Overview

Dataset statistics

Number of variables14
Number of observations2723
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory327.2 KiB
Average record size in memory123.0 B

Variable types

Numeric10
Categorical3
Text1

Dataset

Description23~25 공공데이터 중장기 개방계획에 의한 버스정보시스템 개방자료로서 노선번호,노선명, 노선길이, 정류장 등의 자료를 포함합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=16&beforeMenuCd=DOM_000000201001001000&publicdatapk=15122485

Alerts

배차간격 is highly overall correlated with 노선번호 and 8 other fieldsHigh correlation
노선설명 is highly overall correlated with 노선번호 and 8 other fieldsHigh correlation
회차여부 is highly overall correlated with 노선번호 and 5 other fieldsHigh correlation
노선번호 is highly overall correlated with 노선설명 and 2 other fieldsHigh correlation
노선정보그룹번호 is highly overall correlated with 노선설명 and 1 other fieldsHigh correlation
노선명 is highly overall correlated with 노선설명 and 2 other fieldsHigh correlation
정류장순번 is highly overall correlated with 노선누적길이High correlation
노선누적길이 is highly overall correlated with 정류장순번High correlation
전체노선길이 is highly overall correlated with 회차지순번 and 2 other fieldsHigh correlation
출발정류장번호 is highly overall correlated with 노선설명 and 2 other fieldsHigh correlation
도착정류장번호 is highly overall correlated with 노선설명 and 1 other fieldsHigh correlation
회차지순번 is highly overall correlated with 전체노선길이 and 3 other fieldsHigh correlation
회차여부 is highly imbalanced (53.7%)Imbalance
노선길이 has 40 (1.5%) zerosZeros
노선누적길이 has 32 (1.2%) zerosZeros

Reproduction

Analysis started2024-01-09 22:18:22.308875
Analysis finished2024-01-09 22:18:32.211288
Duration9.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8770592 × 108
Minimum2.8500023 × 108
Maximum2.8800014 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:32.267771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.8500023 × 108
5-th percentile2.8500024 × 108
Q12.8800003 × 108
median2.8800005 × 108
Q32.8800009 × 108
95-th percentile2.8800013 × 108
Maximum2.8800014 × 108
Range2999902
Interquartile range (IQR)57

Descriptive statistics

Standard deviation892272.73
Coefficient of variation (CV)0.003101336
Kurtosis5.31918
Mean2.8770592 × 108
Median Absolute Deviation (MAD)23
Skewness-2.7046763
Sum7.8342323 × 1011
Variance7.9615063 × 1011
MonotonicityIncreasing
2024-01-10T07:18:32.374135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
288000057 71
 
2.6%
288000051 68
 
2.5%
288000105 67
 
2.5%
288000053 65
 
2.4%
288000108 65
 
2.4%
288000063 61
 
2.2%
288000104 61
 
2.2%
288000065 61
 
2.2%
288000078 59
 
2.2%
288000036 59
 
2.2%
Other values (61) 2086
76.6%
ValueCountFrequency (%)
285000234 9
 
0.3%
285000235 9
 
0.3%
285000236 7
 
0.3%
285000237 8
 
0.3%
285000238 7
 
0.3%
285000239 6
 
0.2%
285000240 13
 
0.5%
285000241 12
 
0.4%
285000244 46
1.7%
285000245 48
1.8%
ValueCountFrequency (%)
288000136 28
1.0%
288000132 33
1.2%
288000131 25
0.9%
288000130 51
1.9%
288000128 34
1.2%
288000127 42
1.5%
288000125 36
1.3%
288000119 2
 
0.1%
288000113 31
1.1%
288000111 23
0.8%

노선정보그룹번호
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8792437 × 108
Minimum2.8500023 × 108
Maximum2.8800309 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:32.483275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.8500023 × 108
5-th percentile2.8800151 × 108
Q12.8800228 × 108
median2.8800291 × 108
Q32.8800303 × 108
95-th percentile2.8800309 × 108
Maximum2.8800309 × 108
Range3002858
Interquartile range (IQR)746

Descriptive statistics

Standard deviation478541.86
Coefficient of variation (CV)0.0016620401
Kurtosis33.442386
Mean2.8792437 × 108
Median Absolute Deviation (MAD)174
Skewness-5.951284
Sum7.8401807 × 1011
Variance2.2900231 × 1011
MonotonicityNot monotonic
2024-01-10T07:18:32.592364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
288003022 71
 
2.6%
288001820 68
 
2.5%
288003078 67
 
2.5%
288002046 65
 
2.4%
288003080 65
 
2.4%
288003023 61
 
2.2%
288003074 61
 
2.2%
288003021 61
 
2.2%
288003029 59
 
2.2%
288003042 59
 
2.2%
Other values (61) 2086
76.6%
ValueCountFrequency (%)
285000234 9
 
0.3%
285000235 9
 
0.3%
285000236 7
 
0.3%
285000237 8
 
0.3%
285000238 7
 
0.3%
285000239 6
 
0.2%
285000240 13
0.5%
285000241 12
0.4%
288001251 25
0.9%
288001299 23
0.8%
ValueCountFrequency (%)
288003092 43
1.6%
288003091 27
1.0%
288003089 35
1.3%
288003087 37
1.4%
288003082 51
1.9%
288003080 65
2.4%
288003078 67
2.5%
288003074 61
2.2%
288003043 36
1.3%
288003042 59
2.2%

노선명
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean511.80169
Minimum1
Maximum991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:32.704424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17
Q1303
median501
Q3777
95-th percentile981
Maximum991
Range990
Interquartile range (IQR)474

Descriptive statistics

Standard deviation299.3028
Coefficient of variation (CV)0.58480228
Kurtosis-1.0154837
Mean511.80169
Median Absolute Deviation (MAD)200
Skewness0.0011094345
Sum1393636
Variance89582.164
MonotonicityNot monotonic
2024-01-10T07:18:33.042626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
910 102
 
3.7%
900 94
 
3.5%
512 71
 
2.6%
451 68
 
2.5%
980 67
 
2.5%
501 65
 
2.4%
990 65
 
2.4%
610 61
 
2.2%
600 61
 
2.2%
970 61
 
2.2%
Other values (54) 2008
73.7%
ValueCountFrequency (%)
1 18
 
0.7%
2 23
0.8%
4 31
1.1%
10 2
 
0.1%
16 36
1.3%
17 42
1.5%
18 34
1.2%
20 51
1.9%
21 25
0.9%
22 33
1.2%
ValueCountFrequency (%)
991 51
1.9%
990 65
2.4%
981 44
1.6%
980 67
2.5%
970 61
2.2%
910 102
3.7%
900 94
3.5%
860 25
 
0.9%
850 33
 
1.2%
840 15
 
0.6%

정류장순번
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.62321
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:33.145188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q110
median21
Q335
95-th percentile53
Maximum71
Range70
Interquartile range (IQR)25

Descriptive statistics

Standard deviation15.728518
Coefficient of variation (CV)0.66580781
Kurtosis-0.53561287
Mean23.62321
Median Absolute Deviation (MAD)12
Skewness0.53001211
Sum64326
Variance247.38626
MonotonicityNot monotonic
2024-01-10T07:18:33.275822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 71
 
2.6%
2 71
 
2.6%
3 70
 
2.6%
4 70
 
2.6%
5 70
 
2.6%
6 70
 
2.6%
7 69
 
2.5%
8 67
 
2.5%
9 66
 
2.4%
12 64
 
2.4%
Other values (61) 2035
74.7%
ValueCountFrequency (%)
1 71
2.6%
2 71
2.6%
3 70
2.6%
4 70
2.6%
5 70
2.6%
6 70
2.6%
7 69
2.5%
8 67
2.5%
9 66
2.4%
10 64
2.4%
ValueCountFrequency (%)
71 1
 
< 0.1%
70 1
 
< 0.1%
69 1
 
< 0.1%
68 2
 
0.1%
67 3
0.1%
66 3
0.1%
65 5
0.2%
64 5
0.2%
63 5
0.2%
62 5
0.2%

노선길이
Real number (ℝ)

ZEROS 

Distinct597
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean283.49761
Minimum0
Maximum2137
Zeros40
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:33.424574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q1115.5
median211
Q3367
95-th percentile797.6
Maximum2137
Range2137
Interquartile range (IQR)251.5

Descriptive statistics

Standard deviation258.74434
Coefficient of variation (CV)0.91268613
Kurtosis7.0424057
Mean283.49761
Median Absolute Deviation (MAD)117
Skewness2.2011148
Sum771964
Variance66948.634
MonotonicityNot monotonic
2024-01-10T07:18:33.544697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40
 
1.5%
79 35
 
1.3%
137 33
 
1.2%
193 32
 
1.2%
80 27
 
1.0%
50 22
 
0.8%
227 21
 
0.8%
45 19
 
0.7%
3 19
 
0.7%
183 18
 
0.7%
Other values (587) 2457
90.2%
ValueCountFrequency (%)
0 40
1.5%
2 1
 
< 0.1%
3 19
0.7%
4 5
 
0.2%
5 4
 
0.1%
6 1
 
< 0.1%
9 2
 
0.1%
10 2
 
0.1%
11 1
 
< 0.1%
12 6
 
0.2%
ValueCountFrequency (%)
2137 1
 
< 0.1%
2076 1
 
< 0.1%
1750 6
0.2%
1649 1
 
< 0.1%
1635 1
 
< 0.1%
1634 1
 
< 0.1%
1550 1
 
< 0.1%
1489 2
 
0.1%
1438 6
0.2%
1368 1
 
< 0.1%

노선누적길이
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2211
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11655.703
Minimum0
Maximum40048
Zeros32
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:33.659780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile728
Q14172
median9938
Q317885
95-th percentile27252.8
Maximum40048
Range40048
Interquartile range (IQR)13713

Descriptive statistics

Standard deviation8631.6613
Coefficient of variation (CV)0.74055259
Kurtosis-0.47746007
Mean11655.703
Median Absolute Deviation (MAD)6639
Skewness0.60209349
Sum31738480
Variance74505577
MonotonicityNot monotonic
2024-01-10T07:18:33.771660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32
 
1.2%
3 12
 
0.4%
528 12
 
0.4%
2018 9
 
0.3%
1546 9
 
0.3%
39 9
 
0.3%
728 8
 
0.3%
1828 8
 
0.3%
2354 8
 
0.3%
2601 7
 
0.3%
Other values (2201) 2609
95.8%
ValueCountFrequency (%)
0 32
1.2%
3 12
 
0.4%
12 1
 
< 0.1%
16 1
 
< 0.1%
22 1
 
< 0.1%
25 2
 
0.1%
29 1
 
< 0.1%
30 1
 
< 0.1%
39 9
 
0.3%
52 1
 
< 0.1%
ValueCountFrequency (%)
40048 1
< 0.1%
39878 1
< 0.1%
39349 1
< 0.1%
38907 1
< 0.1%
38569 1
< 0.1%
38163 1
< 0.1%
38037 1
< 0.1%
37417 1
< 0.1%
36862 1
< 0.1%
36535 1
< 0.1%

전체노선길이
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23889.902
Minimum1615
Maximum40059
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:33.890822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1615
5-th percentile10533
Q118816
median24308
Q329927
95-th percentile36747
Maximum40059
Range38444
Interquartile range (IQR)11111

Descriptive statistics

Standard deviation7737.8258
Coefficient of variation (CV)0.32389525
Kurtosis-0.530508
Mean23889.902
Median Absolute Deviation (MAD)5619
Skewness-0.14230755
Sum65052204
Variance59873949
MonotonicityNot monotonic
2024-01-10T07:18:34.004413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40059 71
 
2.6%
32582 68
 
2.5%
36747 67
 
2.5%
33809 65
 
2.4%
31086 65
 
2.4%
36094 61
 
2.2%
30437 61
 
2.2%
30572 61
 
2.2%
27213 59
 
2.2%
30840 59
 
2.2%
Other values (61) 2086
76.6%
ValueCountFrequency (%)
1615 2
 
0.1%
5986 14
0.5%
7471 18
0.7%
7649 23
0.8%
9589 26
1.0%
9987 20
0.7%
10056 25
0.9%
10533 28
1.0%
11042 27
1.0%
11099 20
0.7%
ValueCountFrequency (%)
40059 71
2.6%
36747 67
2.5%
36094 61
2.2%
33809 65
2.4%
33397 54
2.0%
32582 68
2.5%
32305 47
1.7%
31086 65
2.4%
30840 59
2.2%
30572 61
2.2%

노선설명
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
평택
191 
송학면 환승센타
 
185
대흥리
 
182
방죽안오거리
 
172
종합터미널
 
136
Other values (44)
1857 

Length

Max length8
Median length7
Mean length4.3059126
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평택 191
 
7.0%
송학면 환승센타 185
 
6.8%
대흥리 182
 
6.7%
방죽안오거리 172
 
6.3%
종합터미널 136
 
5.0%
명암3리 117
 
4.3%
삽교호 115
 
4.2%
현충사 95
 
3.5%
천안아산역 94
 
3.5%
호서대학교 85
 
3.1%
Other values (39) 1351
49.6%

Length

2024-01-10T07:18:34.120070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평택 191
 
6.6%
송학면 185
 
6.4%
환승센타 185
 
6.4%
대흥리 182
 
6.3%
방죽안오거리 172
 
5.9%
종합터미널 136
 
4.7%
명암3리 117
 
4.0%
삽교호 115
 
4.0%
현충사 95
 
3.3%
천안아산역 94
 
3.2%
Other values (40) 1436
49.4%

노선정보설명
Text

Distinct67
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
2024-01-10T07:18:34.286826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length12.124862
Min length4

Characters and Unicode

Total characters33016
Distinct characters59
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

Unique0 ?
Unique (%)0.0%

Sample

1st row월랑1리 방면
2nd row월랑1리 방면
3rd row월랑1리 방면
4th row월랑1리 방면
5th row월랑1리 방면
ValueCountFrequency (%)
노선개편 524
 
14.2%
상행 179
 
4.8%
링크수정 140
 
3.8%
180808_701상 117
 
3.2%
방면 71
 
1.9%
08114_512상_0817 71
 
1.9%
08114_451상_0817 68
 
1.8%
980번_상행 67
 
1.8%
990번_상행 65
 
1.8%
501번_상행_0326 65
 
1.8%
Other values (63) 2326
63.0%
2024-01-10T07:18:34.568852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4577
13.9%
_ 3933
11.9%
1 3613
10.9%
상 2388
 
7.2%
8 2099
 
6.4%
번 1947
 
5.9%
행 1853
 
5.6%
2 1413
 
4.3%
3 1396
 
4.2%
1031
 
3.1%
Other values (49) 8766
26.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17207
52.1%
Other Letter 10659
32.3%
Connector Punctuation 3933
 
11.9%
Space Separator 1031
 
3.1%
Lowercase Letter 172
 
0.5%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 2388
22.4%
번 1947
18.3%
행 1853
17.4%
노 524
 
4.9%
선 524
 
4.9%
개 524
 
4.9%
편 524
 
4.9%
정 273
 
2.6%
하 166
 
1.6%
수 165
 
1.5%
Other values (32) 1771
16.6%
Decimal Number
ValueCountFrequency (%)
0 4577
26.6%
1 3613
21.0%
8 2099
12.2%
2 1413
 
8.2%
3 1396
 
8.1%
4 989
 
5.7%
7 823
 
4.8%
6 801
 
4.7%
5 793
 
4.6%
9 703
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
t 86
50.0%
e 43
25.0%
s 43
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3933
100.0%
Space Separator
ValueCountFrequency (%)
1031
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22185
67.2%
Hangul 10659
32.3%
Latin 172
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 2388
22.4%
번 1947
18.3%
행 1853
17.4%
노 524
 
4.9%
선 524
 
4.9%
개 524
 
4.9%
편 524
 
4.9%
정 273
 
2.6%
하 166
 
1.6%
수 165
 
1.5%
Other values (32) 1771
16.6%
Common
ValueCountFrequency (%)
0 4577
20.6%
_ 3933
17.7%
1 3613
16.3%
8 2099
9.5%
2 1413
 
6.4%
3 1396
 
6.3%
1031
 
4.6%
4 989
 
4.5%
7 823
 
3.7%
6 801
 
3.6%
Other values (4) 1510
 
6.8%
Latin
ValueCountFrequency (%)
t 86
50.0%
e 43
25.0%
s 43
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22357
67.7%
Hangul 10659
32.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4577
20.5%
_ 3933
17.6%
1 3613
16.2%
8 2099
9.4%
2 1413
 
6.3%
3 1396
 
6.2%
1031
 
4.6%
4 989
 
4.4%
7 823
 
3.7%
6 801
 
3.6%
Other values (7) 1682
 
7.5%
Hangul
ValueCountFrequency (%)
상 2388
22.4%
번 1947
18.3%
행 1853
17.4%
노 524
 
4.9%
선 524
 
4.9%
개 524
 
4.9%
편 524
 
4.9%
정 273
 
2.6%
하 166
 
1.6%
수 165
 
1.5%
Other values (32) 1771
16.6%

배차간격
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
<NA>
561 
40 ~ 240
 
115
160 ~ 240
 
112
120 ~ 180
 
105
40 ~ 140
 
97
Other values (39)
1733 

Length

Max length9
Median length8
Mean length6.6658098
Min length2

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> 561
20.6%
40 ~ 240 115
 
4.2%
160 ~ 240 112
 
4.1%
120 ~ 180 105
 
3.9%
40 ~ 140 97
 
3.6%
40 ~ 40 71
 
2.6%
60 ~ 130 68
 
2.5%
30 ~ 60 67
 
2.5%
160 ~ 280 65
 
2.4%
15 ~ 45 65
 
2.4%
Other values (34) 1397
51.3%

Length

2024-01-10T07:18:34.683521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1966
29.5%
na 561
 
8.4%
40 476
 
7.2%
120 349
 
5.2%
240 281
 
4.2%
60 272
 
4.1%
160 231
 
3.5%
10 214
 
3.2%
180 205
 
3.1%
20 158
 
2.4%
Other values (26) 1942
29.2%

출발정류장번호
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.878465 × 108
Minimum2.8500069 × 108
Maximum2.8801089 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:34.776398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.8500069 × 108
5-th percentile2.8500259 × 108
Q12.8800073 × 108
median2.8801017 × 108
Q32.8801073 × 108
95-th percentile2.8801073 × 108
Maximum2.8801089 × 108
Range3010200
Interquartile range (IQR)9997

Descriptive statistics

Standard deviation674902.1
Coefficient of variation (CV)0.0023446598
Kurtosis13.861701
Mean2.878465 × 108
Median Absolute Deviation (MAD)559
Skewness-3.9812807
Sum7.8380601 × 1011
Variance4.5549285 × 1011
MonotonicityNot monotonic
2024-01-10T07:18:34.890152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
288010726 854
31.4%
288010167 363
13.3%
288000489 308
 
11.3%
288000729 149
 
5.5%
288002093 128
 
4.7%
288010886 116
 
4.3%
285000686 95
 
3.5%
288000448 81
 
3.0%
288001472 61
 
2.2%
288001545 61
 
2.2%
Other values (20) 507
18.6%
ValueCountFrequency (%)
285000686 95
 
3.5%
285000989 36
 
1.3%
285001745 6
 
0.2%
285010152 8
 
0.3%
288000351 26
 
1.0%
288000448 81
 
3.0%
288000489 308
11.3%
288000729 149
5.5%
288000894 28
 
1.0%
288001074 43
 
1.6%
ValueCountFrequency (%)
288010886 116
 
4.3%
288010726 854
31.4%
288010485 2
 
0.1%
288010385 20
 
0.7%
288010170 44
 
1.6%
288010167 363
13.3%
288010138 44
 
1.6%
288010132 24
 
0.9%
288010039 18
 
0.7%
288002096 25
 
0.9%

도착정류장번호
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8221684 × 108
Minimum2.1401572 × 108
Maximum2.8801088 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:35.034853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.1401572 × 108
5-th percentile2.1401572 × 108
Q12.8507148 × 108
median2.8800091 × 108
Q32.8801021 × 108
95-th percentile2.8801062 × 108
Maximum2.8801088 × 108
Range73995155
Interquartile range (IQR)2938722

Descriptive statistics

Standard deviation18772562
Coefficient of variation (CV)0.066518222
Kurtosis9.2544798
Mean2.8221684 × 108
Median Absolute Deviation (MAD)9292
Skewness-3.3451143
Sum7.6847645 × 1011
Variance3.524091 × 1014
MonotonicityNot monotonic
2024-01-10T07:18:35.190775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
285010125 338
 
12.4%
214015723 191
 
7.0%
288010624 139
 
5.1%
288010009 117
 
4.3%
288000013 115
 
4.2%
288010206 114
 
4.2%
285000095 108
 
4.0%
288001632 85
 
3.1%
288010603 85
 
3.1%
288010445 78
 
2.9%
Other values (39) 1353
49.7%
ValueCountFrequency (%)
214015723 191
7.0%
285000095 108
 
4.0%
285001575 7
 
0.3%
285010125 338
12.4%
285010151 7
 
0.3%
285071484 35
 
1.3%
285071625 51
 
1.9%
288000013 115
 
4.2%
288000032 37
 
1.4%
288000112 68
 
2.5%
ValueCountFrequency (%)
288010878 20
 
0.7%
288010740 43
 
1.6%
288010725 14
 
0.5%
288010624 139
5.1%
288010603 85
3.1%
288010484 2
 
0.1%
288010447 33
 
1.2%
288010445 78
2.9%
288010440 38
 
1.4%
288010308 31
 
1.1%

회차여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
1
2456 
0
267 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 2456
90.2%
0 267
 
9.8%

Length

2024-01-10T07:18:35.327662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:35.418571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2456
90.2%
0 267
 
9.8%

회차지순번
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.21594
Minimum3
Maximum174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.1 KiB
2024-01-10T07:18:35.518551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile46
Q178
median104
Q3122
95-th percentile153
Maximum174
Range171
Interquartile range (IQR)44

Descriptive statistics

Standard deviation33.420918
Coefficient of variation (CV)0.33019422
Kurtosis0.14632889
Mean101.21594
Median Absolute Deviation (MAD)20
Skewness-0.11080162
Sum275611
Variance1116.9578
MonotonicityNot monotonic
2024-01-10T07:18:35.629003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96 141
 
5.2%
174 132
 
4.8%
78 123
 
4.5%
122 106
 
3.9%
104 86
 
3.2%
123 82
 
3.0%
74 82
 
3.0%
143 71
 
2.6%
116 68
 
2.5%
135 65
 
2.4%
Other values (49) 1767
64.9%
ValueCountFrequency (%)
3 6
0.2%
8 2
 
0.1%
11 7
0.3%
14 12
0.4%
19 7
0.3%
20 9
0.3%
24 9
0.3%
25 8
0.3%
31 14
0.5%
34 13
0.5%
ValueCountFrequency (%)
174 132
4.8%
153 53
1.9%
146 61
2.2%
143 71
2.6%
136 59
2.2%
135 65
2.4%
128 55
2.0%
127 49
 
1.8%
123 82
3.0%
122 106
3.9%

Interactions

2024-01-10T07:18:31.095404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:23.365134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.366220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.180908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.989026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.799031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.545069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.354341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.406293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.301882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.172048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:23.442754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.444111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.256886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.094129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.874946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.624816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.437378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.514224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.379750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.251728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:23.521519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.521253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.339033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.180466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.949080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.705811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.744290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.618812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.460093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.322263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:23.593185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.594449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.406717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.253979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.016398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.783782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.817384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.715472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.532199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.403132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:23.668976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.676406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.485781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.332479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.087736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.865608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.898784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.820339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.612875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.482358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:23.738180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.756233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.552354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.400009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.151634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.939744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.970674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.892878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.687195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.600790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.050547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.839848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.633317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.482514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.228736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.028836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.053916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.974169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.773975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.707133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.132402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.931461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.710102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.561331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.307538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.109349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.136544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.064852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.856088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.815001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.208879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.015158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.787839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.640165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.388201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.191038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.217341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.143167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.936039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.905265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:24.289105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.100856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:25.886693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:26.721500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:27.469085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:28.272400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:29.301949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:30.223924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:18:31.015477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:18:35.723582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선정보그룹번호노선명정류장순번노선길이노선누적길이전체노선길이노선설명노선정보설명배차간격출발정류장번호도착정류장번호회차여부회차지순번
노선번호1.0000.6700.7340.1470.0940.1670.3331.0001.0001.0000.688NaN1.0000.675
노선정보그룹번호0.6701.0000.7570.3170.0000.2530.3490.8811.000NaN0.951NaN0.6700.990
노선명0.7340.7571.0000.3310.2610.3920.7200.9971.0000.9940.665NaN0.7410.838
정류장순번0.1470.3170.3311.0000.3160.9360.3760.3830.4450.3400.300NaN0.1620.474
노선길이0.0940.0000.2610.3161.0000.3710.1190.2230.2420.1570.061NaN0.0990.139
노선누적길이0.1670.2530.3920.9360.3711.0000.4760.4800.5620.5110.234NaN0.1740.478
전체노선길이0.3330.3490.7200.3760.1190.4761.0000.9801.0000.9940.297NaN0.3360.773
노선설명1.0000.8810.9970.3830.2230.4800.9801.0001.0000.9990.959NaN1.0000.975
노선정보설명1.0001.0001.0000.4450.2420.5621.0001.0001.0001.0000.969NaN1.0000.999
배차간격1.000NaN0.9940.3400.1570.5110.9940.9991.0001.000NaNNaN1.0000.993
출발정류장번호0.6880.9510.6650.3000.0610.2340.2970.9590.969NaN1.000NaN0.7290.922
도착정류장번호NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1.000NaNNaN
회차여부1.0000.6700.7410.1620.0990.1740.3361.0001.0001.0000.729NaN1.0000.694
회차지순번0.6750.9900.8380.4740.1390.4780.7730.9750.9990.9930.922NaN0.6941.000
2024-01-10T07:18:35.838606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배차간격노선설명회차여부
배차간격1.0000.9440.990
노선설명0.9441.0000.991
회차여부0.9900.9911.000
2024-01-10T07:18:35.914783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선정보그룹번호노선명정류장순번노선길이노선누적길이전체노선길이출발정류장번호도착정류장번호회차지순번노선설명배차간격회차여부
노선번호1.0000.1630.0670.0740.0680.1520.3100.3140.0400.1200.9910.9900.998
노선정보그룹번호0.1631.0000.3120.161-0.0150.1240.3040.0880.1070.3840.7791.0000.492
노선명0.0670.3121.0000.149-0.0530.0870.295-0.074-0.3620.3800.9550.9330.580
정류장순번0.0740.1610.1491.0000.2710.9670.3780.083-0.1330.3580.1360.1220.124
노선길이0.068-0.015-0.0530.2711.0000.3100.1370.056-0.021-0.0020.0770.0540.076
노선누적길이0.1520.1240.0870.9670.3101.0000.4050.155-0.0900.3450.1820.2010.133
전체노선길이0.3100.3040.2950.3780.1370.4051.0000.252-0.3230.7480.8640.9370.335
출발정류장번호0.3140.088-0.0740.0830.0560.1550.2521.000-0.1770.3000.9440.9900.716
도착정류장번호0.0400.107-0.362-0.133-0.021-0.090-0.323-0.1771.000-0.2850.9910.9900.086
회차지순번0.1200.3840.3800.358-0.0020.3450.7480.300-0.2851.0000.8100.9380.541
노선설명0.9910.7790.9550.1360.0770.1820.8640.9440.9910.8101.0000.9440.991
배차간격0.9901.0000.9330.1220.0540.2010.9370.9900.9900.9380.9441.0000.990
회차여부0.9980.4920.5800.1240.0760.1330.3350.7160.0860.5410.9910.9901.000

Missing values

2024-01-10T07:18:32.011456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:18:32.155064image/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

노선번호노선정보그룹번호노선명정류장순번노선길이노선누적길이전체노선길이노선설명노선정보설명배차간격출발정류장번호도착정류장번호회차여부회차지순번
028500023428500023483010015103월랑리월랑1리 방면<NA>285000989288001997024
128500023428500023483027252815103월랑리월랑1리 방면<NA>285000989288001997024
22850002342850002348303217120115103월랑리월랑1리 방면<NA>285000989288001997024
32850002342850002348304353155415103월랑리월랑1리 방면<NA>285000989288001997024
428500023428500023483054376315103월랑리월랑1리 방면<NA>285000989288001997024
52850002342850002348306340434915103월랑리월랑1리 방면<NA>285000989288001997024
62850002342850002348307227479615103월랑리월랑1리 방면<NA>285000989288001997024
728500023428500023483081649644515103월랑리월랑1리 방면<NA>285000989288001997024
82850002342850002348309152668915103월랑리월랑1리 방면<NA>285000989288001997024
928500023528500023583010014514종합터미널백석농공단지 방면<NA>288001996285071484020
노선번호노선정보그룹번호노선명정류장순번노선길이노선누적길이전체노선길이노선설명노선정보설명배차간격출발정류장번호도착정류장번호회차여부회차지순번
27132880001362880017111511929642210533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
271428800013628800171115120282689210533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
271528800013628800171115121129724110533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
271628800013628800171115122191743210533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
27172880001362880017111512390777610533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
271828800013628800171115124277814510533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
271928800013628800171115125193847810533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
27202880001362880017111512679887610533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
27212880001362880017111512779925610533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154
272228800013628800171115128152974210533아산시평생학습관0611_151 정류장 추가<NA>288000894288000715154