValueCountFrequency (%)
0 171
7.9%
1 18
 
0.8%
2 6
 
0.3%
3 1
 
< 0.1%
28 2
 
0.1%
55 1
 
< 0.1%
330 1
 
< 0.1%
ValueCountFrequency (%)
330 1
 
< 0.1%
55 1
 
< 0.1%
28 2
 
0.1%
3 1
 
< 0.1%
2 6
 
0.3%
1 18
 
0.8%
0 171
7.9%

차량진입억제용말뚝설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)6.5%
Missing1946
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean2.026087
Minimum0
Maximum128
Zeros188
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:38.175707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum128
Range128
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.061784
Coefficient of variation (CV)4.9661164
Kurtosis115.90472
Mean2.026087
Median Absolute Deviation (MAD)0
Skewness10.06945
Sum466
Variance101.23949
MonotonicityNot monotonic
2024-05-11T16:51:38.427085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 188
 
8.6%
8 14
 
0.6%
2 7
 
0.3%
4 7
 
0.3%
3 3
 
0.1%
5 2
 
0.1%
16 1
 
< 0.1%
1 1
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
Other values (5) 5
 
0.2%
(Missing) 1946
89.4%
ValueCountFrequency (%)
0 188
8.6%
1 1
 
< 0.1%
2 7
 
0.3%
3 3
 
0.1%
4 7
 
0.3%
5 2
 
0.1%
6 1
 
< 0.1%
8 14
 
0.6%
10 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
128 1
 
< 0.1%
68 1
 
< 0.1%
34 1
 
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
13 1
 
< 0.1%
10 1
 
< 0.1%
8 14
0.6%
6 1
 
< 0.1%
5 2
 
0.1%

속도저감시설설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.8%
Missing1964
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean0.1509434
Minimum0
Maximum12
Zeros206
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:38.720812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0512232
Coefficient of variation (CV)6.9643536
Kurtosis84.301852
Mean0.1509434
Median Absolute Deviation (MAD)0
Skewness8.6148061
Sum32
Variance1.1050702
MonotonicityNot monotonic
2024-05-11T16:51:39.063663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 206
 
9.5%
4 2
 
0.1%
5 1
 
< 0.1%
1 1
 
< 0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1964
90.3%
ValueCountFrequency (%)
0 206
9.5%
1 1
 
< 0.1%
4 2
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
0.1%
1 1
 
< 0.1%
0 206
9.5%

교통표지판설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.8%
Missing1963
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean1.2629108
Minimum0
Maximum11
Zeros106
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:39.388639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7091278
Coefficient of variation (CV)1.3533243
Kurtosis7.0009792
Mean1.2629108
Median Absolute Deviation (MAD)1
Skewness2.0731672
Sum269
Variance2.9211179
MonotonicityNot monotonic
2024-05-11T16:51:39.598246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 106
 
4.9%
2 43
 
2.0%
1 26
 
1.2%
3 18
 
0.8%
5 10
 
0.5%
4 8
 
0.4%
11 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 1963
90.2%
ValueCountFrequency (%)
0 106
4.9%
1 26
 
1.2%
2 43
2.0%
3 18
 
0.8%
4 8
 
0.4%
5 10
 
0.5%
10 1
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
10 1
 
< 0.1%
5 10
 
0.5%
4 8
 
0.4%
3 18
 
0.8%
2 43
2.0%
1 26
 
1.2%
0 106
4.9%

이정표설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)3.3%
Missing1964
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean0.63207547
Minimum0
Maximum9
Zeros143
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:39.806855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2107377
Coefficient of variation (CV)1.9154954
Kurtosis13.899538
Mean0.63207547
Median Absolute Deviation (MAD)0
Skewness3.0838555
Sum134
Variance1.4658857
MonotonicityNot monotonic
2024-05-11T16:51:40.003660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 143
 
6.6%
1 34
 
1.6%
2 19
 
0.9%
3 10
 
0.5%
4 4
 
0.2%
7 1
 
< 0.1%
9 1
 
< 0.1%
(Missing) 1964
90.3%
ValueCountFrequency (%)
0 143
6.6%
1 34
 
1.6%
2 19
 
0.9%
3 10
 
0.5%
4 4
 
0.2%
7 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
7 1
 
< 0.1%
4 4
 
0.2%
3 10
 
0.5%
2 19
 
0.9%
1 34
 
1.6%
0 143
6.6%

점자블럭설치개수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)2.9%
Missing1970
Missing (%)90.5%
Infinite0
Infinite (%)0.0%
Mean0.63592233
Minimum0
Maximum30
Zeros144
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:40.211377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum30
Range30
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.9891627
Coefficient of variation (CV)4.7005154
Kurtosis84.94758
Mean0.63592233
Median Absolute Deviation (MAD)0
Skewness9.0304145
Sum131
Variance8.9350935
MonotonicityNot monotonic
2024-05-11T16:51:40.443638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 144
 
6.6%
1 58
 
2.7%
4 1
 
< 0.1%
29 1
 
< 0.1%
10 1
 
< 0.1%
30 1
 
< 0.1%
(Missing) 1970
90.5%
ValueCountFrequency (%)
0 144
6.6%
1 58
2.7%
4 1
 
< 0.1%
10 1
 
< 0.1%
29 1
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
29 1
 
< 0.1%
10 1
 
< 0.1%
4 1
 
< 0.1%
1 58
2.7%
0 144
6.6%

관리기관명
Text

Distinct60
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-05-11T16:51:40.842345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.7867647
Min length4

Characters and Unicode

Total characters21296
Distinct characters95
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.4%

Sample

1st row경기도 평택시청
2nd row경기도 평택시청
3rd row경기도 평택시청
4th row경기도 평택시청
5th row경기도 평택시청
ValueCountFrequency (%)
경기도 848
17.7%
성남시 418
 
8.7%
분당구청 369
 
7.7%
대전광역시 369
 
7.7%
평택시청 246
 
5.1%
건설과 194
 
4.0%
서구청 189
 
3.9%
인천광역시 170
 
3.5%
서원구청 158
 
3.3%
흥덕구 136
 
2.8%
Other values (71) 1695
35.4%
2024-05-11T16:51:41.501857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2616
 
12.3%
청 2323
 
10.9%
시 1679
 
7.9%
구 1484
 
7.0%
도 1145
 
5.4%
경 896
 
4.2%
기 848
 
4.0%
역 624
 
2.9%
남 604
 
2.8%
광 560
 
2.6%
Other values (85) 8517
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18679
87.7%
Space Separator 2616
 
12.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 2323
 
12.4%
시 1679
 
9.0%
구 1484
 
7.9%
도 1145
 
6.1%
경 896
 
4.8%
기 848
 
4.5%
역 624
 
3.3%
남 604
 
3.2%
광 560
 
3.0%
전 517
 
2.8%
Other values (83) 7999
42.8%
Space Separator
ValueCountFrequency (%)
2616
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18679
87.7%
Common 2617
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 2323
 
12.4%
시 1679
 
9.0%
구 1484
 
7.9%
도 1145
 
6.1%
경 896
 
4.8%
기 848
 
4.5%
역 624
 
3.3%
남 604
 
3.2%
광 560
 
3.0%
전 517
 
2.8%
Other values (83) 7999
42.8%
Common
ValueCountFrequency (%)
2616
> 99.9%
+ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18679
87.7%
ASCII 2617
 
12.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2616
> 99.9%
+ 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
청 2323
 
12.4%
시 1679
 
9.0%
구 1484
 
7.9%
도 1145
 
6.1%
경 896
 
4.8%
기 848
 
4.5%
역 624
 
3.3%
남 604
 
3.2%
광 560
 
3.0%
전 517
 
2.8%
Other values (83) 7999
42.8%

관리기관전화번호
Text

Distinct60
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-05-11T16:51:41.922097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.148438
Min length11

Characters and Unicode

Total characters26435
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

Unique9 ?
Unique (%)0.4%

Sample

1st row031-8024-4777
2nd row031-8024-4777
3rd row031-8024-4777
4th row031-8024-4777
5th row031-8024-4777
ValueCountFrequency (%)
031-8024-4777 246
 
11.3%
031-729-8092 213
 
9.8%
042-288-3925 189
 
8.7%
043-201-6372 158
 
7.3%
031-729-7461 156
 
7.2%
043-201-7372 136
 
6.2%
063-290-2805 124
 
5.7%
043-201-8372 107
 
4.9%
032-453-5640 106
 
4.9%
031-8036-7704 91
 
4.2%
Other values (50) 650
29.9%
2024-05-11T16:51:42.587997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4352
16.5%
0 3940
14.9%
2 3435
13.0%
3 2763
10.5%
7 2488
9.4%
4 2426
9.2%
1 1770
6.7%
8 1630
 
6.2%
5 1260
 
4.8%
9 1234
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22083
83.5%
Dash Punctuation 4352
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3940
17.8%
2 3435
15.6%
3 2763
12.5%
7 2488
11.3%
4 2426
11.0%
1 1770
8.0%
8 1630
7.4%
5 1260
 
5.7%
9 1234
 
5.6%
6 1137
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 4352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26435
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4352
16.5%
0 3940
14.9%
2 3435
13.0%
3 2763
10.5%
7 2488
9.4%
4 2426
9.2%
1 1770
6.7%
8 1630
 
6.2%
5 1260
 
4.8%
9 1234
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4352
16.5%
0 3940
14.9%
2 3435
13.0%
3 2763
10.5%
7 2488
9.4%
4 2426
9.2%
1 1770
6.7%
8 1630
 
6.2%
5 1260
 
4.8%
9 1234
 
4.7%

데이터기준일자
Categorical

Distinct43
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2023-10-19
428 
2020-07-17
401 
2024-03-12
246 
2024-02-22
189 
2023-10-06
109 
Other values (38)
803 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st row2024-03-12
2nd row2024-03-12
3rd row2024-03-12
4th row2024-03-12
5th row2024-03-12

Common Values

ValueCountFrequency (%)
2023-10-19 428
19.7%
2020-07-17 401
18.4%
2024-03-12 246
11.3%
2024-02-22 189
8.7%
2023-10-06 109
 
5.0%
2024-03-19 91
 
4.2%
2023-07-04 77
 
3.5%
2024-01-02 75
 
3.4%
2024-02-15 68
 
3.1%
2023-05-26 62
 
2.8%
Other values (33) 430
19.8%

Length

2024-05-11T16:51:42.828769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-10-19 428
19.7%
2020-07-17 401
18.4%
2024-03-12 246
11.3%
2024-02-22 189
8.7%
2023-10-06 109
 
5.0%
2024-03-19 91
 
4.2%
2023-07-04 77
 
3.5%
2024-01-02 75
 
3.4%
2024-02-15 68
 
3.1%
2023-05-26 62
 
2.8%
Other values (33) 430
19.8%

제공기관코드
Real number (ℝ)

Distinct54
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4221439.3
Minimum3000000
Maximum6510000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2024-05-11T16:51:43.047879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3520000
Q13660000
median3910000
Q34720000
95-th percentile5710000
Maximum6510000
Range3510000
Interquartile range (IQR)1060000

Descriptive statistics

Standard deviation806799.4
Coefficient of variation (CV)0.1911195
Kurtosis-0.47323548
Mean4221439.3
Median Absolute Deviation (MAD)250000
Skewness0.97901014
Sum9.185852 × 109
Variance6.5092527 × 1011
MonotonicityNot monotonic
2024-05-11T16:51:43.332759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3780000 418
19.2%
5710000 401
18.4%
3910000 246
11.3%
3660000 189
8.7%
3530000 106
 
4.9%
4000000 91
 
4.2%
3640000 73
 
3.4%
4450000 62
 
2.8%
4721000 62
 
2.8%
4720000 62
 
2.8%
Other values (44) 466
21.4%
ValueCountFrequency (%)
3000000 11
0.5%
3010000 11
0.5%
3020000 4
 
0.2%
3030000 2
 
0.1%
3080000 3
 
0.1%
3100000 4
 
0.2%
3120000 1
 
< 0.1%
3130000 2
 
0.1%
3140000 5
0.2%
3150000 5
0.2%
ValueCountFrequency (%)
6510000 2
 
0.1%
5710000 401
18.4%
5590000 10
 
0.5%
5150000 3
 
0.1%
5120000 22
 
1.0%
4960000 5
 
0.2%
4950000 10
 
0.5%
4870000 1
 
< 0.1%
4810000 6
 
0.3%
4721000 62
 
2.8%

제공기관명
Text

Distinct54
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-05-11T16:51:43.646390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.8639706
Min length7

Characters and Unicode

Total characters17112
Distinct characters71
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.3%

Sample

1st row경기도 평택시
2nd row경기도 평택시
3rd row경기도 평택시
4th row경기도 평택시
5th row경기도 평택시
ValueCountFrequency (%)
경기도 848
19.5%
충청북도 505
11.6%
성남시 418
9.6%
청주시 401
9.2%
대전광역시 369
 
8.5%
평택시 246
 
5.7%
서구 189
 
4.3%
인천광역시 170
 
3.9%
완주군 124
 
2.8%
남동구 106
 
2.4%
Other values (54) 976
22.4%
2024-05-11T16:51:44.270304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2176
 
12.7%
시 1963
 
11.5%
도 1526
 
8.9%
청 906
 
5.3%
경 895
 
5.2%
기 848
 
5.0%
북 669
 
3.9%
구 660
 
3.9%
남 604
 
3.5%
주 601
 
3.5%
Other values (61) 6264
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14936
87.3%
Space Separator 2176
 
12.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1963
 
13.1%
도 1526
 
10.2%
청 906
 
6.1%
경 895
 
6.0%
기 848
 
5.7%
북 669
 
4.5%
구 660
 
4.4%
남 604
 
4.0%
주 601
 
4.0%
광 560
 
3.7%
Other values (60) 5704
38.2%
Space Separator
ValueCountFrequency (%)
2176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14936
87.3%
Common 2176
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1963
 
13.1%
도 1526
 
10.2%
청 906
 
6.1%
경 895
 
6.0%
기 848
 
5.7%
북 669
 
4.5%
구 660
 
4.4%
남 604
 
4.0%
주 601
 
4.0%
광 560
 
3.7%
Other values (60) 5704
38.2%
Common
ValueCountFrequency (%)
2176
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14936
87.3%
ASCII 2176
 
12.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2176
100.0%
Hangul
ValueCountFrequency (%)
시 1963
 
13.1%
도 1526
 
10.2%
청 906
 
6.1%
경 895
 
6.0%
기 848
 
5.7%
북 669
 
4.5%
구 660
 
4.4%
남 604
 
4.0%
주 601
 
4.0%
광 560
 
3.7%
Other values (60) 5704
38.2%

Sample

보행자전용도로명시도명시군구명법정동명지정일자운영방식구분평일운영시작시각평일운영종료시각주말운영시작시각주말운영종료시각보행자전용도로시작점위도보행자전용도로시작점경도보행자전용도로종료점위도보행자전용도로종료점경도자전거보행자겸용도로구분보행자전용도로폭보차분리여부지정목적관리점검일자관리점검결과유지보수내용영상정보기처리기기설치개수보안등설치개수횡단보도설치개수방호울타리설치개수차량진입억제용말뚝설치개수속도저감시설설치개수교통표지판설치개수이정표설치개수점자블럭설치개수관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
0합정동 소로 3-385경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.98696127.1119336.98706127.11216<NA>4.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
1합정동 소로 3-386경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.98951127.1150736.98957127.11529<NA>6.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
2합정동 소로 3-387경기도평택시합정동<NA>전일제00:0023:5900:0023:5936.99033127.1139136.99015127.11396<NA>6.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
3죽백동 소로 2-40경기도평택시죽백동<NA>전일제00:0023:5900:0023:5937.00088127.1128837.00111127.11322<NA>6.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
4죽백동 소로 2-41경기도평택시죽백동<NA>전일제00:0023:5900:0023:5936.99857127.1133136.99893127.11334<NA>8.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
5죽백동 소로 2-42경기도평택시죽백동<NA>전일제00:0023:5900:0023:5937.001836127.11412637.001297127.114735<NA>8.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
6죽백동 소로 2-43경기도평택시죽백동<NA>전일제00:0023:5900:0023:5937.002601127.11427137.002348127.114536<NA>8.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
7비전동 소로 3-13경기도평택시비전동<NA>전일제00:0023:5900:0023:5937.004556127.09491537.003356127.096095<NA>8.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
8비전동 소로 3-14경기도평택시비전동<NA>전일제00:0023:5900:0023:5937.002198127.09605837.002864127.096284<NA>6.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
9비전동 소로 3-15경기도평택시비전동<NA>전일제00:0023:5900:0023:5937.004793127.09874237.003411127.096799<NA>6.0N보행환경개선2023-02-28합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기도 평택시청031-8024-47772024-03-123910000경기도 평택시
보행자전용도로명시도명시군구명법정동명지정일자운영방식구분평일운영시작시각평일운영종료시각주말운영시작시각주말운영종료시각보행자전용도로시작점위도보행자전용도로시작점경도보행자전용도로종료점위도보행자전용도로종료점경도자전거보행자겸용도로구분보행자전용도로폭보차분리여부지정목적관리점검일자관리점검결과유지보수내용영상정보기처리기기설치개수보안등설치개수횡단보도설치개수방호울타리설치개수차량진입억제용말뚝설치개수속도저감시설설치개수교통표지판설치개수이정표설치개수점자블럭설치개수관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
2166둔산중로-7대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.359583127.3831836.359568127.386523<NA>5.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2167둔산중로-8대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.359579127.38656336.359456127.379942<NA>5.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2168둔산중로-9대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.357565127.37451436.357558127.376433<NA>5.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2169둔산중로-10대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.354372127.37675436.354369127.377063<NA>6.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2170둔산중로-11대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.354365127.37764836.354369127.377913<NA>6.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2171둔산중로-12대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.354424127.37809436.354362127.378445<NA>6.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2172둔산중로-13대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.354377127.37869436.354355127.37919<NA>6.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2173둔산중로-14대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.351754127.377636.35152127.378303<NA>5.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2174둔산중로-15대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.351418127.3777536.351248127.378103<NA>5.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구
2175둔산중로-16대전광역시서구둔산동1989-12-23전일제00:0023:5900:0023:5936.350963127.378636.350875127.378829<NA>6.0보행환경개선2023-09-12합격<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>대전광역시 서구청 건설과042-288-39252024-02-223660000대전광역시 서구