Overview

Dataset statistics

Number of variables13
Number of observations22
Missing cells42
Missing cells (%)14.7%
Duplicate rows6
Duplicate rows (%)27.3%
Total size in memory2.4 KiB
Average record size in memory110.0 B

Variable types

Text2
Unsupported11

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2790/C/1/datasetView.do

Alerts

Dataset has 6 (27.3%) duplicate rowsDuplicates
서울도서관 도서분야별/성별 대출 통계(기준: 2018.1월~12월, 단위 : 권) has 17 (77.3%) missing valuesMissing
Unnamed: 1 has 3 (13.6%) missing valuesMissing
Unnamed: 2 has 2 (9.1%) missing valuesMissing
Unnamed: 3 has 2 (9.1%) missing valuesMissing
Unnamed: 4 has 2 (9.1%) missing valuesMissing
Unnamed: 5 has 2 (9.1%) missing valuesMissing
Unnamed: 6 has 2 (9.1%) missing valuesMissing
Unnamed: 7 has 2 (9.1%) missing valuesMissing
Unnamed: 8 has 2 (9.1%) missing valuesMissing
Unnamed: 9 has 2 (9.1%) missing valuesMissing
Unnamed: 10 has 2 (9.1%) missing valuesMissing
Unnamed: 11 has 2 (9.1%) missing valuesMissing
Unnamed: 12 has 2 (9.1%) 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
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 04:09:26.816466
Analysis finished2023-12-11 04:09:27.696963
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서울도서관 도서분야별/성별 대출 통계(기준: 2018.1월~12월, 단위 : 권)
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing17
Missing (%)77.3%
Memory size308.0 B
2023-12-11T13:09:27.818981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.8
Min length2

Characters and Unicode

Total characters14
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row남성
2nd row여성
3rd row기타
4th row탈퇴회원　
5th row합계　
ValueCountFrequency (%)
남성 1
20.0%
여성 1
20.0%
기타 1
20.0%
탈퇴회원 1
20.0%
합계 1
20.0%
2023-12-11T13:09:28.200080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
성 2
14.3%
　 2
14.3%
남 1
7.1%
여 1
7.1%
기 1
7.1%
타 1
7.1%
탈 1
7.1%
퇴 1
7.1%
회 1
7.1%
원 1
7.1%
Other values (2) 2
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
85.7%
Space Separator 2
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 2
16.7%
남 1
8.3%
여 1
8.3%
기 1
8.3%
타 1
8.3%
탈 1
8.3%
퇴 1
8.3%
회 1
8.3%
원 1
8.3%
합 1
8.3%
Space Separator
ValueCountFrequency (%)
　 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
85.7%
Common 2
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 2
16.7%
남 1
8.3%
여 1
8.3%
기 1
8.3%
타 1
8.3%
탈 1
8.3%
퇴 1
8.3%
회 1
8.3%
원 1
8.3%
합 1
8.3%
Common
ValueCountFrequency (%)
　 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
85.7%
None 2
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
성 2
16.7%
남 1
8.3%
여 1
8.3%
기 1
8.3%
타 1
8.3%
탈 1
8.3%
퇴 1
8.3%
회 1
8.3%
원 1
8.3%
합 1
8.3%
None
ValueCountFrequency (%)
　 2
100.0%

Unnamed: 1
Text

MISSING 

Distinct13
Distinct (%)68.4%
Missing3
Missing (%)13.6%
Memory size308.0 B
2023-12-11T13:09:28.401567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.3684211
Min length2

Characters and Unicode

Total characters83
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)36.8%

Sample

1st row연령대
2nd row아동(0-13)
3rd row청소년(14-19)
4th row20대
5th row30대
ValueCountFrequency (%)
20대 2
10.5%
30대 2
10.5%
40대 2
10.5%
50~64세 2
10.5%
65세이상 2
10.5%
소계 2
10.5%
연령대 1
 
5.3%
아동(0-13 1
 
5.3%
청소년(14-19 1
 
5.3%
아동 1
 
5.3%
Other values (3) 3
15.8%
2023-12-11T13:09:28.823567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
 
12.0%
대 7
 
8.4%
4 6
 
7.2%
1 6
 
7.2%
3 4
 
4.8%
5 4
 
4.8%
6 4
 
4.8%
세 4
 
4.8%
) 4
 
4.8%
소 4
 
4.8%
Other values (14) 30
36.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
45.8%
Other Letter 31
37.3%
Close Punctuation 4
 
4.8%
Dash Punctuation 4
 
4.8%
Open Punctuation 4
 
4.8%
Math Symbol 2
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 7
22.6%
세 4
12.9%
소 4
12.9%
동 2
 
6.5%
년 2
 
6.5%
청 2
 
6.5%
계 2
 
6.5%
아 2
 
6.5%
상 2
 
6.5%
이 2
 
6.5%
Other values (2) 2
 
6.5%
Decimal Number
ValueCountFrequency (%)
0 10
26.3%
4 6
15.8%
1 6
15.8%
3 4
 
10.5%
5 4
 
10.5%
6 4
 
10.5%
2 2
 
5.3%
9 2
 
5.3%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52
62.7%
Hangul 31
37.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
19.2%
4 6
11.5%
1 6
11.5%
3 4
 
7.7%
5 4
 
7.7%
6 4
 
7.7%
) 4
 
7.7%
- 4
 
7.7%
( 4
 
7.7%
2 2
 
3.8%
Other values (2) 4
 
7.7%
Hangul
ValueCountFrequency (%)
대 7
22.6%
세 4
12.9%
소 4
12.9%
동 2
 
6.5%
년 2
 
6.5%
청 2
 
6.5%
계 2
 
6.5%
아 2
 
6.5%
상 2
 
6.5%
이 2
 
6.5%
Other values (2) 2
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
62.7%
Hangul 31
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
19.2%
4 6
11.5%
1 6
11.5%
3 4
 
7.7%
5 4
 
7.7%
6 4
 
7.7%
) 4
 
7.7%
- 4
 
7.7%
( 4
 
7.7%
2 2
 
3.8%
Other values (2) 4
 
7.7%
Hangul
ValueCountFrequency (%)
대 7
22.6%
세 4
12.9%
소 4
12.9%
동 2
 
6.5%
년 2
 
6.5%
청 2
 
6.5%
계 2
 
6.5%
아 2
 
6.5%
상 2
 
6.5%
이 2
 
6.5%
Other values (2) 2
 
6.5%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Correlations

2023-12-11T13:09:28.940941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서울도서관 도서분야별/성별 대출 통계(기준: 2018.1월~12월, 단위 : 권)Unnamed: 1
서울도서관 도서분야별/성별 대출 통계(기준: 2018.1월~12월, 단위 : 권)1.0000.000
Unnamed: 10.0001.000

Missing values

2023-12-11T13:09:26.999888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:09:27.221914image/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.
2023-12-11T13:09:27.508132image/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

서울도서관 도서분야별/성별 대출 통계(기준: 2018.1월~12월, 단위 : 권)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
0<NA>연령대총류철학종교사회순수기술예술언어문학역사합계
1남성아동(0-13)118131475754142312878018015474231
2<NA>청소년(14-19)1561587307204168282787651502275
3<NA>20대102566419124923648201206429264597010806
4<NA>30대288014604756977694236524819995877298127189
5<NA>40대415822327638800209233796234174111034405044483
6<NA>50~64세186024661177751890125565890121110580359437753
7<NA>65세이상4841288810196944391748226447435218921001
8<NA>소계1068183993470286385112104362120251824013714481147738
9여성아동126835233431319329610119713843853
서울도서관 도서분야별/성별 대출 통계(기준: 2018.1월~12월, 단위 : 권)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
12<NA>(14-19)NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
13<NA>20대14062434509593462924533246113013264274833753
14<NA>30대1990417594610464145463715532229625532653265292
15<NA>40대225634518728901259055716064188926627583464055
16<NA>50~64세721193361932814652503314881810442236226292
17<NA>65세이상1083961524586329242811715323063852
18<NA>소계6748126483188299245819176291920464358131718382201294
19기타<NA>0004006016026
20탈퇴회원<NA>212821392160891818848614
21합계<NA>17450210756660587051095228125405011163512165832911349672

Duplicate rows

Most frequently occurring

서울도서관 도서분야별/성별 대출 통계(기준: 2018.1월~12월, 단위 : 권)Unnamed: 1# duplicates
0<NA>20대2
1<NA>30대2
2<NA>40대2
3<NA>50~64세2
4<NA>65세이상2
5<NA>소계2