Overview

Dataset statistics

Number of variables6
Number of observations73
Missing cells202
Missing cells (%)46.1%
Duplicate rows2
Duplicate rows (%)2.7%
Total size in memory3.6 KiB
Average record size in memory50.8 B

Variable types

Unsupported5
Text1

Dataset

Description파일 다운로드
Author서울 교통공사
URLhttps://data.seoul.go.kr/dataList/OA-13192/F/1/datasetView.do

Alerts

Dataset has 2 (2.7%) duplicate rowsDuplicates
◎ 휠체어리프트 역별 대수 has 63 (86.3%) missing valuesMissing
Unnamed: 1 has 1 (1.4%) missing valuesMissing
Unnamed: 3 has 1 (1.4%) missing valuesMissing
Unnamed: 4 has 64 (87.7%) missing valuesMissing
2019.12.01.기준 has 73 (100.0%) missing valuesMissing
◎ 휠체어리프트 역별 대수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
2019.12.01.기준 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 06:11:27.881895
Analysis finished2023-12-11 06:11:28.392043
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

◎ 휠체어리프트 역별 대수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)86.3%
Memory size716.0 B

Unnamed: 1
Text

MISSING 

Distinct70
Distinct (%)97.2%
Missing1
Missing (%)1.4%
Memory size716.0 B
2023-12-11T15:11:28.652090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.3888889
Min length2

Characters and Unicode

Total characters244
Distinct characters108
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)94.4%

Sample

1st row역명
2nd row서울(1)
3rd row신설동(1)
4th row청량리(1)
5th row삼성
ValueCountFrequency (%)
고속터미널 2
 
2.8%
잠실 2
 
2.8%
천호 1
 
1.4%
석계 1
 
1.4%
불광 1
 
1.4%
삼각지 1
 
1.4%
상수 1
 
1.4%
상월곡 1
 
1.4%
광명사거리 1
 
1.4%
역명 1
 
1.4%
Other values (60) 60
83.3%
2023-12-11T15:11:29.200475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9
 
3.7%
) 9
 
3.7%
( 9
 
3.7%
대 9
 
3.7%
구 7
 
2.9%
산 6
 
2.5%
청 5
 
2.0%
신 5
 
2.0%
문 5
 
2.0%
광 5
 
2.0%
Other values (98) 175
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216
88.5%
Decimal Number 10
 
4.1%
Close Punctuation 9
 
3.7%
Open Punctuation 9
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9
 
4.2%
대 9
 
4.2%
구 7
 
3.2%
산 6
 
2.8%
청 5
 
2.3%
신 5
 
2.3%
문 5
 
2.3%
광 5
 
2.3%
수 5
 
2.3%
리 4
 
1.9%
Other values (92) 156
72.2%
Decimal Number
ValueCountFrequency (%)
4 4
40.0%
1 3
30.0%
3 2
20.0%
2 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216
88.5%
Common 28
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9
 
4.2%
대 9
 
4.2%
구 7
 
3.2%
산 6
 
2.8%
청 5
 
2.3%
신 5
 
2.3%
문 5
 
2.3%
광 5
 
2.3%
수 5
 
2.3%
리 4
 
1.9%
Other values (92) 156
72.2%
Common
ValueCountFrequency (%)
) 9
32.1%
( 9
32.1%
4 4
14.3%
1 3
 
10.7%
3 2
 
7.1%
2 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216
88.5%
ASCII 28
 
11.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9
 
4.2%
대 9
 
4.2%
구 7
 
3.2%
산 6
 
2.8%
청 5
 
2.3%
신 5
 
2.3%
문 5
 
2.3%
광 5
 
2.3%
수 5
 
2.3%
리 4
 
1.9%
Other values (92) 156
72.2%
ASCII
ValueCountFrequency (%)
) 9
32.1%
( 9
32.1%
4 4
14.3%
1 3
 
10.7%
3 2
 
7.1%
2 1
 
3.6%

Unnamed: 2
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size716.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)1.4%
Memory size716.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing64
Missing (%)87.7%
Memory size716.0 B

2019.12.01.기준
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing73
Missing (%)100.0%
Memory size789.0 B

Missing values

2023-12-11T15:11:28.032945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:11:28.172384image/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.
2023-12-11T15:11:28.310261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

◎ 휠체어리프트 역별 대수Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 42019.12.01.기준
0호선역명기기대수합(호선별)<NA>
11서울(1)W/L19<NA>
2NaN신설동(1)W/L6NaN<NA>
3NaN청량리(1)W/L2NaN<NA>
42삼성W/L112<NA>
5NaN신설동(2)W/L6NaN<NA>
6NaN신정네거리W/L1NaN<NA>
7NaN용답W/L2NaN<NA>
8NaN잠실W/L1NaN<NA>
9NaN한양대W/L1NaN<NA>
◎ 휠체어리프트 역별 대수Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 42019.12.01.기준
63NaN온수W/L5NaN<NA>
64NaN이수W/L4NaN<NA>
65NaN청담W/L2NaN<NA>
668남한산성입구W/L213<NA>
67NaN모란W/L2NaN<NA>
68NaN복정W/L1NaN<NA>
69NaN수진W/L1NaN<NA>
70NaN잠실W/L3NaN<NA>
71NaN천호W/L4NaN<NA>
72총계<NA>149NaNNaN<NA>

Duplicate rows

Most frequently occurring

Unnamed: 1# duplicates
0고속터미널2
1잠실2