Overview

Dataset statistics

Number of variables8
Number of observations95
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory66.4 B

Variable types

Numeric1
Text3
Categorical4

Dataset

Description부산교통공사_도시철도역세권관광지현황_20201020
Author부산교통공사
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3057433

Alerts

역번호 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
인근역명 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 호선 and 2 other fieldsHigh correlation
호선 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연락처 has 2 (2.1%) missing valuesMissing
연번 has unique valuesUnique
관광지명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:47:35.517280
Analysis finished2023-12-10 17:47:38.269669
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-11T02:47:38.497999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.7
Q124.5
median48
Q371.5
95-th percentile90.3
Maximum95
Range94
Interquartile range (IQR)47

Descriptive statistics

Standard deviation27.568098
Coefficient of variation (CV)0.57433536
Kurtosis-1.2
Mean48
Median Absolute Deviation (MAD)24
Skewness0
Sum4560
Variance760
MonotonicityStrictly increasing
2023-12-11T02:47:38.861298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
2 1
 
1.1%
71 1
 
1.1%
70 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
Other values (85) 85
89.5%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
95 1
1.1%
94 1
1.1%
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%

관광지명
Text

UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-11T02:47:39.502974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.3052632
Min length3

Characters and Unicode

Total characters694
Distinct characters215
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)100.0%

Sample

1st row다대포 해수욕장·꿈의낙조분수
2nd row아미산전망대
3rd row몰운대
4th row을숙도 조각공원
5th row을숙도 문화회관
ValueCountFrequency (%)
을숙도 3
 
2.2%
해수욕장 3
 
2.2%
낙동강 3
 
2.2%
해운대 2
 
1.5%
부산 2
 
1.5%
먹자골목 2
 
1.5%
서면 2
 
1.5%
apec 2
 
1.5%
다대포 1
 
0.7%
하우스 1
 
0.7%
Other values (116) 116
84.7%
2023-12-11T02:47:40.501022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
6.1%
원 21
 
3.0%
공 20
 
2.9%
관 19
 
2.7%
산 17
 
2.4%
해 15
 
2.2%
부 15
 
2.2%
대 15
 
2.2%
동 13
 
1.9%
장 13
 
1.9%
Other values (205) 504
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 608
87.6%
Space Separator 42
 
6.1%
Uppercase Letter 26
 
3.7%
Open Punctuation 7
 
1.0%
Close Punctuation 7
 
1.0%
Decimal Number 3
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 21
 
3.5%
공 20
 
3.3%
관 19
 
3.1%
산 17
 
2.8%
해 15
 
2.5%
부 15
 
2.5%
대 15
 
2.5%
동 13
 
2.1%
장 13
 
2.1%
수 12
 
2.0%
Other values (185) 448
73.7%
Uppercase Letter
ValueCountFrequency (%)
E 5
19.2%
F 3
11.5%
A 3
11.5%
C 3
11.5%
B 2
 
7.7%
I 2
 
7.7%
P 2
 
7.7%
L 1
 
3.8%
S 1
 
3.8%
O 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
0 1
33.3%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 608
87.6%
Common 60
 
8.6%
Latin 26
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 21
 
3.5%
공 20
 
3.3%
관 19
 
3.1%
산 17
 
2.8%
해 15
 
2.5%
부 15
 
2.5%
대 15
 
2.5%
동 13
 
2.1%
장 13
 
2.1%
수 12
 
2.0%
Other values (185) 448
73.7%
Latin
ValueCountFrequency (%)
E 5
19.2%
F 3
11.5%
A 3
11.5%
C 3
11.5%
B 2
 
7.7%
I 2
 
7.7%
P 2
 
7.7%
L 1
 
3.8%
S 1
 
3.8%
O 1
 
3.8%
Other values (3) 3
11.5%
Common
ValueCountFrequency (%)
42
70.0%
( 7
 
11.7%
) 7
 
11.7%
· 1
 
1.7%
1 1
 
1.7%
0 1
 
1.7%
4 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 608
87.6%
ASCII 85
 
12.2%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
49.4%
( 7
 
8.2%
) 7
 
8.2%
E 5
 
5.9%
F 3
 
3.5%
A 3
 
3.5%
C 3
 
3.5%
B 2
 
2.4%
I 2
 
2.4%
P 2
 
2.4%
Other values (9) 9
 
10.6%
Hangul
ValueCountFrequency (%)
원 21
 
3.5%
공 20
 
3.3%
관 19
 
3.1%
산 17
 
2.8%
해 15
 
2.5%
부 15
 
2.5%
대 15
 
2.5%
동 13
 
2.1%
장 13
 
2.1%
수 12
 
2.0%
Other values (185) 448
73.7%
None
ValueCountFrequency (%)
· 1
100.0%

연락처
Text

MISSING 

Distinct84
Distinct (%)90.3%
Missing2
Missing (%)2.1%
Memory size892.0 B
2023-12-11T02:47:41.008550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.064516
Min length12

Characters and Unicode

Total characters1122
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)84.9%

Sample

1st row051-207-6041
2nd row051-265-6863
3rd row051-220-4071
4th row051-2205-8014
5th row051-2205-8014
ValueCountFrequency (%)
051-220-1444 4
 
4.3%
051-605-0116 3
 
3.2%
051-2205-8014 3
 
3.2%
051-5500-3314 2
 
2.2%
051-605-4091 2
 
2.2%
051-780-6000 1
 
1.1%
051-508-3122 1
 
1.1%
051-749-4000 1
 
1.1%
051-740-7300 1
 
1.1%
051-720-0323 1
 
1.1%
Other values (74) 74
79.6%
2023-12-11T02:47:41.907132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 232
20.7%
- 186
16.6%
5 154
13.7%
1 148
13.2%
4 103
9.2%
2 80
 
7.1%
7 52
 
4.6%
3 51
 
4.5%
6 45
 
4.0%
8 41
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936
83.4%
Dash Punctuation 186
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 232
24.8%
5 154
16.5%
1 148
15.8%
4 103
11.0%
2 80
 
8.5%
7 52
 
5.6%
3 51
 
5.4%
6 45
 
4.8%
8 41
 
4.4%
9 30
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1122
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 232
20.7%
- 186
16.6%
5 154
13.7%
1 148
13.2%
4 103
9.2%
2 80
 
7.1%
7 52
 
4.6%
3 51
 
4.5%
6 45
 
4.0%
8 41
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 232
20.7%
- 186
16.6%
5 154
13.7%
1 148
13.2%
4 103
9.2%
2 80
 
7.1%
7 52
 
4.6%
3 51
 
4.5%
6 45
 
4.0%
8 41
 
3.7%

주소
Text

Distinct87
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-11T02:47:42.642490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length19.126316
Min length12

Characters and Unicode

Total characters1817
Distinct characters140
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)86.3%

Sample

1st row부산광역시 사하구 다대동
2nd row부산광역시 사하구 다대낙조 2길 77
3rd row부산광역시 사하구 몰운대1길 73
4th row부산광역시 사하구 낙동남로 1233번길 25
5th row부산광역시 사하구 낙동남로 1233번길 25
ValueCountFrequency (%)
부산광역시 91
 
22.6%
해운대구 14
 
3.5%
사하구 13
 
3.2%
중구 12
 
3.0%
동래구 10
 
2.5%
남구 8
 
2.0%
서구 7
 
1.7%
낙동남로 6
 
1.5%
영도구 6
 
1.5%
부산진구 6
 
1.5%
Other values (168) 229
57.0%
2023-12-11T02:47:43.674386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
307
16.9%
산 102
 
5.6%
부 100
 
5.5%
시 99
 
5.4%
광 96
 
5.3%
역 93
 
5.1%
구 92
 
5.1%
로 73
 
4.0%
1 66
 
3.6%
동 44
 
2.4%
Other values (130) 745
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1199
66.0%
Space Separator 307
 
16.9%
Decimal Number 281
 
15.5%
Uppercase Letter 12
 
0.7%
Dash Punctuation 10
 
0.6%
Other Punctuation 4
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 102
 
8.5%
부 100
 
8.3%
시 99
 
8.3%
광 96
 
8.0%
역 93
 
7.8%
구 92
 
7.7%
로 73
 
6.1%
동 44
 
3.7%
대 35
 
2.9%
길 30
 
2.5%
Other values (111) 435
36.3%
Decimal Number
ValueCountFrequency (%)
1 66
23.5%
2 39
13.9%
3 34
12.1%
6 26
 
9.3%
7 22
 
7.8%
4 22
 
7.8%
5 21
 
7.5%
9 20
 
7.1%
8 17
 
6.0%
0 14
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
A 3
25.0%
P 3
25.0%
E 3
25.0%
C 3
25.0%
Space Separator
ValueCountFrequency (%)
307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1199
66.0%
Common 606
33.4%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 102
 
8.5%
부 100
 
8.3%
시 99
 
8.3%
광 96
 
8.0%
역 93
 
7.8%
구 92
 
7.7%
로 73
 
6.1%
동 44
 
3.7%
대 35
 
2.9%
길 30
 
2.5%
Other values (111) 435
36.3%
Common
ValueCountFrequency (%)
307
50.7%
1 66
 
10.9%
2 39
 
6.4%
3 34
 
5.6%
6 26
 
4.3%
7 22
 
3.6%
4 22
 
3.6%
5 21
 
3.5%
9 20
 
3.3%
8 17
 
2.8%
Other values (5) 32
 
5.3%
Latin
ValueCountFrequency (%)
A 3
25.0%
P 3
25.0%
E 3
25.0%
C 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1198
65.9%
ASCII 618
34.0%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
49.7%
1 66
 
10.7%
2 39
 
6.3%
3 34
 
5.5%
6 26
 
4.2%
7 22
 
3.6%
4 22
 
3.6%
5 21
 
3.4%
9 20
 
3.2%
8 17
 
2.8%
Other values (9) 44
 
7.1%
Hangul
ValueCountFrequency (%)
산 102
 
8.5%
부 100
 
8.3%
시 99
 
8.3%
광 96
 
8.0%
역 93
 
7.8%
구 92
 
7.7%
로 73
 
6.1%
동 44
 
3.7%
대 35
 
2.9%
길 30
 
2.5%
Other values (110) 434
36.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

출구번호
Categorical

Distinct21
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
1
25 
5
14 
8
10 
2
9 
57
5 
Other values (16)
32 

Length

Max length5
Median length1
Mean length1.3578947
Min length1

Unique

Unique7 ?
Unique (%)7.4%

Sample

1st row24
2nd row1
3rd row4
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 25
26.3%
5 14
14.7%
8 10
 
10.5%
2 9
 
9.5%
57 5
 
5.3%
3 4
 
4.2%
13 4
 
4.2%
4 3
 
3.2%
10 3
 
3.2%
7 3
 
3.2%
Other values (11) 15
15.8%

Length

2023-12-11T02:47:44.083287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 25
25.8%
5 14
14.4%
8 10
 
10.3%
2 9
 
9.3%
57 5
 
5.2%
3 4
 
4.1%
13 4
 
4.1%
4 3
 
3.1%
10 3
 
3.1%
7 3
 
3.1%
Other values (12) 17
17.5%

호선
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size892.0 B
1
51 
2
26 
4
 
4
김해경전철
 
4
12
 
3
Other values (3)
7 

Length

Max length5
Median length1
Mean length1.2421053
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 51
53.7%
2 26
27.4%
4 4
 
4.2%
김해경전철 4
 
4.2%
12 3
 
3.2%
14 3
 
3.2%
3 3
 
3.2%
23 1
 
1.1%

Length

2023-12-11T02:47:44.500093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:47:44.871557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 51
53.7%
2 26
27.4%
4 4
 
4.2%
김해경전철 4
 
4.2%
12 3
 
3.2%
14 3
 
3.2%
3 3
 
3.2%
23 1
 
1.1%

인근역명
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Memory size892.0 B
남포역
11 
토성역
8 
하단역
 
6
부산역
 
5
대연역
 
5
Other values (28)
60 

Length

Max length7
Median length3
Mean length3.5894737
Min length3

Unique

Unique11 ?
Unique (%)11.6%

Sample

1st row다대포해수욕장
2nd row다대포해수욕장
3rd row다대포해수욕장
4th row하단역
5th row하단역

Common Values

ValueCountFrequency (%)
남포역 11
 
11.6%
토성역 8
 
8.4%
하단역 6
 
6.3%
부산역 5
 
5.3%
대연역 5
 
5.3%
해운대역 4
 
4.2%
자갈치역 4
 
4.2%
중앙역 4
 
4.2%
온천장역 4
 
4.2%
동백역 3
 
3.2%
Other values (23) 41
43.2%

Length

2023-12-11T02:47:45.375850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남포역 11
 
11.6%
토성역 8
 
8.4%
하단역 6
 
6.3%
부산역 5
 
5.3%
대연역 5
 
5.3%
해운대역 4
 
4.2%
자갈치역 4
 
4.2%
중앙역 4
 
4.2%
온천장역 4
 
4.2%
시립미술관역 3
 
3.2%
Other values (23) 41
43.2%

역번호
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)32.6%
Missing0
Missing (%)0.0%
Memory size892.0 B
111
11 
109
8 
102
 
6
213
 
5
113
 
5
Other values (26)
60 

Length

Max length5
Median length3
Mean length3.0526316
Min length2

Unique

Unique9 ?
Unique (%)9.5%

Sample

1st row95
2nd row95
3rd row95
4th row102
5th row102

Common Values

ValueCountFrequency (%)
111 11
 
11.6%
109 8
 
8.4%
102 6
 
6.3%
213 5
 
5.3%
113 5
 
5.3%
203 4
 
4.2%
127 4
 
4.2%
김해경전철 4
 
4.2%
112 4
 
4.2%
110 4
 
4.2%
Other values (21) 40
42.1%

Length

2023-12-11T02:47:46.879287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
111 11
 
11.6%
109 8
 
8.4%
102 6
 
6.3%
213 5
 
5.3%
113 5
 
5.3%
203 4
 
4.2%
127 4
 
4.2%
김해경전철 4
 
4.2%
112 4
 
4.2%
110 4
 
4.2%
Other values (21) 40
42.1%

Interactions

2023-12-11T02:47:37.542893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:47:47.169754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관광지명연락처주소출구번호호선인근역명역번호
연번1.0001.0000.9930.9920.6730.7820.9820.983
관광지명1.0001.0001.0001.0001.0001.0001.0001.000
연락처0.9931.0001.0000.9990.8031.0000.9960.995
주소0.9921.0000.9991.0001.0001.0001.0001.000
출구번호0.6731.0000.8031.0001.0000.7460.8690.880
호선0.7821.0001.0001.0000.7461.0001.0001.000
인근역명0.9821.0000.9961.0000.8691.0001.0001.000
역번호0.9831.0000.9951.0000.8801.0001.0001.000
2023-12-11T02:47:47.430014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구번호역번호호선인근역명
출구번호1.0000.4020.3900.373
역번호0.4021.0000.8580.984
호선0.3900.8581.0000.844
인근역명0.3730.9840.8441.000
2023-12-11T02:47:47.666169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번출구번호호선인근역명역번호
연번1.0000.2970.5190.7470.763
출구번호0.2971.0000.3900.3730.402
호선0.5190.3901.0000.8440.858
인근역명0.7470.3730.8441.0000.984
역번호0.7630.4020.8580.9841.000

Missing values

2023-12-11T02:47:37.829601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:47:38.155942image/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

연번관광지명연락처주소출구번호호선인근역명역번호
01다대포 해수욕장·꿈의낙조분수051-207-6041부산광역시 사하구 다대동241다대포해수욕장95
12아미산전망대051-265-6863부산광역시 사하구 다대낙조 2길 7711다대포해수욕장95
23몰운대051-220-4071부산광역시 사하구 몰운대1길 7341다대포해수욕장95
34을숙도 조각공원051-2205-8014부산광역시 사하구 낙동남로 1233번길 2511하단역102
45을숙도 문화회관051-2205-8014부산광역시 사하구 낙동남로 1233번길 2511하단역102
56을숙도 생태공원051-2205-8014부산광역시 사하구 낙동남로 1233번길 2511하단역102
67낙동강 하구 에코센터051-209-2032부산광역시 사하구 낙동남로 124021하단역102
78낙동강 하류 철새도래지051-209-2000부산광역시 사하구 낙동남로 124021하단역102
89낙동강 문화관051-292-1042부산광역시 사하구 낙동남로 1233번길 111하단역102
910감천문화마을051-220-1444부산광역시 사하구 감내2로 177-1181토성역109
연번관광지명연락처주소출구번호호선인근역명역번호
8586사직야구장051-505-7422부산광역시 동래구 사직로 4513사직역308
8687강서체육공원051-970-1211부산광역시 강서구 체육공원로 4313체육공원역316
8788동래읍성 임진왜란 역사관051-605-0116부산광역시 동래구 수민동 도시철도 4호선 수안역 (수안역내)역사내4수안역403
8889충렬사051-523-4223부산광역시 동래구 충렬대로 34514충렬사역405
8990경전철홍보관051-605-0116부산광역시 기장군 철마면 반송로 1180기지창 내4안평역414
9091휴메트로테마공원051-605-0116부산광역시 기장군 철마면 반송로 1180기지창 내4안평역414
9192수로왕릉055-332-2305경상남도 김해시 가락로93번길 262김해경전철수로왕릉김해경전철
9293연지공원055-330-4511경상남도 김해시 금관대로 1368번길 71김해경전철연지공원김해경전철
9394구지봉공원(구지봉 고인돌)055-338-1330경상남도 김해시 구지로 135번길 43-12김해경전철박물관김해경전철
9495김해문화의전당055-320-1234경상남도 김해시 김해대로 20601김해경전철박물관김해경전철