Overview

Dataset statistics

Number of variables8
Number of observations149
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.0 KiB
Average record size in memory68.9 B

Variable types

Categorical2
Text2
Numeric4

Dataset

Description부산교통공사_소음측정정보_20191231
Author부산교통공사
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15083212

Alerts

호선.1 is highly overall correlated with 호선High correlation
호선 is highly overall correlated with 호선.1High correlation
평균(Leq) is highly overall correlated with 최대(Lmax) and 1 other fieldsHigh correlation
최대(Lmax) is highly overall correlated with 평균(Leq)High correlation
평균(Leq).1 is highly overall correlated with 평균(Leq) and 1 other fieldsHigh correlation
최대(Lmax).1 is highly overall correlated with 평균(Leq).1High correlation

Reproduction

Analysis started2023-12-10 17:30:46.161806
Analysis finished2023-12-10 17:30:51.608868
Duration5.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

호선
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2호선
42 
1호선(신차)
39 
1호선(구차)
39 
3호선
16 
4호선
13 

Length

Max length7
Median length7
Mean length5.0939597
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호선(신차)
2nd row1호선(신차)
3rd row1호선(신차)
4th row1호선(신차)
5th row1호선(신차)

Common Values

ValueCountFrequency (%)
2호선 42
28.2%
1호선(신차) 39
26.2%
1호선(구차) 39
26.2%
3호선 16
 
10.7%
4호선 13
 
8.7%

Length

2023-12-11T02:30:51.810696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:30:52.117143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2호선 42
28.2%
1호선(신차 39
26.2%
1호선(구차 39
26.2%
3호선 16
 
10.7%
4호선 13
 
8.7%

구간
Text

Distinct112
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T02:30:52.844564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length6.2348993
Min length5

Characters and Unicode

Total characters929
Distinct characters135
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)50.3%

Sample

1st row노포→범어사
2nd row범어사→남산
3rd row남산→두실
4th row두실→구서
5th row구서→장전
ValueCountFrequency (%)
노포→범어사 2
 
1.3%
중앙→남포 2
 
1.3%
범어사→남산 2
 
1.3%
자갈치→토성 2
 
1.3%
토성→동대신 2
 
1.3%
동대신→서대신 2
 
1.3%
서대신→대티 2
 
1.3%
대티→괴정 2
 
1.3%
남포→자갈치 2
 
1.3%
초량→부산역 2
 
1.3%
Other values (102) 129
86.6%
2023-12-11T02:30:53.906857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
→ 149
 
16.0%
산 46
 
5.0%
대 45
 
4.8%
동 30
 
3.2%
28
 
3.0%
부 26
 
2.8%
장 25
 
2.7%
포 20
 
2.2%
남 19
 
2.0%
서 18
 
1.9%
Other values (125) 523
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 746
80.3%
Math Symbol 149
 
16.0%
Space Separator 28
 
3.0%
Other Punctuation 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 46
 
6.2%
대 45
 
6.0%
동 30
 
4.0%
부 26
 
3.5%
장 25
 
3.4%
포 20
 
2.7%
남 19
 
2.5%
서 18
 
2.4%
신 16
 
2.1%
사 16
 
2.1%
Other values (122) 485
65.0%
Math Symbol
ValueCountFrequency (%)
→ 149
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Other Punctuation
ValueCountFrequency (%)
? 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 746
80.3%
Common 183
 
19.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 46
 
6.2%
대 45
 
6.0%
동 30
 
4.0%
부 26
 
3.5%
장 25
 
3.4%
포 20
 
2.7%
남 19
 
2.5%
서 18
 
2.4%
신 16
 
2.1%
사 16
 
2.1%
Other values (122) 485
65.0%
Common
ValueCountFrequency (%)
→ 149
81.4%
28
 
15.3%
? 6
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 746
80.3%
Arrows 149
 
16.0%
ASCII 34
 
3.7%

Most frequent character per block

Arrows
ValueCountFrequency (%)
→ 149
100.0%
Hangul
ValueCountFrequency (%)
산 46
 
6.2%
대 45
 
6.0%
동 30
 
4.0%
부 26
 
3.5%
장 25
 
3.4%
포 20
 
2.7%
남 19
 
2.5%
서 18
 
2.4%
신 16
 
2.1%
사 16
 
2.1%
Other values (122) 485
65.0%
ASCII
ValueCountFrequency (%)
28
82.4%
? 6
 
17.6%

평균(Leq)
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.64698
Minimum57.7
Maximum78.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T02:30:54.262626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57.7
5-th percentile59.84
Q165.9
median69.3
Q371.6
95-th percentile74.52
Maximum78.1
Range20.4
Interquartile range (IQR)5.7

Descriptive statistics

Standard deviation4.3377594
Coefficient of variation (CV)0.063189369
Kurtosis-0.19915877
Mean68.64698
Median Absolute Deviation (MAD)2.8
Skewness-0.52870878
Sum10228.4
Variance18.816156
MonotonicityNot monotonic
2023-12-11T02:30:54.622661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69.3 6
 
4.0%
70.3 5
 
3.4%
71.2 5
 
3.4%
70.9 4
 
2.7%
65.9 4
 
2.7%
66.8 4
 
2.7%
68.9 4
 
2.7%
70.7 4
 
2.7%
72.2 3
 
2.0%
71.6 2
 
1.3%
Other values (87) 108
72.5%
ValueCountFrequency (%)
57.7 2
1.3%
59.1 2
1.3%
59.2 1
0.7%
59.6 1
0.7%
59.7 1
0.7%
59.8 1
0.7%
59.9 1
0.7%
61.2 1
0.7%
61.5 1
0.7%
61.8 2
1.3%
ValueCountFrequency (%)
78.1 1
0.7%
77.2 1
0.7%
76.4 1
0.7%
76.2 1
0.7%
75.8 1
0.7%
75.6 1
0.7%
74.7 1
0.7%
74.6 1
0.7%
74.4 2
1.3%
74.2 1
0.7%

최대(Lmax)
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.484564
Minimum63.2
Maximum87.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T02:30:54.999388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum63.2
5-th percentile67
Q172.4
median75.2
Q377.9
95-th percentile84.44
Maximum87.5
Range24.3
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation4.846045
Coefficient of variation (CV)0.064199152
Kurtosis0.077355095
Mean75.484564
Median Absolute Deviation (MAD)2.8
Skewness0.12063039
Sum11247.2
Variance23.484152
MonotonicityNot monotonic
2023-12-11T02:30:55.335764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.9 5
 
3.4%
73.5 4
 
2.7%
65.2 4
 
2.7%
77.0 4
 
2.7%
75.2 4
 
2.7%
82.1 4
 
2.7%
73.9 3
 
2.0%
76.5 3
 
2.0%
85.6 3
 
2.0%
71.8 3
 
2.0%
Other values (83) 112
75.2%
ValueCountFrequency (%)
63.2 1
 
0.7%
65.2 4
2.7%
65.5 1
 
0.7%
66.8 2
1.3%
67.3 2
1.3%
69.0 1
 
0.7%
69.1 1
 
0.7%
69.3 1
 
0.7%
69.6 1
 
0.7%
69.7 1
 
0.7%
ValueCountFrequency (%)
87.5 1
 
0.7%
86.5 1
 
0.7%
86.1 1
 
0.7%
85.6 3
2.0%
84.8 1
 
0.7%
84.6 1
 
0.7%
84.2 1
 
0.7%
84.0 1
 
0.7%
82.8 1
 
0.7%
82.4 2
1.3%

호선.1
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2호선
42 
1호선(신차)
39 
1호선(구차)
39 
3호선
16 
4호선
13 

Length

Max length7
Median length7
Mean length5.0939597
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호선(신차)
2nd row1호선(신차)
3rd row1호선(신차)
4th row1호선(신차)
5th row1호선(신차)

Common Values

ValueCountFrequency (%)
2호선 42
28.2%
1호선(신차) 39
26.2%
1호선(구차) 39
26.2%
3호선 16
 
10.7%
4호선 13
 
8.7%

Length

2023-12-11T02:30:55.622483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:30:55.881169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2호선 42
28.2%
1호선(신차 39
26.2%
1호선(구차 39
26.2%
3호선 16
 
10.7%
4호선 13
 
8.7%

구간.1
Text

Distinct110
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T02:30:56.392284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.1744966
Min length5

Characters and Unicode

Total characters920
Distinct characters135
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)47.7%

Sample

1st row다대포해수욕장→다대포항
2nd row다대포항→낫개
3rd row낫개→신장림
4th row신장림→장림
5th row장림→동매
ValueCountFrequency (%)
다대포해수욕장→다대포항 2
 
1.3%
동대신→토성 2
 
1.3%
동래→명륜 2
 
1.3%
다대포항→낫개 2
 
1.3%
서면→부전 2
 
1.3%
부전→양정 2
 
1.3%
양정→시청 2
 
1.3%
시청→연산 2
 
1.3%
연산→교대 2
 
1.3%
교대→동래 2
 
1.3%
Other values (100) 129
86.6%
2023-12-11T02:30:57.139775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
→ 149
 
16.2%
산 46
 
5.0%
대 45
 
4.9%
동 28
 
3.0%
부 26
 
2.8%
24
 
2.6%
장 23
 
2.5%
포 20
 
2.2%
남 19
 
2.1%
서 18
 
2.0%
Other values (125) 522
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 742
80.7%
Math Symbol 149
 
16.2%
Space Separator 24
 
2.6%
Other Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 46
 
6.2%
대 45
 
6.1%
동 28
 
3.8%
부 26
 
3.5%
장 23
 
3.1%
포 20
 
2.7%
남 19
 
2.6%
서 18
 
2.4%
신 16
 
2.2%
사 16
 
2.2%
Other values (122) 485
65.4%
Math Symbol
ValueCountFrequency (%)
→ 149
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Punctuation
ValueCountFrequency (%)
? 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 742
80.7%
Common 178
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 46
 
6.2%
대 45
 
6.1%
동 28
 
3.8%
부 26
 
3.5%
장 23
 
3.1%
포 20
 
2.7%
남 19
 
2.6%
서 18
 
2.4%
신 16
 
2.2%
사 16
 
2.2%
Other values (122) 485
65.4%
Common
ValueCountFrequency (%)
→ 149
83.7%
24
 
13.5%
? 5
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 742
80.7%
Arrows 149
 
16.2%
ASCII 29
 
3.2%

Most frequent character per block

Arrows
ValueCountFrequency (%)
→ 149
100.0%
Hangul
ValueCountFrequency (%)
산 46
 
6.2%
대 45
 
6.1%
동 28
 
3.8%
부 26
 
3.5%
장 23
 
3.1%
포 20
 
2.7%
남 19
 
2.6%
서 18
 
2.4%
신 16
 
2.2%
사 16
 
2.2%
Other values (122) 485
65.4%
ASCII
ValueCountFrequency (%)
24
82.8%
? 5
 
17.2%

평균(Leq).1
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.389933
Minimum57.2
Maximum76.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T02:30:57.393580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57.2
5-th percentile59.66
Q165.6
median69.3
Q371.4
95-th percentile74.36
Maximum76.9
Range19.7
Interquartile range (IQR)5.8

Descriptive statistics

Standard deviation4.3940953
Coefficient of variation (CV)0.064250616
Kurtosis-0.30891805
Mean68.389933
Median Absolute Deviation (MAD)2.6
Skewness-0.60104259
Sum10190.1
Variance19.308074
MonotonicityNot monotonic
2023-12-11T02:30:57.668634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.7 4
 
2.7%
71.3 4
 
2.7%
71.4 4
 
2.7%
68.9 4
 
2.7%
67.2 3
 
2.0%
65.6 3
 
2.0%
68.6 3
 
2.0%
70.1 3
 
2.0%
69.5 3
 
2.0%
69.9 3
 
2.0%
Other values (87) 115
77.2%
ValueCountFrequency (%)
57.2 1
0.7%
58.0 1
0.7%
58.5 1
0.7%
58.6 1
0.7%
58.7 1
0.7%
58.8 1
0.7%
58.9 1
0.7%
59.5 1
0.7%
59.9 1
0.7%
60.5 1
0.7%
ValueCountFrequency (%)
76.9 1
0.7%
76.2 1
0.7%
75.8 1
0.7%
75.2 1
0.7%
74.9 1
0.7%
74.7 2
1.3%
74.4 1
0.7%
74.3 1
0.7%
74.1 1
0.7%
73.7 1
0.7%

최대(Lmax).1
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.22953
Minimum62.1
Maximum87.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T02:30:57.967316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62.1
5-th percentile66.7
Q172.5
median75.2
Q378.4
95-th percentile83.24
Maximum87.8
Range25.7
Interquartile range (IQR)5.9

Descriptive statistics

Standard deviation5.0654567
Coefficient of variation (CV)0.067333356
Kurtosis0.066875939
Mean75.22953
Median Absolute Deviation (MAD)3
Skewness-0.12775328
Sum11209.2
Variance25.658852
MonotonicityNot monotonic
2023-12-11T02:30:58.250587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.8 5
 
3.4%
78.9 4
 
2.7%
75.2 4
 
2.7%
76.9 3
 
2.0%
73.5 3
 
2.0%
72.7 3
 
2.0%
75.0 3
 
2.0%
78.8 3
 
2.0%
72.5 3
 
2.0%
78.2 2
 
1.3%
Other values (95) 116
77.9%
ValueCountFrequency (%)
62.1 1
0.7%
63.7 1
0.7%
63.8 1
0.7%
63.9 1
0.7%
64.0 1
0.7%
64.1 1
0.7%
65.7 1
0.7%
66.7 2
1.3%
66.9 1
0.7%
67.0 1
0.7%
ValueCountFrequency (%)
87.8 1
0.7%
87.4 1
0.7%
86.1 1
0.7%
85.7 1
0.7%
83.9 1
0.7%
83.8 1
0.7%
83.5 1
0.7%
83.4 1
0.7%
83.0 1
0.7%
82.9 2
1.3%

Interactions

2023-12-11T02:30:49.623235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:47.046586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:48.063326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:48.826151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:49.883457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:47.340224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:48.295645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:49.046981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:50.085771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:47.574247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:48.467110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:49.222028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:50.337483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:47.832553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:48.670637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:30:49.433953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:30:58.410691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선평균(Leq)최대(Lmax)호선.1평균(Leq).1최대(Lmax).1
호선1.0000.7950.7461.0000.8420.735
평균(Leq)0.7951.0000.8960.7950.5540.424
최대(Lmax)0.7460.8961.0000.7460.5880.425
호선.11.0000.7950.7461.0000.8420.735
평균(Leq).10.8420.5540.5880.8421.0000.880
최대(Lmax).10.7350.4240.4250.7350.8801.000
2023-12-11T02:30:58.577105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선.1호선
호선.11.0001.000
호선1.0001.000
2023-12-11T02:30:58.714084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평균(Leq)최대(Lmax)평균(Leq).1최대(Lmax).1호선호선.1
평균(Leq)1.0000.9110.5440.4760.4430.443
최대(Lmax)0.9111.0000.4910.4360.3950.395
평균(Leq).10.5440.4911.0000.9020.4950.495
최대(Lmax).10.4760.4360.9021.0000.3860.386
호선0.4430.3950.4950.3861.0001.000
호선.10.4430.3950.4950.3861.0001.000

Missing values

2023-12-11T02:30:50.589723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:30:51.420211image/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

호선구간평균(Leq)최대(Lmax)호선.1구간.1평균(Leq).1최대(Lmax).1
01호선(신차)노포→범어사67.373.41호선(신차)다대포해수욕장→다대포항75.280.5
11호선(신차)범어사→남산71.274.51호선(신차)다대포항→낫개73.679.4
21호선(신차)남산→두실72.276.61호선(신차)낫개→신장림73.279.0
31호선(신차)두실→구서70.775.41호선(신차)신장림→장림73.277.1
41호선(신차)구서→장전69.376.01호선(신차)장림→동매73.682.5
51호선(신차)장전→부산대69.373.91호선(신차)동매→신평76.985.7
61호선(신차)부산대→온천장68.973.91호선(신차)신평→하단70.477.9
71호선(신차)온천장→명륜68.774.91호선(신차)하단→당리71.676.9
81호선(신차)명륜→동래68.372.31호선(신차)당리→사하68.874.6
91호선(신차)동래→교대68.874.71호선(신차)사하→괴정69.574.8
호선구간평균(Leq)최대(Lmax)호선.1구간.1평균(Leq).1최대(Lmax).1
1394호선영산대→석대67.572.54호선낙민→충렬사65.669.1
1404호선석대→반여농산물시장68.173.34호선충렬사→명장64.869.1
1414호선반여농산물시장→금사68.674.94호선명장→서동65.670.6
1424호선금사→서동66.073.24호선서동→금사65.672.9
1434호선서동→명장66.870.14호선금사→반여농산물시장67.075.4
1444호선명장→충렬사69.375.14호선반여농산물시장→석대68.273.0
1454호선충렬사→낙민67.174.44호선석대→영산대68.174.8
1464호선낙민→수안68.974.64호선영산대→동부산대학65.972.8
1474호선수안→동래68.974.34호선동부산대학→고촌65.873.5
1484호선동래→미남65.369.84호선고촌→안평63.669.7