Overview

Dataset statistics

Number of variables3
Number of observations6749
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory158.3 KiB
Average record size in memory24.0 B

Variable types

Text1
DateTime1
Categorical1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15644/A/1/datasetView.do

Reproduction

Analysis started2024-05-11 00:11:54.464972
Analysis finished2024-05-11 00:11:55.116410
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자전거번호
Text

Distinct4974
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
2024-05-11T00:11:55.516125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters60741
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3691 ?
Unique (%)54.7%

Sample

1st rowSPB-37924
2nd rowSPB-43077
3rd rowSPB-32462
4th rowSPB-39801
5th rowSPB-37194
ValueCountFrequency (%)
spb-31084 10
 
0.1%
spb-30722 7
 
0.1%
spb-34307 7
 
0.1%
spb-32743 7
 
0.1%
spb-50197 6
 
0.1%
spb-32106 6
 
0.1%
spb-42382 6
 
0.1%
spb-02189 6
 
0.1%
spb-35868 6
 
0.1%
spb-36054 6
 
0.1%
Other values (4964) 6682
99.0%
2024-05-11T00:11:56.506927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 6792
11.2%
S 6749
11.1%
P 6749
11.1%
B 6749
11.1%
- 6749
11.1%
4 4287
7.1%
5 3536
 
5.8%
2 3332
 
5.5%
1 3310
 
5.4%
0 3266
 
5.4%
Other values (4) 9222
15.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33745
55.6%
Uppercase Letter 20247
33.3%
Dash Punctuation 6749
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 6792
20.1%
4 4287
12.7%
5 3536
10.5%
2 3332
9.9%
1 3310
9.8%
0 3266
9.7%
9 2327
 
6.9%
6 2325
 
6.9%
8 2289
 
6.8%
7 2281
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
S 6749
33.3%
P 6749
33.3%
B 6749
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 6749
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40494
66.7%
Latin 20247
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
3 6792
16.8%
- 6749
16.7%
4 4287
10.6%
5 3536
8.7%
2 3332
8.2%
1 3310
8.2%
0 3266
8.1%
9 2327
 
5.7%
6 2325
 
5.7%
8 2289
 
5.7%
Latin
ValueCountFrequency (%)
S 6749
33.3%
P 6749
33.3%
B 6749
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60741
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 6792
11.2%
S 6749
11.1%
P 6749
11.1%
B 6749
11.1%
- 6749
11.1%
4 4287
7.1%
5 3536
 
5.8%
2 3332
 
5.5%
1 3310
 
5.4%
0 3266
 
5.4%
Other values (4) 9222
15.2%

등록일시
Date

Distinct5778
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
Minimum2020-11-01 00:10:00
Maximum2021-01-30 23:23:00
2024-05-11T00:11:56.936181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:11:57.403114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

고장구분
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
기타
2507 
체인
1270 
안장
1147 
단말기
705 
타이어
656 

Length

Max length4
Median length3
Mean length2.6703215
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row안장
3rd row체인
4th row안장
5th row체인

Common Values

ValueCountFrequency (%)
기타 2507
37.1%
체인 1270
18.8%
안장 1147
17.0%
단말기 705
 
10.4%
타이어 656
 
9.7%
페달 464
 
6.9%

Length

2024-05-11T00:11:57.849061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:11:58.205399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 2507
37.1%
체인 1270
18.8%
안장 1147
17.0%
단말기 705
 
10.4%
타이어 656
 
9.7%
페달 464
 
6.9%

Missing values

2024-05-11T00:11:54.751241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T00:11:55.010344image/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

자전거번호등록일시고장구분
0SPB-379242020-11-01 0:10기타
1SPB-430772020-11-01 0:24안장
2SPB-324622020-11-01 0:53체인
3SPB-398012020-11-01 1:09안장
4SPB-371942020-11-01 1:16체인
5SPB-508512020-11-01 1:19타이어
6SPB-447172020-11-01 1:49체인
7SPB-301722020-11-01 1:50체인
8SPB-338072020-11-01 2:01단말기
9SPB-306752020-11-01 2:08체인
자전거번호등록일시고장구분
6739SPB-537052021-01-30 18:54기타
6740SPB-350242021-01-30 18:54타이어
6741SPB-509872021-01-30 19:18기타
6742SPB-402242021-01-30 20:28기타
6743SPB-340692021-01-30 21:11기타
6744SPB-301212021-01-30 21:33기타
6745SPB-515562021-01-30 22:25기타
6746SPB-316822021-01-30 22:50기타
6747SPB-357882021-01-30 23:00기타
6748SPB-388032021-01-30 23:23타이어