Overview

Dataset statistics

Number of variables7
Number of observations960
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory56.4 KiB
Average record size in memory60.1 B

Variable types

Categorical6
Numeric1

Dataset

Description서울메트로9호선에서 운영하는 노선의 승강장 이격거리에 대한 데이터로 철도운영기관명,선명,역명,승강장번호,차량순서,차량출입문번호,안전거리
Author국가철도공단
URLhttps://www.data.go.kr/data/15041522/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 13:41:42.079663
Analysis finished2023-12-12 13:41:42.721364
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
서울9호선
960 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울9호선
2nd row서울9호선
3rd row서울9호선
4th row서울9호선
5th row서울9호선

Common Values

ValueCountFrequency (%)
서울9호선 960
100.0%

Length

2023-12-12T22:41:42.811909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:42.934901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울9호선 960
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
9호선
960 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9호선
2nd row9호선
3rd row9호선
4th row9호선
5th row9호선

Common Values

ValueCountFrequency (%)
9호선 960
100.0%

Length

2023-12-12T22:41:43.047155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:43.144593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9호선 960
100.0%

역명
Categorical

Distinct30
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
가양
 
32
개화
 
32
고속터미널
 
32
공항시장
 
32
구반포
 
32
Other values (25)
800 

Length

Max length9
Median length7
Mean length3.3666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가양 32
 
3.3%
개화 32
 
3.3%
고속터미널 32
 
3.3%
공항시장 32
 
3.3%
구반포 32
 
3.3%
국회의사당 32
 
3.3%
김포공항 32
 
3.3%
노들 32
 
3.3%
노량진 32
 
3.3%
당산 32
 
3.3%
Other values (20) 640
66.7%

Length

2023-12-12T22:41:43.269128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가양 32
 
3.3%
개화 32
 
3.3%
증미 32
 
3.3%
종합운동장 32
 
3.3%
염창 32
 
3.3%
여의도 32
 
3.3%
언주 32
 
3.3%
양천향교 32
 
3.3%
신방화 32
 
3.3%
신반포 32
 
3.3%
Other values (20) 640
66.7%

승강장번호
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
1
480 
2
480 

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 (%)
1 480
50.0%
2 480
50.0%

Length

2023-12-12T22:41:43.436169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:43.570812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 480
50.0%
2 480
50.0%

차량순서
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
1
240 
2
240 
3
240 
4
240 

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 (%)
1 240
25.0%
2 240
25.0%
3 240
25.0%
4 240
25.0%

Length

2023-12-12T22:41:43.668539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:43.782634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 240
25.0%
2 240
25.0%
3 240
25.0%
4 240
25.0%

차량출입문번호
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
1
240 
2
240 
4
240 
3
240 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 240
25.0%
2 240
25.0%
4 240
25.0%
3 240
25.0%

Length

2023-12-12T22:41:43.898350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:44.018085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 240
25.0%
2 240
25.0%
4 240
25.0%
3 240
25.0%

안전거리
Real number (ℝ)

Distinct65
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9417708
Minimum3.8
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2023-12-12T22:41:44.170300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.8
5-th percentile4.9
Q15.6
median7
Q37.9
95-th percentile9.5
Maximum15
Range11.2
Interquartile range (IQR)2.3

Descriptive statistics

Standard deviation1.5397463
Coefficient of variation (CV)0.22180886
Kurtosis0.97114455
Mean6.9417708
Median Absolute Deviation (MAD)1.2
Skewness0.64515434
Sum6664.1
Variance2.3708186
MonotonicityNot monotonic
2023-12-12T22:41:44.347727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.8 47
 
4.9%
7.0 38
 
4.0%
7.2 38
 
4.0%
5.2 34
 
3.5%
5.3 34
 
3.5%
5.4 33
 
3.4%
7.8 33
 
3.4%
7.3 31
 
3.2%
5.5 30
 
3.1%
7.6 29
 
3.0%
Other values (55) 613
63.9%
ValueCountFrequency (%)
3.8 1
 
0.1%
4.0 1
 
0.1%
4.2 1
 
0.1%
4.5 7
 
0.7%
4.6 4
 
0.4%
4.7 7
 
0.7%
4.8 19
2.0%
4.9 26
2.7%
5.0 26
2.7%
5.1 15
1.6%
ValueCountFrequency (%)
15.0 2
 
0.2%
13.5 1
 
0.1%
12.7 1
 
0.1%
12.0 1
 
0.1%
11.0 3
 
0.3%
10.9 1
 
0.1%
10.0 1
 
0.1%
9.9 6
0.6%
9.8 12
1.2%
9.7 9
0.9%

Interactions

2023-12-12T22:41:42.384940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:41:44.499646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명승강장번호차량순서차량출입문번호안전거리
역명1.0000.0000.0000.0000.845
승강장번호0.0001.0000.0000.0000.057
차량순서0.0000.0001.0000.0000.145
차량출입문번호0.0000.0000.0001.0000.000
안전거리0.8450.0570.1450.0001.000
2023-12-12T22:41:44.609177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명차량출입문번호차량순서승강장번호
역명1.0000.0000.0000.000
차량출입문번호0.0001.0000.0000.000
차량순서0.0000.0001.0000.000
승강장번호0.0000.0000.0001.000
2023-12-12T22:41:44.748347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안전거리역명승강장번호차량순서차량출입문번호
안전거리1.0000.4440.0440.0870.000
역명0.4441.0000.0000.0000.000
승강장번호0.0440.0001.0000.0000.000
차량순서0.0870.0000.0001.0000.000
차량출입문번호0.0000.0000.0000.0001.000

Missing values

2023-12-12T22:41:42.537726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:41:42.667978image/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
0서울9호선9호선가양1115.6
1서울9호선9호선가양1124.7
2서울9호선9호선가양1146.0
3서울9호선9호선가양1135.4
4서울9호선9호선가양1215.6
5서울9호선9호선가양1225.7
6서울9호선9호선가양1235.7
7서울9호선9호선가양1245.7
8서울9호선9호선가양1316.0
9서울9호선9호선가양1335.5
철도운영기관명선명역명승강장번호차량순서차량출입문번호안전거리
950서울9호선9호선흑석(중앙대입구)2229.2
951서울9호선9호선흑석(중앙대입구)2248.5
952서울9호선9호선흑석(중앙대입구)2318.0
953서울9호선9호선흑석(중앙대입구)2349.9
954서울9호선9호선흑석(중앙대입구)2328.1
955서울9호선9호선흑석(중앙대입구)2338.1
956서울9호선9호선흑석(중앙대입구)2419.4
957서울9호선9호선흑석(중앙대입구)2429.3
958서울9호선9호선흑석(중앙대입구)2449.2
959서울9호선9호선흑석(중앙대입구)2439.6