Overview

Dataset statistics

Number of variables7
Number of observations1809
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory106.1 KiB
Average record size in memory60.1 B

Variable types

Numeric4
Text2
DateTime1

Dataset

Description춘천시 버스정류장에 대한 모바일서비스번호, 관리번호, 정류장명, 위도, 경도, 및 데이터기준일에 대한 자료버스노선 정보와는 별개로, 승강장 자체에 대한 정보만 포함함
Author강원특별자치도 춘천시
URLhttps://www.data.go.kr/data/15045129/fileData.do

Alerts

데이터 기준일 has constant value ""Constant
정류장 번호 is highly overall correlated with 관리번호High correlation
관리번호 is highly overall correlated with 정류장 번호High correlation
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 16:55:59.352771
Analysis finished2024-03-14 16:56:04.798778
Duration5.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정류장 번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1808
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1991.5379
Minimum1001
Maximum5963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-03-15T01:56:05.015717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1091.4
Q11453
median1905
Q32398
95-th percentile2808.6
Maximum5963
Range4962
Interquartile range (IQR)945

Descriptive statistics

Standard deviation777.25337
Coefficient of variation (CV)0.39027798
Kurtosis9.3435649
Mean1991.5379
Median Absolute Deviation (MAD)469
Skewness2.3591826
Sum3602692
Variance604122.81
MonotonicityIncreasing
2024-03-15T01:56:05.372838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2551 2
 
0.1%
1001 1
 
0.1%
2232 1
 
0.1%
2230 1
 
0.1%
2229 1
 
0.1%
2226 1
 
0.1%
2225 1
 
0.1%
2224 1
 
0.1%
2223 1
 
0.1%
2220 1
 
0.1%
Other values (1798) 1798
99.4%
ValueCountFrequency (%)
1001 1
0.1%
1002 1
0.1%
1003 1
0.1%
1004 1
0.1%
1005 1
0.1%
1006 1
0.1%
1007 1
0.1%
1008 1
0.1%
1009 1
0.1%
1010 1
0.1%
ValueCountFrequency (%)
5963 1
0.1%
5961 1
0.1%
5960 1
0.1%
5959 1
0.1%
5958 1
0.1%
5957 1
0.1%
5956 1
0.1%
5955 1
0.1%
5954 1
0.1%
5949 1
0.1%

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1809
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5112598 × 108
Minimum2.5 × 108
Maximum2.6500078 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-03-15T01:56:05.629597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.5 × 108
5-th percentile2.500011 × 108
Q12.5000153 × 108
median2.5000204 × 108
Q32.500268 × 108
95-th percentile2.6500069 × 108
Maximum2.6500078 × 108
Range15000778
Interquartile range (IQR)25273

Descriptive statistics

Standard deviation3759655.9
Coefficient of variation (CV)0.014971195
Kurtosis8.8207488
Mean2.5112598 × 108
Median Absolute Deviation (MAD)794
Skewness3.2355098
Sum4.5428689 × 1011
Variance1.4135013 × 1013
MonotonicityNot monotonic
2024-03-15T01:56:06.063683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
250001192 1
 
0.1%
250002224 1
 
0.1%
250002255 1
 
0.1%
250002253 1
 
0.1%
250002252 1
 
0.1%
250002249 1
 
0.1%
250002248 1
 
0.1%
250002247 1
 
0.1%
250002246 1
 
0.1%
250002243 1
 
0.1%
Other values (1799) 1799
99.4%
ValueCountFrequency (%)
250000003 1
0.1%
250000004 1
0.1%
250000005 1
0.1%
250000006 1
0.1%
250000010 1
0.1%
250000011 1
0.1%
250000040 1
0.1%
250000041 1
0.1%
250000042 1
0.1%
250000138 1
0.1%
ValueCountFrequency (%)
265000781 1
0.1%
265000780 1
0.1%
265000779 1
0.1%
265000778 1
0.1%
265000777 1
0.1%
265000776 1
0.1%
265000775 1
0.1%
265000774 1
0.1%
265000773 1
0.1%
265000772 1
0.1%

정류장명
Text

Distinct953
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-03-15T01:56:08.048228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.0093975
Min length2

Characters and Unicode

Total characters9062
Distinct characters396
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

Unique311 ?
Unique (%)17.2%

Sample

1st row대형약국
2nd row산림조합강원본부
3rd row산림조합강원본부
4th row발산3리
5th row금광터
ValueCountFrequency (%)
월송1리 12
 
0.7%
발산2리 11
 
0.6%
방동1리 9
 
0.5%
박암리 9
 
0.5%
지암리 8
 
0.4%
발산1리 8
 
0.4%
오월2리 8
 
0.4%
군자3리 8
 
0.4%
신촌1리 7
 
0.4%
당림1리 7
 
0.4%
Other values (943) 1722
95.2%
2024-03-15T01:56:09.907803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 825
 
9.1%
1 255
 
2.8%
2 247
 
2.7%
구 194
 
2.1%
원 175
 
1.9%
교 174
 
1.9%
지 169
 
1.9%
입 167
 
1.8%
동 156
 
1.7%
산 135
 
1.5%
Other values (386) 6565
72.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8178
90.2%
Decimal Number 699
 
7.7%
Uppercase Letter 107
 
1.2%
Close Punctuation 34
 
0.4%
Open Punctuation 34
 
0.4%
Other Punctuation 9
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 825
 
10.1%
구 194
 
2.4%
원 175
 
2.1%
교 174
 
2.1%
지 169
 
2.1%
입 167
 
2.0%
동 156
 
1.9%
산 135
 
1.7%
사 129
 
1.6%
천 129
 
1.6%
Other values (363) 5925
72.5%
Decimal Number
ValueCountFrequency (%)
1 255
36.5%
2 247
35.3%
3 128
18.3%
4 39
 
5.6%
5 12
 
1.7%
6 7
 
1.0%
7 4
 
0.6%
8 3
 
0.4%
9 2
 
0.3%
0 2
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
A 96
89.7%
K 3
 
2.8%
S 2
 
1.9%
B 2
 
1.9%
M 1
 
0.9%
L 1
 
0.9%
H 1
 
0.9%
T 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/ 7
77.8%
. 2
 
22.2%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8178
90.2%
Common 776
 
8.6%
Latin 108
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 825
 
10.1%
구 194
 
2.4%
원 175
 
2.1%
교 174
 
2.1%
지 169
 
2.1%
입 167
 
2.0%
동 156
 
1.9%
산 135
 
1.7%
사 129
 
1.6%
천 129
 
1.6%
Other values (363) 5925
72.5%
Common
ValueCountFrequency (%)
1 255
32.9%
2 247
31.8%
3 128
16.5%
4 39
 
5.0%
) 34
 
4.4%
( 34
 
4.4%
5 12
 
1.5%
/ 7
 
0.9%
6 7
 
0.9%
7 4
 
0.5%
Other values (4) 9
 
1.2%
Latin
ValueCountFrequency (%)
A 96
88.9%
K 3
 
2.8%
S 2
 
1.9%
B 2
 
1.9%
e 1
 
0.9%
M 1
 
0.9%
L 1
 
0.9%
H 1
 
0.9%
T 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8178
90.2%
ASCII 884
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 825
 
10.1%
구 194
 
2.4%
원 175
 
2.1%
교 174
 
2.1%
지 169
 
2.1%
입 167
 
2.0%
동 156
 
1.9%
산 135
 
1.7%
사 129
 
1.6%
천 129
 
1.6%
Other values (363) 5925
72.5%
ASCII
ValueCountFrequency (%)
1 255
28.8%
2 247
27.9%
3 128
14.5%
A 96
 
10.9%
4 39
 
4.4%
) 34
 
3.8%
( 34
 
3.8%
5 12
 
1.4%
/ 7
 
0.8%
6 7
 
0.8%
Other values (13) 25
 
2.8%

정류장명(영어)
Text

Distinct950
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-03-15T01:56:11.453837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length19.677722
Min length2

Characters and Unicode

Total characters35597
Distinct characters73
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)17.1%

Sample

1st rowDaehyeong Pharmacy
2nd rowNational Forestry Cooperative Federation Gangwon
3rd rowNational Forestry Cooperative Federation Gangwon
4th rowBalsan 3(sam)-ri
5th rowGeumgwangteo Village
ValueCountFrequency (%)
2(i)-ri 208
 
4.6%
1(il)-ri 205
 
4.5%
entrance 184
 
4.1%
apartment 137
 
3.0%
school 105
 
2.3%
terminus 99
 
2.2%
village 94
 
2.1%
3(sam)-ri 88
 
1.9%
center 63
 
1.4%
hall 59
 
1.3%
Other values (805) 3285
72.6%
2024-03-15T01:56:13.268088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 3193
 
9.0%
a 2767
 
7.8%
2734
 
7.7%
i 2502
 
7.0%
o 2444
 
6.9%
e 2375
 
6.7%
r 1953
 
5.5%
g 1554
 
4.4%
l 1370
 
3.8%
t 1199
 
3.4%
Other values (63) 13506
37.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 25929
72.8%
Uppercase Letter 3868
 
10.9%
Space Separator 2734
 
7.7%
Dash Punctuation 955
 
2.7%
Open Punctuation 695
 
2.0%
Close Punctuation 693
 
1.9%
Decimal Number 691
 
1.9%
Other Punctuation 30
 
0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 599
15.5%
C 337
 
8.7%
G 303
 
7.8%
H 285
 
7.4%
E 278
 
7.2%
A 221
 
5.7%
J 202
 
5.2%
T 198
 
5.1%
B 184
 
4.8%
P 180
 
4.7%
Other values (16) 1081
27.9%
Lowercase Letter
ValueCountFrequency (%)
n 3193
12.3%
a 2767
10.7%
i 2502
9.6%
o 2444
9.4%
e 2375
9.2%
r 1953
 
7.5%
g 1554
 
6.0%
l 1370
 
5.3%
t 1199
 
4.6%
m 1029
 
4.0%
Other values (15) 5543
21.4%
Decimal Number
ValueCountFrequency (%)
1 256
37.0%
2 246
35.6%
3 123
17.8%
4 36
 
5.2%
5 12
 
1.7%
6 7
 
1.0%
7 4
 
0.6%
8 3
 
0.4%
0 2
 
0.3%
9 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
' 9
30.0%
/ 7
23.3%
& 5
16.7%
. 3
 
10.0%
# 2
 
6.7%
, 2
 
6.7%
？ 2
 
6.7%
Space Separator
ValueCountFrequency (%)
2734
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 955
100.0%
Open Punctuation
ValueCountFrequency (%)
( 695
100.0%
Close Punctuation
ValueCountFrequency (%)
) 693
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29797
83.7%
Common 5800
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 3193
 
10.7%
a 2767
 
9.3%
i 2502
 
8.4%
o 2444
 
8.2%
e 2375
 
8.0%
r 1953
 
6.6%
g 1554
 
5.2%
l 1370
 
4.6%
t 1199
 
4.0%
m 1029
 
3.5%
Other values (41) 9411
31.6%
Common
ValueCountFrequency (%)
2734
47.1%
- 955
 
16.5%
( 695
 
12.0%
) 693
 
11.9%
1 256
 
4.4%
2 246
 
4.2%
3 123
 
2.1%
4 36
 
0.6%
5 12
 
0.2%
' 9
 
0.2%
Other values (12) 41
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35593
> 99.9%
Punctuation 2
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 3193
 
9.0%
a 2767
 
7.8%
2734
 
7.7%
i 2502
 
7.0%
o 2444
 
6.9%
e 2375
 
6.7%
r 1953
 
5.5%
g 1554
 
4.4%
l 1370
 
3.8%
t 1199
 
3.4%
Other values (61) 13502
37.9%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
None
ValueCountFrequency (%)
？ 2
100.0%

경도
Real number (ℝ)

Distinct1725
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.71335
Minimum127.51237
Maximum127.90446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-03-15T01:56:13.547165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.51237
5-th percentile127.58855
Q1127.67446
median127.72413
Q3127.75348
95-th percentile127.79754
Maximum127.90446
Range0.39209
Interquartile range (IQR)0.07902

Descriptive statistics

Standard deviation0.064775077
Coefficient of variation (CV)0.00050719114
Kurtosis0.40995298
Mean127.71335
Median Absolute Deviation (MAD)0.03524
Skewness-0.30593984
Sum231033.44
Variance0.0041958106
MonotonicityNot monotonic
2024-03-15T01:56:13.831246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.75179 3
 
0.2%
127.75555 2
 
0.1%
127.75496 2
 
0.1%
127.74245 2
 
0.1%
127.61677 2
 
0.1%
127.73068 2
 
0.1%
127.75271 2
 
0.1%
127.71229 2
 
0.1%
127.73085 2
 
0.1%
127.74418 2
 
0.1%
Other values (1715) 1788
98.8%
ValueCountFrequency (%)
127.51237 1
0.1%
127.51241 1
0.1%
127.52203 1
0.1%
127.5222 1
0.1%
127.52918 1
0.1%
127.53396 1
0.1%
127.5341 1
0.1%
127.53776 1
0.1%
127.53872 1
0.1%
127.54383 1
0.1%
ValueCountFrequency (%)
127.90446 1
0.1%
127.90438 1
0.1%
127.90091 1
0.1%
127.8966 1
0.1%
127.89646 1
0.1%
127.89257 1
0.1%
127.89225 1
0.1%
127.89165 1
0.1%
127.88958 1
0.1%
127.88823 1
0.1%

위도
Real number (ℝ)

Distinct1737
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.866745
Minimum37.67548
Maximum38.05419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-03-15T01:56:14.276134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.67548
5-th percentile37.731812
Q137.82047
median37.86994
Q337.92203
95-th percentile37.992142
Maximum38.05419
Range0.37871
Interquartile range (IQR)0.10156

Descriptive statistics

Standard deviation0.078279095
Coefficient of variation (CV)0.0020672254
Kurtosis-0.3266642
Mean37.866745
Median Absolute Deviation (MAD)0.05104
Skewness-0.15514551
Sum68500.941
Variance0.0061276168
MonotonicityNot monotonic
2024-03-15T01:56:14.639520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7977 3
 
0.2%
37.86158 3
 
0.2%
37.9663 3
 
0.2%
37.95409 2
 
0.1%
37.83373 2
 
0.1%
37.77647 2
 
0.1%
37.8642 2
 
0.1%
37.85456 2
 
0.1%
37.85641 2
 
0.1%
37.89694 2
 
0.1%
Other values (1727) 1786
98.7%
ValueCountFrequency (%)
37.67548 1
0.1%
37.67562 1
0.1%
37.67705 1
0.1%
37.67723 1
0.1%
37.6787 1
0.1%
37.67881 1
0.1%
37.68115 1
0.1%
37.6812 1
0.1%
37.68233 1
0.1%
37.68236 1
0.1%
ValueCountFrequency (%)
38.05419 1
0.1%
38.05402 1
0.1%
38.05262 1
0.1%
38.05254 1
0.1%
38.05087 1
0.1%
38.05073 1
0.1%
38.05051 1
0.1%
38.05044 1
0.1%
38.04968 1
0.1%
38.0471 1
0.1%

데이터 기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum2024-01-02 00:00:00
Maximum2024-01-02 00:00:00
2024-03-15T01:56:14.874644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:15.191047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T01:56:03.145675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:55:59.891479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:01.123921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:02.274524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:03.343467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:00.180999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:01.404833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:02.521124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:03.665541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:00.478379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:01.692242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:02.752647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:04.067950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:00.832454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:01.989005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:56:02.955638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:56:15.420853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류장 번호관리번호경도위도
정류장 번호1.0000.6790.2290.590
관리번호0.6791.0000.3180.753
경도0.2290.3181.0000.662
위도0.5900.7530.6621.000
2024-03-15T01:56:15.674857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류장 번호관리번호경도위도
정류장 번호1.0000.743-0.003-0.022
관리번호0.7431.0000.0450.028
경도-0.0030.0451.0000.236
위도-0.0220.0280.2361.000

Missing values

2024-03-15T01:56:04.300487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:56:04.636209image/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

정류장 번호관리번호정류장명정류장명(영어)경도위도데이터 기준일
01001250001192대형약국Daehyeong Pharmacy127.7751337.8762024-01-02
11002250001193산림조합강원본부National Forestry Cooperative Federation Gangwon127.7535837.887212024-01-02
21003250001194산림조합강원본부National Forestry Cooperative Federation Gangwon127.7532537.886912024-01-02
31004250001195발산3리Balsan 3(sam)-ri127.7457737.959092024-01-02
41005250001196금광터Geumgwangteo Village127.7463737.953342024-01-02
51006250001197운전면허시험장Driver’s License Examination Office127.7508337.947542024-01-02
61007250001198소양강댐주차장Soyanggang Dam Parking Lot127.8018837.938022024-01-02
71008250001199폴리텍2캠퍼스Korea Polytechnics 2nd Campus127.7395637.912122024-01-02
81009250001200월곡리Wolgok-ri127.7982637.917392024-01-02
91010250001201감정리Gamjeong-ri127.7866737.903752024-01-02
정류장 번호관리번호정류장명정류장명(영어)경도위도데이터 기준일
17995949257800099두미리종점Dumi-ri Terminus127.6623637.68122024-01-02
18005954257800104모곡Mogok127.6069937.675482024-01-02
18015955257800105모곡Mogok127.6071137.675622024-01-02
18025956257800106용골상회Yonggol General Store127.6797937.691512024-01-02
18035957257800107용골상회Yonggol General Store127.679937.691252024-01-02
18045958257800108반곡망단이Bangok Mangdani127.6738537.695222024-01-02
18055959257800109반곡망단이Bangok Mangdani127.6737837.695082024-01-02
18065960257800113역전평Yeokjeonpyeong127.7963137.728712024-01-02
18075961257800114역전평Yeokjeonpyeong127.796537.728672024-01-02
18085963257800116산수1리2반Sansu 1(il)-ri 2(i)-ban127.6832637.712312024-01-02