Overview

Dataset statistics

Number of variables18
Number of observations1497
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory220.9 KiB
Average record size in memory151.1 B

Variable types

Text5
Categorical9
Numeric4

Dataset

Description전라남도 지역 내 도로별 제한 속도를 단속하기 위한 무인 단속 카메라 설치 및 위치 정보 제공함으로써 국민들의 알 권리를 충족하고자 합니다.
Author경찰청 전라남도경찰청
URLhttps://www.data.go.kr/data/15127387/fileData.do

Alerts

관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
보호구역구분 is highly overall correlated with 시도명 and 1 other fieldsHigh correlation
시군구명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
도로노선방향 is highly overall correlated with 제한속도 and 2 other fieldsHigh correlation
시도명 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 시군구명High correlation
경도 is highly overall correlated with 시군구명High correlation
제한속도 is highly overall correlated with 설치연도 and 2 other fieldsHigh correlation
설치연도 is highly overall correlated with 제한속도High correlation
도로종류 is highly overall correlated with 제한속도 and 1 other fieldsHigh correlation
시도명 is highly imbalanced (98.5%)Imbalance
도로노선방향 is highly imbalanced (90.7%)Imbalance
무인교통단속카메라관리번호 has unique valuesUnique
설치장소 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:44:22.331991
Analysis finished2024-04-06 08:44:31.597094
Duration9.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

무인교통단속카메라관리번호
Text

UNIQUE 

Distinct1497
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2024-04-06T17:44:32.302900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters7485
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1497 ?
Unique (%)100.0%

Sample

1st rowF6228
2nd rowF6229
3rd rowF6392
4th rowF6393
5th rowF6395
ValueCountFrequency (%)
f6228 1
 
0.1%
h0549 1
 
0.1%
h0817 1
 
0.1%
h0613 1
 
0.1%
h0612 1
 
0.1%
h0611 1
 
0.1%
h0610 1
 
0.1%
h0609 1
 
0.1%
h0608 1
 
0.1%
h0607 1
 
0.1%
Other values (1487) 1487
99.3%
2024-04-06T17:44:33.538978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 717
9.6%
8 667
8.9%
7 661
8.8%
2 654
8.7%
4 651
8.7%
5 630
8.4%
6 612
8.2%
9 587
7.8%
H 549
7.3%
0 531
7.1%
Other values (3) 1226
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5988
80.0%
Uppercase Letter 1497
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 667
11.1%
7 661
11.0%
2 654
10.9%
4 651
10.9%
5 630
10.5%
6 612
10.2%
9 587
9.8%
0 531
8.9%
1 508
8.5%
3 487
8.1%
Uppercase Letter
ValueCountFrequency (%)
G 717
47.9%
H 549
36.7%
F 231
 
15.4%

Most occurring scripts

ValueCountFrequency (%)
Common 5988
80.0%
Latin 1497
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 667
11.1%
7 661
11.0%
2 654
10.9%
4 651
10.9%
5 630
10.5%
6 612
10.2%
9 587
9.8%
0 531
8.9%
1 508
8.5%
3 487
8.1%
Latin
ValueCountFrequency (%)
G 717
47.9%
H 549
36.7%
F 231
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G 717
9.6%
8 667
8.9%
7 661
8.8%
2 654
8.7%
4 651
8.7%
5 630
8.4%
6 612
8.2%
9 587
7.8%
H 549
7.3%
0 531
7.1%
Other values (3) 1226
16.4%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
전라남도
1495 
광주광역시
 
2

Length

Max length5
Median length4
Mean length4.001336
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광주광역시
2nd row광주광역시
3rd row전라남도
4th row전라남도
5th row전라남도

Common Values

ValueCountFrequency (%)
전라남도 1495
99.9%
광주광역시 2
 
0.1%

Length

2024-04-06T17:44:34.122355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:34.501278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 1495
99.9%
광주광역시 2
 
0.1%

시군구명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
나주시
151 
여수시
145 
광양시
126 
순천시
109 
목포시
106 
Other values (26)
860 

Length

Max length3
Median length3
Mean length2.998664
Min length2

Unique

Unique9 ?
Unique (%)0.6%

Sample

1st row북구
2nd row북구
3rd row순천시
4th row순천시
5th row담양군

Common Values

ValueCountFrequency (%)
나주시 151
 
10.1%
여수시 145
 
9.7%
광양시 126
 
8.4%
순천시 109
 
7.3%
목포시 106
 
7.1%
해남군 94
 
6.3%
무안군 73
 
4.9%
고흥군 69
 
4.6%
영암군 67
 
4.5%
보성군 61
 
4.1%
Other values (21) 496
33.1%

Length

2024-04-06T17:44:34.917563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
나주시 151
 
10.1%
여수시 145
 
9.7%
광양시 126
 
8.4%
순천시 109
 
7.3%
목포시 106
 
7.1%
해남군 94
 
6.3%
무안군 73
 
4.9%
고흥군 69
 
4.6%
영암군 67
 
4.5%
보성군 61
 
4.1%
Other values (21) 496
33.1%

도로종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
일반국도
492 
시도
350 
지방도
331 
군도
286 
고속국도
 
38

Length

Max length4
Median length3
Mean length2.9291917
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반국도 492
32.9%
시도 350
23.4%
지방도 331
22.1%
군도 286
19.1%
고속국도 38
 
2.5%

Length

2024-04-06T17:44:35.362118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:35.712932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반국도 492
32.9%
시도 350
23.4%
지방도 331
22.1%
군도 286
19.1%
고속국도 38
 
2.5%

도로노선번호
Text

Distinct74
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2024-04-06T17:44:36.236108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.5183701
Min length2

Characters and Unicode

Total characters3770
Distinct characters16
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

Unique17 ?
Unique (%)1.1%

Sample

1st row25번
2nd row25번
3rd row25번
4th row10번
5th row25번
ValueCountFrequency (%)
0번 709
47.4%
2번 114
 
7.6%
13번 63
 
4.2%
77번 51
 
3.4%
1번 49
 
3.3%
23번 48
 
3.2%
15번 40
 
2.7%
18번 39
 
2.6%
17번 25
 
1.7%
22번 24
 
1.6%
Other values (64) 335
22.4%
2024-04-06T17:44:37.418097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
번 1492
39.6%
0 778
20.6%
2 306
 
8.1%
1 304
 
8.1%
8 213
 
5.6%
5 158
 
4.2%
3 153
 
4.1%
7 151
 
4.0%
6 73
 
1.9%
4 68
 
1.8%
Other values (6) 74
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2269
60.2%
Other Letter 1501
39.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 778
34.3%
2 306
 
13.5%
1 304
 
13.4%
8 213
 
9.4%
5 158
 
7.0%
3 153
 
6.7%
7 151
 
6.7%
6 73
 
3.2%
4 68
 
3.0%
9 65
 
2.9%
Other Letter
ValueCountFrequency (%)
번 1492
99.4%
반 2
 
0.1%
지 2
 
0.1%
방 2
 
0.1%
도 2
 
0.1%
버 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2269
60.2%
Hangul 1501
39.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 778
34.3%
2 306
 
13.5%
1 304
 
13.4%
8 213
 
9.4%
5 158
 
7.0%
3 153
 
6.7%
7 151
 
6.7%
6 73
 
3.2%
4 68
 
3.0%
9 65
 
2.9%
Hangul
ValueCountFrequency (%)
번 1492
99.4%
반 2
 
0.1%
지 2
 
0.1%
방 2
 
0.1%
도 2
 
0.1%
버 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2269
60.2%
Hangul 1501
39.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
번 1492
99.4%
반 2
 
0.1%
지 2
 
0.1%
방 2
 
0.1%
도 2
 
0.1%
버 1
 
0.1%
ASCII
ValueCountFrequency (%)
0 778
34.3%
2 306
 
13.5%
1 304
 
13.4%
8 213
 
9.4%
5 158
 
7.0%
3 153
 
6.7%
7 151
 
6.7%
6 73
 
3.2%
4 68
 
3.0%
9 65
 
2.9%

도로노선명
Text

Distinct549
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2024-04-06T17:44:38.318231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.6165665
Min length2

Characters and Unicode

Total characters5414
Distinct characters262
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

Unique280 ?
Unique (%)18.7%

Sample

1st row호남고속도로
2nd row호남고속도로
3rd row호남고속도로 상행로
4th row남해고속도로 상행로
5th row호남고속도로 상행로
ValueCountFrequency (%)
영산로 47
 
3.1%
녹색로 42
 
2.8%
예향로 31
 
2.0%
진도대로 25
 
1.6%
장흥대로 20
 
1.3%
우주항공로 18
 
1.2%
제철로 17
 
1.1%
관광레저로 15
 
1.0%
호남고속도로 14
 
0.9%
청자로 14
 
0.9%
Other values (537) 1275
84.0%
2024-04-06T17:44:39.685108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 1402
25.9%
대 153
 
2.8%
산 139
 
2.6%
길 118
 
2.2%
영 115
 
2.1%
도 90
 
1.7%
고 71
 
1.3%
남 69
 
1.3%
진 64
 
1.2%
광 62
 
1.1%
Other values (252) 3131
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5318
98.2%
Decimal Number 75
 
1.4%
Space Separator 21
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1402
26.4%
대 153
 
2.9%
산 139
 
2.6%
길 118
 
2.2%
영 115
 
2.2%
도 90
 
1.7%
고 71
 
1.3%
남 69
 
1.3%
진 64
 
1.2%
광 62
 
1.2%
Other values (245) 3035
57.1%
Decimal Number
ValueCountFrequency (%)
1 36
48.0%
2 22
29.3%
4 8
 
10.7%
5 4
 
5.3%
3 4
 
5.3%
0 1
 
1.3%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5318
98.2%
Common 96
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1402
26.4%
대 153
 
2.9%
산 139
 
2.6%
길 118
 
2.2%
영 115
 
2.2%
도 90
 
1.7%
고 71
 
1.3%
남 69
 
1.3%
진 64
 
1.2%
광 62
 
1.2%
Other values (245) 3035
57.1%
Common
ValueCountFrequency (%)
1 36
37.5%
2 22
22.9%
21
21.9%
4 8
 
8.3%
5 4
 
4.2%
3 4
 
4.2%
0 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5318
98.2%
ASCII 96
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 1402
26.4%
대 153
 
2.9%
산 139
 
2.6%
길 118
 
2.2%
영 115
 
2.2%
도 90
 
1.7%
고 71
 
1.3%
남 69
 
1.3%
진 64
 
1.2%
광 62
 
1.2%
Other values (245) 3035
57.1%
ASCII
ValueCountFrequency (%)
1 36
37.5%
2 22
22.9%
21
21.9%
4 8
 
8.3%
5 4
 
4.2%
3 4
 
4.2%
0 1
 
1.0%

도로노선방향
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
3
1470 
2
 
16
1
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 1470
98.2%
2 16
 
1.1%
1 11
 
0.7%

Length

2024-04-06T17:44:40.076246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:40.405409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1470
98.2%
2 16
 
1.1%
1 11
 
0.7%

소재지지번주소
Text

Distinct1296
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2024-04-06T17:44:41.179109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length20.764195
Min length12

Characters and Unicode

Total characters31084
Distinct characters233
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

Unique1114 ?
Unique (%)74.4%

Sample

1st row광주광역시 북구 오치동 478-6
2nd row광주광역시 북구 용봉동 산 129-7
3rd row전라남도 순천시 주암면 복다리 209
4th row전라남도 순천시 서면 구상리 132-2
5th row전라남도 담양군 무정면 오례리 75-3
ValueCountFrequency (%)
전라남도 1492
 
21.0%
나주시 153
 
2.2%
여수시 139
 
2.0%
광양시 129
 
1.8%
순천시 113
 
1.6%
해남군 95
 
1.3%
목포시 93
 
1.3%
무안군 71
 
1.0%
고흥군 69
 
1.0%
영암군 66
 
0.9%
Other values (2057) 4690
66.0%
2024-04-06T17:44:42.449592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5614
18.1%
남 1710
 
5.5%
도 1641
 
5.3%
전 1560
 
5.0%
라 1514
 
4.9%
1 1301
 
4.2%
- 1133
 
3.6%
리 1116
 
3.6%
군 908
 
2.9%
2 760
 
2.4%
Other values (223) 13827
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18360
59.1%
Decimal Number 5977
 
19.2%
Space Separator 5614
 
18.1%
Dash Punctuation 1133
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 1710
 
9.3%
도 1641
 
8.9%
전 1560
 
8.5%
라 1514
 
8.2%
리 1116
 
6.1%
군 908
 
4.9%
면 758
 
4.1%
시 636
 
3.5%
동 498
 
2.7%
읍 367
 
2.0%
Other values (211) 7652
41.7%
Decimal Number
ValueCountFrequency (%)
1 1301
21.8%
2 760
12.7%
3 621
10.4%
4 538
9.0%
5 512
 
8.6%
6 491
 
8.2%
7 472
 
7.9%
8 448
 
7.5%
9 424
 
7.1%
0 410
 
6.9%
Space Separator
ValueCountFrequency (%)
5614
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18360
59.1%
Common 12724
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 1710
 
9.3%
도 1641
 
8.9%
전 1560
 
8.5%
라 1514
 
8.2%
리 1116
 
6.1%
군 908
 
4.9%
면 758
 
4.1%
시 636
 
3.5%
동 498
 
2.7%
읍 367
 
2.0%
Other values (211) 7652
41.7%
Common
ValueCountFrequency (%)
5614
44.1%
1 1301
 
10.2%
- 1133
 
8.9%
2 760
 
6.0%
3 621
 
4.9%
4 538
 
4.2%
5 512
 
4.0%
6 491
 
3.9%
7 472
 
3.7%
8 448
 
3.5%
Other values (2) 834
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18360
59.1%
ASCII 12724
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5614
44.1%
1 1301
 
10.2%
- 1133
 
8.9%
2 760
 
6.0%
3 621
 
4.9%
4 538
 
4.2%
5 512
 
4.0%
6 491
 
3.9%
7 472
 
3.7%
8 448
 
3.5%
Other values (2) 834
 
6.6%
Hangul
ValueCountFrequency (%)
남 1710
 
9.3%
도 1641
 
8.9%
전 1560
 
8.5%
라 1514
 
8.2%
리 1116
 
6.1%
군 908
 
4.9%
면 758
 
4.1%
시 636
 
3.5%
동 498
 
2.7%
읍 367
 
2.0%
Other values (211) 7652
41.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1325
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.880929
Minimum34.29582
Maximum35.433015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:44:42.838049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.29582
5-th percentile34.458993
Q134.744451
median34.883475
Q335.020214
95-th percentile35.288106
Maximum35.433015
Range1.1371943
Interquartile range (IQR)0.275763

Descriptive statistics

Standard deviation0.2423647
Coefficient of variation (CV)0.0069483443
Kurtosis-0.39523946
Mean34.880929
Median Absolute Deviation (MAD)0.1382143
Skewness-0.047280649
Sum52216.751
Variance0.05874065
MonotonicityNot monotonic
2024-04-06T17:44:43.287674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.9271974 9
 
0.6%
34.933897 4
 
0.3%
35.02685004 4
 
0.3%
34.79171024 3
 
0.2%
34.74614007 3
 
0.2%
35.20460209 3
 
0.2%
34.5231696 3
 
0.2%
35.2671193 3
 
0.2%
34.78703984 3
 
0.2%
35.03461003 3
 
0.2%
Other values (1315) 1459
97.5%
ValueCountFrequency (%)
34.29582028 1
0.1%
34.311839 1
0.1%
34.3123686 1
0.1%
34.31451711 1
0.1%
34.318189 1
0.1%
34.321051 1
0.1%
34.324538 1
0.1%
34.32768178 1
0.1%
34.332433 1
0.1%
34.33705411 1
0.1%
ValueCountFrequency (%)
35.43301453 1
0.1%
35.43197832 1
0.1%
35.43196916 1
0.1%
35.41519532 1
0.1%
35.4149506 1
0.1%
35.41380282 1
0.1%
35.40755123 1
0.1%
35.40754182 1
0.1%
35.404099 1
0.1%
35.403901 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1324
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97965
Minimum125.93645
Maximum127.76727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:44:43.795443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125.93645
5-th percentile126.34877
Q1126.5515
median126.88116
Q3127.48216
95-th percentile127.70448
Maximum127.76727
Range1.830825
Interquartile range (IQR)0.9306518

Descriptive statistics

Standard deviation0.47526227
Coefficient of variation (CV)0.0037428223
Kurtosis-1.3529843
Mean126.97965
Median Absolute Deviation (MAD)0.4147229
Skewness0.20984729
Sum190088.54
Variance0.22587422
MonotonicityNot monotonic
2024-04-06T17:44:44.308364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.7044802 9
 
0.6%
126.6178401 4
 
0.3%
127.696491 4
 
0.3%
126.4304656 3
 
0.2%
126.3939666 3
 
0.2%
126.551484 3
 
0.2%
126.3791243 3
 
0.2%
126.3915809 3
 
0.2%
126.5610746 3
 
0.2%
126.4266222 3
 
0.2%
Other values (1314) 1459
97.5%
ValueCountFrequency (%)
125.936448 1
0.1%
126.0492423 1
0.1%
126.101643 1
0.1%
126.125331 1
0.1%
126.129347 1
0.1%
126.1522899 1
0.1%
126.1536472 1
0.1%
126.1667783 2
0.1%
126.1912626 1
0.1%
126.192509 1
0.1%
ValueCountFrequency (%)
127.767273 1
0.1%
127.7666646 1
0.1%
127.7661797 1
0.1%
127.7658036 1
0.1%
127.7648221 1
0.1%
127.7585785 1
0.1%
127.7569428 1
0.1%
127.7557931 1
0.1%
127.753572 1
0.1%
127.7533902 1
0.1%

설치장소
Text

UNIQUE 

Distinct1497
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2024-04-06T17:44:45.188247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39
Mean length32.082832
Min length13

Characters and Unicode

Total characters48028
Distinct characters493
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1497 ?
Unique (%)100.0%

Sample

1st row호남고속도로 상행 77.2km
2nd row호남고속도로 하행 77.3km
3rd row호남고속도로 상행 19.5km(순천→광주)
4th row남해고속도로 상행 7.9km(광양→순천)
5th row호남고속도로 상행 54.7K(순천→천안)
ValueCountFrequency (%)
나주시 150
 
2.1%
여수시 141
 
2.0%
광양시 120
 
1.7%
순천시 104
 
1.5%
해남군 95
 
1.3%
목포시 92
 
1.3%
무안군 73
 
1.0%
고흥군 69
 
1.0%
영암군 66
 
0.9%
보성군 59
 
0.8%
Other values (3615) 6172
86.4%
2024-04-06T17:44:46.516474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5651
 
11.8%
리 1534
 
3.2%
( 1494
 
3.1%
) 1490
 
3.1%
→ 1435
 
3.0%
1 1303
 
2.7%
- 1093
 
2.3%
교 1040
 
2.2%
면 1038
 
2.2%
군 967
 
2.0%
Other values (483) 30983
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30587
63.7%
Decimal Number 5962
 
12.4%
Space Separator 5651
 
11.8%
Open Punctuation 1494
 
3.1%
Close Punctuation 1490
 
3.1%
Math Symbol 1445
 
3.0%
Dash Punctuation 1093
 
2.3%
Uppercase Letter 200
 
0.4%
Other Punctuation 72
 
0.1%
Lowercase Letter 34
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1534
 
5.0%
교 1040
 
3.4%
면 1038
 
3.4%
군 967
 
3.2%
동 776
 
2.5%
시 754
 
2.5%
초 697
 
2.3%
학 615
 
2.0%
산 597
 
2.0%
등 514
 
1.7%
Other values (438) 22055
72.1%
Uppercase Letter
ValueCountFrequency (%)
C 68
34.0%
I 60
30.0%
K 23
 
11.5%
G 14
 
7.0%
T 9
 
4.5%
S 8
 
4.0%
L 5
 
2.5%
N 3
 
1.5%
P 2
 
1.0%
H 2
 
1.0%
Other values (6) 6
 
3.0%
Decimal Number
ValueCountFrequency (%)
1 1303
21.9%
2 784
13.1%
3 630
10.6%
4 527
8.8%
5 506
 
8.5%
6 480
 
8.1%
7 473
 
7.9%
8 444
 
7.4%
9 408
 
6.8%
0 407
 
6.8%
Lowercase Letter
ValueCountFrequency (%)
k 21
61.8%
c 4
 
11.8%
m 4
 
11.8%
i 3
 
8.8%
t 1
 
2.9%
j 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
@ 35
48.6%
. 31
43.1%
, 3
 
4.2%
＠ 2
 
2.8%
& 1
 
1.4%
Math Symbol
ValueCountFrequency (%)
→ 1435
99.3%
~ 5
 
0.3%
> 4
 
0.3%
↔ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5651
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1494
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1490
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1093
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30587
63.7%
Common 17207
35.8%
Latin 234
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1534
 
5.0%
교 1040
 
3.4%
면 1038
 
3.4%
군 967
 
3.2%
동 776
 
2.5%
시 754
 
2.5%
초 697
 
2.3%
학 615
 
2.0%
산 597
 
2.0%
등 514
 
1.7%
Other values (438) 22055
72.1%
Common
ValueCountFrequency (%)
5651
32.8%
( 1494
 
8.7%
) 1490
 
8.7%
→ 1435
 
8.3%
1 1303
 
7.6%
- 1093
 
6.4%
2 784
 
4.6%
3 630
 
3.7%
4 527
 
3.1%
5 506
 
2.9%
Other values (13) 2294
13.3%
Latin
ValueCountFrequency (%)
C 68
29.1%
I 60
25.6%
K 23
 
9.8%
k 21
 
9.0%
G 14
 
6.0%
T 9
 
3.8%
S 8
 
3.4%
L 5
 
2.1%
c 4
 
1.7%
m 4
 
1.7%
Other values (12) 18
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30586
63.7%
ASCII 16003
33.3%
Arrows 1436
 
3.0%
None 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5651
35.3%
( 1494
 
9.3%
) 1490
 
9.3%
1 1303
 
8.1%
- 1093
 
6.8%
2 784
 
4.9%
3 630
 
3.9%
4 527
 
3.3%
5 506
 
3.2%
6 480
 
3.0%
Other values (32) 2045
 
12.8%
Hangul
ValueCountFrequency (%)
리 1534
 
5.0%
교 1040
 
3.4%
면 1038
 
3.4%
군 967
 
3.2%
동 776
 
2.5%
시 754
 
2.5%
초 697
 
2.3%
학 615
 
2.0%
산 597
 
2.0%
등 514
 
1.7%
Other values (437) 22054
72.1%
Arrows
ValueCountFrequency (%)
→ 1435
99.9%
↔ 1
 
0.1%
None
ValueCountFrequency (%)
＠ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
100.0%

단속구분
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
1
930 
2
560 
3
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 930
62.1%
2 560
37.4%
3 7
 
0.5%

Length

2024-04-06T17:44:46.982378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:47.290746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 930
62.1%
2 560
37.4%
3 7
 
0.5%

제한속도
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.242485
Minimum0
Maximum110
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:44:47.592437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q130
median50
Q360
95-th percentile80
Maximum110
Range110
Interquartile range (IQR)30

Descriptive statistics

Standard deviation20.131403
Coefficient of variation (CV)0.39286547
Kurtosis-0.85155992
Mean51.242485
Median Absolute Deviation (MAD)20
Skewness0.39914328
Sum76710
Variance405.27338
MonotonicityNot monotonic
2024-04-06T17:44:47.933916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
30 594
39.7%
60 335
22.4%
80 190
 
12.7%
50 188
 
12.6%
70 131
 
8.8%
100 32
 
2.1%
40 12
 
0.8%
90 10
 
0.7%
110 4
 
0.3%
0 1
 
0.1%
ValueCountFrequency (%)
0 1
 
0.1%
30 594
39.7%
40 12
 
0.8%
50 188
 
12.6%
60 335
22.4%
70 131
 
8.8%
80 190
 
12.7%
90 10
 
0.7%
100 32
 
2.1%
110 4
 
0.3%
ValueCountFrequency (%)
110 4
 
0.3%
100 32
 
2.1%
90 10
 
0.7%
80 190
 
12.7%
70 131
 
8.8%
60 335
22.4%
50 188
 
12.6%
40 12
 
0.8%
30 594
39.7%
0 1
 
0.1%

보호구역구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
<NA>
933 
2
554 
1
 
10

Length

Max length4
Median length4
Mean length2.8697395
Min length1

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> 933
62.3%
2 554
37.0%
1 10
 
0.7%

Length

2024-04-06T17:44:48.360719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:48.718416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 933
62.3%
2 554
37.0%
1 10
 
0.7%

설치연도
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.9145
Minimum2011
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:44:49.013485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2015
Q12019
median2021
Q32022
95-th percentile2022
Maximum2023
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5156004
Coefficient of variation (CV)0.0012453995
Kurtosis1.5756405
Mean2019.9145
Median Absolute Deviation (MAD)1
Skewness-1.4307661
Sum3023812
Variance6.3282456
MonotonicityNot monotonic
2024-04-06T17:44:49.355061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2022 432
28.9%
2021 420
28.1%
2020 150
 
10.0%
2018 117
 
7.8%
2019 108
 
7.2%
2017 65
 
4.3%
2015 60
 
4.0%
2016 50
 
3.3%
2013 37
 
2.5%
2023 32
 
2.1%
Other values (3) 26
 
1.7%
ValueCountFrequency (%)
2011 16
 
1.1%
2012 4
 
0.3%
2013 37
 
2.5%
2014 6
 
0.4%
2015 60
 
4.0%
2016 50
 
3.3%
2017 65
4.3%
2018 117
7.8%
2019 108
7.2%
2020 150
10.0%
ValueCountFrequency (%)
2023 32
 
2.1%
2022 432
28.9%
2021 420
28.1%
2020 150
 
10.0%
2019 108
 
7.2%
2018 117
 
7.8%
2017 65
 
4.3%
2016 50
 
3.3%
2015 60
 
4.0%
2014 6
 
0.4%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
전라남도경찰청
1497 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도경찰청 1497
100.0%

Length

2024-04-06T17:44:49.689847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:50.054517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도경찰청 1497
100.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
061-289-3293
1497 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row061-289-3293
2nd row061-289-3293
3rd row061-289-3293
4th row061-289-3293
5th row061-289-3293

Common Values

ValueCountFrequency (%)
061-289-3293 1497
100.0%

Length

2024-04-06T17:44:50.420075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:50.730220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
061-289-3293 1497
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-03-07
1497 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-07
2nd row2023-03-07
3rd row2023-03-07
4th row2023-03-07
5th row2023-03-07

Common Values

ValueCountFrequency (%)
2023-03-07 1497
100.0%

Length

2024-04-06T17:44:51.115608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:44:51.418722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-07 1497
100.0%

Interactions

2024-04-06T17:44:28.916510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:25.539861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:26.633340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:27.834209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:29.173642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:25.801147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:26.933047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:28.106884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:29.418925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:26.081676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:27.259097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:28.388341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:29.694860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:26.353033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:27.539224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:28.641069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:44:51.646802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명도로종류도로노선번호도로노선방향위도경도단속구분제한속도보호구역구분설치연도
시도명1.0001.0000.1810.3520.2610.1890.1080.0000.222NaNNaN
시군구명1.0001.0000.6860.8420.5280.9200.9570.4630.5260.1680.402
도로종류0.1810.6861.0000.8690.6310.5530.5810.2690.7790.1680.567
도로노선번호0.3520.8420.8691.0000.8400.6800.7120.2020.7480.0000.637
도로노선방향0.2610.5280.6310.8401.0000.2050.1690.0000.881NaN0.344
위도0.1890.9200.5530.6800.2051.0000.7260.3060.2460.0900.247
경도0.1080.9570.5810.7120.1690.7261.0000.3350.2550.2200.278
단속구분0.0000.4630.2690.2020.0000.3060.3351.0000.5830.0000.344
제한속도0.2220.5260.7790.7480.8810.2460.2550.5831.0000.6310.444
보호구역구분NaN0.1680.1680.000NaN0.0900.2200.0000.6311.0000.130
설치연도NaN0.4020.5670.6370.3440.2470.2780.3440.4440.1301.000
2024-04-06T17:44:52.063266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보호구역구분시군구명도로종류단속구분도로노선방향시도명
보호구역구분1.0000.1310.2050.0001.0001.000
시군구명0.1311.0000.4020.2630.3130.990
도로종류0.2050.4021.0000.2110.5920.221
단속구분0.0000.2630.2111.0000.0000.000
도로노선방향1.0000.3130.5920.0001.0000.424
시도명1.0000.9900.2210.0000.4241.000
2024-04-06T17:44:52.420473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도제한속도설치연도시도명시군구명도로종류도로노선방향단속구분보호구역구분
위도1.0000.1270.087-0.1020.1440.6390.2610.1240.1920.068
경도0.1271.0000.021-0.0550.0820.7560.2790.1020.2130.167
제한속도0.0870.0211.000-0.5110.2210.2240.5960.6070.3120.438
설치연도-0.102-0.055-0.5111.0000.3050.1680.2790.3180.2150.139
시도명0.1440.0820.2210.3051.0000.9900.2210.4240.0001.000
시군구명0.6390.7560.2240.1680.9901.0000.4020.3130.2630.131
도로종류0.2610.2790.5960.2790.2210.4021.0000.5920.2110.205
도로노선방향0.1240.1020.6070.3180.4240.3130.5921.0000.0001.000
단속구분0.1920.2130.3120.2150.0000.2630.2110.0001.0000.000
보호구역구분0.0680.1670.4380.1391.0000.1310.2051.0000.0001.000

Missing values

2024-04-06T17:44:30.656117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:44:31.337922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

무인교통단속카메라관리번호시도명시군구명도로종류도로노선번호도로노선명도로노선방향소재지지번주소위도경도설치장소단속구분제한속도보호구역구분설치연도관리기관명관리기관전화번호데이터기준일자
0F6228광주광역시북구고속국도25번호남고속도로1광주광역시 북구 오치동 478-635.184013126.899502호남고속도로 상행 77.2km1100<NA>2011전라남도경찰청061-289-32932023-03-07
1F6229광주광역시북구고속국도25번호남고속도로1광주광역시 북구 용봉동 산 129-735.184337126.896253호남고속도로 하행 77.3km1100<NA>2011전라남도경찰청061-289-32932023-03-07
2F6392전라남도순천시고속국도25번호남고속도로 상행로1전라남도 순천시 주암면 복다리 20935.052043127.282141호남고속도로 상행 19.5km(순천→광주)1100<NA>2011전라남도경찰청061-289-32932023-03-07
3F6393전라남도순천시고속국도10번남해고속도로 상행로1전라남도 순천시 서면 구상리 132-234.991239127.550383남해고속도로 상행 7.9km(광양→순천)1100<NA>2011전라남도경찰청061-289-32932023-03-07
4F6395전라남도담양군고속국도25번호남고속도로 상행로1전라남도 담양군 무정면 오례리 75-335.263085127.092448호남고속도로 상행 54.7K(순천→천안)1100<NA>2011전라남도경찰청061-289-32932023-03-07
5F6396전라남도광양시일반국도28번순광로3전라남도 광양시 광양읍 인서리 445-634.968559127.588556광양시 광양읍 인서리 268-4 전남도립미술관앞(순천→광양)160<NA>2011전라남도경찰청061-289-32932023-03-07
6F6397전라남도보성군일반국도29번화보로3전라남도 보성군 미력면 미력리 495-134.824159127.092077보성군 미력면 미력리 중촌마을앞(광주→보성)180<NA>2011전라남도경찰청061-289-32932023-03-07
7F6398전라남도광양시지방도0번항만로3전라남도 광양시 도이동 84234.915297127.674752광양시 도이동 황금물류센타앞(광양→여수)160<NA>2011전라남도경찰청061-289-32932023-03-07
8F6401전라남도함평군일반국도23번함영로3전라남도 함평군 학교면 사거리 1082-135.036957126.534369함평군 학교면 월산리 낙천동마을앞(학교→함평)180<NA>2011전라남도경찰청061-289-32932023-03-07
9F6402전라남도목포시지방도1번고하대로3전라남도 목포시 산정동 1801-1634.803641126.367254목포시 산정동 북항교차로 (영암 -> 목포)250<NA>2011전라남도경찰청061-289-32932023-03-07
무인교통단속카메라관리번호시도명시군구명도로종류도로노선번호도로노선명도로노선방향소재지지번주소위도경도설치장소단속구분제한속도보호구역구분설치연도관리기관명관리기관전화번호데이터기준일자
1487H7276전라남도장성군군도25번황토로3전라남도 장성군 남면 분향리 1038-1635.244806126.80043장성군 남면 분향리 1038-16 분향초등학교(분향초→장성읍)13022023전라남도경찰청061-289-32932023-03-07
1488H7277전라남도장성군군도24번사창로3전라남도 장성군 삼계면 사창리 244-235.259861126.666799장성군 삼계면 사창리 244-2 사창초등학교(사창시장→사창사거리)13022023전라남도경찰청061-289-32932023-03-07
1489H7278전라남도장성군지방도708번신흥로3전라남도 장성군 북일면 오산리 106-135.384694126.794852장성군 북일면 오산리 106-1 북일초등학교(고창→신흥리교차로)13022023전라남도경찰청061-289-32932023-03-07
1490H7279전라남도장성군지방도15번방자로3전라남도 장성군 북이면 신평리 16-535.431978126.804525장성군 북이면 신평리 16-5 북이초등학교(백양사TG→백암중)13022023전라남도경찰청061-289-32932023-03-07
1491H7280전라남도장성군군도15번백양로3전라남도 장성군 북하면 약수리 389-135.407551126.881399장성군 북하면 약수리 389-1 약수초등학교(약수초→백양사)13022023전라남도경찰청061-289-32932023-03-07
1492H7439전라남도완도군일반국도77번고금로3전라남도 완도군 고금면 청용리 1063-634.417348126.808943완도군 고금면 청용리 1063-6 청학리버스정류장(강진→고금)10<NA>2023전라남도경찰청061-289-32932023-03-07
1493H7440전라남도진도군일반국도18번거룡길3전라남도 진도군 의신면 거룡리 47-434.425605126.280357진도군 의신면 거룡리 47-4 거룡마을(돈지→금갑)150<NA>2023전라남도경찰청061-289-32932023-03-07
1494H7441전라남도진도군일반국도18번거룡길3전라남도 진도군 의신면 거룡리 47-434.425605126.280357진도군 의신면 거룡리 47-4 거룡마을(금갑→돈지)150<NA>2023전라남도경찰청061-289-32932023-03-07
1495H7442전라남도진도군일반국도18번진도대로3전라남도 진도군 의신면 송정리 448-134.411703126.272757진도군 의신면 송정리 448-1 송정마을(돈지→금갑)160<NA>2023전라남도경찰청061-289-32932023-03-07
1496H7443전라남도진도군일반국도18번진도대로3전라남도 진도군 의신면 송정리 448-134.411703126.272757진도군 의신면 송정리 448-1 송정마을(금갑→돈지)160<NA>2023전라남도경찰청061-289-32932023-03-07