Overview

Dataset statistics

Number of variables7
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory61.3 B

Variable types

Text4
Categorical1
Numeric2

Dataset

Description현재 운영하고 있는 국가 비점오염물질 측정망의 측정소에 대한 데이터로서 측정소명, 상세 좌표, 주소 등을 제공합니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15070156/fileData.do

Alerts

측정소 번호 has unique valuesUnique
측정소 명 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
주소 has unique valuesUnique
상세주소 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:20:41.624407
Analysis finished2024-03-16 04:20:42.689356
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정소 번호
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-16T13:20:42.913399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.675
Min length7

Characters and Unicode

Total characters307
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

Unique40 ?
Unique (%)100.0%

Sample

1st row3301N10
2nd row30116045
3rd row22016044
4th row50036065
5th row20136051
ValueCountFrequency (%)
3301n10 1
 
2.5%
30116045 1
 
2.5%
33026042 1
 
2.5%
10016063 1
 
2.5%
2003n10 1
 
2.5%
10016043 1
 
2.5%
50026047 1
 
2.5%
1012n10 1
 
2.5%
2022n30 1
 
2.5%
330109nm10 1
 
2.5%
Other values (30) 30
75.0%
2024-03-16T13:20:43.338290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 99
32.2%
1 65
21.2%
2 30
 
9.8%
3 26
 
8.5%
6 26
 
8.5%
N 19
 
6.2%
4 15
 
4.9%
5 14
 
4.6%
9 6
 
2.0%
8 3
 
1.0%
Other values (3) 4
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 286
93.2%
Uppercase Letter 21
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 99
34.6%
1 65
22.7%
2 30
 
10.5%
3 26
 
9.1%
6 26
 
9.1%
4 15
 
5.2%
5 14
 
4.9%
9 6
 
2.1%
8 3
 
1.0%
7 2
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
N 19
90.5%
S 1
 
4.8%
M 1
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 286
93.2%
Latin 21
 
6.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 99
34.6%
1 65
22.7%
2 30
 
10.5%
3 26
 
9.1%
6 26
 
9.1%
4 15
 
5.2%
5 14
 
4.9%
9 6
 
2.1%
8 3
 
1.0%
7 2
 
0.7%
Latin
ValueCountFrequency (%)
N 19
90.5%
S 1
 
4.8%
M 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 99
32.2%
1 65
21.2%
2 30
 
9.8%
3 26
 
8.5%
6 26
 
8.5%
N 19
 
6.2%
4 15
 
4.9%
5 14
 
4.6%
9 6
 
2.0%
8 3
 
1.0%
Other values (3) 4
 
1.3%

측정소 명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-16T13:20:43.586766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.05
Min length3

Characters and Unicode

Total characters122
Distinct characters61
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st rowN가련
2nd rowN가산
3rd rowN내황
4th rowN대촌
5th rowN도진
ValueCountFrequency (%)
n가련 1
 
2.5%
n가산 1
 
2.5%
n팔왕 1
 
2.5%
n오장 1
 
2.5%
n옥수 1
 
2.5%
n용산 1
 
2.5%
n용진 1
 
2.5%
n자운 1
 
2.5%
n장유 1
 
2.5%
n전주천2 1
 
2.5%
Other values (30) 30
75.0%
2024-03-16T13:20:44.162448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 40
32.8%
천 4
 
3.3%
진 3
 
2.5%
동 3
 
2.5%
송 2
 
1.6%
화 2
 
1.6%
한 2
 
1.6%
용 2
 
1.6%
장 2
 
1.6%
오 2
 
1.6%
Other values (51) 60
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81
66.4%
Uppercase Letter 40
32.8%
Decimal Number 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 4
 
4.9%
진 3
 
3.7%
동 3
 
3.7%
송 2
 
2.5%
화 2
 
2.5%
한 2
 
2.5%
용 2
 
2.5%
장 2
 
2.5%
오 2
 
2.5%
가 2
 
2.5%
Other values (49) 57
70.4%
Uppercase Letter
ValueCountFrequency (%)
N 40
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81
66.4%
Latin 40
32.8%
Common 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 4
 
4.9%
진 3
 
3.7%
동 3
 
3.7%
송 2
 
2.5%
화 2
 
2.5%
한 2
 
2.5%
용 2
 
2.5%
장 2
 
2.5%
오 2
 
2.5%
가 2
 
2.5%
Other values (49) 57
70.4%
Latin
ValueCountFrequency (%)
N 40
100.0%
Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81
66.4%
ASCII 41
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 40
97.6%
2 1
 
2.4%
Hangul
ValueCountFrequency (%)
천 4
 
4.9%
진 3
 
3.7%
동 3
 
3.7%
송 2
 
2.5%
화 2
 
2.5%
한 2
 
2.5%
용 2
 
2.5%
장 2
 
2.5%
오 2
 
2.5%
가 2
 
2.5%
Other values (49) 57
70.4%

사용 여부
Categorical

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
Y
25 
D
13 
N
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowD
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
Y 25
62.5%
D 13
32.5%
N 2
 
5.0%

Length

2024-03-16T13:20:44.313600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:20:44.445032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 25
62.5%
d 13
32.5%
n 2
 
5.0%

위도
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.521478
Minimum35.052924
Maximum38.282397
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-03-16T13:20:44.626652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.052924
5-th percentile35.177478
Q135.715676
median36.483615
Q337.366406
95-th percentile38.116143
Maximum38.282397
Range3.2294726
Interquartile range (IQR)1.6507303

Descriptive statistics

Standard deviation0.98272443
Coefficient of variation (CV)0.026908123
Kurtosis-1.2864003
Mean36.521478
Median Absolute Deviation (MAD)0.8293422
Skewness0.11126678
Sum1460.8591
Variance0.96574731
MonotonicityNot monotonic
2024-03-16T13:20:44.776690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
35.8398343 1
 
2.5%
37.3377626 1
 
2.5%
36.5574731 1
 
2.5%
37.6531208 1
 
2.5%
35.2151986 1
 
2.5%
37.8309155 1
 
2.5%
35.1783606 1
 
2.5%
35.8829248 1
 
2.5%
35.7278751 1
 
2.5%
36.9764948 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
35.052924 1
2.5%
35.1607138 1
2.5%
35.1783606 1
2.5%
35.1985632 1
2.5%
35.2151986 1
2.5%
35.2883036 1
2.5%
35.380375 1
2.5%
35.4578783 1
2.5%
35.5504587 1
2.5%
35.6790782 1
2.5%
ValueCountFrequency (%)
38.2823966 1
2.5%
38.2638146 1
2.5%
38.1083709 1
2.5%
37.8309155 1
2.5%
37.6531208 1
2.5%
37.5316801 1
2.5%
37.4933315 1
2.5%
37.4637964 1
2.5%
37.4576434 1
2.5%
37.4523368 1
2.5%

경도
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.84919
Minimum126.74655
Maximum129.35076
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-03-16T13:20:44.938081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.74655
5-th percentile126.7866
Q1127.0317
median127.81711
Q3128.68483
95-th percentile129.01538
Maximum129.35076
Range2.604206
Interquartile range (IQR)1.6531245

Descriptive statistics

Standard deviation0.85759019
Coefficient of variation (CV)0.0067078266
Kurtosis-1.6801999
Mean127.84919
Median Absolute Deviation (MAD)0.81880475
Skewness0.10976141
Sum5113.9676
Variance0.73546094
MonotonicityNot monotonic
2024-03-16T13:20:45.066128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
127.1084889 1
 
2.5%
127.1119149 1
 
2.5%
128.6797872 1
 
2.5%
128.6999558 1
 
2.5%
126.746553 1
 
2.5%
128.4140355 1
 
2.5%
128.8644529 1
 
2.5%
127.0903797 1
 
2.5%
126.7872226 1
 
2.5%
127.03549 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
126.746553 1
2.5%
126.7747945 1
2.5%
126.7872226 1
2.5%
126.8193483 1
2.5%
126.8385878 1
2.5%
126.8489425 1
2.5%
126.8932829 1
2.5%
126.9976054 1
2.5%
126.9990041 1
2.5%
127.0203494 1
2.5%
ValueCountFrequency (%)
129.350759 1
2.5%
129.0458703 1
2.5%
129.013771 1
2.5%
128.8644529 1
2.5%
128.8621094 1
2.5%
128.848685 1
2.5%
128.8462083 1
2.5%
128.7957926 1
2.5%
128.7374502 1
2.5%
128.6999558 1
2.5%

주소
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-16T13:20:45.453463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length20
Min length15

Characters and Unicode

Total characters800
Distinct characters125
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

Unique40 ?
Unique (%)100.0%

Sample

1st row전라북도 전주시 완산구 여울로 161
2nd row충청북도 진천군 덕산읍 덕금로 300
3rd row울산광역시 중구 내황14길 94
4th row광주광역시 남구 도장길 51
5th row경상북도 고령군 우곡면 우곡로 928
ValueCountFrequency (%)
강원도 10
 
5.3%
경기도 7
 
3.7%
전라북도 6
 
3.2%
경상남도 5
 
2.7%
경상북도 4
 
2.1%
정선군 4
 
2.1%
서구 3
 
1.6%
임계면 3
 
1.6%
전주시 3
 
1.6%
광주광역시 3
 
1.6%
Other values (127) 140
74.5%
2024-03-16T13:20:45.922907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
 
18.5%
도 34
 
4.2%
로 32
 
4.0%
1 28
 
3.5%
시 24
 
3.0%
2 21
 
2.6%
면 18
 
2.2%
4 16
 
2.0%
경 16
 
2.0%
군 16
 
2.0%
Other values (115) 447
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 500
62.5%
Space Separator 148
 
18.5%
Decimal Number 139
 
17.4%
Dash Punctuation 13
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 34
 
6.8%
로 32
 
6.4%
시 24
 
4.8%
면 18
 
3.6%
경 16
 
3.2%
군 16
 
3.2%
광 13
 
2.6%
구 13
 
2.6%
북 13
 
2.6%
전 12
 
2.4%
Other values (103) 309
61.8%
Decimal Number
ValueCountFrequency (%)
1 28
20.1%
2 21
15.1%
4 16
11.5%
5 14
10.1%
0 13
9.4%
7 11
 
7.9%
3 11
 
7.9%
6 10
 
7.2%
9 8
 
5.8%
8 7
 
5.0%
Space Separator
ValueCountFrequency (%)
148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 500
62.5%
Common 300
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 34
 
6.8%
로 32
 
6.4%
시 24
 
4.8%
면 18
 
3.6%
경 16
 
3.2%
군 16
 
3.2%
광 13
 
2.6%
구 13
 
2.6%
북 13
 
2.6%
전 12
 
2.4%
Other values (103) 309
61.8%
Common
ValueCountFrequency (%)
148
49.3%
1 28
 
9.3%
2 21
 
7.0%
4 16
 
5.3%
5 14
 
4.7%
0 13
 
4.3%
- 13
 
4.3%
7 11
 
3.7%
3 11
 
3.7%
6 10
 
3.3%
Other values (2) 15
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 500
62.5%
ASCII 300
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
49.3%
1 28
 
9.3%
2 21
 
7.0%
4 16
 
5.3%
5 14
 
4.7%
0 13
 
4.3%
- 13
 
4.3%
7 11
 
3.7%
3 11
 
3.7%
6 10
 
3.3%
Other values (2) 15
 
5.0%
Hangul
ValueCountFrequency (%)
도 34
 
6.8%
로 32
 
6.4%
시 24
 
4.8%
면 18
 
3.6%
경 16
 
3.2%
군 16
 
3.2%
광 13
 
2.6%
구 13
 
2.6%
북 13
 
2.6%
전 12
 
2.4%
Other values (103) 309
61.8%

상세주소
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-16T13:20:46.229822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length17
Mean length16.05
Min length11

Characters and Unicode

Total characters642
Distinct characters127
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row전주시 덕진구 덕진동(가련교)
2nd row진천군 덕산읍 인산리(가산교)
3rd row울산시 중구 반구동(내황교)
4th row전남 나주시 남평읍 평산리 1354(대촌새마을교)
5th row고령군 우곡면 도진리(도진교)
ValueCountFrequency (%)
대전시 3
 
2.5%
서구 3
 
2.5%
임계면 3
 
2.5%
정선군 3
 
2.5%
전주시 2
 
1.7%
평택시 2
 
1.7%
양산시 2
 
1.7%
김해시 2
 
1.7%
화성시 2
 
1.7%
덕진구 2
 
1.7%
Other values (89) 94
79.7%
2024-03-16T13:20:46.661223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
 
12.3%
( 40
 
6.2%
교 40
 
6.2%
) 40
 
6.2%
동 28
 
4.4%
리 25
 
3.9%
시 23
 
3.6%
면 18
 
2.8%
산 16
 
2.5%
군 15
 
2.3%
Other values (117) 318
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 476
74.1%
Space Separator 79
 
12.3%
Open Punctuation 40
 
6.2%
Close Punctuation 40
 
6.2%
Decimal Number 7
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 40
 
8.4%
동 28
 
5.9%
리 25
 
5.3%
시 23
 
4.8%
면 18
 
3.8%
산 16
 
3.4%
군 15
 
3.2%
구 15
 
3.2%
대 12
 
2.5%
진 10
 
2.1%
Other values (109) 274
57.6%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
2 1
 
14.3%
3 1
 
14.3%
5 1
 
14.3%
4 1
 
14.3%
Space Separator
ValueCountFrequency (%)
79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 476
74.1%
Common 166
 
25.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 40
 
8.4%
동 28
 
5.9%
리 25
 
5.3%
시 23
 
4.8%
면 18
 
3.8%
산 16
 
3.4%
군 15
 
3.2%
구 15
 
3.2%
대 12
 
2.5%
진 10
 
2.1%
Other values (109) 274
57.6%
Common
ValueCountFrequency (%)
79
47.6%
( 40
24.1%
) 40
24.1%
1 3
 
1.8%
2 1
 
0.6%
3 1
 
0.6%
5 1
 
0.6%
4 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 476
74.1%
ASCII 166
 
25.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
47.6%
( 40
24.1%
) 40
24.1%
1 3
 
1.8%
2 1
 
0.6%
3 1
 
0.6%
5 1
 
0.6%
4 1
 
0.6%
Hangul
ValueCountFrequency (%)
교 40
 
8.4%
동 28
 
5.9%
리 25
 
5.3%
시 23
 
4.8%
면 18
 
3.8%
산 16
 
3.4%
군 15
 
3.2%
구 15
 
3.2%
대 12
 
2.5%
진 10
 
2.1%
Other values (109) 274
57.6%

Interactions

2024-03-16T13:20:42.216237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:20:42.041059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:20:42.356861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:20:42.126614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:20:47.064762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정소 번호측정소 명사용 여부위도경도주소상세주소
측정소 번호1.0001.0001.0001.0001.0001.0001.000
측정소 명1.0001.0001.0001.0001.0001.0001.000
사용 여부1.0001.0001.0000.6680.5141.0001.000
위도1.0001.0000.6681.0000.7551.0001.000
경도1.0001.0000.5140.7551.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.000
상세주소1.0001.0001.0001.0001.0001.0001.000
2024-03-16T13:20:47.165951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도사용 여부
위도1.0000.1130.341
경도0.1131.0000.347
사용 여부0.3410.3471.000

Missing values

2024-03-16T13:20:42.489474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:20:42.635632image/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

측정소 번호측정소 명사용 여부위도경도주소상세주소
03301N10N가련Y35.839834127.108489전라북도 전주시 완산구 여울로 161전주시 덕진구 덕진동(가련교)
130116045N가산D36.876303127.477517충청북도 진천군 덕산읍 덕금로 300진천군 덕산읍 인산리(가산교)
222016044N내황Y35.550459129.350759울산광역시 중구 내황14길 94울산시 중구 반구동(내황교)
350036065N대촌Y35.052924126.819348광주광역시 남구 도장길 51전남 나주시 남평읍 평산리 1354(대촌새마을교)
420136051N도진Y35.679078128.339271경상북도 고령군 우곡면 우곡로 928고령군 우곡면 도진리(도진교)
520116050N동암Y35.897758128.352537경상북도 성주군 선남면 명관로 458성주군 선남면 동암리(동암교)
611016053N동연Y37.053286126.997605경기도 평택시 고덕면 청원로 645-28평택시 고덕면 동청리(동연교)
733026041N동진D35.756959126.774794전라북도 부안군 동진면 고마제로 356-32부안군 동진면 동전리(동진대교)
833016040N만경D35.910239126.838588전라북도 김제시 청하면 강변로 173-7김제 청하면 동지산리(만경대교)
93009N30N만년Y36.350563127.350826대전광역시 서구 계룡로 200대전시 서구 월평동(만년교)
측정소 번호측정소 명사용 여부위도경도주소상세주소
301101N10N팽성Y36.976495127.03549경기도 평택시 팽성읍 팽성대교길 178평택시 팽성읍 원정리(팽성대교)
3111016056N하갈Y37.257351127.097229경기도 용인시 기흥구 덕영대로 1926-1용인시 기흥구 하갈동(하갈교)
323009N10N한밭Y36.357152127.401563대전광역시 서구 둔산북로 215대전시 서구 둔산동(한밭대교)
333009N20N한빛Y36.409757127.414465대전광역시 유성구 아리랑로21번길 647대전시 유성구 전민동(한빛대교)
341001N30N혈천D37.463796128.846208강원도 정선군 임계면 혈천윗길 3정선 임계면 낙천리(혈천교하류)
352022N20N호포Y35.288304129.013771경상남도 양산시 동면 호포로 69양산시 동면 가산리(호포대교)
3620226046N화목Y35.198563128.862109경상남도 김해시 화목로 74-20김해시 화목동(화목1교)
3720206064N화영Y35.457878128.461258경상남도 창녕군 장마면 영산장마로 112창녕군 장마면 산지리(화영교)
381101N20N황계Y37.224179127.020349경기도 화성시 황계길 150화성시 황계동(황계교)
392022N10N효충Y35.380375129.04587경상남도 양산시 상북면 어곡터널로 190양산시 상북면 소토리(효충교)