Overview

Dataset statistics

Number of variables5
Number of observations105
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory42.3 B

Variable types

Categorical3
Numeric1
Text1

Dataset

Description부산4호선에 포함된 도시광역철도역들의 철도운영기관명,선명,역명,출구번호,출구별 주요시설명 등의 데이터 입니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15068952/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 11:34:46.051515
Analysis finished2023-12-12 11:34:46.845920
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
부산교통공사
105 

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 105
100.0%

Length

2023-12-12T20:34:46.985287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:34:47.167660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산교통공사 105
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
4호선
105 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4호선
2nd row4호선
3rd row4호선
4th row4호선
5th row4호선

Common Values

ValueCountFrequency (%)
4호선 105
100.0%

Length

2023-12-12T20:34:47.369367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:34:47.570006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4호선 105
100.0%

역명
Categorical

Distinct14
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size972.0 B
동래
12 
낙민
10 
수안
10 
영산대(아랫반송)
10 
충렬사(안락)
10 
Other values (9)
53 

Length

Max length10
Median length2
Mean length3.7809524
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고촌
2nd row고촌
3rd row고촌
4th row금사
5th row금사

Common Values

ValueCountFrequency (%)
동래 12
11.4%
낙민 10
9.5%
수안 10
9.5%
영산대(아랫반송) 10
9.5%
충렬사(안락) 10
9.5%
미남 9
8.6%
윗반송 9
8.6%
금사 8
7.6%
명장 8
7.6%
서동 6
5.7%
Other values (4) 13
12.4%

Length

2023-12-12T20:34:47.750254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
동래 12
11.4%
낙민 10
9.5%
수안 10
9.5%
영산대(아랫반송 10
9.5%
충렬사(안락 10
9.5%
미남 9
8.6%
윗반송 9
8.6%
금사 8
7.6%
명장 8
7.6%
서동 6
5.7%
Other values (4) 13
12.4%

출구번호
Real number (ℝ)

Distinct14
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.752381
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T20:34:47.952801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile8.8
Maximum14
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.7588353
Coefficient of variation (CV)0.7352226
Kurtosis2.523206
Mean3.752381
Median Absolute Deviation (MAD)1
Skewness1.5907118
Sum394
Variance7.6111722
MonotonicityNot monotonic
2023-12-12T20:34:48.173511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 29
27.6%
4 18
17.1%
3 17
16.2%
1 16
15.2%
7 6
 
5.7%
8 6
 
5.7%
5 4
 
3.8%
6 3
 
2.9%
10 1
 
1.0%
11 1
 
1.0%
Other values (4) 4
 
3.8%
ValueCountFrequency (%)
1 16
15.2%
2 29
27.6%
3 17
16.2%
4 18
17.1%
5 4
 
3.8%
6 3
 
2.9%
7 6
 
5.7%
8 6
 
5.7%
9 1
 
1.0%
10 1
 
1.0%
ValueCountFrequency (%)
14 1
 
1.0%
13 1
 
1.0%
12 1
 
1.0%
11 1
 
1.0%
10 1
 
1.0%
9 1
 
1.0%
8 6
5.7%
7 6
5.7%
6 3
2.9%
5 4
3.8%

출구별 주요시설명
Text

Distinct89
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size972.0 B
2023-12-12T20:34:48.602554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length6.4190476
Min length3

Characters and Unicode

Total characters674
Distinct characters141
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)71.4%

Sample

1st row반송방면
2nd row운봉우체국
3rd row안평방면
4th row금사동주민센터
5th row금사초등학교
ValueCountFrequency (%)
반송방면 3
 
2.6%
내성교차로방면 3
 
2.6%
미남초등학교 2
 
1.7%
동래경찰서 2
 
1.7%
석대방면 2
 
1.7%
부산광역시 2
 
1.7%
운봉우체국 2
 
1.7%
안락교차로방면 2
 
1.7%
반여농산물시장 2
 
1.7%
사직지구대 2
 
1.7%
Other values (89) 94
81.0%
2023-12-12T20:34:49.322118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 35
 
5.2%
동 29
 
4.3%
학 28
 
4.2%
방 21
 
3.1%
면 20
 
3.0%
등 19
 
2.8%
산 16
 
2.4%
송 16
 
2.4%
안 15
 
2.2%
초 15
 
2.2%
Other values (131) 460
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 638
94.7%
Decimal Number 18
 
2.7%
Space Separator 11
 
1.6%
Uppercase Letter 4
 
0.6%
Other Punctuation 2
 
0.3%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 35
 
5.5%
동 29
 
4.5%
학 28
 
4.4%
방 21
 
3.3%
면 20
 
3.1%
등 19
 
3.0%
산 16
 
2.5%
송 16
 
2.5%
안 15
 
2.4%
초 15
 
2.4%
Other values (120) 424
66.5%
Decimal Number
ValueCountFrequency (%)
1 7
38.9%
2 5
27.8%
3 4
22.2%
9 2
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
Y 1
25.0%
M 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 639
94.8%
Common 31
 
4.6%
Latin 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 35
 
5.5%
동 29
 
4.5%
학 28
 
4.4%
방 21
 
3.3%
면 20
 
3.1%
등 19
 
3.0%
산 16
 
2.5%
송 16
 
2.5%
안 15
 
2.3%
초 15
 
2.3%
Other values (121) 425
66.5%
Common
ValueCountFrequency (%)
11
35.5%
1 7
22.6%
2 5
16.1%
3 4
 
12.9%
9 2
 
6.5%
/ 2
 
6.5%
Latin
ValueCountFrequency (%)
C 1
25.0%
Y 1
25.0%
M 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 638
94.7%
ASCII 35
 
5.2%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 35
 
5.5%
동 29
 
4.5%
학 28
 
4.4%
방 21
 
3.3%
면 20
 
3.1%
등 19
 
3.0%
산 16
 
2.5%
송 16
 
2.5%
안 15
 
2.4%
초 15
 
2.4%
Other values (120) 424
66.5%
ASCII
ValueCountFrequency (%)
11
31.4%
1 7
20.0%
2 5
14.3%
3 4
 
11.4%
9 2
 
5.7%
/ 2
 
5.7%
C 1
 
2.9%
Y 1
 
2.9%
M 1
 
2.9%
A 1
 
2.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

Interactions

2023-12-12T20:34:46.352711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:34:49.509329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명출구번호출구별 주요시설명
역명1.0000.5690.000
출구번호0.5691.0000.000
출구별 주요시설명0.0000.0001.000
2023-12-12T20:34:49.686656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구번호역명
출구번호1.0000.263
역명0.2631.000

Missing values

2023-12-12T20:34:46.582392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:34:46.763445image/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

철도운영기관명선명역명출구번호출구별 주요시설명
0부산교통공사4호선고촌1반송방면
1부산교통공사4호선고촌2운봉우체국
2부산교통공사4호선고촌4안평방면
3부산교통공사4호선금사1금사동주민센터
4부산교통공사4호선금사1금사초등학교
5부산교통공사4호선금사1부산지방노동위원회
6부산교통공사4호선금사2금사동방면
7부산교통공사4호선금사3석대사거리방면
8부산교통공사4호선금사4금정구종합사회복지관
9부산교통공사4호선금사4서금지구대
철도운영기관명선명역명출구번호출구별 주요시설명
95부산교통공사4호선충렬사(안락)1충렬사
96부산교통공사4호선충렬사(안락)1충렬지구대
97부산교통공사4호선충렬사(안락)2동래봉생병원
98부산교통공사4호선충렬사(안락)2미래병원
99부산교통공사4호선충렬사(안락)2안락교차로방면
100부산교통공사4호선충렬사(안락)2좋은애인병원
101부산교통공사4호선충렬사(안락)2한마음교회
102부산교통공사4호선충렬사(안락)3동현교회
103부산교통공사4호선충렬사(안락)3학산여자 중/고등학교
104부산교통공사4호선충렬사(안락)4서원시장