Overview

Dataset statistics

Number of variables15
Number of observations419
Missing cells446
Missing cells (%)7.1%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory50.9 KiB
Average record size in memory124.3 B

Variable types

Text6
Categorical7
Numeric2

Dataset

Description충처남도 무인교통단속카메라 정보로 시도명, 시군구명, 도로종류, 도로노선번호, 소재지, 설치 장소, 관리기관 명 등의 현황 데이터입니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=30&beforeMenuCd=DOM_000000201001001000&publicdatapk=15118678

Alerts

Dataset has 1 (0.2%) duplicate rowsDuplicates
관리기관전화번호 is highly overall correlated with 제한속도 and 6 other fieldsHigh correlation
시군구명 is highly overall correlated with 제한속도 and 5 other fieldsHigh correlation
도로노선방향 is highly overall correlated with 시도명 and 3 other fieldsHigh correlation
시도명 is highly overall correlated with 제한속도 and 4 other fieldsHigh correlation
관리기관명 is highly overall correlated with 제한속도 and 6 other fieldsHigh correlation
도로종류 is highly overall correlated with 제한속도 and 5 other fieldsHigh correlation
제한속도 is highly overall correlated with 시도명 and 4 other fieldsHigh correlation
단속구분 is highly overall correlated with 시군구명 and 3 other fieldsHigh correlation
시도명 is highly imbalanced (97.6%)Imbalance
도로노선번호 has 28 (6.7%) missing valuesMissing
소재지도로명주소 has 178 (42.5%) missing valuesMissing
소재지지번주소 has 101 (24.1%) missing valuesMissing
설치년도 has 139 (33.2%) missing valuesMissing
제한속도 has 228 (54.4%) zerosZeros

Reproduction

Analysis started2024-01-09 20:22:31.117754
Analysis finished2024-01-09 20:22:32.927540
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

무인교통단속카메라관리번호
Text

Distinct394
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-01-10T05:22:33.133437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.4224344
Min length1

Characters and Unicode

Total characters2691
Distinct characters149
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique383 ?
Unique (%)91.4%

Sample

1st row천안서북-F0074
2nd row천안서북-F0075
3rd row천안서북-F0076
4th row천안서북-F0071
5th row천안서북-F0072
ValueCountFrequency (%)
44825001 12
 
2.7%
앞 5
 
1.1%
1 3
 
0.7%
3 3
 
0.7%
4 3
 
0.7%
2 3
 
0.7%
사거리 3
 
0.7%
시내 2
 
0.5%
2
 
0.5%
청보초 2
 
0.5%
Other values (395) 405
91.4%
2024-01-10T05:22:33.534309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 357
 
13.3%
- 139
 
5.2%
1 131
 
4.9%
천 122
 
4.5%
서 118
 
4.4%
2 104
 
3.9%
F 100
 
3.7%
안 100
 
3.7%
4 86
 
3.2%
_ 82
 
3.0%
Other values (139) 1352
50.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1050
39.0%
Other Letter 1035
38.5%
Uppercase Letter 360
 
13.4%
Dash Punctuation 139
 
5.2%
Connector Punctuation 82
 
3.0%
Space Separator 24
 
0.9%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 122
 
11.8%
서 118
 
11.4%
안 100
 
9.7%
북 76
 
7.3%
스 40
 
3.9%
테 34
 
3.3%
시 34
 
3.3%
광 29
 
2.8%
동 29
 
2.8%
템 27
 
2.6%
Other values (116) 426
41.2%
Decimal Number
ValueCountFrequency (%)
0 357
34.0%
1 131
 
12.5%
2 104
 
9.9%
4 86
 
8.2%
3 78
 
7.4%
5 67
 
6.4%
6 62
 
5.9%
8 62
 
5.9%
7 60
 
5.7%
9 43
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
F 100
27.8%
A 66
18.3%
N 45
12.5%
E 38
 
10.6%
X 38
 
10.6%
P 38
 
10.6%
O 21
 
5.8%
D 7
 
1.9%
W 7
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 139
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 82
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1296
48.2%
Hangul 1035
38.5%
Latin 360
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 122
 
11.8%
서 118
 
11.4%
안 100
 
9.7%
북 76
 
7.3%
스 40
 
3.9%
테 34
 
3.3%
시 34
 
3.3%
광 29
 
2.8%
동 29
 
2.8%
템 27
 
2.6%
Other values (116) 426
41.2%
Common
ValueCountFrequency (%)
0 357
27.5%
- 139
 
10.7%
1 131
 
10.1%
2 104
 
8.0%
4 86
 
6.6%
_ 82
 
6.3%
3 78
 
6.0%
5 67
 
5.2%
6 62
 
4.8%
8 62
 
4.8%
Other values (4) 128
 
9.9%
Latin
ValueCountFrequency (%)
F 100
27.8%
A 66
18.3%
N 45
12.5%
E 38
 
10.6%
X 38
 
10.6%
P 38
 
10.6%
O 21
 
5.8%
D 7
 
1.9%
W 7
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1656
61.5%
Hangul 1035
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 357
21.6%
- 139
 
8.4%
1 131
 
7.9%
2 104
 
6.3%
F 100
 
6.0%
4 86
 
5.2%
_ 82
 
5.0%
3 78
 
4.7%
5 67
 
4.0%
A 66
 
4.0%
Other values (13) 446
26.9%
Hangul
ValueCountFrequency (%)
천 122
 
11.8%
서 118
 
11.4%
안 100
 
9.7%
북 76
 
7.3%
스 40
 
3.9%
테 34
 
3.3%
시 34
 
3.3%
광 29
 
2.8%
동 29
 
2.8%
템 27
 
2.6%
Other values (116) 426
41.2%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
충청남도
418 
전라북도
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 418
99.8%
전라북도 1
 
0.2%

Length

2024-01-10T05:22:33.664648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:22:33.758659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 418
99.8%
전라북도 1
 
0.2%

시군구명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
서산시
100 
아산시
100 
서북구
76 
보령시
57 
논산시
28 
Other values (5)
58 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서산시 100
23.9%
아산시 100
23.9%
서북구 76
18.1%
보령시 57
13.6%
논산시 28
 
6.7%
동남구 24
 
5.7%
태안군 12
 
2.9%
서천군 11
 
2.6%
예산군 7
 
1.7%
청양군 4
 
1.0%

Length

2024-01-10T05:22:33.868048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:22:34.039980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서산시 100
23.9%
아산시 100
23.9%
서북구 76
18.1%
보령시 57
13.6%
논산시 28
 
6.7%
동남구 24
 
5.7%
태안군 12
 
2.9%
서천군 11
 
2.6%
예산군 7
 
1.7%
청양군 4
 
1.0%

도로종류
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
일반국도
126 
5
111 
시도
56 
기타
51 
2
32 
Other values (5)
43 

Length

Max length4
Median length3
Mean length2.2529833
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
일반국도 126
30.1%
5 111
26.5%
시도 56
13.4%
기타 51
12.2%
2 32
 
7.6%
지방도 14
 
3.3%
군도 12
 
2.9%
4 10
 
2.4%
6 6
 
1.4%
1 1
 
0.2%

Length

2024-01-10T05:22:34.213218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:22:34.340218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반국도 126
30.1%
5 111
26.5%
시도 56
13.4%
기타 51
12.2%
2 32
 
7.6%
지방도 14
 
3.3%
군도 12
 
2.9%
4 10
 
2.4%
6 6
 
1.4%
1 1
 
0.2%

도로노선번호
Text

MISSING 

Distinct177
Distinct (%)45.3%
Missing28
Missing (%)6.7%
Memory size3.4 KiB
2024-01-10T05:22:34.595505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length4.0997442
Min length1

Characters and Unicode

Total characters1603
Distinct characters42
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

Unique120 ?
Unique (%)30.7%

Sample

1st row광로3-2
2nd row광로3-1
3rd row중로1-131
4th row중로1-83
5th row중로2-7
ValueCountFrequency (%)
0 52
 
12.4%
29번 22
 
5.3%
국도 21
 
5.0%
해당없음 19
 
4.5%
29호선 12
 
2.9%
32번 10
 
2.4%
70번 8
 
1.9%
70호 7
 
1.7%
국지도 7
 
1.7%
2-101 6
 
1.4%
Other values (168) 255
60.9%
2024-01-10T05:22:34.973908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 168
 
10.5%
2 165
 
10.3%
번 140
 
8.7%
- 129
 
8.0%
로 128
 
8.0%
3 107
 
6.7%
0 103
 
6.4%
9 63
 
3.9%
중 58
 
3.6%
7 52
 
3.2%
Other values (32) 490
30.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 799
49.8%
Other Letter 647
40.4%
Dash Punctuation 129
 
8.0%
Space Separator 28
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 140
21.6%
로 128
19.8%
중 58
9.0%
도 45
 
7.0%
대 39
 
6.0%
호 35
 
5.4%
국 29
 
4.5%
선 23
 
3.6%
음 19
 
2.9%
해 19
 
2.9%
Other values (20) 112
17.3%
Decimal Number
ValueCountFrequency (%)
1 168
21.0%
2 165
20.7%
3 107
13.4%
0 103
12.9%
9 63
 
7.9%
7 52
 
6.5%
4 40
 
5.0%
5 38
 
4.8%
8 36
 
4.5%
6 27
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 956
59.6%
Hangul 647
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 140
21.6%
로 128
19.8%
중 58
9.0%
도 45
 
7.0%
대 39
 
6.0%
호 35
 
5.4%
국 29
 
4.5%
선 23
 
3.6%
음 19
 
2.9%
해 19
 
2.9%
Other values (20) 112
17.3%
Common
ValueCountFrequency (%)
1 168
17.6%
2 165
17.3%
- 129
13.5%
3 107
11.2%
0 103
10.8%
9 63
 
6.6%
7 52
 
5.4%
4 40
 
4.2%
5 38
 
4.0%
8 36
 
3.8%
Other values (2) 55
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 956
59.6%
Hangul 647
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 168
17.6%
2 165
17.3%
- 129
13.5%
3 107
11.2%
0 103
10.8%
9 63
 
6.6%
7 52
 
5.4%
4 40
 
4.2%
5 38
 
4.0%
8 36
 
3.8%
Other values (2) 55
 
5.8%
Hangul
ValueCountFrequency (%)
번 140
21.6%
로 128
19.8%
중 58
9.0%
도 45
 
7.0%
대 39
 
6.0%
호 35
 
5.4%
국 29
 
4.5%
선 23
 
3.6%
음 19
 
2.9%
해 19
 
2.9%
Other values (20) 112
17.3%

도로노선명
Text

Distinct157
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-01-10T05:22:35.258063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.5322196
Min length1

Characters and Unicode

Total characters1480
Distinct characters139
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

Unique86 ?
Unique (%)20.5%

Sample

1st row공원로
2nd row공원로
3rd row3공단6로
4th row한들3로
5th row성정공원5로
ValueCountFrequency (%)
무 38
 
8.5%
국도 22
 
4.9%
중앙로 15
 
3.4%
충의로 13
 
2.9%
29호선 12
 
2.7%
서해로 11
 
2.5%
시민로 11
 
2.5%
중로 10
 
2.2%
번영로 10
 
2.2%
계백로 9
 
2.0%
Other values (148) 296
66.2%
2024-01-10T05:22:35.639358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 311
 
21.0%
도 47
 
3.2%
무 40
 
2.7%
대 33
 
2.2%
2 31
 
2.1%
호 31
 
2.1%
중 30
 
2.0%
국 30
 
2.0%
정 30
 
2.0%
길 29
 
2.0%
Other values (129) 868
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1322
89.3%
Decimal Number 130
 
8.8%
Space Separator 28
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 311
23.5%
도 47
 
3.6%
무 40
 
3.0%
대 33
 
2.5%
호 31
 
2.3%
중 30
 
2.3%
국 30
 
2.3%
정 30
 
2.3%
길 29
 
2.2%
서 28
 
2.1%
Other values (118) 713
53.9%
Decimal Number
ValueCountFrequency (%)
2 31
23.8%
1 19
14.6%
3 18
13.8%
9 16
12.3%
7 9
 
6.9%
4 9
 
6.9%
6 8
 
6.2%
0 8
 
6.2%
8 7
 
5.4%
5 5
 
3.8%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1322
89.3%
Common 158
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 311
23.5%
도 47
 
3.6%
무 40
 
3.0%
대 33
 
2.5%
호 31
 
2.3%
중 30
 
2.3%
국 30
 
2.3%
정 30
 
2.3%
길 29
 
2.2%
서 28
 
2.1%
Other values (118) 713
53.9%
Common
ValueCountFrequency (%)
2 31
19.6%
28
17.7%
1 19
12.0%
3 18
11.4%
9 16
10.1%
7 9
 
5.7%
4 9
 
5.7%
6 8
 
5.1%
0 8
 
5.1%
8 7
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1322
89.3%
ASCII 158
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 311
23.5%
도 47
 
3.6%
무 40
 
3.0%
대 33
 
2.5%
호 31
 
2.3%
중 30
 
2.3%
국 30
 
2.3%
정 30
 
2.3%
길 29
 
2.2%
서 28
 
2.1%
Other values (118) 713
53.9%
ASCII
ValueCountFrequency (%)
2 31
19.6%
28
17.7%
1 19
12.0%
3 18
11.4%
9 16
10.1%
7 9
 
5.7%
4 9
 
5.7%
6 8
 
5.1%
0 8
 
5.1%
8 7
 
4.4%

도로노선방향
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
3
215 
<NA>
160 
2
24 
1
 
20

Length

Max length4
Median length1
Mean length2.1455847
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 215
51.3%
<NA> 160
38.2%
2 24
 
5.7%
1 20
 
4.8%

Length

2024-01-10T05:22:35.764261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:22:35.861871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 215
51.3%
na 160
38.2%
2 24
 
5.7%
1 20
 
4.8%

소재지도로명주소
Text

MISSING 

Distinct227
Distinct (%)94.2%
Missing178
Missing (%)42.5%
Memory size3.4 KiB
2024-01-10T05:22:36.118126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length19.410788
Min length14

Characters and Unicode

Total characters4678
Distinct characters135
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

Unique216 ?
Unique (%)89.6%

Sample

1st row충청남도 천안시 서북구 공원로 195
2nd row충청남도 천안시 서북구 공원로 195
3rd row충청남도 천안시 서북구 3공단6로 33
4th row충청남도 천안시 서북구 한들3로 76
5th row충청남도 천안시 서북구 성정공원5로 21
ValueCountFrequency (%)
충청남도 239
21.2%
아산시 100
 
8.9%
천안시 100
 
8.9%
서북구 74
 
6.6%
배방읍 31
 
2.7%
동남구 26
 
2.3%
보령시 18
 
1.6%
서천군 11
 
1.0%
서천읍 10
 
0.9%
번영로 9
 
0.8%
Other values (310) 511
45.3%
2024-01-10T05:22:36.561416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
888
19.0%
남 275
 
5.9%
청 255
 
5.5%
충 249
 
5.3%
도 241
 
5.2%
시 231
 
4.9%
로 209
 
4.5%
천 143
 
3.1%
1 139
 
3.0%
산 132
 
2.8%
Other values (125) 1916
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3044
65.1%
Space Separator 888
 
19.0%
Decimal Number 715
 
15.3%
Dash Punctuation 31
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 275
 
9.0%
청 255
 
8.4%
충 249
 
8.2%
도 241
 
7.9%
시 231
 
7.6%
로 209
 
6.9%
천 143
 
4.7%
산 132
 
4.3%
서 114
 
3.7%
아 105
 
3.4%
Other values (113) 1090
35.8%
Decimal Number
ValueCountFrequency (%)
1 139
19.4%
2 125
17.5%
3 82
11.5%
4 71
9.9%
5 68
9.5%
8 53
 
7.4%
7 51
 
7.1%
6 46
 
6.4%
9 40
 
5.6%
0 40
 
5.6%
Space Separator
ValueCountFrequency (%)
888
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3044
65.1%
Common 1634
34.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 275
 
9.0%
청 255
 
8.4%
충 249
 
8.2%
도 241
 
7.9%
시 231
 
7.6%
로 209
 
6.9%
천 143
 
4.7%
산 132
 
4.3%
서 114
 
3.7%
아 105
 
3.4%
Other values (113) 1090
35.8%
Common
ValueCountFrequency (%)
888
54.3%
1 139
 
8.5%
2 125
 
7.6%
3 82
 
5.0%
4 71
 
4.3%
5 68
 
4.2%
8 53
 
3.2%
7 51
 
3.1%
6 46
 
2.8%
9 40
 
2.4%
Other values (2) 71
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3044
65.1%
ASCII 1634
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
888
54.3%
1 139
 
8.5%
2 125
 
7.6%
3 82
 
5.0%
4 71
 
4.3%
5 68
 
4.2%
8 53
 
3.2%
7 51
 
3.1%
6 46
 
2.8%
9 40
 
2.4%
Other values (2) 71
 
4.3%
Hangul
ValueCountFrequency (%)
남 275
 
9.0%
청 255
 
8.4%
충 249
 
8.2%
도 241
 
7.9%
시 231
 
7.6%
로 209
 
6.9%
천 143
 
4.7%
산 132
 
4.3%
서 114
 
3.7%
아 105
 
3.4%
Other values (113) 1090
35.8%

소재지지번주소
Text

MISSING 

Distinct289
Distinct (%)90.9%
Missing101
Missing (%)24.1%
Memory size3.4 KiB
2024-01-10T05:22:36.923631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length20.63522
Min length15

Characters and Unicode

Total characters6562
Distinct characters135
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

Unique262 ?
Unique (%)82.4%

Sample

1st row충청남도 천안시 서북구 불당동 1292
2nd row충청남도 천안시 서북구 불당동 1292
3rd row충청남도 천안시 서북구 차암동 448
4th row충청남도 천안시 서북구 백석동 35-27
5th row충청남도 천안시 서북구 성정동 1499
ValueCountFrequency (%)
충청남도 318
20.9%
천안시 100
 
6.6%
서산시 99
 
6.5%
서북구 74
 
4.9%
보령시 57
 
3.7%
논산시 28
 
1.8%
동남구 26
 
1.7%
두정동 18
 
1.2%
성연면 16
 
1.1%
성정동 15
 
1.0%
Other values (431) 770
50.6%
2024-01-10T05:22:37.409189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1203
18.3%
남 363
 
5.5%
청 340
 
5.2%
충 318
 
4.8%
도 318
 
4.8%
시 284
 
4.3%
동 221
 
3.4%
1 220
 
3.4%
산 199
 
3.0%
- 197
 
3.0%
Other values (125) 2899
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3926
59.8%
Decimal Number 1236
 
18.8%
Space Separator 1203
 
18.3%
Dash Punctuation 197
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 363
 
9.2%
청 340
 
8.7%
충 318
 
8.1%
도 318
 
8.1%
시 284
 
7.2%
동 221
 
5.6%
산 199
 
5.1%
서 196
 
5.0%
천 160
 
4.1%
리 145
 
3.7%
Other values (113) 1382
35.2%
Decimal Number
ValueCountFrequency (%)
1 220
17.8%
3 150
12.1%
2 142
11.5%
4 125
10.1%
6 113
9.1%
5 111
9.0%
8 108
8.7%
9 95
7.7%
7 95
7.7%
0 77
 
6.2%
Space Separator
ValueCountFrequency (%)
1203
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 197
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3926
59.8%
Common 2636
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 363
 
9.2%
청 340
 
8.7%
충 318
 
8.1%
도 318
 
8.1%
시 284
 
7.2%
동 221
 
5.6%
산 199
 
5.1%
서 196
 
5.0%
천 160
 
4.1%
리 145
 
3.7%
Other values (113) 1382
35.2%
Common
ValueCountFrequency (%)
1203
45.6%
1 220
 
8.3%
- 197
 
7.5%
3 150
 
5.7%
2 142
 
5.4%
4 125
 
4.7%
6 113
 
4.3%
5 111
 
4.2%
8 108
 
4.1%
9 95
 
3.6%
Other values (2) 172
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3926
59.8%
ASCII 2636
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1203
45.6%
1 220
 
8.3%
- 197
 
7.5%
3 150
 
5.7%
2 142
 
5.4%
4 125
 
4.7%
6 113
 
4.3%
5 111
 
4.2%
8 108
 
4.1%
9 95
 
3.6%
Other values (2) 172
 
6.5%
Hangul
ValueCountFrequency (%)
남 363
 
9.2%
청 340
 
8.7%
충 318
 
8.1%
도 318
 
8.1%
시 284
 
7.2%
동 221
 
5.6%
산 199
 
5.1%
서 196
 
5.0%
천 160
 
4.1%
리 145
 
3.7%
Other values (113) 1382
35.2%

설치장소
Text

Distinct392
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-01-10T05:22:37.623824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length13.577566
Min length3

Characters and Unicode

Total characters5689
Distinct characters329
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique379 ?
Unique (%)90.5%

Sample

1st row펜타포트101동주변
2nd row펜타포트103동주변
3rd row3공단6로부근
4th row한들3로주변
5th row성정공원5로주변
ValueCountFrequency (%)
앞 52
 
4.7%
서산 29
 
2.6%
충청남도 28
 
2.5%
충남 28
 
2.5%
서산시 28
 
2.5%
논산시 28
 
2.5%
입구 25
 
2.2%
사거리 24
 
2.1%
충의로 23
 
2.1%
서해로 16
 
1.4%
Other values (527) 836
74.8%
2024-01-10T05:22:37.941244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
722
 
12.7%
로 203
 
3.6%
산 195
 
3.4%
리 155
 
2.7%
서 139
 
2.4%
동 111
 
2.0%
교 105
 
1.8%
거 101
 
1.8%
) 95
 
1.7%
( 94
 
1.7%
Other values (319) 3769
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4370
76.8%
Space Separator 722
 
12.7%
Decimal Number 275
 
4.8%
Close Punctuation 96
 
1.7%
Open Punctuation 95
 
1.7%
Math Symbol 56
 
1.0%
Dash Punctuation 49
 
0.9%
Uppercase Letter 17
 
0.3%
Other Punctuation 7
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 203
 
4.6%
산 195
 
4.5%
리 155
 
3.5%
서 139
 
3.2%
동 111
 
2.5%
교 105
 
2.4%
거 101
 
2.3%
사 90
 
2.1%
충 82
 
1.9%
성 79
 
1.8%
Other values (290) 3110
71.2%
Decimal Number
ValueCountFrequency (%)
1 54
19.6%
3 46
16.7%
4 37
13.5%
2 37
13.5%
6 25
9.1%
0 17
 
6.2%
8 17
 
6.2%
5 16
 
5.8%
7 14
 
5.1%
9 12
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
C 5
29.4%
I 4
23.5%
E 3
17.6%
A 2
 
11.8%
K 1
 
5.9%
P 1
 
5.9%
T 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
@ 4
57.1%
/ 2
28.6%
. 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 95
99.0%
】 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 94
98.9%
【 1
 
1.1%
Space Separator
ValueCountFrequency (%)
722
100.0%
Math Symbol
ValueCountFrequency (%)
→ 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4370
76.8%
Common 1301
 
22.9%
Latin 18
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 203
 
4.6%
산 195
 
4.5%
리 155
 
3.5%
서 139
 
3.2%
동 111
 
2.5%
교 105
 
2.4%
거 101
 
2.3%
사 90
 
2.1%
충 82
 
1.9%
성 79
 
1.8%
Other values (290) 3110
71.2%
Common
ValueCountFrequency (%)
722
55.5%
) 95
 
7.3%
( 94
 
7.2%
→ 56
 
4.3%
1 54
 
4.2%
- 49
 
3.8%
3 46
 
3.5%
4 37
 
2.8%
2 37
 
2.8%
6 25
 
1.9%
Other values (11) 86
 
6.6%
Latin
ValueCountFrequency (%)
C 5
27.8%
I 4
22.2%
E 3
16.7%
A 2
 
11.1%
m 1
 
5.6%
K 1
 
5.6%
P 1
 
5.6%
T 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4370
76.8%
ASCII 1261
 
22.2%
Arrows 56
 
1.0%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
722
57.3%
) 95
 
7.5%
( 94
 
7.5%
1 54
 
4.3%
- 49
 
3.9%
3 46
 
3.6%
4 37
 
2.9%
2 37
 
2.9%
6 25
 
2.0%
0 17
 
1.3%
Other values (16) 85
 
6.7%
Hangul
ValueCountFrequency (%)
로 203
 
4.6%
산 195
 
4.5%
리 155
 
3.5%
서 139
 
3.2%
동 111
 
2.5%
교 105
 
2.4%
거 101
 
2.3%
사 90
 
2.1%
충 82
 
1.9%
성 79
 
1.8%
Other values (290) 3110
71.2%
Arrows
ValueCountFrequency (%)
→ 56
100.0%
None
ValueCountFrequency (%)
】 1
50.0%
【 1
50.0%

단속구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
4
277 
99
53 
2
48 
1
41 

Length

Max length2
Median length1
Mean length1.1264916
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 277
66.1%
99 53
 
12.6%
2 48
 
11.5%
1 41
 
9.8%

Length

2024-01-10T05:22:38.051914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:22:38.154945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 277
66.1%
99 53
 
12.6%
2 48
 
11.5%
1 41
 
9.8%

제한속도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.923628
Minimum0
Maximum110
Zeros228
Zeros (%)54.4%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T05:22:38.236084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q360
95-th percentile80
Maximum110
Range110
Interquartile range (IQR)60

Descriptive statistics

Standard deviation32.631536
Coefficient of variation (CV)1.1685994
Kurtosis-1.4651334
Mean27.923628
Median Absolute Deviation (MAD)0
Skewness0.50027058
Sum11700
Variance1064.8171
MonotonicityNot monotonic
2024-01-10T05:22:38.334366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 228
54.4%
80 51
 
12.2%
70 39
 
9.3%
60 37
 
8.8%
50 27
 
6.4%
30 23
 
5.5%
40 13
 
3.1%
110 1
 
0.2%
ValueCountFrequency (%)
0 228
54.4%
30 23
 
5.5%
40 13
 
3.1%
50 27
 
6.4%
60 37
 
8.8%
70 39
 
9.3%
80 51
 
12.2%
110 1
 
0.2%
ValueCountFrequency (%)
110 1
 
0.2%
80 51
 
12.2%
70 39
 
9.3%
60 37
 
8.8%
50 27
 
6.4%
40 13
 
3.1%
30 23
 
5.5%
0 228
54.4%

설치년도
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)4.6%
Missing139
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean2015.6571
Minimum2006
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T05:22:38.441386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2011
Q12013
median2016
Q32019
95-th percentile2020
Maximum2020
Range14
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.1321467
Coefficient of variation (CV)0.0015539085
Kurtosis-0.34903259
Mean2015.6571
Median Absolute Deviation (MAD)3
Skewness-0.57020528
Sum564384
Variance9.8103431
MonotonicityNot monotonic
2024-01-10T05:22:38.554079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2019 63
15.0%
2017 32
 
7.6%
2016 29
 
6.9%
2015 27
 
6.4%
2014 23
 
5.5%
2013 22
 
5.3%
2012 20
 
4.8%
2011 19
 
4.5%
2018 17
 
4.1%
2020 15
 
3.6%
Other values (3) 13
 
3.1%
(Missing) 139
33.2%
ValueCountFrequency (%)
2006 3
 
0.7%
2009 7
 
1.7%
2010 3
 
0.7%
2011 19
4.5%
2012 20
4.8%
2013 22
5.3%
2014 23
5.5%
2015 27
6.4%
2016 29
6.9%
2017 32
7.6%
ValueCountFrequency (%)
2020 15
 
3.6%
2019 63
15.0%
2018 17
 
4.1%
2017 32
7.6%
2016 29
6.9%
2015 27
6.4%
2014 23
 
5.5%
2013 22
 
5.3%
2012 20
 
4.8%
2011 19
 
4.5%

관리기관명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
아산시청 교통행정과
100 
충남지방경찰청
99 
충청남도 천안시 서북구청
76 
충청남도 보령시청
57 
충청남도 논산시청
28 
Other values (6)
59 

Length

Max length13
Median length9
Mean length9.2386635
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row충청남도 천안시 서북구청
2nd row충청남도 천안시 서북구청
3rd row충청남도 천안시 서북구청
4th row충청남도 천안시 서북구청
5th row충청남도 천안시 서북구청

Common Values

ValueCountFrequency (%)
아산시청 교통행정과 100
23.9%
충남지방경찰청 99
23.6%
충청남도 천안시 서북구청 76
18.1%
충청남도 보령시청 57
13.6%
충청남도 논산시청 28
 
6.7%
충청남도 천안시 동남구청 24
 
5.7%
태안군 12
 
2.9%
서천군 11
 
2.6%
예산군 7
 
1.7%
청양군청 4
 
1.0%

Length

2024-01-10T05:22:38.659753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청남도 185
23.0%
아산시청 100
12.4%
교통행정과 100
12.4%
천안시 100
12.4%
충남지방경찰청 99
12.3%
서북구청 76
9.5%
보령시청 57
 
7.1%
논산시청 28
 
3.5%
동남구청 24
 
3.0%
태안군 12
 
1.5%
Other values (4) 23
 
2.9%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
041-540-2953
100 
041-521-6420
76 
041-336-2253
59 
041-336-2256
40 
041-930-3982
40 
Other values (8)
104 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row041-521-6420
2nd row041-521-6420
3rd row041-521-6420
4th row041-521-6420
5th row041-521-6420

Common Values

ValueCountFrequency (%)
041-540-2953 100
23.9%
041-521-6420 76
18.1%
041-336-2253 59
14.1%
041-336-2256 40
 
9.5%
041-930-3982 40
 
9.5%
041-746-6257 28
 
6.7%
041-521-4421 24
 
5.7%
041-930-3972 17
 
4.1%
041-670-2366 12
 
2.9%
041-950-4127 11
 
2.6%
Other values (3) 12
 
2.9%

Length

2024-01-10T05:22:38.750730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
041-540-2953 100
23.9%
041-521-6420 76
18.1%
041-336-2253 59
14.1%
041-336-2256 40
 
9.5%
041-930-3982 40
 
9.5%
041-746-6257 28
 
6.7%
041-521-4421 24
 
5.7%
041-930-3972 17
 
4.1%
041-670-2366 12
 
2.9%
041-950-4127 11
 
2.6%
Other values (3) 12
 
2.9%

Interactions

2024-01-10T05:22:32.309100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:22:32.175232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:22:32.375498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:22:32.236896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:22:38.818476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명도로종류도로노선방향단속구분제한속도설치년도관리기관명관리기관전화번호
시도명1.0000.0001.000NaN0.1851.0000.0001.0001.000
시군구명0.0001.0000.9700.9230.7630.7880.7591.0001.000
도로종류1.0000.9701.0000.6260.7150.8400.6840.9400.948
도로노선방향NaN0.9230.6261.0000.7730.4590.2420.9230.790
단속구분0.1850.7630.7150.7731.0000.8230.5950.7610.902
제한속도1.0000.7880.8400.4590.8231.0000.6350.8660.882
설치년도0.0000.7590.6840.2420.5950.6351.0000.7590.641
관리기관명1.0001.0000.9400.9230.7610.8660.7591.0001.000
관리기관전화번호1.0001.0000.9480.7900.9020.8820.6411.0001.000
2024-01-10T05:22:38.927703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관전화번호시군구명도로노선방향시도명관리기관명단속구분도로종류
관리기관전화번호1.0000.9960.6660.9870.9980.7730.800
시군구명0.9961.0000.6690.0000.9990.5710.699
도로노선방향0.6660.6691.0001.0000.6690.4330.493
시도명0.9870.0001.0001.0000.9890.1220.990
관리기관명0.9980.9990.6690.9891.0000.5760.774
단속구분0.7730.5710.4330.1220.5761.0000.515
도로종류0.8000.6990.4930.9900.7740.5151.000
2024-01-10T05:22:39.022956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제한속도설치년도시도명시군구명도로종류도로노선방향단속구분관리기관명관리기관전화번호
제한속도1.0000.4540.9930.5310.6090.3450.4890.6520.662
설치년도0.4541.0000.0000.3450.2870.1550.4560.3450.355
시도명0.9930.0001.0000.0000.9901.0000.1220.9890.987
시군구명0.5310.3450.0001.0000.6990.6690.5710.9990.996
도로종류0.6090.2870.9900.6991.0000.4930.5150.7740.800
도로노선방향0.3450.1551.0000.6690.4931.0000.4330.6690.666
단속구분0.4890.4560.1220.5710.5150.4331.0000.5760.773
관리기관명0.6520.3450.9890.9990.7740.6690.5761.0000.998
관리기관전화번호0.6620.3550.9870.9960.8000.6660.7730.9981.000

Missing values

2024-01-10T05:22:32.479992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:22:32.683026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-10T05:22:32.840749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

무인교통단속카메라관리번호시도명시군구명도로종류도로노선번호도로노선명도로노선방향소재지도로명주소소재지지번주소설치장소단속구분제한속도설치년도관리기관명관리기관전화번호
0천안서북-F0074충청남도서북구5광로3-2공원로3충청남도 천안시 서북구 공원로 195충청남도 천안시 서북구 불당동 1292펜타포트101동주변402019충청남도 천안시 서북구청041-521-6420
1천안서북-F0075충청남도서북구5광로3-1공원로3충청남도 천안시 서북구 공원로 195충청남도 천안시 서북구 불당동 1292펜타포트103동주변402015충청남도 천안시 서북구청041-521-6420
2천안서북-F0076충청남도서북구5중로1-1313공단6로3충청남도 천안시 서북구 3공단6로 33충청남도 천안시 서북구 차암동 4483공단6로부근402015충청남도 천안시 서북구청041-521-6420
3천안서북-F0071충청남도서북구5중로1-83한들3로3충청남도 천안시 서북구 한들3로 76충청남도 천안시 서북구 백석동 35-27한들3로주변402014충청남도 천안시 서북구청041-521-6420
4천안서북-F0072충청남도서북구5중로2-7성정공원5로3충청남도 천안시 서북구 성정공원5로 21충청남도 천안시 서북구 성정동 1499성정공원5로주변402014충청남도 천안시 서북구청041-521-6420
5천안서북-F0073충청남도서북구5중로1-31불당11로3충청남도 천안시 서북구 불당11로 101충청남도 천안시 서북구 불당동 802봉서산로주변402014충청남도 천안시 서북구청041-521-6420
6천안서북-F0047충청남도서북구5광로3-3공원로3충청남도 천안시 서북구 공원로 227충청남도 천안시 서북구 불당동 1299갤러리아 삼거리402017충청남도 천안시 서북구청041-521-6420
7천안서북-F0048충청남도서북구5대로3-11두정상가7길3충청남도 천안시 서북구 두정상가7길 32충청남도 천안시 서북구 두정동 1393한국 마사회402017충청남도 천안시 서북구청041-521-6420
8천안서북-F0049충청남도서북구5대로2-3광장로3충청남도 천안시 서북구 광장로 231충청남도 천안시 서북구 불당동 1421불당14로상공회의소402017충청남도 천안시 서북구청041-521-6420
9천안서북-F0050충청남도서북구5소로2-749불당4로3충청남도 천안시 서북구 불당4로 39-21충청남도 천안시 서북구 불당동 860불당초등학교402011충청남도 천안시 서북구청041-521-6420
무인교통단속카메라관리번호시도명시군구명도로종류도로노선번호도로노선명도로노선방향소재지도로명주소소재지지번주소설치장소단속구분제한속도설치년도관리기관명관리기관전화번호
409NEXPA_01충청남도아산시일반국도48번실옥로<NA>충청남도 아산시 실옥로 48<NA>천도초등학교주변402006아산시청 교통행정과041-540-2953
410NEXPA_02충청남도아산시일반국도374번시민로<NA>충청남도 아산시 시민로 374<NA>온양관광호텔 사거리402006아산시청 교통행정과041-540-2953
411NEXPA_03충청남도아산시일반국도1627번온천대로<NA>충청남도 아산시 온천대로 1627<NA>동신초등학교주변402006아산시청 교통행정과041-540-2953
4121충청남도예산군기타609호읍내리3충청남도 예산군 덕산면 읍내길 12-4충청남도 예산군 덕산면 읍내리 344덕산초등학교주변402010예산군041-339-7699
4132충청남도예산군기타중로1-2호주교리3충청남도 예산군 예산읍 예산로 23충청남도 예산군 예산읍 주교리 278-17주교사거리주변402012예산군041-339-7699
4143충청남도예산군기타대로1-2호산성리3충청남도 예산군 예산읍 금오대로 45충청남도 예산군 예산읍 산성리 882시외버스터미널주변402013예산군041-339-7699
4154충청남도예산군기타중로3-2호예산리3충청남도 예산군 예산읍 예산로 223충청남도 예산군 예산읍 예산리 516-8삼선당약국주변402014예산군041-339-7699
4165충청남도예산군기타중로3-2호예산리3충청남도 예산군 예산읍 임성로 7-2충청남도 예산군 예산읍 예산리 494-3광덕주단주변402014예산군041-339-7699
4176충청남도예산군기타중로1-18호군청로예산리3충청남도 예산군 예산읍 예산로 189충청남도 예산군 예산읍 예산리 786군청사주변402019예산군041-339-7699
4187충청남도예산군기타1호산성리3충청남도 예산군 예산읍 역전로 150-3충청남도 예산군 예산읍 산성리 709-5서오아파트주변402019예산군041-339-7699

Duplicate rows

Most frequently occurring

무인교통단속카메라관리번호시도명시군구명도로종류도로노선번호도로노선명도로노선방향소재지도로명주소소재지지번주소설치장소단속구분제한속도설치년도관리기관명관리기관전화번호# duplicates
044825001충청남도태안군군도동백로동백로3<NA>충청남도 태안군 태안읍 동문리 903동백로430<NA>태안군041-670-23662