Overview

Dataset statistics

Number of variables6
Number of observations213
Missing cells916
Missing cells (%)71.7%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory10.9 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 32 (15.0%) missing valuesMissing
대여건수 has 32 (15.0%) missing valuesMissing
Unnamed: 2 has 213 (100.0%) missing valuesMissing
Unnamed: 3 has 213 (100.0%) missing valuesMissing
Unnamed: 4 has 213 (100.0%) missing valuesMissing
Unnamed: 5 has 213 (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 06:51:59.233920
Analysis finished2023-12-11 06:51:59.610363
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일시
Date

MISSING 

Distinct181
Distinct (%)100.0%
Missing32
Missing (%)15.0%
Memory size1.8 KiB
Minimum2022-01-01 00:00:00
Maximum2022-06-30 00:00:00
2023-12-11T15:51:59.692613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:51:59.837732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대여건수
Text

MISSING 

Distinct181
Distinct (%)100.0%
Missing32
Missing (%)15.0%
Memory size1.8 KiB
2023-12-11T15:52:00.299302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.4751381
Min length7

Characters and Unicode

Total characters1534
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

Unique181 ?
Unique (%)100.0%

Sample

1st row 29,185
2nd row 28,914
3rd row 53,573
4th row 56,344
5th row 57,413
ValueCountFrequency (%)
41,704 1
 
0.6%
179,409 1
 
0.6%
156,150 1
 
0.6%
157,045 1
 
0.6%
115,321 1
 
0.6%
125,572 1
 
0.6%
123,804 1
 
0.6%
155,868 1
 
0.6%
161,630 1
 
0.6%
169,370 1
 
0.6%
Other values (171) 171
94.5%
2023-12-11T15:52:00.898876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
362
23.6%
, 181
11.8%
1 163
10.6%
4 113
 
7.4%
7 111
 
7.2%
5 102
 
6.6%
8 96
 
6.3%
6 93
 
6.1%
3 88
 
5.7%
2 81
 
5.3%
Other values (2) 144
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 991
64.6%
Space Separator 362
 
23.6%
Other Punctuation 181
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 163
16.4%
4 113
11.4%
7 111
11.2%
5 102
10.3%
8 96
9.7%
6 93
9.4%
3 88
8.9%
2 81
8.2%
9 74
7.5%
0 70
7.1%
Space Separator
ValueCountFrequency (%)
362
100.0%
Other Punctuation
ValueCountFrequency (%)
, 181
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1534
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
362
23.6%
, 181
11.8%
1 163
10.6%
4 113
 
7.4%
7 111
 
7.2%
5 102
 
6.6%
8 96
 
6.3%
6 93
 
6.1%
3 88
 
5.7%
2 81
 
5.3%
Other values (2) 144
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1534
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
362
23.6%
, 181
11.8%
1 163
10.6%
4 113
 
7.4%
7 111
 
7.2%
5 102
 
6.6%
8 96
 
6.3%
6 93
 
6.1%
3 88
 
5.7%
2 81
 
5.3%
Other values (2) 144
 
9.4%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

Missing values

2023-12-11T15:51:59.337114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:51:59.445487image/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.
2023-12-11T15:51:59.545833image/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
02022-01-0129,185<NA><NA><NA><NA>
12022-01-0228,914<NA><NA><NA><NA>
22022-01-0353,573<NA><NA><NA><NA>
32022-01-0456,344<NA><NA><NA><NA>
42022-01-0557,413<NA><NA><NA><NA>
52022-01-0659,714<NA><NA><NA><NA>
62022-01-0760,422<NA><NA><NA><NA>
72022-01-0845,366<NA><NA><NA><NA>
82022-01-0938,304<NA><NA><NA><NA>
92022-01-1058,706<NA><NA><NA><NA>
대여일시대여건수Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
203<NA><NA><NA><NA><NA><NA>
204<NA><NA><NA><NA><NA><NA>
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>

Duplicate rows

Most frequently occurring

대여일시대여건수# duplicates
0<NA><NA>32