Overview

Dataset statistics

Number of variables6
Number of observations215
Missing cells990
Missing cells (%)76.7%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory11.0 KiB
Average record size in memory52.6 B

Variable types

DateTime1
Text1
Unsupported4

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-14994/F/1/datasetView.do

Alerts

Dataset has 1 (0.5%) duplicate rowsDuplicates
대여일시 has 65 (30.2%) missing valuesMissing
대여건수 has 65 (30.2%) missing valuesMissing
Unnamed: 2 has 215 (100.0%) missing valuesMissing
Unnamed: 3 has 215 (100.0%) missing valuesMissing
Unnamed: 4 has 215 (100.0%) missing valuesMissing
Unnamed: 5 has 215 (100.0%) missing valuesMissing
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
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 06:51:47.704591
Analysis finished2023-12-11 06:51:48.100980
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일시
Date

MISSING 

Distinct150
Distinct (%)100.0%
Missing65
Missing (%)30.2%
Memory size1.8 KiB
Minimum2021-02-01 00:00:00
Maximum2021-06-30 00:00:00
2023-12-11T15:51:48.168664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:51:48.304874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대여건수
Text

MISSING 

Distinct149
Distinct (%)99.3%
Missing65
Missing (%)30.2%
Memory size1.8 KiB
2023-12-11T15:51:48.606984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.4133333
Min length7

Characters and Unicode

Total characters1262
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)98.7%

Sample

1st row 41,152
2nd row 31,136
3rd row 31,016
4th row 20,201
5th row 37,675
ValueCountFrequency (%)
41,123 2
 
1.3%
120,869 1
 
0.7%
128,239 1
 
0.7%
73,912 1
 
0.7%
114,851 1
 
0.7%
93,814 1
 
0.7%
130,314 1
 
0.7%
130,245 1
 
0.7%
128,298 1
 
0.7%
36,082 1
 
0.7%
Other values (139) 139
92.7%
2023-12-11T15:51:49.060701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
300
23.8%
1 151
12.0%
, 150
11.9%
2 96
 
7.6%
3 84
 
6.7%
0 73
 
5.8%
7 73
 
5.8%
8 71
 
5.6%
5 67
 
5.3%
9 67
 
5.3%
Other values (2) 130
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 812
64.3%
Space Separator 300
 
23.8%
Other Punctuation 150
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 151
18.6%
2 96
11.8%
3 84
10.3%
0 73
9.0%
7 73
9.0%
8 71
8.7%
5 67
8.3%
9 67
8.3%
4 65
8.0%
6 65
8.0%
Space Separator
ValueCountFrequency (%)
300
100.0%
Other Punctuation
ValueCountFrequency (%)
, 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1262
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
300
23.8%
1 151
12.0%
, 150
11.9%
2 96
 
7.6%
3 84
 
6.7%
0 73
 
5.8%
7 73
 
5.8%
8 71
 
5.6%
5 67
 
5.3%
9 67
 
5.3%
Other values (2) 130
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
300
23.8%
1 151
12.0%
, 150
11.9%
2 96
 
7.6%
3 84
 
6.7%
0 73
 
5.8%
7 73
 
5.8%
8 71
 
5.6%
5 67
 
5.3%
9 67
 
5.3%
Other values (2) 130
10.3%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing215
Missing (%)100.0%
Memory size2.0 KiB

Missing values

2023-12-11T15:51:47.842043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:51:47.953843image/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.
2023-12-11T15:51:48.050400image/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

대여일시대여건수Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
02021-02-0141,152<NA><NA><NA><NA>
12021-02-0231,136<NA><NA><NA><NA>
22021-02-0331,016<NA><NA><NA><NA>
32021-02-0420,201<NA><NA><NA><NA>
42021-02-0537,675<NA><NA><NA><NA>
52021-02-0641,507<NA><NA><NA><NA>
62021-02-0735,676<NA><NA><NA><NA>
72021-02-0834,253<NA><NA><NA><NA>
82021-02-0941,159<NA><NA><NA><NA>
92021-02-1046,659<NA><NA><NA><NA>
대여일시대여건수Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
205<NA><NA><NA><NA><NA><NA>
206<NA><NA><NA><NA><NA><NA>
207<NA><NA><NA><NA><NA><NA>
208<NA><NA><NA><NA><NA><NA>
209<NA><NA><NA><NA><NA><NA>
210<NA><NA><NA><NA><NA><NA>
211<NA><NA><NA><NA><NA><NA>
212<NA><NA><NA><NA><NA><NA>
213<NA><NA><NA><NA><NA><NA>
214<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

대여일시대여건수# duplicates
0<NA><NA>65