Overview

Dataset statistics

Number of variables9
Number of observations80
Missing cells0
Missing cells (%)0.0%
Duplicate rows34
Duplicate rows (%)42.5%
Total size in memory5.9 KiB
Average record size in memory75.7 B

Variable types

Categorical9

Dataset

Description부산교통공사에서 운영하는 3호선 역사들의 환승정보 데이터로 철도운영기관명, 선명, 역명, 환승철도운영기관, 환승선명, 환승이후역명, 환승기점역명, 차량순서, 차량출입문번호의 데이터가 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041078/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
Dataset has 34 (42.5%) duplicate rowsDuplicates
환승기점역명 is highly overall correlated with 역명 and 3 other fieldsHigh correlation
역명 is highly overall correlated with 환승철도운영기관 and 3 other fieldsHigh correlation
환승선명 is highly overall correlated with 역명 and 3 other fieldsHigh correlation
환승철도운영기관 is highly overall correlated with 역명 and 3 other fieldsHigh correlation
환승이후역명 is highly overall correlated with 역명 and 3 other fieldsHigh correlation
역명 is highly imbalanced (54.7%)Imbalance
환승철도운영기관 is highly imbalanced (71.4%)Imbalance
환승선명 is highly imbalanced (61.3%)Imbalance

Reproduction

Analysis started2023-12-12 03:11:01.139602
Analysis finished2023-12-12 03:11:02.091256
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
부산교통공사
80 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산교통공사 80
100.0%

Length

2023-12-12T12:11:02.195533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:02.340306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산교통공사 80
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
3호선
80 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3호선
2nd row3호선
3rd row3호선
4th row3호선
5th row3호선

Common Values

ValueCountFrequency (%)
3호선 80
100.0%

Length

2023-12-12T12:11:02.464424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:02.602577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3호선 80
100.0%

역명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
수영
64 
연산
 
4
거제(법원·검찰청)
 
4
덕천(부산과기대)
 
4
미남
 
2

Length

Max length10
Median length2
Mean length2.75
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수영 64
80.0%
연산 4
 
5.0%
거제(법원·검찰청) 4
 
5.0%
덕천(부산과기대) 4
 
5.0%
미남 2
 
2.5%
대저 2
 
2.5%

Length

2023-12-12T12:11:02.794001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:02.963665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영 64
80.0%
연산 4
 
5.0%
거제(법원·검찰청 4
 
5.0%
덕천(부산과기대 4
 
5.0%
미남 2
 
2.5%
대저 2
 
2.5%

환승철도운영기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
부산교통공사
74 
코레일
 
4
부산김해경전철
 
2

Length

Max length7
Median length6
Mean length5.875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산교통공사 74
92.5%
코레일 4
 
5.0%
부산김해경전철 2
 
2.5%

Length

2023-12-12T12:11:03.554582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:03.732921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산교통공사 74
92.5%
코레일 4
 
5.0%
부산김해경전철 2
 
2.5%

환승선명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
2호선
68 
1호선
 
4
동해
 
4
4호선
 
2
부산김해경전철
 
2

Length

Max length7
Median length3
Mean length3.05
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2호선
2nd row2호선
3rd row2호선
4th row2호선
5th row2호선

Common Values

ValueCountFrequency (%)
2호선 68
85.0%
1호선 4
 
5.0%
동해 4
 
5.0%
4호선 2
 
2.5%
부산김해경전철 2
 
2.5%

Length

2023-12-12T12:11:03.896702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:04.048532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2호선 68
85.0%
1호선 4
 
5.0%
동해 4
 
5.0%
4호선 2
 
2.5%
부산김해경전철 2
 
2.5%

환승이후역명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
민락
32 
광안
32 
교대
4 
시청(연제)
 
2
거제해맞이
 
2
Other values (5)
8 

Length

Max length9
Median length2
Mean length2.35
Min length2

Unique

Unique2 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
민락 32
40.0%
광안 32
40.0%
교대 4
 
5.0%
시청(연제) 2
 
2.5%
거제해맞이 2
 
2.5%
동래 2
 
2.5%
구명 2
 
2.5%
수정(방송통신대) 2
 
2.5%
등구 1
 
1.2%
평강 1
 
1.2%

Length

2023-12-12T12:11:04.202671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:04.391457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민락 32
40.0%
광안 32
40.0%
교대 4
 
5.0%
시청(연제 2
 
2.5%
거제해맞이 2
 
2.5%
동래 2
 
2.5%
구명 2
 
2.5%
수정(방송통신대 2
 
2.5%
등구 1
 
1.2%
평강 1
 
1.2%

환승기점역명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
장산(해운대백병원)
34 
양산(시청·동원과학기술대학교)
34 
신평
 
2
노포(종합버스터미널)
 
2
일광
 
2
Other values (4)
6 

Length

Max length16
Median length11
Mean length11.8625
Min length2

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st row장산(해운대백병원)
2nd row장산(해운대백병원)
3rd row장산(해운대백병원)
4th row장산(해운대백병원)
5th row장산(해운대백병원)

Common Values

ValueCountFrequency (%)
장산(해운대백병원) 34
42.5%
양산(시청·동원과학기술대학교) 34
42.5%
신평 2
 
2.5%
노포(종합버스터미널) 2
 
2.5%
일광 2
 
2.5%
부전 2
 
2.5%
안평(고촌주택단지) 2
 
2.5%
사상(서부터미널) 1
 
1.2%
대사 1
 
1.2%

Length

2023-12-12T12:11:04.597957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:04.779497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장산(해운대백병원 34
42.5%
양산(시청·동원과학기술대학교 34
42.5%
신평 2
 
2.5%
노포(종합버스터미널 2
 
2.5%
일광 2
 
2.5%
부전 2
 
2.5%
안평(고촌주택단지 2
 
2.5%
사상(서부터미널 1
 
1.2%
대사 1
 
1.2%

차량순서
Categorical

Distinct4
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2
22 
1
21 
4
20 
3
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 22
27.5%
1 21
26.2%
4 20
25.0%
3 17
21.2%

Length

2023-12-12T12:11:04.971645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:05.104902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 22
27.5%
1 21
26.2%
4 20
25.0%
3 17
21.2%

차량출입문번호
Categorical

Distinct4
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
4
23 
1
21 
2
18 
3
18 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row1

Common Values

ValueCountFrequency (%)
4 23
28.7%
1 21
26.2%
2 18
22.5%
3 18
22.5%

Length

2023-12-12T12:11:05.250288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:05.373834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 23
28.7%
1 21
26.2%
2 18
22.5%
3 18
22.5%

Correlations

2023-12-12T12:11:05.466377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명환승철도운영기관환승선명환승이후역명환승기점역명차량순서차량출입문번호
역명1.0001.0001.0000.9800.9800.1520.199
환승철도운영기관1.0001.0001.0000.9391.0000.1530.171
환승선명1.0001.0001.0000.9971.0000.0950.139
환승이후역명0.9800.9390.9971.0000.9800.0000.000
환승기점역명0.9801.0001.0000.9801.0000.0000.000
차량순서0.1520.1530.0950.0000.0001.0000.000
차량출입문번호0.1990.1710.1390.0000.0000.0001.000
2023-12-12T12:11:05.626727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환승기점역명차량출입문번호역명환승선명차량순서환승철도운영기관환승이후역명
환승기점역명1.0000.0000.8640.9730.0000.9600.920
차량출입문번호0.0001.0000.1250.1100.0000.1590.000
역명0.8640.1251.0000.9930.0930.9800.916
환승선명0.9730.1100.9931.0000.0730.9870.895
차량순서0.0000.0000.0930.0731.0000.1420.000
환승철도운영기관0.9600.1590.9800.9870.1421.0000.880
환승이후역명0.9200.0000.9160.8950.0000.8801.000
2023-12-12T12:11:05.787391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명환승철도운영기관환승선명환승이후역명환승기점역명차량순서차량출입문번호
역명1.0000.9800.9930.9160.8640.0930.125
환승철도운영기관0.9801.0000.9870.8800.9600.1420.159
환승선명0.9930.9871.0000.8950.9730.0730.110
환승이후역명0.9160.8800.8951.0000.9200.0000.000
환승기점역명0.8640.9600.9730.9201.0000.0000.000
차량순서0.0930.1420.0730.0000.0001.0000.000
차량출입문번호0.1250.1590.1100.0000.0000.0001.000

Missing values

2023-12-12T12:11:01.764061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:11:01.998805image/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

철도운영기관명선명역명환승철도운영기관환승선명환승이후역명환승기점역명차량순서차량출입문번호
0부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)11
1부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)12
2부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)13
3부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)14
4부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)21
5부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)22
6부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)23
7부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)24
8부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)31
9부산교통공사3호선수영부산교통공사2호선민락장산(해운대백병원)32
철도운영기관명선명역명환승철도운영기관환승선명환승이후역명환승기점역명차량순서차량출입문번호
70부산교통공사3호선거제(법원·검찰청)코레일동해거제해맞이부전12
71부산교통공사3호선거제(법원·검찰청)코레일동해교대일광12
72부산교통공사3호선미남부산교통공사4호선동래안평(고촌주택단지)31
73부산교통공사3호선미남부산교통공사4호선동래안평(고촌주택단지)24
74부산교통공사3호선덕천(부산과기대)부산교통공사2호선구명장산(해운대백병원)11
75부산교통공사3호선덕천(부산과기대)부산교통공사2호선수정(방송통신대)양산(시청·동원과학기술대학교)24
76부산교통공사3호선덕천(부산과기대)부산교통공사2호선구명장산(해운대백병원)11
77부산교통공사3호선덕천(부산과기대)부산교통공사2호선수정(방송통신대)양산(시청·동원과학기술대학교)24
78부산교통공사3호선대저부산김해경전철부산김해경전철등구사상(서부터미널)24
79부산교통공사3호선대저부산김해경전철부산김해경전철평강대사24

Duplicate rows

Most frequently occurring

철도운영기관명선명역명환승철도운영기관환승선명환승이후역명환승기점역명차량순서차량출입문번호# duplicates
0부산교통공사3호선덕천(부산과기대)부산교통공사2호선구명장산(해운대백병원)112
1부산교통공사3호선덕천(부산과기대)부산교통공사2호선수정(방송통신대)양산(시청·동원과학기술대학교)242
2부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)112
3부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)122
4부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)132
5부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)142
6부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)212
7부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)222
8부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)232
9부산교통공사3호선수영부산교통공사2호선광안양산(시청·동원과학기술대학교)242