Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

Text1
DateTime1
Categorical1

Dataset

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

Reproduction

Analysis started2024-03-13 19:21:06.689148
Analysis finished2024-03-13 19:21:06.889132
Duration0.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자전거번호
Text

Distinct7750
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T04:21:07.083692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
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

Unique6005 ?
Unique (%)60.1%

Sample

1st rowSPB-01918
2nd rowSPB-18359
3rd rowSPB-00297
4th rowSPB-06666
5th rowSPB-12360
ValueCountFrequency (%)
spb-00007 14
 
0.1%
spb-00001 14
 
0.1%
spb-00120 14
 
0.1%
spb-00005 13
 
0.1%
spb-00013 9
 
0.1%
spb-00008 9
 
0.1%
spb-00011 8
 
0.1%
spb-06441 7
 
0.1%
spb-00002 7
 
0.1%
spb-00014 7
 
0.1%
Other values (7740) 9898
99.0%
2024-03-14T04:21:07.470602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 10000
11.1%
P 10000
11.1%
B 10000
11.1%
- 10000
11.1%
1 8712
9.7%
0 8502
9.4%
2 5252
 
5.8%
5 4089
 
4.5%
4 4080
 
4.5%
3 4047
 
4.5%
Other values (4) 15318
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50000
55.6%
Uppercase Letter 30000
33.3%
Dash Punctuation 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8712
17.4%
0 8502
17.0%
2 5252
10.5%
5 4089
8.2%
4 4080
8.2%
3 4047
8.1%
6 3938
7.9%
7 3857
7.7%
8 3779
7.6%
9 3744
7.5%
Uppercase Letter
ValueCountFrequency (%)
S 10000
33.3%
P 10000
33.3%
B 10000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60000
66.7%
Latin 30000
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 10000
16.7%
1 8712
14.5%
0 8502
14.2%
2 5252
8.8%
5 4089
6.8%
4 4080
6.8%
3 4047
6.7%
6 3938
 
6.6%
7 3857
 
6.4%
8 3779
 
6.3%
Latin
ValueCountFrequency (%)
S 10000
33.3%
P 10000
33.3%
B 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 10000
11.1%
P 10000
11.1%
B 10000
11.1%
- 10000
11.1%
1 8712
9.7%
0 8502
9.4%
2 5252
 
5.8%
5 4089
 
4.5%
4 4080
 
4.5%
3 4047
 
4.5%
Other values (4) 15318
17.0%

등록일시
Date

Distinct9871
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2016-02-14 18:32:56
Maximum2019-10-06 05:00:30
2024-03-14T04:21:07.586914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T04:21:07.689663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

고장구분
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단말기
2398 
체인
2069 
타이어
1992 
기타
1603 
안장
1221 
Other values (3)
717 

Length

Max length7
Median length4
Mean length2.8085
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단말기
2nd row기타
3rd row기타
4th row체인
5th row타이어

Common Values

ValueCountFrequency (%)
단말기 2398
24.0%
체인 2069
20.7%
타이어 1992
19.9%
기타 1603
16.0%
안장 1221
12.2%
페달 630
 
6.3%
파손 67
 
0.7%
잠금장치 불량 20
 
0.2%

Length

2024-03-14T04:21:07.782292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T04:21:07.876581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단말기 2398
23.9%
체인 2069
20.6%
타이어 1992
19.9%
기타 1603
16.0%
안장 1221
12.2%
페달 630
 
6.3%
파손 67
 
0.7%
잠금장치 20
 
0.2%
불량 20
 
0.2%

Missing values

2024-03-14T04:21:06.797992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T04:21:06.860911image/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
36922SPB-019182019-01-06 13:25:40단말기
53747SPB-183592019-05-25 04:45:49기타
1691SPB-002972017-05-25 21:37:25기타
23796SPB-066662018-09-11 08:49:24체인
38962SPB-123602019-02-23 22:43:44타이어
10321SPB-114352018-05-20 22:14:19타이어
35566SPB-076032018-12-06 12:04:01타이어
78919SPB-214792019-08-07 22:11:26단말기
64115SPB-035782019-06-24 08:29:22단말기
75433SPB-121362019-07-24 20:11:59타이어
자전거번호등록일시고장구분
81105SPB-133352019-08-16 19:01:11기타
72152SPB-169852019-07-15 01:56:06타이어
89330SPB-161122019-09-09 22:31:49기타
61306SPB-110012019-06-16 18:41:48기타
42559SPB-018492019-04-07 14:08:28단말기
89026SPB-225322019-09-08 23:49:50단말기
14917SPB-063702018-07-08 02:24:16단말기
706SPB-009662016-10-06 18:10:26단말기
53364SPB-028612019-05-23 22:57:37안장
48672SPB-002222019-05-08 20:10:25단말기