Overview

Dataset statistics

Number of variables6
Number of observations581
Missing cells581
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.6 KiB
Average record size in memory52.2 B

Variable types

Numeric3
Text2
Unsupported1

Dataset

Description밀양시에서 제공하는 버스정류장 정보데이터입니다
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15061892

Alerts

기타(정류장 관련) has 581 (100.0%) missing valuesMissing
연번 has unique valuesUnique
기타(정류장 관련) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 00:56:07.575200
Analysis finished2023-12-11 00:56:08.893460
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct581
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean291
Minimum1
Maximum581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-11T09:56:08.953956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile30
Q1146
median291
Q3436
95-th percentile552
Maximum581
Range580
Interquartile range (IQR)290

Descriptive statistics

Standard deviation167.86453
Coefficient of variation (CV)0.57685405
Kurtosis-1.2
Mean291
Median Absolute Deviation (MAD)145
Skewness0
Sum169071
Variance28178.5
MonotonicityStrictly increasing
2023-12-11T09:56:09.077516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
365 1
 
0.2%
385 1
 
0.2%
386 1
 
0.2%
387 1
 
0.2%
388 1
 
0.2%
389 1
 
0.2%
390 1
 
0.2%
391 1
 
0.2%
392 1
 
0.2%
Other values (571) 571
98.3%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
581 1
0.2%
580 1
0.2%
579 1
0.2%
578 1
0.2%
577 1
0.2%
576 1
0.2%
575 1
0.2%
574 1
0.2%
573 1
0.2%
572 1
0.2%

정류장(소)명
Text

Distinct309
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-11T09:56:09.430139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length3.2478485
Min length2

Characters and Unicode

Total characters1887
Distinct characters253
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

Unique78 ?
Unique (%)13.4%

Sample

1st rowKT&G
2nd row가곡삼거리
3rd row가곡삼거리
4th row가곡삼거리
5th row가곡시장
ValueCountFrequency (%)
금곡 6
 
1.0%
평촌 6
 
1.0%
동산 6
 
1.0%
임고정 4
 
0.7%
대촌 4
 
0.7%
한목 4
 
0.7%
신촌 4
 
0.7%
관동 4
 
0.7%
평리 4
 
0.7%
인산 4
 
0.7%
Other values (301) 538
92.1%
2023-12-11T09:56:09.924546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 70
 
3.7%
리 44
 
2.3%
산 40
 
2.1%
곡 39
 
2.1%
아 36
 
1.9%
양 32
 
1.7%
트 31
 
1.6%
신 31
 
1.6%
정 30
 
1.6%
밀 29
 
1.5%
Other values (243) 1505
79.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1875
99.4%
Space Separator 3
 
0.2%
Uppercase Letter 3
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Decimal Number 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 70
 
3.7%
리 44
 
2.3%
산 40
 
2.1%
곡 39
 
2.1%
아 36
 
1.9%
양 32
 
1.7%
트 31
 
1.7%
신 31
 
1.7%
정 30
 
1.6%
밀 29
 
1.5%
Other values (235) 1493
79.6%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
K 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1875
99.4%
Common 9
 
0.5%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 70
 
3.7%
리 44
 
2.3%
산 40
 
2.1%
곡 39
 
2.1%
아 36
 
1.9%
양 32
 
1.7%
트 31
 
1.7%
신 31
 
1.7%
정 30
 
1.6%
밀 29
 
1.5%
Other values (235) 1493
79.6%
Common
ValueCountFrequency (%)
3
33.3%
) 2
22.2%
( 2
22.2%
2 1
 
11.1%
& 1
 
11.1%
Latin
ValueCountFrequency (%)
G 1
33.3%
K 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1875
99.4%
ASCII 12
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 70
 
3.7%
리 44
 
2.3%
산 40
 
2.1%
곡 39
 
2.1%
아 36
 
1.9%
양 32
 
1.7%
트 31
 
1.7%
신 31
 
1.7%
정 30
 
1.6%
밀 29
 
1.5%
Other values (235) 1493
79.6%
ASCII
ValueCountFrequency (%)
3
25.0%
) 2
16.7%
( 2
16.7%
2 1
 
8.3%
G 1
 
8.3%
K 1
 
8.3%
T 1
 
8.3%
& 1
 
8.3%

경도
Real number (ℝ)

Distinct578
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.76036
Minimum128.59031
Maximum128.9844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-11T09:56:10.061958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.59031
5-th percentile128.61949
Q1128.72464
median128.75424
Q3128.79817
95-th percentile128.89995
Maximum128.9844
Range0.3940972
Interquartile range (IQR)0.0735333

Descriptive statistics

Standard deviation0.078823153
Coefficient of variation (CV)0.00061216939
Kurtosis0.071592439
Mean128.76036
Median Absolute Deviation (MAD)0.0392861
Skewness0.18788653
Sum74809.771
Variance0.0062130895
MonotonicityNot monotonic
2023-12-11T09:56:10.193537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.7425889 2
 
0.3%
128.7514028 2
 
0.3%
128.7516722 2
 
0.3%
128.7642722 1
 
0.2%
128.7796361 1
 
0.2%
128.6267139 1
 
0.2%
128.6148472 1
 
0.2%
128.7192722 1
 
0.2%
128.7192972 1
 
0.2%
128.7796471 1
 
0.2%
Other values (568) 568
97.8%
ValueCountFrequency (%)
128.5903056 1
0.2%
128.5913667 1
0.2%
128.5914389 1
0.2%
128.5924056 1
0.2%
128.592475 1
0.2%
128.5960194 1
0.2%
128.5960361 1
0.2%
128.5982528 1
0.2%
128.5982611 1
0.2%
128.6002194 1
0.2%
ValueCountFrequency (%)
128.9844028 1
0.2%
128.9682194 1
0.2%
128.9681611 1
0.2%
128.9588389 1
0.2%
128.9588167 1
0.2%
128.9534333 1
0.2%
128.9531667 1
0.2%
128.9516194 1
0.2%
128.9430944 1
0.2%
128.9430056 1
0.2%

위도
Real number (ℝ)

Distinct579
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.495432
Minimum35.353324
Maximum35.603703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2023-12-11T09:56:10.320322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.353324
5-th percentile35.394728
Q135.473625
median35.49815
Q335.526072
95-th percentile35.580008
Maximum35.603703
Range0.25037871
Interquartile range (IQR)0.05244722

Descriptive statistics

Standard deviation0.051860785
Coefficient of variation (CV)0.0014610552
Kurtosis0.34085436
Mean35.495432
Median Absolute Deviation (MAD)0.02504445
Skewness-0.47937654
Sum20622.846
Variance0.002689541
MonotonicityNot monotonic
2023-12-11T09:56:10.446899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.59179444 2
 
0.3%
35.50772778 2
 
0.3%
35.47795556 1
 
0.2%
35.51293611 1
 
0.2%
35.54183056 1
 
0.2%
35.54183889 1
 
0.2%
35.35731682 1
 
0.2%
35.35738056 1
 
0.2%
35.46604444 1
 
0.2%
35.46562222 1
 
0.2%
Other values (569) 569
97.9%
ValueCountFrequency (%)
35.35332407 1
0.2%
35.3534 1
0.2%
35.3557478 1
0.2%
35.35576111 1
0.2%
35.35731682 1
0.2%
35.35738056 1
0.2%
35.35916077 1
0.2%
35.35922645 1
0.2%
35.36075278 1
0.2%
35.36081496 1
0.2%
ValueCountFrequency (%)
35.60370278 1
0.2%
35.60361388 1
0.2%
35.59985556 1
0.2%
35.59979444 1
0.2%
35.59915556 1
0.2%
35.59908333 1
0.2%
35.59879444 1
0.2%
35.59869167 1
0.2%
35.59720013 1
0.2%
35.59711628 1
0.2%

운행노선번호
Text

Distinct270
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-11T09:56:10.638165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length603
Median length236
Mean length59.462995
Min length2

Characters and Unicode

Total characters34548
Distinct characters85
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

Unique168 ?
Unique (%)28.9%

Sample

1st row1-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1초동,1칠성,2가곡,2금동,2번,2부산대,2용성,2초동,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-2번,5번,6-1번,6번,6부산대,6상동,6상동1,6상동2,6엄광,6활성,6활성1,7-1번,7롯데,7번,7삼랑,7지동,가곡,수산2,화봉1
2nd row1-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1초동,1칠성,2가곡,2금동,2번,2부산대,2용성,2청운,2초동,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-2번,5번,6-1번,6번,6부산대,6상동,6상동1,6상동2,6엄광,6활성,6활성1,7-1번,7롯데,7번,7삼랑,7지동,가곡,수산2,화봉1
3rd row1-2금동,1금동,4-1롯데,4-1번,4-1번.,4-1용성,4-1청운,4구기,4대항1,4대항2,4대항3,4대항4,4대항5,4대항6,4대항7,4대항8,4대항9,4번,4초동,4퇴로1,4퇴로2,4퇴로3,4퇴로4,4퇴로5,4퇴로6,4퇴로7,4퇴로8,5금동,5밀성고,5번,5시청,9롯데,9번,남산1,대흥동2,삼랑진,해동1
4th row1-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1칠성,1칠성.,2가곡,2금동,2번,2부산대,2용성,2초동,2초동.,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-1롯데,4-1번,4-1번.,4-1용성,4-1청운,4-2번,4구기,4대항1,4대항2,4대항3,4대항4,4대항5,4대항6,4대항7,4대항8,4대항9,4부산대,4퇴로1,4퇴로2,4퇴로3,4퇴로4,4퇴로5,4퇴로6,4퇴로7,4퇴로8,5금동,5밀성고,5밀성고,5번,5번,5시청,5시청,6-1번,6번,6부산대,6상동,6상동2,6엄광,6활성,7-1번,7롯데,7번,7삼랑,7지동,9롯데,9번,가곡,금동1,금동1-2,금동2,금동4,금동7-1,남산1,대흥동2,삼랑진,용성1,해동1,화봉1
5th row1-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1칠성,1칠성.,2가곡,2번,2부산대,2용성,2초동,2초동.,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-1롯데,4-1번,4-1번.,4-1용성,4-1청운,4-2번,4구기,4대항1,4대항2,4대항3,4대항4,4대항5,4대항6,4대항7,4대항8,4대항9,4부산대,4퇴로1,4퇴로2,4퇴로3,4퇴로4,4퇴로5,4퇴로6,4퇴로7,4퇴로8,5금동,5밀성고,5번,5시청,6-1번,6번,6부산대,6상동,6상동2,6엄광,6활성,가곡,용성1,화봉1
ValueCountFrequency (%)
얼음골,얼음골1,얼음골2,얼음골3 19
 
3.3%
국전,국전1,국전2,국전3,국전4 13
 
2.2%
상촌,수산1,수산2,오산 9
 
1.5%
대촌1,대촌2 9
 
1.5%
수산1,수산2,해동1 9
 
1.5%
남산1,남산2 9
 
1.5%
3상동,6상동,6상동1,6상동2,도곡1,도곡2,도곡4,상동,신곡1,신곡3,신곡4,신곡5,신곡6,신곡7,옥산,옥산1,옥산2 9
 
1.5%
신곡1,신곡3,신곡4,신곡5,신곡6,신곡7 8
 
1.4%
감물리,감물리1,감물리2,감물리3,감물리4,감물리5 8
 
1.4%
수산1,수산2,오산 8
 
1.4%
Other values (260) 480
82.6%
2023-12-11T09:56:10.958981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 7332
21.2%
1 2530
 
7.3%
2 1806
 
5.2%
4 1742
 
5.0%
동 1149
 
3.3%
대 1020
 
3.0%
3 913
 
2.6%
- 818
 
2.4%
번 746
 
2.2%
산 742
 
2.1%
Other values (75) 15750
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17197
49.8%
Decimal Number 8979
26.0%
Other Punctuation 7554
21.9%
Dash Punctuation 818
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1149
 
6.7%
대 1020
 
5.9%
번 746
 
4.3%
산 742
 
4.3%
곡 692
 
4.0%
가 585
 
3.4%
성 525
 
3.1%
항 499
 
2.9%
초 455
 
2.6%
로 431
 
2.5%
Other values (62) 10353
60.2%
Decimal Number
ValueCountFrequency (%)
1 2530
28.2%
2 1806
20.1%
4 1742
19.4%
3 913
 
10.2%
6 717
 
8.0%
5 497
 
5.5%
7 477
 
5.3%
9 152
 
1.7%
8 113
 
1.3%
0 32
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 7332
97.1%
. 222
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 818
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17351
50.2%
Hangul 17197
49.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1149
 
6.7%
대 1020
 
5.9%
번 746
 
4.3%
산 742
 
4.3%
곡 692
 
4.0%
가 585
 
3.4%
성 525
 
3.1%
항 499
 
2.9%
초 455
 
2.6%
로 431
 
2.5%
Other values (62) 10353
60.2%
Common
ValueCountFrequency (%)
, 7332
42.3%
1 2530
 
14.6%
2 1806
 
10.4%
4 1742
 
10.0%
3 913
 
5.3%
- 818
 
4.7%
6 717
 
4.1%
5 497
 
2.9%
7 477
 
2.7%
. 222
 
1.3%
Other values (3) 297
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17351
50.2%
Hangul 17197
49.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 7332
42.3%
1 2530
 
14.6%
2 1806
 
10.4%
4 1742
 
10.0%
3 913
 
5.3%
- 818
 
4.7%
6 717
 
4.1%
5 497
 
2.9%
7 477
 
2.7%
. 222
 
1.3%
Other values (3) 297
 
1.7%
Hangul
ValueCountFrequency (%)
동 1149
 
6.7%
대 1020
 
5.9%
번 746
 
4.3%
산 742
 
4.3%
곡 692
 
4.0%
가 585
 
3.4%
성 525
 
3.1%
항 499
 
2.9%
초 455
 
2.6%
로 431
 
2.5%
Other values (62) 10353
60.2%

기타(정류장 관련)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing581
Missing (%)100.0%
Memory size5.2 KiB

Interactions

2023-12-11T09:56:08.445288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:07.854895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:08.135700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:08.536476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:07.948312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:08.229060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:08.633738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:08.050587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:56:08.353128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:56:11.029306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경도위도
연번1.0000.4480.491
경도0.4481.0000.678
위도0.4910.6781.000
2023-12-11T09:56:11.097908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경도위도
연번1.000-0.0740.040
경도-0.0741.0000.125
위도0.0400.1251.000

Missing values

2023-12-11T09:56:08.759905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:56:08.859302image/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

연번정류장(소)명경도위도운행노선번호기타(정류장 관련)
01KT&G128.76427235.4779561-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1초동,1칠성,2가곡,2금동,2번,2부산대,2용성,2초동,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-2번,5번,6-1번,6번,6부산대,6상동,6상동1,6상동2,6엄광,6활성,6활성1,7-1번,7롯데,7번,7삼랑,7지동,가곡,수산2,화봉1<NA>
12가곡삼거리128.76722835.4753421-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1초동,1칠성,2가곡,2금동,2번,2부산대,2용성,2청운,2초동,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-2번,5번,6-1번,6번,6부산대,6상동,6상동1,6상동2,6엄광,6활성,6활성1,7-1번,7롯데,7번,7삼랑,7지동,가곡,수산2,화봉1<NA>
23가곡삼거리128.76718135.4750171-2금동,1금동,4-1롯데,4-1번,4-1번.,4-1용성,4-1청운,4구기,4대항1,4대항2,4대항3,4대항4,4대항5,4대항6,4대항7,4대항8,4대항9,4번,4초동,4퇴로1,4퇴로2,4퇴로3,4퇴로4,4퇴로5,4퇴로6,4퇴로7,4퇴로8,5금동,5밀성고,5번,5시청,9롯데,9번,남산1,대흥동2,삼랑진,해동1<NA>
34가곡삼거리128.767735.4749391-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1칠성,1칠성.,2가곡,2금동,2번,2부산대,2용성,2초동,2초동.,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-1롯데,4-1번,4-1번.,4-1용성,4-1청운,4-2번,4구기,4대항1,4대항2,4대항3,4대항4,4대항5,4대항6,4대항7,4대항8,4대항9,4부산대,4퇴로1,4퇴로2,4퇴로3,4퇴로4,4퇴로5,4퇴로6,4퇴로7,4퇴로8,5금동,5밀성고,5밀성고,5번,5번,5시청,5시청,6-1번,6번,6부산대,6상동,6상동2,6엄광,6활성,7-1번,7롯데,7번,7삼랑,7지동,9롯데,9번,가곡,금동1,금동1-2,금동2,금동4,금동7-1,남산1,대흥동2,삼랑진,용성1,해동1,화봉1<NA>
45가곡시장128.76554735.4763861-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1칠성,1칠성.,2가곡,2번,2부산대,2용성,2초동,2초동.,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-1롯데,4-1번,4-1번.,4-1용성,4-1청운,4-2번,4구기,4대항1,4대항2,4대항3,4대항4,4대항5,4대항6,4대항7,4대항8,4대항9,4부산대,4퇴로1,4퇴로2,4퇴로3,4퇴로4,4퇴로5,4퇴로6,4퇴로7,4퇴로8,5금동,5밀성고,5번,5시청,6-1번,6번,6부산대,6상동,6상동2,6엄광,6활성,가곡,용성1,화봉1<NA>
56가곡시장128.76523935.4769081-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1초동,1칠성,2가곡,2금동,2번,2부산대,2용성,2청운,2초동,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-2번,5번,6-1번,6번,6부산대,6상동,6상동1,6상동2,6엄광,6활성,6활성1,7-1번,7롯데,7번,7삼랑,7지동,가곡,수산2,화봉1<NA>
67가곡종점128.60317535.567419두곡<NA>
78가곡주공아파트128.77231435.4729111-2가곡,1-2금동,1-2번,1-2부산대,1가곡,1금동,1번,1부산대,1서가정,1용성,1칠성,1칠성.,2가곡,2금동,2번,2부산대,2용성,2초동,2초동.,2칠성,3-1번,3-1부산대,3금곡,3번,3상동,4-1롯데,4-1번,4-1번.,4-1용성,4-1청운,4-2번,4대항1,4대항2,4대항3,4대항4,4대항5,4대항6,4대항7,4대항8,4부산대,4퇴로1,4퇴로2,4퇴로3,4퇴로4,4퇴로5,4퇴로6,4퇴로8,5금동,5밀성고,5번,5번,5시청,6-1번,6번,6부산대,6상동2,6엄광,6활성,7-1번,7롯데,7번,7삼랑,7지동,9번,가곡,남산1,삼랑진,용성,용성1,칠성,해동1,화봉1<NA>
89가례128.60028335.4884311서가정,서가정1,서가정2,서가정3,서가정4,서가정5,서가정6<NA>
910가례128.60021935.4883471서가정,서가정1,서가정2,서가정3,서가정4,서가정5,서가정6<NA>
연번정류장(소)명경도위도운행노선번호기타(정류장 관련)
571572화동128.78898935.5056396엄광,감물리,감물리1,감물리2,감물리3,감물리4,감물리5,고례1,고례2,고례3,국전,국전1,국전2,국전3,국전4,발례,발례1,발례2,얼음골,얼음골1,얼음골2,얼음골3,엄광2,표충사,표충사1,표충사2,표충사3<NA>
572573화동128.78896435.505525감물리,감물리1,감물리2,감물리3,감물리4,감물리5,고례1,고례2,고례3,국전,국전1,국전2,국전3,국전4,발례,발례1,발례2,얼음골,얼음골1,얼음골2,얼음골3,엄광1,표충사,표충사1,표충사2,표충사3<NA>
573574화봉128.63067835.499069영신2,영신3,화봉1<NA>
574575화봉128.63056735.498964영신2,영신3,화봉1<NA>
575576화산마을128.73172535.5257314대항4,4퇴로4,4퇴로7<NA>
576577화산마을128.73164735.5256394대항5,4대항9,4퇴로3<NA>
577578화성128.80137835.406994삼랑진<NA>
578579화성128.80122535.406947삼랑진<NA>
579580활성128.80602235.4849366활성,6활성1<NA>
580581횟골종점128.67325835.577428대촌1,대촌2<NA>