Overview

Dataset statistics

Number of variables7
Number of observations588
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.6 KiB
Average record size in memory60.2 B

Variable types

Categorical5
Numeric2

Dataset

Description공항철도 노선의 승강장 이격거리에 대한 데이터로 철도운영기관명, 선명, 역명, 승강장이격거리에 대한 승강장번호, 차량순서, 차량출입문번호, 안전거리의 데이터가 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041491/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-11 23:25:47.282594
Analysis finished2023-12-11 23:25:47.985568
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
공항철도
588 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공항철도 588
100.0%

Length

2023-12-12T08:25:48.048621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:48.146642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공항철도 588
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
공항
588 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공항 588
100.0%

Length

2023-12-12T08:25:48.232254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:48.317997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공항 588
100.0%

역명
Categorical

Distinct12
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
서울역
60 
검암
48 
계양
48 
공덕
48 
공항화물청사
48 
Other values (7)
336 

Length

Max length8
Median length6
Mean length3.8979592
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울역 60
10.2%
검암 48
8.2%
계양 48
8.2%
공덕 48
8.2%
공항화물청사 48
8.2%
김포공항 48
8.2%
디지털미디어시티 48
8.2%
영종 48
8.2%
운서 48
8.2%
인천국제공항 48
8.2%
Other values (2) 96
16.3%

Length

2023-12-12T08:25:48.422359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울역 60
10.2%
검암 48
8.2%
계양 48
8.2%
공덕 48
8.2%
공항화물청사 48
8.2%
김포공항 48
8.2%
디지털미디어시티 48
8.2%
영종 48
8.2%
운서 48
8.2%
인천국제공항 48
8.2%
Other values (2) 96
16.3%

승강장번호
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
1
288 
2
288 
3
 
12

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 (%)
1 288
49.0%
2 288
49.0%
3 12
 
2.0%

Length

2023-12-12T08:25:48.527202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:48.615211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 288
49.0%
2 288
49.0%
3 12
 
2.0%

차량순서
Real number (ℝ)

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-12T08:25:48.698302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3.5
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7092792
Coefficient of variation (CV)0.48836549
Kurtosis-1.2691511
Mean3.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum2058
Variance2.9216354
MonotonicityNot monotonic
2023-12-12T08:25:48.804992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 98
16.7%
2 98
16.7%
3 98
16.7%
4 98
16.7%
5 98
16.7%
6 98
16.7%
ValueCountFrequency (%)
1 98
16.7%
2 98
16.7%
3 98
16.7%
4 98
16.7%
5 98
16.7%
6 98
16.7%
ValueCountFrequency (%)
6 98
16.7%
5 98
16.7%
4 98
16.7%
3 98
16.7%
2 98
16.7%
1 98
16.7%

차량출입문번호
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
1
150 
2
150 
3
144 
4
144 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 150
25.5%
2 150
25.5%
3 144
24.5%
4 144
24.5%

Length

2023-12-12T08:25:48.913416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:25:49.306897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 150
25.5%
2 150
25.5%
3 144
24.5%
4 144
24.5%

안전거리
Real number (ℝ)

Distinct43
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3743197
Minimum5.2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-12T08:25:49.423215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.2
5-th percentile6.4
Q17.5
median8.5
Q39.5
95-th percentile10
Maximum10
Range4.8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1125291
Coefficient of variation (CV)0.13285009
Kurtosis-0.50568507
Mean8.3743197
Median Absolute Deviation (MAD)1
Skewness-0.48425748
Sum4924.1
Variance1.237721
MonotonicityNot monotonic
2023-12-12T08:25:49.537574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
9.5 101
17.2%
8.0 65
 
11.1%
9.0 56
 
9.5%
8.5 41
 
7.0%
10.0 37
 
6.3%
7.5 35
 
6.0%
7.0 21
 
3.6%
7.8 20
 
3.4%
6.5 17
 
2.9%
7.3 14
 
2.4%
Other values (33) 181
30.8%
ValueCountFrequency (%)
5.2 2
 
0.3%
5.4 2
 
0.3%
5.5 3
 
0.5%
5.7 2
 
0.3%
5.8 3
 
0.5%
6.0 9
1.5%
6.2 4
 
0.7%
6.3 2
 
0.3%
6.4 4
 
0.7%
6.5 17
2.9%
ValueCountFrequency (%)
10.0 37
 
6.3%
9.8 8
 
1.4%
9.7 4
 
0.7%
9.6 13
 
2.2%
9.5 101
17.2%
9.4 10
 
1.7%
9.3 3
 
0.5%
9.2 8
 
1.4%
9.1 2
 
0.3%
9.0 56
9.5%

Interactions

2023-12-12T08:25:47.642600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:25:47.482353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:25:47.746806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:25:47.553935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:25:49.626935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명승강장번호차량순서차량출입문번호안전거리
역명1.0000.5170.0000.0000.715
승강장번호0.5171.0000.0000.0750.445
차량순서0.0000.0001.0000.0000.132
차량출입문번호0.0000.0750.0001.0000.000
안전거리0.7150.4450.1320.0001.000
2023-12-12T08:25:49.717927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명승강장번호차량출입문번호
역명1.0000.2710.000
승강장번호0.2711.0000.070
차량출입문번호0.0000.0701.000
2023-12-12T08:25:49.803510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차량순서안전거리역명승강장번호차량출입문번호
차량순서1.0000.0210.0000.0000.000
안전거리0.0211.0000.4040.2970.000
역명0.0000.4041.0000.2710.000
승강장번호0.0000.2970.2711.0000.070
차량출입문번호0.0000.0000.0000.0701.000

Missing values

2023-12-12T08:25:47.854553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:25:47.947912image/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
0공항철도공항검암1139.5
1공항철도공항검암1149.5
2공항철도공항검암1119.5
3공항철도공항검암1127.0
4공항철도공항검암1239.7
5공항철도공항검암1249.5
6공항철도공항검암1219.5
7공항철도공항검암1226.5
8공항철도공항검암1326.5
9공항철도공항검암1339.6
철도운영기관명선명역명승강장번호차량순서차량출입문번호안전거리
578공항철도공항홍대입구24310.0
579공항철도공항홍대입구24210.0
580공항철도공항홍대입구2549.0
581공항철도공항홍대입구2529.5
582공항철도공항홍대입구2519.5
583공항철도공항홍대입구2539.5
584공항철도공항홍대입구2628.6
585공항철도공항홍대입구2639.0
586공항철도공항홍대입구2649.5
587공항철도공항홍대입구2618.6