Overview

Dataset statistics

Number of variables6
Number of observations122
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory49.1 B

Variable types

Categorical5
Text1

Dataset

Description파일 다운로드
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-13293/F/1/datasetView.do

Alerts

호선 is highly overall correlated with 개폐방식High correlation
개폐방식 is highly overall correlated with 호선High correlation
사업방식 is highly overall correlated with 설치일High correlation
설치일 is highly overall correlated with 사업방식 and 1 other fieldsHigh correlation
공사업체 is highly overall correlated with 설치일High correlation

Reproduction

Analysis started2024-04-17 04:25:46.179600
Analysis finished2024-04-17 04:25:46.567117
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

호선
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2호선
52 
3호선
34 
4호선
26 
1호선
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호선
2nd row1호선
3rd row1호선
4th row1호선
5th row1호선

Common Values

ValueCountFrequency (%)
2호선 52
42.6%
3호선 34
27.9%
4호선 26
21.3%
1호선 10
 
8.2%

Length

2024-04-17T13:25:46.617054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:25:46.692747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2호선 52
42.6%
3호선 34
27.9%
4호선 26
21.3%
1호선 10
 
8.2%

개폐방식
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
센서 방식
70 
RF+센서 방식
52 

Length

Max length8
Median length5
Mean length6.2786885
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row센서 방식
2nd row센서 방식
3rd row센서 방식
4th row센서 방식
5th row센서 방식

Common Values

ValueCountFrequency (%)
센서 방식 70
57.4%
RF+센서 방식 52
42.6%

Length

2024-04-17T13:25:46.798819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:25:46.897029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방식 122
50.0%
센서 70
28.7%
rf+센서 52
21.3%

역사명
Text

Distinct113
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-17T13:25:47.139508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.4918033
Min length2

Characters and Unicode

Total characters426
Distinct characters144
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)85.2%

Sample

1st row서 울
2nd row시 청
3rd row종 각
4th row종로3가
5th row종로5가
ValueCountFrequency (%)
신 6
 
3.2%
대 6
 
3.2%
수 5
 
2.7%
동 4
 
2.2%
당 4
 
2.2%
서 3
 
1.6%
사 3
 
1.6%
원 3
 
1.6%
청 3
 
1.6%
교 2
 
1.1%
Other values (125) 146
78.9%
2024-04-17T13:25:47.502329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
14.8%
대 21
 
4.9%
신 16
 
3.8%
구 14
 
3.3%
동 13
 
3.1%
로 11
 
2.6%
문 9
 
2.1%
입 8
 
1.9%
지 8
 
1.9%
가 7
 
1.6%
Other values (134) 256
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 353
82.9%
Space Separator 63
 
14.8%
Decimal Number 6
 
1.4%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 21
 
5.9%
신 16
 
4.5%
구 14
 
4.0%
동 13
 
3.7%
로 11
 
3.1%
문 9
 
2.5%
입 8
 
2.3%
지 8
 
2.3%
가 7
 
2.0%
사 6
 
1.7%
Other values (128) 240
68.0%
Decimal Number
ValueCountFrequency (%)
3 4
66.7%
4 1
 
16.7%
5 1
 
16.7%
Space Separator
ValueCountFrequency (%)
63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 353
82.9%
Common 73
 
17.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 21
 
5.9%
신 16
 
4.5%
구 14
 
4.0%
동 13
 
3.7%
로 11
 
3.1%
문 9
 
2.5%
입 8
 
2.3%
지 8
 
2.3%
가 7
 
2.0%
사 6
 
1.7%
Other values (128) 240
68.0%
Common
ValueCountFrequency (%)
63
86.3%
3 4
 
5.5%
) 2
 
2.7%
( 2
 
2.7%
4 1
 
1.4%
5 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 353
82.9%
ASCII 73
 
17.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
86.3%
3 4
 
5.5%
) 2
 
2.7%
( 2
 
2.7%
4 1
 
1.4%
5 1
 
1.4%
Hangul
ValueCountFrequency (%)
대 21
 
5.9%
신 16
 
4.5%
구 14
 
4.0%
동 13
 
3.7%
로 11
 
3.1%
문 9
 
2.5%
입 8
 
2.3%
지 8
 
2.3%
가 7
 
2.0%
사 6
 
1.7%
Other values (128) 240
68.0%

사업방식
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
자체
95 
민자
24 
서울시(신설역)
 
3

Length

Max length8
Median length2
Mean length2.147541
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민자
2nd row민자
3rd row자체
4th row민자
5th row자체

Common Values

ValueCountFrequency (%)
자체 95
77.9%
민자 24
 
19.7%
서울시(신설역) 3
 
2.5%

Length

2024-04-17T13:25:47.613137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:25:47.690763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자체 95
77.9%
민자 24
 
19.7%
서울시(신설역 3
 
2.5%

설치일
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
’09.12.29
39 
’09.12.30
18 
’09.11.30
8 
’09.06.24
 
4
’09.12.22
 
3
Other values (31)
50 

Length

Max length9
Median length9
Mean length8.9918033
Min length8

Unique

Unique15 ?
Unique (%)12.3%

Sample

1st row’07.11.01
2nd row’0712.03
3rd row’09.12.29
4th row’08.01.03
5th row’09.12.29

Common Values

ValueCountFrequency (%)
’09.12.29 39
32.0%
’09.12.30 18
14.8%
’09.11.30 8
 
6.6%
’09.06.24 4
 
3.3%
’09.12.22 3
 
2.5%
’06.06.14 3
 
2.5%
’09.03.31 3
 
2.5%
’08.06.18 3
 
2.5%
’09.05.13 2
 
1.6%
’07.08.30 2
 
1.6%
Other values (26) 37
30.3%

Length

2024-04-17T13:25:47.771739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
’09.12.29 39
32.0%
’09.12.30 18
14.8%
’09.11.30 8
 
6.6%
’09.06.24 4
 
3.3%
’09.12.22 3
 
2.5%
’06.06.14 3
 
2.5%
’09.03.31 3
 
2.5%
’08.06.18 3
 
2.5%
’07.11.01 2
 
1.6%
’08.02.01 2
 
1.6%
Other values (26) 37
30.3%

공사업체
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
현대E/L
68 
삼중테크
36 
피에쓰에쓰텍
14 
서윤산업
 
4

Length

Max length6
Median length5
Mean length4.7868852
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row현대E/L
2nd row현대E/L
3rd row현대E/L
4th row현대E/L
5th row현대E/L

Common Values

ValueCountFrequency (%)
현대E/L 68
55.7%
삼중테크 36
29.5%
피에쓰에쓰텍 14
 
11.5%
서윤산업 4
 
3.3%

Length

2024-04-17T13:25:47.867947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:25:47.954161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
현대e/l 68
55.7%
삼중테크 36
29.5%
피에쓰에쓰텍 14
 
11.5%
서윤산업 4
 
3.3%

Correlations

2024-04-17T13:25:48.013043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선개폐방식사업방식설치일공사업체
호선1.0001.0000.2810.5910.387
개폐방식1.0001.0000.1950.6140.125
사업방식0.2810.1951.0000.8640.251
설치일0.5910.6140.8641.0000.989
공사업체0.3870.1250.2510.9891.000
2024-04-17T13:25:48.096134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선개폐방식사업방식공사업체설치일
호선1.0000.9920.2680.1580.269
개폐방식0.9921.0000.3190.0810.416
사업방식0.2680.3191.0000.2380.534
공사업체0.1580.0810.2381.0000.750
설치일0.2690.4160.5340.7501.000
2024-04-17T13:25:48.169596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선개폐방식사업방식설치일공사업체
호선1.0000.9920.2680.2690.158
개폐방식0.9921.0000.3190.4160.081
사업방식0.2680.3191.0000.5340.238
설치일0.2690.4160.5341.0000.750
공사업체0.1580.0810.2380.7501.000

Missing values

2024-04-17T13:25:46.459068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T13:25:46.536501image/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

호선개폐방식역사명사업방식설치일공사업체
01호선센서 방식서 울민자’07.11.01현대E/L
11호선센서 방식시 청민자’0712.03현대E/L
21호선센서 방식종 각자체’09.12.29현대E/L
31호선센서 방식종로3가민자’08.01.03현대E/L
41호선센서 방식종로5가자체’09.12.29현대E/L
51호선센서 방식동대문자체’08.06.18서윤산업
61호선센서 방식동 묘자체’06.01.10현대E/L
71호선센서 방식신설동자체’09.12.29현대E/L
81호선센서 방식제기동자체’09.12.29현대E/L
91호선센서 방식청량리자체’09.12.29현대E/L
호선개폐방식역사명사업방식설치일공사업체
1124호선센서 방식회 현자체’07.11.29현대E/L
1134호선센서 방식서울역자체’09.12.29현대E/L
1144호선센서 방식숙대입구자체’09.12.30삼중테크
1154호선센서 방식삼각지자체’09.12.29현대E/L
1164호선센서 방식신용산자체’09.03.31피에쓰에쓰텍
1174호선센서 방식이 촌자체’09.12.30삼중테크
1184호선센서 방식동 작자체’09.06.24현대E/L
1194호선센서 방식사 당자체’09.12.29현대E/L
1204호선센서 방식총신대입구자체’09.12.17삼중테크
1214호선센서 방식남태령자체’09.12.30삼중테크