Overview

Dataset statistics

Number of variables6
Number of observations37
Missing cells147
Missing cells (%)66.2%
Duplicate rows1
Duplicate rows (%)2.7%
Total size in memory2.0 KiB
Average record size in memory54.6 B

Variable types

Unsupported3
Text3

Dataset

Description부산광역시북구_사회조사결과_20221231
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15117946

Alerts

Dataset has 1 (2.7%) duplicate rowsDuplicates
Unnamed: 0 has 37 (100.0%) missing valuesMissing
2022 부산사회조사 통계표 has 5 (13.5%) missing valuesMissing
Unnamed: 2 has 37 (100.0%) missing valuesMissing
Unnamed: 3 has 14 (37.8%) missing valuesMissing
Unnamed: 4 has 37 (100.0%) missing valuesMissing
Unnamed: 5 has 17 (45.9%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 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

Reproduction

Analysis started2023-12-10 17:19:19.210460
Analysis finished2023-12-10 17:19:20.447551
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

2022 부산사회조사 통계표
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing5
Missing (%)13.5%
Memory size428.0 B
2023-12-11T02:19:20.846723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19.5
Mean length15.03125
Min length5

Characters and Unicode

Total characters481
Distinct characters136
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row조사대상 가구원 일반적 특성
2nd rowI. 건강
3rd row01.운동횟수
4th row01-1.운동을 하지 않은 이유
5th row01-2.운동 시 이용시설(공간)(복수응답)
ValueCountFrequency (%)
의료기관 3
 
3.2%
환경 3
 
3.2%
대한 3
 
3.2%
02.건강증진을 2
 
2.1%
사유 2
 
2.1%
만족도 2
 
2.1%
두려움 2
 
2.1%
범죄피해에 2
 
2.1%
안전 2
 
2.1%
위한 2
 
2.1%
Other values (72) 72
75.8%
2023-12-11T02:19:21.766074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
13.1%
. 31
 
6.4%
1 21
 
4.4%
0 17
 
3.5%
안 9
 
1.9%
사 9
 
1.9%
( 8
 
1.7%
) 8
 
1.7%
부 8
 
1.7%
I 7
 
1.5%
Other values (126) 300
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 292
60.7%
Decimal Number 64
 
13.3%
Space Separator 63
 
13.1%
Other Punctuation 31
 
6.4%
Open Punctuation 8
 
1.7%
Close Punctuation 8
 
1.7%
Uppercase Letter 8
 
1.7%
Dash Punctuation 7
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 9
 
3.1%
사 9
 
3.1%
부 8
 
2.7%
이 7
 
2.4%
전 7
 
2.4%
한 6
 
2.1%
수 6
 
2.1%
의 6
 
2.1%
대 5
 
1.7%
답 5
 
1.7%
Other values (109) 224
76.7%
Decimal Number
ValueCountFrequency (%)
1 21
32.8%
0 17
26.6%
2 6
 
9.4%
4 4
 
6.2%
7 4
 
6.2%
6 3
 
4.7%
3 3
 
4.7%
5 2
 
3.1%
8 2
 
3.1%
9 2
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
I 7
87.5%
V 1
 
12.5%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Punctuation
ValueCountFrequency (%)
. 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 292
60.7%
Common 181
37.6%
Latin 8
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 9
 
3.1%
사 9
 
3.1%
부 8
 
2.7%
이 7
 
2.4%
전 7
 
2.4%
한 6
 
2.1%
수 6
 
2.1%
의 6
 
2.1%
대 5
 
1.7%
답 5
 
1.7%
Other values (109) 224
76.7%
Common
ValueCountFrequency (%)
63
34.8%
. 31
17.1%
1 21
 
11.6%
0 17
 
9.4%
( 8
 
4.4%
) 8
 
4.4%
- 7
 
3.9%
2 6
 
3.3%
4 4
 
2.2%
7 4
 
2.2%
Other values (5) 12
 
6.6%
Latin
ValueCountFrequency (%)
I 7
87.5%
V 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 292
60.7%
ASCII 189
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
33.3%
. 31
16.4%
1 21
 
11.1%
0 17
 
9.0%
( 8
 
4.2%
) 8
 
4.2%
I 7
 
3.7%
- 7
 
3.7%
2 6
 
3.2%
4 4
 
2.1%
Other values (7) 17
 
9.0%
Hangul
ValueCountFrequency (%)
안 9
 
3.1%
사 9
 
3.1%
부 8
 
2.7%
이 7
 
2.4%
전 7
 
2.4%
한 6
 
2.1%
수 6
 
2.1%
의 6
 
2.1%
대 5
 
1.7%
답 5
 
1.7%
Other values (109) 224
76.7%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

Unnamed: 3
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing14
Missing (%)37.8%
Memory size428.0 B
2023-12-11T02:19:22.279632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length15.521739
Min length7

Characters and Unicode

Total characters357
Distinct characters105
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st rowV. 사회통합
2nd row20.지역민으로서의 자부심
3rd row21.지역민으로서의 지역정체성
4th row22.주관적 귀속계층
5th row23.사회적 관계 소통 정도
ValueCountFrequency (%)
자녀의 2
 
3.2%
정도 2
 
3.2%
신뢰도 2
 
3.2%
대한 2
 
3.2%
및 2
 
3.2%
v 1
 
1.6%
36.월평균 1
 
1.6%
ⅵ 1
 
1.6%
가구관련사항 1
 
1.6%
32.주거형태(가구주 1
 
1.6%
Other values (47) 47
75.8%
2023-12-11T02:19:23.035803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
10.9%
. 23
 
6.4%
2 12
 
3.4%
3 12
 
3.4%
주 12
 
3.4%
가 12
 
3.4%
) 11
 
3.1%
( 11
 
3.1%
구 10
 
2.8%
1 7
 
2.0%
Other values (95) 208
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 219
61.3%
Decimal Number 48
 
13.4%
Space Separator 39
 
10.9%
Other Punctuation 23
 
6.4%
Close Punctuation 11
 
3.1%
Open Punctuation 11
 
3.1%
Dash Punctuation 4
 
1.1%
Letter Number 1
 
0.3%
Uppercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 12
 
5.5%
가 12
 
5.5%
구 10
 
4.6%
거 6
 
2.7%
도 6
 
2.7%
족 5
 
2.3%
사 5
 
2.3%
의 5
 
2.3%
자 5
 
2.3%
부 5
 
2.3%
Other values (78) 148
67.6%
Decimal Number
ValueCountFrequency (%)
2 12
25.0%
3 12
25.0%
1 7
14.6%
8 4
 
8.3%
7 3
 
6.2%
9 2
 
4.2%
5 2
 
4.2%
6 2
 
4.2%
0 2
 
4.2%
4 2
 
4.2%
Space Separator
ValueCountFrequency (%)
39
100.0%
Other Punctuation
ValueCountFrequency (%)
. 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅵ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
V 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 219
61.3%
Common 136
38.1%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 12
 
5.5%
가 12
 
5.5%
구 10
 
4.6%
거 6
 
2.7%
도 6
 
2.7%
족 5
 
2.3%
사 5
 
2.3%
의 5
 
2.3%
자 5
 
2.3%
부 5
 
2.3%
Other values (78) 148
67.6%
Common
ValueCountFrequency (%)
39
28.7%
. 23
16.9%
2 12
 
8.8%
3 12
 
8.8%
) 11
 
8.1%
( 11
 
8.1%
1 7
 
5.1%
8 4
 
2.9%
- 4
 
2.9%
7 3
 
2.2%
Other values (5) 10
 
7.4%
Latin
ValueCountFrequency (%)
Ⅵ 1
50.0%
V 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 219
61.3%
ASCII 137
38.4%
Number Forms 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
28.5%
. 23
16.8%
2 12
 
8.8%
3 12
 
8.8%
) 11
 
8.0%
( 11
 
8.0%
1 7
 
5.1%
8 4
 
2.9%
- 4
 
2.9%
7 3
 
2.2%
Other values (6) 11
 
8.0%
Hangul
ValueCountFrequency (%)
주 12
 
5.5%
가 12
 
5.5%
구 10
 
4.6%
거 6
 
2.7%
도 6
 
2.7%
족 5
 
2.3%
사 5
 
2.3%
의 5
 
2.3%
자 5
 
2.3%
부 5
 
2.3%
Other values (78) 148
67.6%
Number Forms
ValueCountFrequency (%)
Ⅵ 1
100.0%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)100.0%
Memory size465.0 B

Unnamed: 5
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing17
Missing (%)45.9%
Memory size428.0 B
2023-12-11T02:19:23.455478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19.5
Mean length14.6
Min length9

Characters and Unicode

Total characters292
Distinct characters111
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st rowⅦ. 개인관련사항
2nd row49.유배우 여성의 맞벌이 여부 및 1주간 경제활동
3rd row50.유배우 여성의 일하는 사유
4th row51.맞벌이 여성의 일 중단 시기
5th row52.이주계획 여부 및 이주시기
ValueCountFrequency (%)
여성의 3
 
5.1%
여부 2
 
3.4%
및 2
 
3.4%
이유 2
 
3.4%
◆ 2
 
3.4%
시기 2
 
3.4%
ⅶ 1
 
1.7%
61.지역교육만족도 1
 
1.7%
계획 1
 
1.7%
58.귀농귀촌 1
 
1.7%
Other values (42) 42
71.2%
2023-12-11T02:19:24.223986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
13.4%
. 19
 
6.5%
5 13
 
4.5%
이 9
 
3.1%
귀 8
 
2.7%
유 7
 
2.4%
6 7
 
2.4%
주 6
 
2.1%
여 6
 
2.1%
지 5
 
1.7%
Other values (101) 173
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 185
63.4%
Space Separator 39
 
13.4%
Decimal Number 38
 
13.0%
Other Punctuation 22
 
7.5%
Other Symbol 2
 
0.7%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%
Letter Number 1
 
0.3%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 9
 
4.9%
귀 8
 
4.3%
유 7
 
3.8%
주 6
 
3.2%
여 6
 
3.2%
지 5
 
2.7%
성 5
 
2.7%
촌 4
 
2.2%
시 4
 
2.2%
농 4
 
2.2%
Other values (82) 127
68.6%
Decimal Number
ValueCountFrequency (%)
5 13
34.2%
6 7
18.4%
1 4
 
10.5%
4 3
 
7.9%
2 3
 
7.9%
3 2
 
5.3%
9 2
 
5.3%
0 2
 
5.3%
7 1
 
2.6%
8 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 19
86.4%
, 2
 
9.1%
· 1
 
4.5%
Space Separator
ValueCountFrequency (%)
39
100.0%
Other Symbol
ValueCountFrequency (%)
◆ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅶ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185
63.4%
Common 106
36.3%
Latin 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 9
 
4.9%
귀 8
 
4.3%
유 7
 
3.8%
주 6
 
3.2%
여 6
 
3.2%
지 5
 
2.7%
성 5
 
2.7%
촌 4
 
2.2%
시 4
 
2.2%
농 4
 
2.2%
Other values (82) 127
68.6%
Common
ValueCountFrequency (%)
39
36.8%
. 19
17.9%
5 13
 
12.3%
6 7
 
6.6%
1 4
 
3.8%
4 3
 
2.8%
2 3
 
2.8%
3 2
 
1.9%
, 2
 
1.9%
◆ 2
 
1.9%
Other values (8) 12
 
11.3%
Latin
ValueCountFrequency (%)
Ⅶ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 185
63.4%
ASCII 103
35.3%
Geometric Shapes 2
 
0.7%
None 1
 
0.3%
Number Forms 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
37.9%
. 19
18.4%
5 13
 
12.6%
6 7
 
6.8%
1 4
 
3.9%
4 3
 
2.9%
2 3
 
2.9%
3 2
 
1.9%
, 2
 
1.9%
) 2
 
1.9%
Other values (6) 9
 
8.7%
Hangul
ValueCountFrequency (%)
이 9
 
4.9%
귀 8
 
4.3%
유 7
 
3.8%
주 6
 
3.2%
여 6
 
3.2%
지 5
 
2.7%
성 5
 
2.7%
촌 4
 
2.2%
시 4
 
2.2%
농 4
 
2.2%
Other values (82) 127
68.6%
Geometric Shapes
ValueCountFrequency (%)
◆ 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅶ 1
100.0%

Correlations

2023-12-11T02:19:24.426153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2022 부산사회조사 통계표Unnamed: 3Unnamed: 5
2022 부산사회조사 통계표1.0001.0001.000
Unnamed: 31.0001.0001.000
Unnamed: 51.0001.0001.000

Missing values

2023-12-11T02:19:19.848908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:19:20.096627image/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.
2023-12-11T02:19:20.315553image/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

Unnamed: 02022 부산사회조사 통계표Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0<NA><NA><NA><NA><NA><NA>
1<NA>조사대상 가구원 일반적 특성<NA><NA><NA><NA>
2<NA><NA><NA><NA><NA><NA>
3<NA>I. 건강<NA>V. 사회통합<NA>Ⅶ. 개인관련사항
4<NA>01.운동횟수<NA>20.지역민으로서의 자부심<NA>49.유배우 여성의 맞벌이 여부 및 1주간 경제활동
5<NA>01-1.운동을 하지 않은 이유<NA>21.지역민으로서의 지역정체성<NA>50.유배우 여성의 일하는 사유
6<NA>01-2.운동 시 이용시설(공간)(복수응답)<NA>22.주관적 귀속계층<NA>51.맞벌이 여성의 일 중단 시기
7<NA>02.건강증진을 위한 방안(주된응답)<NA>23.사회적 관계 소통 정도<NA>52.이주계획 여부 및 이주시기
8<NA>02.건강증진을 위한 방안(복수응답)<NA>24.후원(기부) 여부<NA>52-1.이주 희망지역
9<NA>03.스트레스 요인별 체감수준<NA>25.후원(기부) 내용<NA>53.이주하려는 이유
Unnamed: 02022 부산사회조사 통계표Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
27<NA>IV. 가족<NA><NA><NA><NA>
28<NA>13.선호하는 가족형태<NA><NA><NA><NA>
29<NA>14.부모와의 동거 선호사유<NA><NA><NA><NA>
30<NA>15.선호하는 노후 생활형태<NA><NA><NA><NA>
31<NA>16.노후 준비방법(만30세 이상)(복수응답)<NA><NA><NA><NA>
32<NA>17.부모님 생존여부<NA><NA><NA><NA>
33<NA>17-1.부모님과 동거여부<NA><NA><NA><NA>
34<NA>17-2.부모 부양 책임자<NA><NA><NA><NA>
35<NA>18.출산율 증가방안<NA><NA><NA><NA>
36<NA>19.가족 관계 만족도<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

2022 부산사회조사 통계표Unnamed: 3Unnamed: 5# duplicates
0<NA><NA><NA>2