Overview

Dataset statistics

Number of variables8
Number of observations576
Missing cells154
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.3 KiB
Average record size in memory66.2 B

Variable types

Categorical2
Text3
Numeric2
DateTime1

Dataset

Description충청남도 홍성군 버스정류소 현황 데이터로 구분(읍면), 번호표, 정류소명, 소재지지번주소, 위도, 경도, 기타사항, 데이터기준일자 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15114013/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
경도 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 경도High correlation
기타사항 is highly imbalanced (93.1%)Imbalance
번호표 has 42 (7.3%) missing valuesMissing
소재지지번주소 has 14 (2.4%) missing valuesMissing
위도 has 49 (8.5%) missing valuesMissing
경도 has 49 (8.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:27:18.897307
Analysis finished2023-12-12 09:27:20.231375
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
홍북읍
86 
홍성읍
67 
갈산면
56 
홍동면
53 
구항면
52 
Other values (6)
262 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
홍북읍 86
14.9%
홍성읍 67
11.6%
갈산면 56
9.7%
홍동면 53
9.2%
구항면 52
9.0%
서부면 52
9.0%
광천읍 51
8.9%
금마면 45
7.8%
장곡면 41
7.1%
결성면 37
6.4%

Length

2023-12-12T18:27:20.293821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
홍북읍 86
14.9%
홍성읍 67
11.6%
갈산면 56
9.7%
홍동면 53
9.2%
구항면 52
9.0%
서부면 52
9.0%
광천읍 51
8.9%
금마면 45
7.8%
장곡면 41
7.1%
결성면 37
6.4%

번호표
Text

MISSING 

Distinct534
Distinct (%)100.0%
Missing42
Missing (%)7.3%
Memory size4.6 KiB
2023-12-12T18:27:20.607587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2136
Distinct characters29
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

Unique534 ?
Unique (%)100.0%

Sample

1st row홍성01
2nd row홍성02
3rd row홍성03
4th row홍성04
5th row홍성05
ValueCountFrequency (%)
홍성17 1
 
0.2%
결성33 1
 
0.2%
결성28 1
 
0.2%
결성27 1
 
0.2%
결성26 1
 
0.2%
결성25 1
 
0.2%
결성24 1
 
0.2%
결성23 1
 
0.2%
결성22 1
 
0.2%
결성21 1
 
0.2%
Other values (524) 524
98.1%
2023-12-12T18:27:21.225765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
홍 199
 
9.3%
1 169
 
7.9%
2 168
 
7.9%
3 152
 
7.1%
0 148
 
6.9%
4 120
 
5.6%
성 102
 
4.8%
북 82
 
3.8%
5 77
 
3.6%
6 70
 
3.3%
Other values (19) 849
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1068
50.0%
Decimal Number 1068
50.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 199
18.6%
성 102
 
9.6%
북 82
 
7.7%
동 51
 
4.8%
서 50
 
4.7%
부 50
 
4.7%
구 49
 
4.6%
항 49
 
4.6%
천 47
 
4.4%
광 47
 
4.4%
Other values (9) 342
32.0%
Decimal Number
ValueCountFrequency (%)
1 169
15.8%
2 168
15.7%
3 152
14.2%
0 148
13.9%
4 120
11.2%
5 77
7.2%
6 70
6.6%
7 61
 
5.7%
8 53
 
5.0%
9 50
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1068
50.0%
Common 1068
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 199
18.6%
성 102
 
9.6%
북 82
 
7.7%
동 51
 
4.8%
서 50
 
4.7%
부 50
 
4.7%
구 49
 
4.6%
항 49
 
4.6%
천 47
 
4.4%
광 47
 
4.4%
Other values (9) 342
32.0%
Common
ValueCountFrequency (%)
1 169
15.8%
2 168
15.7%
3 152
14.2%
0 148
13.9%
4 120
11.2%
5 77
7.2%
6 70
6.6%
7 61
 
5.7%
8 53
 
5.0%
9 50
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1068
50.0%
ASCII 1068
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
홍 199
18.6%
성 102
 
9.6%
북 82
 
7.7%
동 51
 
4.8%
서 50
 
4.7%
부 50
 
4.7%
구 49
 
4.6%
항 49
 
4.6%
천 47
 
4.4%
광 47
 
4.4%
Other values (9) 342
32.0%
ASCII
ValueCountFrequency (%)
1 169
15.8%
2 168
15.7%
3 152
14.2%
0 148
13.9%
4 120
11.2%
5 77
7.2%
6 70
6.6%
7 61
 
5.7%
8 53
 
5.0%
9 50
 
4.7%

정류소명
Text

Distinct498
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T18:27:21.625445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length4.609375
Min length2

Characters and Unicode

Total characters2655
Distinct characters270
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

Unique430 ?
Unique (%)74.7%

Sample

1st row홍성역
2nd row홍성의료원
3rd row홍성의료원
4th row농협동부지소
5th row홍성전통시장
ValueCountFrequency (%)
신촌 5
 
0.9%
홍성전통시장 3
 
0.5%
홍성여고앞 3
 
0.5%
월계리 3
 
0.5%
하대 3
 
0.5%
백동 3
 
0.5%
황곡 3
 
0.5%
내포유치원 3
 
0.5%
공리 3
 
0.5%
벽계 2
 
0.3%
Other values (491) 550
94.7%
2023-12-12T18:27:22.287794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 192
 
7.2%
마 107
 
4.0%
을 98
 
3.7%
구 75
 
2.8%
동 59
 
2.2%
산 55
 
2.1%
회 47
 
1.8%
관 47
 
1.8%
성 43
 
1.6%
입 42
 
1.6%
Other values (260) 1890
71.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2569
96.8%
Decimal Number 46
 
1.7%
Uppercase Letter 20
 
0.8%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%
Space Separator 5
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 192
 
7.5%
마 107
 
4.2%
을 98
 
3.8%
구 75
 
2.9%
동 59
 
2.3%
산 55
 
2.1%
회 47
 
1.8%
관 47
 
1.8%
성 43
 
1.7%
입 42
 
1.6%
Other values (244) 1804
70.2%
Decimal Number
ValueCountFrequency (%)
1 22
47.8%
2 15
32.6%
3 5
 
10.9%
5 2
 
4.3%
9 1
 
2.2%
4 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
A 4
20.0%
T 4
20.0%
P 4
20.0%
H 3
15.0%
L 3
15.0%
S 2
10.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2569
96.8%
Common 66
 
2.5%
Latin 20
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 192
 
7.5%
마 107
 
4.2%
을 98
 
3.8%
구 75
 
2.9%
동 59
 
2.3%
산 55
 
2.1%
회 47
 
1.8%
관 47
 
1.8%
성 43
 
1.7%
입 42
 
1.6%
Other values (244) 1804
70.2%
Common
ValueCountFrequency (%)
1 22
33.3%
2 15
22.7%
( 6
 
9.1%
) 6
 
9.1%
3 5
 
7.6%
5
 
7.6%
, 3
 
4.5%
5 2
 
3.0%
9 1
 
1.5%
4 1
 
1.5%
Latin
ValueCountFrequency (%)
A 4
20.0%
T 4
20.0%
P 4
20.0%
H 3
15.0%
L 3
15.0%
S 2
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2569
96.8%
ASCII 86
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 192
 
7.5%
마 107
 
4.2%
을 98
 
3.8%
구 75
 
2.9%
동 59
 
2.3%
산 55
 
2.1%
회 47
 
1.8%
관 47
 
1.8%
성 43
 
1.7%
입 42
 
1.6%
Other values (244) 1804
70.2%
ASCII
ValueCountFrequency (%)
1 22
25.6%
2 15
17.4%
( 6
 
7.0%
) 6
 
7.0%
3 5
 
5.8%
5
 
5.8%
A 4
 
4.7%
T 4
 
4.7%
P 4
 
4.7%
H 3
 
3.5%
Other values (6) 12
14.0%

소재지지번주소
Text

MISSING 

Distinct543
Distinct (%)96.6%
Missing14
Missing (%)2.4%
Memory size4.6 KiB
2023-12-12T18:27:22.734450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length198
Median length22
Mean length24.487544
Min length18

Characters and Unicode

Total characters13762
Distinct characters128
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

Unique529 ?
Unique (%)94.1%

Sample

1st row충청남도 홍성군 홍성읍 고암리 450-6
2nd row충청남도 홍성군 홍성읍 고암리 572-2
3rd row충청남도 홍성군 홍성읍 고암리 1018
4th row충청남도 홍성군 홍성읍 의사로 48
5th row충청남도 홍성군 홍성읍 대교리 395-1
ValueCountFrequency (%)
충청남도 758
23.8%
홍성군 757
23.8%
홍북읍 73
 
2.3%
홍성읍 67
 
2.1%
갈산면 55
 
1.7%
홍동면 53
 
1.7%
서부면 52
 
1.6%
구항면 52
 
1.6%
금마면 45
 
1.4%
장곡면 41
 
1.3%
Other values (668) 1232
38.7%
2023-12-12T18:27:23.386451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2636
19.2%
홍 954
 
6.9%
성 883
 
6.4%
남 778
 
5.7%
도 762
 
5.5%
청 762
 
5.5%
충 758
 
5.5%
군 757
 
5.5%
리 547
 
4.0%
- 438
 
3.2%
Other values (118) 4487
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8595
62.5%
Space Separator 2636
 
19.2%
Decimal Number 2093
 
15.2%
Dash Punctuation 438
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 954
11.1%
성 883
10.3%
남 778
9.1%
도 762
8.9%
청 762
8.9%
충 758
8.8%
군 757
8.8%
리 547
 
6.4%
면 372
 
4.3%
읍 180
 
2.1%
Other values (106) 1842
21.4%
Decimal Number
ValueCountFrequency (%)
1 384
18.3%
2 295
14.1%
3 234
11.2%
4 219
10.5%
6 202
9.7%
5 183
8.7%
7 171
8.2%
8 158
7.5%
9 132
 
6.3%
0 115
 
5.5%
Space Separator
ValueCountFrequency (%)
2636
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 438
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8595
62.5%
Common 5167
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 954
11.1%
성 883
10.3%
남 778
9.1%
도 762
8.9%
청 762
8.9%
충 758
8.8%
군 757
8.8%
리 547
 
6.4%
면 372
 
4.3%
읍 180
 
2.1%
Other values (106) 1842
21.4%
Common
ValueCountFrequency (%)
2636
51.0%
- 438
 
8.5%
1 384
 
7.4%
2 295
 
5.7%
3 234
 
4.5%
4 219
 
4.2%
6 202
 
3.9%
5 183
 
3.5%
7 171
 
3.3%
8 158
 
3.1%
Other values (2) 247
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8595
62.5%
ASCII 5167
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2636
51.0%
- 438
 
8.5%
1 384
 
7.4%
2 295
 
5.7%
3 234
 
4.5%
4 219
 
4.2%
6 202
 
3.9%
5 183
 
3.5%
7 171
 
3.3%
8 158
 
3.1%
Other values (2) 247
 
4.8%
Hangul
ValueCountFrequency (%)
홍 954
11.1%
성 883
10.3%
남 778
9.1%
도 762
8.9%
청 762
8.9%
충 758
8.8%
군 757
8.8%
리 547
 
6.4%
면 372
 
4.3%
읍 180
 
2.1%
Other values (106) 1842
21.4%

위도
Real number (ℝ)

MISSING 

Distinct516
Distinct (%)97.9%
Missing49
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean36.577224
Minimum36.477098
Maximum36.669106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-12T18:27:23.633676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.477098
5-th percentile36.49992
Q136.543029
median36.581947
Q336.610204
95-th percentile36.652674
Maximum36.669106
Range0.19200784
Interquartile range (IQR)0.06717458

Descriptive statistics

Standard deviation0.045429288
Coefficient of variation (CV)0.0012420103
Kurtosis-0.77959582
Mean36.577224
Median Absolute Deviation (MAD)0.03491145
Skewness-0.10645287
Sum19276.197
Variance0.0020638202
MonotonicityNot monotonic
2023-12-12T18:27:23.864039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.6272692 2
 
0.3%
36.58472424 2
 
0.3%
36.584631 2
 
0.3%
36.64536283 2
 
0.3%
36.58736831 2
 
0.3%
36.59422638 2
 
0.3%
36.5946801 2
 
0.3%
36.65600101 2
 
0.3%
36.58920954 2
 
0.3%
36.61325611 2
 
0.3%
Other values (506) 507
88.0%
(Missing) 49
 
8.5%
ValueCountFrequency (%)
36.47709808 1
0.2%
36.47765566 1
0.2%
36.48172402 1
0.2%
36.4844751 1
0.2%
36.48498582 1
0.2%
36.48527291 1
0.2%
36.4861494 1
0.2%
36.48699134 1
0.2%
36.48766316 1
0.2%
36.48768943 1
0.2%
ValueCountFrequency (%)
36.66910592 1
0.2%
36.66719473 1
0.2%
36.66523011 1
0.2%
36.66325186 1
0.2%
36.66261157 1
0.2%
36.66031459 1
0.2%
36.65974086 1
0.2%
36.65929035 1
0.2%
36.65904371 1
0.2%
36.65900339 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct516
Distinct (%)97.9%
Missing49
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean126.6333
Minimum126.46084
Maximum126.77192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-12T18:27:24.075965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.46084
5-th percentile126.49363
Q1126.57243
median126.65029
Q3126.6906
95-th percentile126.73926
Maximum126.77192
Range0.3110759
Interquartile range (IQR)0.1181636

Descriptive statistics

Standard deviation0.07646689
Coefficient of variation (CV)0.00060384504
Kurtosis-0.81629101
Mean126.6333
Median Absolute Deviation (MAD)0.0561099
Skewness-0.40503479
Sum66735.749
Variance0.0058471852
MonotonicityNot monotonic
2023-12-12T18:27:24.265291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5202138 2
 
0.3%
126.6286042 2
 
0.3%
126.5321725 2
 
0.3%
126.6645244 2
 
0.3%
126.6690957 2
 
0.3%
126.6652741 2
 
0.3%
126.6545022 2
 
0.3%
126.6780184 2
 
0.3%
126.6678473 2
 
0.3%
126.5262093 2
 
0.3%
Other values (506) 507
88.0%
(Missing) 49
 
8.5%
ValueCountFrequency (%)
126.4608438 1
0.2%
126.4612498 1
0.2%
126.4656902 1
0.2%
126.4678908 1
0.2%
126.4697895 1
0.2%
126.4709653 1
0.2%
126.4713678 1
0.2%
126.472107 1
0.2%
126.4721687 1
0.2%
126.4722214 1
0.2%
ValueCountFrequency (%)
126.7719197 1
0.2%
126.7694934 1
0.2%
126.7666073 1
0.2%
126.7660761 1
0.2%
126.7636913 1
0.2%
126.7635345 1
0.2%
126.7591581 1
0.2%
126.7570348 1
0.2%
126.7560473 1
0.2%
126.7538435 1
0.2%

기타사항
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
564 
미설치
 
8
내포로1526번길197 파란지붕 집 앞
 
1
마을 창고 앞 정자, 운동기구 근처
 
1
명칭은 "소리"로 되어있음
 
1

Length

Max length21
Median length4
Mean length4.0555556
Min length2

Unique

Unique4 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 564
97.9%
미설치 8
 
1.4%
내포로1526번길197 파란지붕 집 앞 1
 
0.2%
마을 창고 앞 정자, 운동기구 근처 1
 
0.2%
명칭은 "소리"로 되어있음 1
 
0.2%
이설 1
 
0.2%

Length

2023-12-12T18:27:24.479121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:27:24.634358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 564
96.2%
미설치 8
 
1.4%
앞 2
 
0.3%
내포로1526번길197 1
 
0.2%
파란지붕 1
 
0.2%
집 1
 
0.2%
마을 1
 
0.2%
창고 1
 
0.2%
정자 1
 
0.2%
운동기구 1
 
0.2%
Other values (5) 5
 
0.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2023-05-23 00:00:00
Maximum2023-05-23 00:00:00
2023-12-12T18:27:24.776417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:24.912578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:27:19.662793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:19.440838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:19.768188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:19.549851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:27:25.016227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분위도경도기타사항
구분1.0000.7270.8250.709
위도0.7271.0000.4980.000
경도0.8250.4981.0000.521
기타사항0.7090.0000.5211.000
2023-12-12T18:27:25.164429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기타사항
구분1.0000.493
기타사항0.4931.000
2023-12-12T18:27:25.291123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도구분기타사항
위도1.0000.1210.4170.000
경도0.1211.0000.5380.109
구분0.4170.5381.0000.493
기타사항0.0000.1090.4931.000

Missing values

2023-12-12T18:27:19.901637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:27:20.052342image/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.
2023-12-12T18:27:20.169526image/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

구분번호표정류소명소재지지번주소위도경도기타사항데이터기준일자
0홍성읍홍성01홍성역충청남도 홍성군 홍성읍 고암리 450-636.600209126.68028<NA>2023-05-23
1홍성읍홍성02홍성의료원충청남도 홍성군 홍성읍 고암리 572-236.599724126.675374<NA>2023-05-23
2홍성읍홍성03홍성의료원충청남도 홍성군 홍성읍 고암리 101836.599934126.674804<NA>2023-05-23
3홍성읍홍성04농협동부지소충청남도 홍성군 홍성읍 의사로 48<NA><NA><NA>2023-05-23
4홍성읍홍성05홍성전통시장충청남도 홍성군 홍성읍 대교리 395-136.600887126.669721<NA>2023-05-23
5홍성읍홍성06장군상오거리충청남도 홍성군 홍성읍 고암리 533-136.600564126.670406<NA>2023-05-23
6홍성읍홍성07홍성전통시장충청남도 홍성군 홍성읍 대교리 395-1636.600962126.669316<NA>2023-05-23
7홍성읍홍성08홍성전통시장충청남도 홍성군 홍성읍 오관리 311-736.601184126.667375<NA>2023-05-23
8홍성읍홍성09농협중앙회충청남도 홍성군 홍성읍 오관리 288-236.601764126.666415<NA>2023-05-23
9홍성읍홍성10오관파출소앞충청남도 홍성군 홍성읍 오관리 307-136.600272126.665818<NA>2023-05-23
구분번호표정류소명소재지지번주소위도경도기타사항데이터기준일자
566금마면금마36봉서충청남도 홍성군 금마면 봉서리 767-4<NA><NA><NA>2023-05-23
567금마면금마37봉암충청남도 홍성군 금마면 월암리 457-7<NA><NA><NA>2023-05-23
568금마면금마38마사월굴마을입구충청남도 홍성군 금마면 월암리 887-1<NA><NA><NA>2023-05-23
569금마면금마39마사마을충청남도 홍성군 금마면 월암리 219<NA><NA><NA>2023-05-23
570금마면금마40금굴충청남도 홍성군 금마면 화양리 481-3<NA><NA><NA>2023-05-23
571금마면금마41화양역충청남도 홍성군 금마면 화양리 174-5<NA><NA><NA>2023-05-23
572금마면금마42화전평촌마을충청남도 홍성군 금마면 화양리 165-4<NA><NA><NA>2023-05-23
573금마면금마43화전마을충청남도 홍성군 금마면 화양리 28-3<NA><NA><NA>2023-05-23
574금마면<NA>송강마을3거리충청남도 홍성군 금마면 송강리 252-5<NA><NA><NA>2023-05-23
575금마면<NA>화전충청남도 홍성군 금마면 화양리 177-22<NA><NA><NA>2023-05-23