Overview

Dataset statistics

Number of variables10
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory86.4 B

Variable types

Categorical6
Numeric1
Boolean3

Dataset

Description공항철도에 대한 승강장 정보(상하행 등) 관련 데이터로 철도운영기관명, 선명, 역명, 승강장번호, 상하행구분, 지상구분, 역층, 승강장연결 여부, 스크린도어 유무, 안전발판 유무의 데이터가 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041169/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
스크린도어 유무 has constant value ""Constant
역층 is highly overall correlated with 역명 and 3 other fieldsHigh correlation
역명 is highly overall correlated with 역층 and 3 other fieldsHigh correlation
지상구분 is highly overall correlated with 역층 and 2 other fieldsHigh correlation
승강장연결 여부 is highly overall correlated with 역층 and 1 other fieldsHigh correlation
안전발판 유무 is highly overall correlated with 역층 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 20:10:51.878265
Analysis finished2023-12-12 20:10:52.638171
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
공항철도주식회사
30 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공항철도주식회사 30
100.0%

Length

2023-12-13T05:10:52.711602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:52.846813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공항철도주식회사 30
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
공항철도
30 

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 30
100.0%

Length

2023-12-13T05:10:52.984753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:53.095013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공항철도 30
100.0%

역명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
디지털미디어시티
4 
서울역
3 
검암
2 
계양
2 
공덕
2 
Other values (9)
17 

Length

Max length8
Median length6
Mean length4.4333333
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
디지털미디어시티 4
13.3%
서울역 3
10.0%
검암 2
 
6.7%
계양 2
 
6.7%
공덕 2
 
6.7%
공항화물청사 2
 
6.7%
김포공항 2
 
6.7%
마곡나루 2
 
6.7%
영종 2
 
6.7%
운서 2
 
6.7%
Other values (4) 7
23.3%

Length

2023-12-13T05:10:53.209064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
디지털미디어시티 4
13.3%
서울역 3
10.0%
검암 2
 
6.7%
계양 2
 
6.7%
공덕 2
 
6.7%
공항화물청사 2
 
6.7%
김포공항 2
 
6.7%
마곡나루 2
 
6.7%
영종 2
 
6.7%
운서 2
 
6.7%
Other values (4) 7
23.3%

승강장번호
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2
14 
1
13 
3
2 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
2 14
46.7%
1 13
43.3%
3 2
 
6.7%
4 1
 
3.3%

Length

2023-12-13T05:10:53.369231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:53.497498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 14
46.7%
1 13
43.3%
3 2
 
6.7%
4 1
 
3.3%

상하행
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
하행
16 
상행
14 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row하행
2nd row상행
3rd row상행
4th row하행
5th row상행

Common Values

ValueCountFrequency (%)
하행 16
53.3%
상행 14
46.7%

Length

2023-12-13T05:10:53.620828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:53.748790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하행 16
53.3%
상행 14
46.7%

지상구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
지하
20 
지상
10 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지상
2nd row지상
3rd row지상
4th row지상
5th row지하

Common Values

ValueCountFrequency (%)
지하 20
66.7%
지상 10
33.3%

Length

2023-12-13T05:10:53.876355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:53.993691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하 20
66.7%
지상 10
33.3%

역층
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:10:54.081005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7290619
Coefficient of variation (CV)0.55776191
Kurtosis0.53447699
Mean3.1
Median Absolute Deviation (MAD)1
Skewness1.0360525
Sum93
Variance2.9896552
MonotonicityNot monotonic
2023-12-13T05:10:54.210269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 10
33.3%
3 6
20.0%
4 5
16.7%
1 4
 
13.3%
7 3
 
10.0%
5 2
 
6.7%
ValueCountFrequency (%)
1 4
 
13.3%
2 10
33.3%
3 6
20.0%
4 5
16.7%
5 2
 
6.7%
7 3
 
10.0%
ValueCountFrequency (%)
7 3
 
10.0%
5 2
 
6.7%
4 5
16.7%
3 6
20.0%
2 10
33.3%
1 4
 
13.3%

승강장연결 여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
26 
False
4 
ValueCountFrequency (%)
True 26
86.7%
False 4
 
13.3%
2023-12-13T05:10:54.336646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

스크린도어 유무
Boolean

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
30 
ValueCountFrequency (%)
True 30
100.0%
2023-12-13T05:10:54.432274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

안전발판 유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
18 
True
12 
ValueCountFrequency (%)
False 18
60.0%
True 12
40.0%
2023-12-13T05:10:54.519792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-13T05:10:52.272097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:10:54.591989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명승강장번호상하행지상구분역층승강장연결 여부안전발판 유무
역명1.0000.0000.0001.0000.9911.0000.995
승강장번호0.0001.0000.6820.0000.0000.6990.000
상하행0.0000.6821.0000.0000.0000.0000.000
지상구분1.0000.0000.0001.0000.9230.0000.944
역층0.9910.0000.0000.9231.0000.9100.766
승강장연결 여부1.0000.6990.0000.0000.9101.0000.195
안전발판 유무0.9950.0000.0000.9440.7660.1951.000
2023-12-13T05:10:54.715783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명상하행지상구분승강장연결 여부안전발판 유무승강장번호
역명1.0000.0000.7560.7560.7070.000
상하행0.0001.0000.0000.0000.0000.461
지상구분0.7560.0001.0000.0000.7850.000
승강장연결 여부0.7560.0000.0001.0000.1200.475
안전발판 유무0.7070.0000.7850.1201.0000.000
승강장번호0.0000.4610.0000.4750.0001.000
2023-12-13T05:10:54.857304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역층역명승강장번호상하행지상구분승강장연결 여부안전발판 유무
역층1.0000.7890.0000.0000.6960.6770.526
역명0.7891.0000.0000.0000.7560.7560.707
승강장번호0.0000.0001.0000.4610.0000.4750.000
상하행0.0000.0000.4611.0000.0000.0000.000
지상구분0.6960.7560.0000.0001.0000.0000.785
승강장연결 여부0.6770.7560.4750.0000.0001.0000.120
안전발판 유무0.5260.7070.0000.0000.7850.1201.000

Missing values

2023-12-13T05:10:52.405373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:10:52.578490image/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

철도운영기관명선명역명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
0공항철도주식회사공항철도검암1하행지상2YYY
1공항철도주식회사공항철도검암2상행지상2YYY
2공항철도주식회사공항철도계양2상행지상2YYY
3공항철도주식회사공항철도계양1하행지상2YYY
4공항철도주식회사공항철도공덕2상행지하5YYN
5공항철도주식회사공항철도공덕1하행지하5YYN
6공항철도주식회사공항철도공항화물청사1하행지하2YYN
7공항철도주식회사공항철도공항화물청사2상행지하2YYN
8공항철도주식회사공항철도김포공항2하행지하4YYN
9공항철도주식회사공항철도김포공항1상행지하3YYN
철도운영기관명선명역명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
20공항철도주식회사공항철도영종2상행지상1YYY
21공항철도주식회사공항철도운서1하행지상2YYY
22공항철도주식회사공항철도운서2상행지상2YYY
23공항철도주식회사공항철도인천공항1터미널2하행지하4YYN
24공항철도주식회사공항철도인천공항1터미널1상행지하4YYN
25공항철도주식회사공항철도인천공항2터미널2하행지하3YYY
26공항철도주식회사공항철도청라국제도시2하행지상1YYY
27공항철도주식회사공항철도청라국제도시1상행지상1YYY
28공항철도주식회사공항철도홍대입구2상행지하4YYY
29공항철도주식회사공항철도홍대입구1하행지하4YYN