Overview

Dataset statistics

Number of variables7
Number of observations544
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.0 KiB
Average record size in memory60.2 B

Variable types

Categorical6
Numeric1

Dataset

Description부산교통공사에서 운영하는 부산3호선의 승강장 이격거리에 대한 데이터로 철도운영기관명,선명,역명,승강장번호,차량순서,차량출입문번호,안전거리 등이 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041496/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant

Reproduction

Analysis started2023-12-12 22:44:42.264760
Analysis finished2023-12-12 22:44:42.882286
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
부산교통공사
544 

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 544
100.0%

Length

2023-12-13T07:44:42.956168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:44:43.052527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산교통공사 544
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
3호선
544 

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 544
100.0%

Length

2023-12-13T07:44:43.141855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:44:43.250371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3호선 544
100.0%

역명
Categorical

Distinct17
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
강서구청
 
32
거제(법원·검찰청)
 
32
구포
 
32
남산정(부산폴리텍대학)
 
32
대저
 
32
Other values (12)
384 

Length

Max length12
Median length10
Mean length4.5882353
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강서구청 32
 
5.9%
거제(법원·검찰청) 32
 
5.9%
구포 32
 
5.9%
남산정(부산폴리텍대학) 32
 
5.9%
대저 32
 
5.9%
덕천(부산과기대) 32
 
5.9%
만덕 32
 
5.9%
망미(병무청) 32
 
5.9%
물만골 32
 
5.9%
미남 32
 
5.9%
Other values (7) 224
41.2%

Length

2023-12-13T07:44:43.341251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구청 32
 
5.9%
미남 32
 
5.9%
종합운동장 32
 
5.9%
연산 32
 
5.9%
숙등(부민병원 32
 
5.9%
수영 32
 
5.9%
사직 32
 
5.9%
배산 32
 
5.9%
물만골 32
 
5.9%
거제(법원·검찰청 32
 
5.9%
Other values (7) 224
41.2%

승강장번호
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
1
272 
2
272 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 272
50.0%
2 272
50.0%

Length

2023-12-13T07:44:43.464223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:44:43.562438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 272
50.0%
2 272
50.0%

차량순서
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
1
136 
2
136 
3
136 
4
136 

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 (%)
1 136
25.0%
2 136
25.0%
3 136
25.0%
4 136
25.0%

Length

2023-12-13T07:44:43.667579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:44:43.761487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 136
25.0%
2 136
25.0%
3 136
25.0%
4 136
25.0%

차량출입문번호
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2
136 
1
136 
3
136 
4
136 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 136
25.0%
1 136
25.0%
3 136
25.0%
4 136
25.0%

Length

2023-12-13T07:44:43.865416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:44:43.960590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 136
25.0%
1 136
25.0%
3 136
25.0%
4 136
25.0%

안전거리
Real number (ℝ)

Distinct38
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4617647
Minimum4.5
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-13T07:44:44.065653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.5
5-th percentile8.7
Q19.1
median9.4
Q39.6
95-th percentile11
Maximum16
Range11.5
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation1.2123556
Coefficient of variation (CV)0.12813208
Kurtosis11.973956
Mean9.4617647
Median Absolute Deviation (MAD)0.2
Skewness1.3675119
Sum5147.2
Variance1.4698061
MonotonicityNot monotonic
2023-12-13T07:44:44.212666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
9.5 82
15.1%
9.3 60
11.0%
9.0 55
10.1%
9.2 53
9.7%
9.4 52
9.6%
9.6 36
 
6.6%
9.8 33
 
6.1%
9.7 32
 
5.9%
9.1 27
 
5.0%
8.9 19
 
3.5%
Other values (28) 95
17.5%
ValueCountFrequency (%)
4.5 1
 
0.2%
5.0 7
1.3%
5.2 1
 
0.2%
5.5 2
 
0.4%
6.0 1
 
0.2%
6.5 2
 
0.4%
7.0 1
 
0.2%
8.0 4
0.7%
8.5 5
0.9%
8.6 3
0.6%
ValueCountFrequency (%)
16.0 2
 
0.4%
15.5 3
0.6%
15.0 1
 
0.2%
14.5 3
0.6%
14.0 3
0.6%
13.5 1
 
0.2%
13.0 1
 
0.2%
12.5 3
0.6%
12.0 6
1.1%
11.8 1
 
0.2%

Interactions

2023-12-13T07:44:42.559799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:44:44.379947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명승강장번호차량순서차량출입문번호안전거리
역명1.0000.0000.0000.0000.616
승강장번호0.0001.0000.0000.0000.112
차량순서0.0000.0001.0000.0000.117
차량출입문번호0.0000.0000.0001.0000.222
안전거리0.6160.1120.1170.2221.000
2023-12-13T07:44:44.503158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차량출입문번호차량순서역명승강장번호
차량출입문번호1.0000.0000.0000.000
차량순서0.0001.0000.0000.000
역명0.0000.0001.0000.000
승강장번호0.0000.0000.0001.000
2023-12-13T07:44:44.628877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안전거리역명승강장번호차량순서차량출입문번호
안전거리1.0000.2940.0860.0740.135
역명0.2941.0000.0000.0000.000
승강장번호0.0860.0001.0000.0000.000
차량순서0.0740.0000.0001.0000.000
차량출입문번호0.1350.0000.0000.0001.000

Missing values

2023-12-13T07:44:42.710654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:44:42.829010image/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

철도운영기관명선명역명승강장번호차량순서차량출입문번호안전거리
0부산교통공사3호선강서구청1129.3
1부산교통공사3호선강서구청1119.4
2부산교통공사3호선강서구청1139.3
3부산교통공사3호선강서구청1149.5
4부산교통공사3호선강서구청1219.7
5부산교통공사3호선강서구청1229.6
6부산교통공사3호선강서구청1239.7
7부산교통공사3호선강서구청1249.6
8부산교통공사3호선강서구청1319.8
9부산교통공사3호선강서구청1329.8
철도운영기관명선명역명승강장번호차량순서차량출입문번호안전거리
534부산교통공사3호선체육공원2249.2
535부산교통공사3호선체육공원2239.1
536부산교통공사3호선체육공원2329.5
537부산교통공사3호선체육공원2318.6
538부산교통공사3호선체육공원2349.3
539부산교통공사3호선체육공원2339.2
540부산교통공사3호선체육공원2429.6
541부산교통공사3호선체육공원2419.4
542부산교통공사3호선체육공원2449.5
543부산교통공사3호선체육공원2439.4