Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells17
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory752.0 KiB
Average record size in memory77.0 B

Variable types

Categorical2
Numeric5
Text1

Dataset

Description나주시 시내버스 승하차 정보를 월간으로 제공합니다.수집기간은 매월 1일부터 말일까지 이며 노선, 정류소, 운행시간대에 따른 승차인원과 하차인원에 대한 정보를 제공합니다.
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15113178/fileData.do

Alerts

노선ID is highly overall correlated with 노선명High correlation
노선명 is highly overall correlated with 노선IDHigh correlation
승차인원 has 3035 (30.3%) zerosZeros
하차인원 has 4508 (45.1%) zerosZeros

Reproduction

Analysis started2024-03-15 01:24:12.756774
Analysis finished2024-03-15 01:24:22.198091
Duration9.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-02-05
826 
2024-02-06
824 
2024-02-02
815 
2024-02-01
795 
2024-02-07
766 
Other values (10)
5974 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-10
2nd row2024-02-04
3rd row2024-02-04
4th row2024-02-11
5th row2024-02-03

Common Values

ValueCountFrequency (%)
2024-02-05 826
 
8.3%
2024-02-06 824
 
8.2%
2024-02-02 815
 
8.2%
2024-02-01 795
 
8.0%
2024-02-07 766
 
7.7%
2024-02-14 735
 
7.3%
2024-02-08 733
 
7.3%
2024-02-13 730
 
7.3%
2024-02-03 685
 
6.9%
2024-02-15 598
 
6.0%
Other values (5) 2493
24.9%

Length

2024-03-15T10:24:22.450440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-02-05 826
 
8.3%
2024-02-06 824
 
8.2%
2024-02-02 815
 
8.2%
2024-02-01 795
 
8.0%
2024-02-07 766
 
7.7%
2024-02-14 735
 
7.3%
2024-02-08 733
 
7.3%
2024-02-13 730
 
7.3%
2024-02-03 685
 
6.9%
2024-02-15 598
 
6.0%
Other values (5) 2493
24.9%

노선ID
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4505.2506
Minimum176
Maximum9919
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:24:22.797059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176
5-th percentile1110
Q11610
median2220
Q37771
95-th percentile9919
Maximum9919
Range9743
Interquartile range (IQR)6161

Descriptive statistics

Standard deviation3395.093
Coefficient of variation (CV)0.75358582
Kurtosis-1.3988613
Mean4505.2506
Median Absolute Deviation (MAD)1110
Skewness0.52001399
Sum45052506
Variance11526656
MonotonicityNot monotonic
2024-03-15T10:24:23.063999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1610 2768
27.7%
1611 1540
15.4%
9917 628
 
6.3%
9919 600
 
6.0%
9918 593
 
5.9%
7772 384
 
3.8%
7771 340
 
3.4%
1110 307
 
3.1%
7770 298
 
3.0%
4020 287
 
2.9%
Other values (46) 2255
22.6%
ValueCountFrequency (%)
176 70
 
0.7%
177 6
 
0.1%
178 6
 
0.1%
179 3
 
< 0.1%
180 4
 
< 0.1%
181 2
 
< 0.1%
1009 45
 
0.4%
1010 83
 
0.8%
1110 307
3.1%
1111 7
 
0.1%
ValueCountFrequency (%)
9919 600
6.0%
9918 593
5.9%
9917 628
6.3%
8020 8
 
0.1%
8019 59
 
0.6%
7772 384
3.8%
7771 340
3.4%
7770 298
3.0%
7302 24
 
0.2%
7106 6
 
0.1%

노선명
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
160
2768 
161
1540 
997
628 
999
600 
998
593 
Other values (43)
3871 

Length

Max length6
Median length3
Mean length3.1105
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row160
2nd row500
3rd row160
4th row161
5th row160

Common Values

ValueCountFrequency (%)
160 2768
27.7%
161 1540
15.4%
997 628
 
6.3%
999 600
 
6.0%
998 593
 
5.9%
7002 384
 
3.8%
7001 340
 
3.4%
100 307
 
3.1%
7000 298
 
3.0%
402 287
 
2.9%
Other values (38) 2255
22.6%

Length

2024-03-15T10:24:23.441699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
160 2768
27.7%
161 1540
15.4%
997 628
 
6.3%
999 600
 
6.0%
998 593
 
5.9%
7002 384
 
3.8%
7001 340
 
3.4%
100 307
 
3.1%
7000 298
 
3.0%
402 287
 
2.9%
Other values (38) 2255
22.6%

정류소ID
Real number (ℝ)

Distinct896
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1157.6692
Minimum0
Maximum5140
Zeros17
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:24:23.792468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile90
Q1403.75
median893
Q31847
95-th percentile2329
Maximum5140
Range5140
Interquartile range (IQR)1443.25

Descriptive statistics

Standard deviation1093.4785
Coefficient of variation (CV)0.9445518
Kurtosis5.027976
Mean1157.6692
Median Absolute Deviation (MAD)570
Skewness2.0618199
Sum11576692
Variance1195695.3
MonotonicityNot monotonic
2024-03-15T10:24:24.142293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2195 126
 
1.3%
188 126
 
1.3%
962 111
 
1.1%
729 97
 
1.0%
2194 84
 
0.8%
192 83
 
0.8%
199 75
 
0.8%
184 72
 
0.7%
1927 69
 
0.7%
73 62
 
0.6%
Other values (886) 9095
91.0%
ValueCountFrequency (%)
0 17
0.2%
1 1
 
< 0.1%
6 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
16 1
 
< 0.1%
17 2
 
< 0.1%
18 2
 
< 0.1%
19 1
 
< 0.1%
20 2
 
< 0.1%
ValueCountFrequency (%)
5140 1
 
< 0.1%
5139 2
 
< 0.1%
5126 19
0.2%
5125 4
 
< 0.1%
5123 3
 
< 0.1%
5122 13
0.1%
5121 1
 
< 0.1%
5115 15
0.1%
5114 23
0.2%
5113 2
 
< 0.1%

정류소명
Text

Distinct579
Distinct (%)5.8%
Missing17
Missing (%)0.2%
Memory size156.2 KiB
2024-03-15T10:24:25.086632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length5.5960132
Min length2

Characters and Unicode

Total characters55865
Distinct characters305
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

Unique123 ?
Unique (%)1.2%

Sample

1st row도로교통공단
2nd row다시파출소
3rd row말바우시장(남)
4th row서석고
5th row나주국민체육센터
ValueCountFrequency (%)
나주역 161
 
1.6%
나주시청 131
 
1.3%
영산포터미널(상행 126
 
1.3%
광주송정역 119
 
1.2%
영산포터미널(하행 111
 
1.1%
운천역 100
 
1.0%
성북아파트 97
 
1.0%
중흥s클래스센트럴1차 97
 
1.0%
풍물시장 91
 
0.9%
중앙로 90
 
0.9%
Other values (570) 8907
88.8%
2024-03-15T10:24:26.265154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 1436
 
2.6%
주 1435
 
2.6%
정 1147
 
2.1%
터 1141
 
2.0%
남 1104
 
2.0%
대 1041
 
1.9%
교 1028
 
1.8%
트 1026
 
1.8%
장 997
 
1.8%
시 979
 
1.8%
Other values (295) 44531
79.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52110
93.3%
Close Punctuation 811
 
1.5%
Open Punctuation 811
 
1.5%
Uppercase Letter 763
 
1.4%
Decimal Number 710
 
1.3%
Other Punctuation 613
 
1.1%
Space Separator 47
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1436
 
2.8%
주 1435
 
2.8%
정 1147
 
2.2%
터 1141
 
2.2%
남 1104
 
2.1%
대 1041
 
2.0%
교 1028
 
2.0%
트 1026
 
2.0%
장 997
 
1.9%
시 979
 
1.9%
Other values (271) 40776
78.2%
Uppercase Letter
ValueCountFrequency (%)
S 216
28.3%
L 175
22.9%
H 128
16.8%
K 92
12.1%
G 50
 
6.6%
T 39
 
5.1%
N 23
 
3.0%
D 20
 
2.6%
P 7
 
0.9%
X 7
 
0.9%
Other values (2) 6
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 329
46.3%
2 136
19.2%
4 68
 
9.6%
9 62
 
8.7%
3 49
 
6.9%
5 36
 
5.1%
6 27
 
3.8%
0 3
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 811
100.0%
Open Punctuation
ValueCountFrequency (%)
( 811
100.0%
Other Punctuation
ValueCountFrequency (%)
. 613
100.0%
Space Separator
ValueCountFrequency (%)
47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52110
93.3%
Common 2992
 
5.4%
Latin 763
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1436
 
2.8%
주 1435
 
2.8%
정 1147
 
2.2%
터 1141
 
2.2%
남 1104
 
2.1%
대 1041
 
2.0%
교 1028
 
2.0%
트 1026
 
2.0%
장 997
 
1.9%
시 979
 
1.9%
Other values (271) 40776
78.2%
Common
ValueCountFrequency (%)
) 811
27.1%
( 811
27.1%
. 613
20.5%
1 329
11.0%
2 136
 
4.5%
4 68
 
2.3%
9 62
 
2.1%
3 49
 
1.6%
47
 
1.6%
5 36
 
1.2%
Other values (2) 30
 
1.0%
Latin
ValueCountFrequency (%)
S 216
28.3%
L 175
22.9%
H 128
16.8%
K 92
12.1%
G 50
 
6.6%
T 39
 
5.1%
N 23
 
3.0%
D 20
 
2.6%
P 7
 
0.9%
X 7
 
0.9%
Other values (2) 6
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52110
93.3%
ASCII 3755
 
6.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 1436
 
2.8%
주 1435
 
2.8%
정 1147
 
2.2%
터 1141
 
2.2%
남 1104
 
2.1%
대 1041
 
2.0%
교 1028
 
2.0%
트 1026
 
2.0%
장 997
 
1.9%
시 979
 
1.9%
Other values (271) 40776
78.2%
ASCII
ValueCountFrequency (%)
) 811
21.6%
( 811
21.6%
. 613
16.3%
1 329
8.8%
S 216
 
5.8%
L 175
 
4.7%
2 136
 
3.6%
H 128
 
3.4%
K 92
 
2.5%
4 68
 
1.8%
Other values (14) 376
10.0%

운행시간대
Real number (ℝ)

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.3939
Minimum5
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:24:26.637082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q19
median13
Q317
95-th percentile21
Maximum23
Range18
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.5491111
Coefficient of variation (CV)0.33964052
Kurtosis-1.0198015
Mean13.3939
Median Absolute Deviation (MAD)4
Skewness0.14424841
Sum133939
Variance20.694412
MonotonicityNot monotonic
2024-03-15T10:24:27.035920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
8 751
 
7.5%
9 707
 
7.1%
16 698
 
7.0%
7 694
 
6.9%
13 690
 
6.9%
12 656
 
6.6%
15 656
 
6.6%
17 655
 
6.6%
10 653
 
6.5%
14 650
 
6.5%
Other values (9) 3190
31.9%
ValueCountFrequency (%)
5 75
 
0.8%
6 314
3.1%
7 694
6.9%
8 751
7.5%
9 707
7.1%
10 653
6.5%
11 630
6.3%
12 656
6.6%
13 690
6.9%
14 650
6.5%
ValueCountFrequency (%)
23 94
 
0.9%
22 240
 
2.4%
21 355
3.5%
20 428
4.3%
19 477
4.8%
18 577
5.8%
17 655
6.6%
16 698
7.0%
15 656
6.6%
14 650
6.5%

승차인원
Real number (ℝ)

ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.535
Minimum0
Maximum80
Zeros3035
Zeros (%)30.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:24:27.523314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum80
Range80
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.8478037
Coefficient of variation (CV)1.8552467
Kurtosis231.1946
Mean1.535
Median Absolute Deviation (MAD)1
Skewness11.529459
Sum15350
Variance8.109986
MonotonicityNot monotonic
2024-03-15T10:24:28.004741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 3952
39.5%
0 3035
30.3%
2 1432
 
14.3%
3 631
 
6.3%
4 345
 
3.5%
5 199
 
2.0%
6 131
 
1.3%
7 55
 
0.5%
8 51
 
0.5%
9 37
 
0.4%
Other values (30) 132
 
1.3%
ValueCountFrequency (%)
0 3035
30.3%
1 3952
39.5%
2 1432
 
14.3%
3 631
 
6.3%
4 345
 
3.5%
5 199
 
2.0%
6 131
 
1.3%
7 55
 
0.5%
8 51
 
0.5%
9 37
 
0.4%
ValueCountFrequency (%)
80 2
< 0.1%
65 1
< 0.1%
63 1
< 0.1%
62 1
< 0.1%
59 1
< 0.1%
49 1
< 0.1%
47 1
< 0.1%
46 1
< 0.1%
36 1
< 0.1%
34 1
< 0.1%

하차인원
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.075
Minimum0
Maximum70
Zeros4508
Zeros (%)45.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:24:28.542659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile4
Maximum70
Range70
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.0663015
Coefficient of variation (CV)1.9221409
Kurtosis279.10099
Mean1.075
Median Absolute Deviation (MAD)1
Skewness11.580839
Sum10750
Variance4.269602
MonotonicityNot monotonic
2024-03-15T10:24:29.265664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 4508
45.1%
1 3363
33.6%
2 1084
 
10.8%
3 452
 
4.5%
4 223
 
2.2%
5 125
 
1.2%
6 80
 
0.8%
8 38
 
0.4%
7 38
 
0.4%
9 20
 
0.2%
Other values (20) 69
 
0.7%
ValueCountFrequency (%)
0 4508
45.1%
1 3363
33.6%
2 1084
 
10.8%
3 452
 
4.5%
4 223
 
2.2%
5 125
 
1.2%
6 80
 
0.8%
7 38
 
0.4%
8 38
 
0.4%
9 20
 
0.2%
ValueCountFrequency (%)
70 1
 
< 0.1%
59 1
 
< 0.1%
58 1
 
< 0.1%
44 1
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
24 1
 
< 0.1%
22 3
< 0.1%
21 2
< 0.1%
20 1
 
< 0.1%

Interactions

2024-03-15T10:24:19.897636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:14.337035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:15.687746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:17.052269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:18.321263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:20.209319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:14.592461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:16.076718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:17.221741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:18.638905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:20.493109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:14.856725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:16.314756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:17.451020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:18.993330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:20.800896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:15.133458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:16.593579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:17.742407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:19.288985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:21.110840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:15.416532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:16.872132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:18.037109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:24:19.593026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:24:29.597889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜노선ID노선명정류소ID운행시간대승차인원하차인원
날짜1.0000.1130.1940.0650.1010.0230.040
노선ID0.1131.0001.0000.4390.1850.1190.101
노선명0.1941.0001.0000.6210.2400.3560.464
정류소ID0.0650.4390.6211.0000.0580.1060.042
운행시간대0.1010.1850.2400.0581.0000.0580.000
승차인원0.0230.1190.3560.1060.0581.0000.789
하차인원0.0400.1010.4640.0420.0000.7891.000
2024-03-15T10:24:29.946792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜노선명
날짜1.0000.056
노선명0.0561.000
2024-03-15T10:24:30.244769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선ID정류소ID운행시간대승차인원하차인원날짜노선명
노선ID1.0000.2380.002-0.044-0.0810.0430.998
정류소ID0.2381.0000.032-0.035-0.0250.0300.302
운행시간대0.0020.0321.000-0.0180.0370.0360.083
승차인원-0.044-0.035-0.0181.000-0.3110.0040.127
하차인원-0.081-0.0250.037-0.3111.0000.0170.183
날짜0.0430.0300.0360.0040.0171.0000.056
노선명0.9980.3020.0830.1270.1830.0561.000

Missing values

2024-03-15T10:24:21.538718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:24:22.025812image/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

날짜노선ID노선명정류소ID정류소명운행시간대승차인원하차인원
652542024-02-101610160901도로교통공단2301
260272024-02-045502500283다시파출소1401
234152024-02-041610160382말바우시장(남)742
708742024-02-111611161689서석고1301
166582024-02-0316101601926나주국민체육센터1810
421682024-02-0699179971930고동교차로710
977632024-02-154010401729성북아파트722
121552024-02-02402040292구석삼거리1001
528682024-02-081610160697도산역1020
106002024-02-0216111611932대방엘리움2차2201
날짜노선ID노선명정류소ID정류소명운행시간대승차인원하차인원
599682024-02-091610160183나주시청1701
486342024-02-07666060090구교육청1610
867832024-02-141110100262노인복지회관902
481272024-02-0740204021266나주중앙병원710
38612024-02-013020302149금천사거리.광탄마을1801
731322024-02-1199199995069남평시장입구1310
236452024-02-041610160651상무지구입구2301
508742024-02-079918998535백운광장1652
947672024-02-151610160259노안남초교.만호1612
151572024-02-0299189981905통정길1510