Overview

Dataset statistics

Number of variables9
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory80.5 B

Variable types

Numeric3
Categorical4
Text2

Dataset

Description부산광역시연제구_벽보게시판현황_20230419
Author부산광역시 연제구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3082205

Alerts

벽보규격(가로) has constant value ""Constant
벽보규격(세로) has constant value ""Constant
순번 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 순번High correlation
행정동 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:38:02.024764
Analysis finished2023-12-10 16:38:03.499729
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.5
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T01:38:03.594834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.85
Q110.25
median19.5
Q328.75
95-th percentile36.15
Maximum38
Range37
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation11.113055
Coefficient of variation (CV)0.56990028
Kurtosis-1.2
Mean19.5
Median Absolute Deviation (MAD)9.5
Skewness0
Sum741
Variance123.5
MonotonicityStrictly increasing
2023-12-11T01:38:03.765150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1 1
 
2.6%
30 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
31 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%
29 1
2.6%

행정동
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
연산1동
8 
거제1동
7 
연산2동
7 
연산9동
7 
거제2동
2 
Other values (4)
7 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row거제1동
2nd row거제1동
3rd row거제1동
4th row거제1동
5th row거제1동

Common Values

ValueCountFrequency (%)
연산1동 8
21.1%
거제1동 7
18.4%
연산2동 7
18.4%
연산9동 7
18.4%
거제2동 2
 
5.3%
거제3동 2
 
5.3%
연산4동 2
 
5.3%
연산6동 2
 
5.3%
연산5동 1
 
2.6%

Length

2023-12-11T01:38:03.907212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:04.037204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연산1동 8
21.1%
거제1동 7
18.4%
연산2동 7
18.4%
연산9동 7
18.4%
거제2동 2
 
5.3%
거제3동 2
 
5.3%
연산4동 2
 
5.3%
연산6동 2
 
5.3%
연산5동 1
 
2.6%

명칭
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-11T01:38:04.321756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length16.368421
Min length6

Characters and Unicode

Total characters622
Distinct characters158
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

Unique38 ?
Unique (%)100.0%

Sample

1st row롯데캐슬APT입구 사거리 건널목
2nd row이사벨고 건너편 철길 아래(국영인쇄소 담)
3rd row한양프라자 옆 건널목(우리은행 맞은편)
4th row거제1차 현대홈타운 놀이터 앞
5th row구 송월타올 삼거리
ValueCountFrequency (%)
앞 14
 
9.6%
입구 9
 
6.2%
맞은편 6
 
4.1%
옆 6
 
4.1%
건널목 5
 
3.4%
정문 5
 
3.4%
우측 5
 
3.4%
구 4
 
2.7%
건너편 3
 
2.1%
버스정류소 3
 
2.1%
Other values (73) 86
58.9%
2023-12-11T01:38:05.291560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
 
17.8%
구 22
 
3.5%
앞 16
 
2.6%
아 15
 
2.4%
편 15
 
2.4%
은 14
 
2.3%
트 13
 
2.1%
정 11
 
1.8%
맞 11
 
1.8%
입 11
 
1.8%
Other values (148) 383
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
75.7%
Space Separator 111
 
17.8%
Open Punctuation 11
 
1.8%
Close Punctuation 11
 
1.8%
Uppercase Letter 9
 
1.4%
Decimal Number 6
 
1.0%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 22
 
4.7%
앞 16
 
3.4%
아 15
 
3.2%
편 15
 
3.2%
은 14
 
3.0%
트 13
 
2.8%
정 11
 
2.3%
맞 11
 
2.3%
입 11
 
2.3%
파 11
 
2.3%
Other values (131) 332
70.5%
Uppercase Letter
ValueCountFrequency (%)
G 2
22.2%
L 1
11.1%
S 1
11.1%
K 1
11.1%
T 1
11.1%
P 1
11.1%
A 1
11.1%
M 1
11.1%
Decimal Number
ValueCountFrequency (%)
7 2
33.3%
2 2
33.3%
5 1
16.7%
1 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
75.7%
Common 142
 
22.8%
Latin 9
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 22
 
4.7%
앞 16
 
3.4%
아 15
 
3.2%
편 15
 
3.2%
은 14
 
3.0%
트 13
 
2.8%
정 11
 
2.3%
맞 11
 
2.3%
입 11
 
2.3%
파 11
 
2.3%
Other values (131) 332
70.5%
Common
ValueCountFrequency (%)
111
78.2%
( 11
 
7.7%
) 11
 
7.7%
, 2
 
1.4%
7 2
 
1.4%
2 2
 
1.4%
. 1
 
0.7%
5 1
 
0.7%
1 1
 
0.7%
Latin
ValueCountFrequency (%)
G 2
22.2%
L 1
11.1%
S 1
11.1%
K 1
11.1%
T 1
11.1%
P 1
11.1%
A 1
11.1%
M 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
75.7%
ASCII 151
 
24.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
73.5%
( 11
 
7.3%
) 11
 
7.3%
, 2
 
1.3%
G 2
 
1.3%
7 2
 
1.3%
2 2
 
1.3%
L 1
 
0.7%
S 1
 
0.7%
K 1
 
0.7%
Other values (7) 7
 
4.6%
Hangul
ValueCountFrequency (%)
구 22
 
4.7%
앞 16
 
3.4%
아 15
 
3.2%
편 15
 
3.2%
은 14
 
3.0%
트 13
 
2.8%
정 11
 
2.3%
맞 11
 
2.3%
입 11
 
2.3%
파 11
 
2.3%
Other values (131) 332
70.5%

주소
Text

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-11T01:38:05.849944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length17.868421
Min length15

Characters and Unicode

Total characters679
Distinct characters53
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)94.7%

Sample

1st row부산광역시 연제구 세병로 44
2nd row부산광역시 연제구 중앙대로 1196
3rd row부산광역시 연제구 명륜로 3
4th row부산광역시 연제구 거제동 1482-1
5th row부산광역시 연제구 중앙대로 1255
ValueCountFrequency (%)
부산광역시 38
25.0%
연제구 38
25.0%
연산동 6
 
3.9%
중앙대로 5
 
3.3%
반송로 5
 
3.3%
과정로 4
 
2.6%
3 3
 
2.0%
거제동 3
 
2.0%
연수로 3
 
2.0%
2220-1 2
 
1.3%
Other values (45) 45
29.6%
2023-12-11T01:38:06.301467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
16.8%
연 50
 
7.4%
산 44
 
6.5%
제 43
 
6.3%
부 38
 
5.6%
광 38
 
5.6%
역 38
 
5.6%
시 38
 
5.6%
구 38
 
5.6%
로 29
 
4.3%
Other values (43) 209
30.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 437
64.4%
Decimal Number 119
 
17.5%
Space Separator 114
 
16.8%
Dash Punctuation 9
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 50
11.4%
산 44
10.1%
제 43
9.8%
부 38
8.7%
광 38
8.7%
역 38
8.7%
시 38
8.7%
구 38
8.7%
로 29
6.6%
동 10
 
2.3%
Other values (31) 71
16.2%
Decimal Number
ValueCountFrequency (%)
1 26
21.8%
2 20
16.8%
3 13
10.9%
4 12
10.1%
0 12
10.1%
9 11
9.2%
5 7
 
5.9%
6 7
 
5.9%
7 6
 
5.0%
8 5
 
4.2%
Space Separator
ValueCountFrequency (%)
114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 437
64.4%
Common 242
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 50
11.4%
산 44
10.1%
제 43
9.8%
부 38
8.7%
광 38
8.7%
역 38
8.7%
시 38
8.7%
구 38
8.7%
로 29
6.6%
동 10
 
2.3%
Other values (31) 71
16.2%
Common
ValueCountFrequency (%)
114
47.1%
1 26
 
10.7%
2 20
 
8.3%
3 13
 
5.4%
4 12
 
5.0%
0 12
 
5.0%
9 11
 
4.5%
- 9
 
3.7%
5 7
 
2.9%
6 7
 
2.9%
Other values (2) 11
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 437
64.4%
ASCII 242
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
47.1%
1 26
 
10.7%
2 20
 
8.3%
3 13
 
5.4%
4 12
 
5.0%
0 12
 
5.0%
9 11
 
4.5%
- 9
 
3.7%
5 7
 
2.9%
6 7
 
2.9%
Other values (2) 11
 
4.5%
Hangul
ValueCountFrequency (%)
연 50
11.4%
산 44
10.1%
제 43
9.8%
부 38
8.7%
광 38
8.7%
역 38
8.7%
시 38
8.7%
구 38
8.7%
로 29
6.6%
동 10
 
2.3%
Other values (31) 71
16.2%

게시대유형
Categorical

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
F2
18 
F1
12 
F3
8 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF2
2nd rowF1
3rd rowF2
4th rowF3
5th rowF1

Common Values

ValueCountFrequency (%)
F2 18
47.4%
F1 12
31.6%
F3 8
21.1%

Length

2023-12-11T01:38:06.475417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:06.647031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f2 18
47.4%
f1 12
31.6%
f3 8
21.1%

벽보규격(가로)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
400
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row400
2nd row400
3rd row400
4th row400
5th row400

Common Values

ValueCountFrequency (%)
400 38
100.0%

Length

2023-12-11T01:38:06.836568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:06.994869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
400 38
100.0%

벽보규격(세로)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
550
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row550
2nd row550
3rd row550
4th row550
5th row550

Common Values

ValueCountFrequency (%)
550 38
100.0%

Length

2023-12-11T01:38:07.168829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:07.343360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
550 38
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08518
Minimum129.06201
Maximum129.1078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T01:38:07.500974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.06201
5-th percentile129.07024
Q1129.07818
median129.08198
Q3129.08898
95-th percentile129.10735
Maximum129.1078
Range0.0457949
Interquartile range (IQR)0.010797375

Descriptive statistics

Standard deviation0.012165376
Coefficient of variation (CV)9.4243012 × 10-5
Kurtosis-0.21808934
Mean129.08518
Median Absolute Deviation (MAD)0.0053062
Skewness0.66291934
Sum4905.2367
Variance0.00014799637
MonotonicityNot monotonic
2023-12-11T01:38:07.734268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
129.1073512 2
 
5.3%
129.0845915 1
 
2.6%
129.0768239 1
 
2.6%
129.0813103 1
 
2.6%
129.0744878 1
 
2.6%
129.0788177 1
 
2.6%
129.0801965 1
 
2.6%
129.0801988 1
 
2.6%
129.0832505 1
 
2.6%
129.082571 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
129.0620097 1
2.6%
129.0681771 1
2.6%
129.0706009 1
2.6%
129.0708266 1
2.6%
129.0726265 1
2.6%
129.0743695 1
2.6%
129.0744878 1
2.6%
129.0768239 1
2.6%
129.0770102 1
2.6%
129.0779695 1
2.6%
ValueCountFrequency (%)
129.1078046 1
2.6%
129.1073512 2
5.3%
129.1073452 1
2.6%
129.1068338 1
2.6%
129.1064607 1
2.6%
129.104814 1
2.6%
129.0933366 1
2.6%
129.0897835 1
2.6%
129.0893337 1
2.6%
129.0879146 1
2.6%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.186237
Minimum35.174518
Maximum35.199139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T01:38:07.914992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.174518
5-th percentile35.175229
Q135.180322
median35.187505
Q335.191103
95-th percentile35.195389
Maximum35.199139
Range0.02462048
Interquartile range (IQR)0.010781307

Descriptive statistics

Standard deviation0.0065132456
Coefficient of variation (CV)0.00018510776
Kurtosis-0.84362419
Mean35.186237
Median Absolute Deviation (MAD)0.004088975
Skewness-0.14188247
Sum1337.077
Variance4.2422368 × 10-5
MonotonicityNot monotonic
2023-12-11T01:38:08.103617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
35.18023281 2
 
5.3%
35.19338294 1
 
2.6%
35.18058956 1
 
2.6%
35.17615076 1
 
2.6%
35.17910501 1
 
2.6%
35.17528064 1
 
2.6%
35.18406588 1
 
2.6%
35.18423712 1
 
2.6%
35.1841918 1
 
2.6%
35.18345875 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
35.17451842 1
2.6%
35.1749378 1
2.6%
35.17528064 1
2.6%
35.17615076 1
2.6%
35.17807302 1
2.6%
35.17897994 1
2.6%
35.17910501 1
2.6%
35.17928366 1
2.6%
35.18023281 2
5.3%
35.18058956 1
2.6%
ValueCountFrequency (%)
35.1991389 1
2.6%
35.19648677 1
2.6%
35.19519542 1
2.6%
35.19412054 1
2.6%
35.19370811 1
2.6%
35.19367894 1
2.6%
35.19338294 1
2.6%
35.1916367 1
2.6%
35.19136963 1
2.6%
35.19126678 1
2.6%

Interactions

2023-12-11T01:38:03.020194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:02.431514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:02.736378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:03.109274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:02.544009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:02.838211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:03.192391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:02.638506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:02.937905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:38:08.238737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동명칭주소게시대유형위도경도
순번1.0000.8731.0001.0000.0000.7070.838
행정동0.8731.0001.0001.0000.5680.7590.767
명칭1.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0000.6061.0001.000
게시대유형0.0000.5681.0000.6061.0000.4080.000
위도0.7070.7591.0001.0000.4081.0000.000
경도0.8380.7671.0001.0000.0000.0001.000
2023-12-11T01:38:08.380623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시대유형행정동
게시대유형1.0000.264
행정동0.2641.000
2023-12-11T01:38:08.494209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도행정동게시대유형
순번1.0000.638-0.6930.6310.000
위도0.6381.000-0.1910.5100.272
경도-0.693-0.1911.0000.4710.000
행정동0.6310.5100.4711.0000.264
게시대유형0.0000.2720.0000.2641.000

Missing values

2023-12-11T01:38:03.313067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:38:03.448640image/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

순번행정동명칭주소게시대유형벽보규격(가로)벽보규격(세로)위도경도
01거제1동롯데캐슬APT입구 사거리 건널목부산광역시 연제구 세병로 44F2400550129.08459135.193383
12거제1동이사벨고 건너편 철길 아래(국영인쇄소 담)부산광역시 연제구 중앙대로 1196F1400550129.07947935.193708
23거제1동한양프라자 옆 건널목(우리은행 맞은편)부산광역시 연제구 명륜로 3F2400550129.08122935.196487
34거제1동거제1차 현대홈타운 놀이터 앞부산광역시 연제구 거제동 1482-1F3400550129.07262735.193679
45거제1동구 송월타올 삼거리부산광역시 연제구 중앙대로 1255F1400550129.07796935.199139
56거제1동교육대학교입구 기아자동차 대리점앞부산광역시 연제구 교대로 3F1400550129.07947735.195195
67거제1동연제우체국 앞부산광역시 연제구 법원북로 33F2400550129.07060135.194121
78거제2동아시아드 홈플러스 맞은편부산광역시 연제구 종합운동장로 7F1400550129.0620135.191267
89거제2동거제2동 거제2주택재개발지구 아래 해들마루빌라 담 (건널목)부산광역시 연제구 거제동 922-7F3400550129.06817735.188481
910거제3동현대아파트 맞은편 철길 건널목 옆부산광역시 연제구 거제동 847-4F1400550129.07082735.185393
순번행정동명칭주소게시대유형벽보규격(가로)벽보규격(세로)위도경도
2829연산5동시청역 7번출구부산광역시 연제구 중앙대로 1029F1400550129.07682435.18059
2930연산6동연제중학교 정문 입구부산광역시 연제구 쌍미천로 62F3400550129.08978435.179284
3031연산6동연제구 장애인 협회 맞은편(구.연산7파출소 맞은 편)부산광역시 연제구 연산동 1927-2F3400550129.08743635.174518
3132연산9동망미주공아파트 입구 우측 건널목부산광역시 연제구 연산동 2220-1F2400550129.10735135.180233
3233연산9동토곡사거리 국민은행 앞부산광역시 연제구 과정로 190F2400550129.10646135.188227
3334연산9동망미주공아파트 입구 우측부산광역시 연제구 연산동 2220-1F3400550129.10735135.180233
3435연산9동안락교 입구 우측부산광역시 연제구 연산동 2042-26F3400550129.10780535.190162
3536연산9동망미주공아파트 입구 옆 아래부산광역시 연제구 과정로 86F2400550129.10734535.17898
3637연산9동LG아파트 입구 상가 맞은 편부산광역시 연제구 연산동 243-14F2400550129.10481435.185006
3738연산9동토곡사거리 청담 앞부산광역시 연제구 연안로 1F1400550129.10683435.188215