Overview

Dataset statistics

Number of variables4
Number of observations30
Missing cells50
Missing cells (%)41.7%
Duplicate rows1
Duplicate rows (%)3.3%
Total size in memory1.1 KiB
Average record size in memory36.4 B

Variable types

Text4

Dataset

Description소통체감도조사2014년_공공
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202570

Alerts

Dataset has 1 (3.3%) duplicate rowsDuplicates
2014 소통 체감도 조사결과 has 22 (73.3%) missing valuesMissing
Unnamed: 1 has 2 (6.7%) missing valuesMissing
Unnamed: 2 has 2 (6.7%) missing valuesMissing
Unnamed: 3 has 24 (80.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 00:28:56.611677
Analysis finished2024-03-14 00:28:57.294975
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2014 소통 체감도 조사결과
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing22
Missing (%)73.3%
Memory size372.0 B
2024-03-14T09:28:57.431873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10.5
Mean length9.375
Min length4

Characters and Unicode

Total characters75
Distinct characters45
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row설문항목
2nd row도정 소식 인지 경로
3rd row소통 체감도
4th row소통이 안 되는 이유
5th row소통 활성화 방안
ValueCountFrequency (%)
소통 2
 
8.3%
소통이 2
 
8.3%
설문항목 1
 
4.2%
방안 1
 
4.2%
필요한 1
 
4.2%
중 1
 
4.2%
핵심과제 1
 
4.2%
민선6기 1
 
4.2%
방법 1
 
4.2%
확대 1
 
4.2%
Other values (12) 12
50.0%
2024-03-14T09:28:57.700350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
21.3%
소 5
 
6.7%
통 4
 
5.3%
이 3
 
4.0%
도 3
 
4.0%
방 2
 
2.7%
기 2
 
2.7%
안 2
 
2.7%
민 2
 
2.7%
중 1
 
1.3%
Other values (35) 35
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58
77.3%
Space Separator 16
 
21.3%
Decimal Number 1
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 5
 
8.6%
통 4
 
6.9%
이 3
 
5.2%
도 3
 
5.2%
방 2
 
3.4%
기 2
 
3.4%
안 2
 
3.4%
민 2
 
3.4%
중 1
 
1.7%
선 1
 
1.7%
Other values (33) 33
56.9%
Space Separator
ValueCountFrequency (%)
16
100.0%
Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58
77.3%
Common 17
 
22.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 5
 
8.6%
통 4
 
6.9%
이 3
 
5.2%
도 3
 
5.2%
방 2
 
3.4%
기 2
 
3.4%
안 2
 
3.4%
민 2
 
3.4%
중 1
 
1.7%
선 1
 
1.7%
Other values (33) 33
56.9%
Common
ValueCountFrequency (%)
16
94.1%
6 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58
77.3%
ASCII 17
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
94.1%
6 1
 
5.9%
Hangul
ValueCountFrequency (%)
소 5
 
8.6%
통 4
 
6.9%
이 3
 
5.2%
도 3
 
5.2%
방 2
 
3.4%
기 2
 
3.4%
안 2
 
3.4%
민 2
 
3.4%
중 1
 
1.7%
선 1
 
1.7%
Other values (33) 33
56.9%

Unnamed: 1
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-03-14T09:28:57.876466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9
Mean length6.6785714
Min length3

Characters and Unicode

Total characters187
Distinct characters91
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row응답내용
2nd rowTV·신문
3rd row인터넷
4th row공무원
5th row가족·친구
ValueCountFrequency (%)
도정에 3
 
5.8%
대한 3
 
5.8%
그렇다 2
 
3.8%
도민 2
 
3.8%
확대 2
 
3.8%
부족 2
 
3.8%
참여기회 2
 
3.8%
도정 2
 
3.8%
홍보 2
 
3.8%
아니다 2
 
3.8%
Other values (28) 30
57.7%
2024-03-14T09:28:58.169476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
12.8%
도 7
 
3.7%
분 5
 
2.7%
대 5
 
2.7%
야 5
 
2.7%
정 5
 
2.7%
· 4
 
2.1%
회 4
 
2.1%
보 4
 
2.1%
다 4
 
2.1%
Other values (81) 120
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
83.4%
Space Separator 24
 
12.8%
Other Punctuation 5
 
2.7%
Uppercase Letter 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 7
 
4.5%
분 5
 
3.2%
대 5
 
3.2%
야 5
 
3.2%
정 5
 
3.2%
회 4
 
2.6%
보 4
 
2.6%
다 4
 
2.6%
한 3
 
1.9%
에 3
 
1.9%
Other values (76) 111
71.2%
Other Punctuation
ValueCountFrequency (%)
· 4
80.0%
, 1
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
V 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
83.4%
Common 29
 
15.5%
Latin 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 7
 
4.5%
분 5
 
3.2%
대 5
 
3.2%
야 5
 
3.2%
정 5
 
3.2%
회 4
 
2.6%
보 4
 
2.6%
다 4
 
2.6%
한 3
 
1.9%
에 3
 
1.9%
Other values (76) 111
71.2%
Common
ValueCountFrequency (%)
24
82.8%
· 4
 
13.8%
, 1
 
3.4%
Latin
ValueCountFrequency (%)
T 1
50.0%
V 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
83.4%
ASCII 27
 
14.4%
None 4
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
88.9%
T 1
 
3.7%
V 1
 
3.7%
, 1
 
3.7%
Hangul
ValueCountFrequency (%)
도 7
 
4.5%
분 5
 
3.2%
대 5
 
3.2%
야 5
 
3.2%
정 5
 
3.2%
회 4
 
2.6%
보 4
 
2.6%
다 4
 
2.6%
한 3
 
1.9%
에 3
 
1.9%
Other values (76) 111
71.2%
None
ValueCountFrequency (%)
· 4
100.0%

Unnamed: 2
Text

MISSING 

Distinct26
Distinct (%)92.9%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-03-14T09:28:58.331546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.6785714
Min length2

Characters and Unicode

Total characters103
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)85.7%

Sample

1st row응답률
2nd row63.4
3rd row16.1
4th row5.9
5th row8.7
ValueCountFrequency (%)
5.9 2
 
7.1%
13.1 2
 
7.1%
응답률 1
 
3.6%
42.1 1
 
3.6%
4.7 1
 
3.6%
13.7 1
 
3.6%
30.7 1
 
3.6%
13.6 1
 
3.6%
50.7 1
 
3.6%
22.7 1
 
3.6%
Other values (16) 16
57.1%
2024-03-14T09:28:58.682797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 26
25.2%
1 18
17.5%
3 9
 
8.7%
7 9
 
8.7%
4 8
 
7.8%
2 8
 
7.8%
6 7
 
6.8%
9 5
 
4.9%
5 4
 
3.9%
8 4
 
3.9%
Other values (4) 5
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
71.8%
Other Punctuation 26
 
25.2%
Other Letter 3
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
24.3%
3 9
12.2%
7 9
12.2%
4 8
10.8%
2 8
10.8%
6 7
 
9.5%
9 5
 
6.8%
5 4
 
5.4%
8 4
 
5.4%
0 2
 
2.7%
Other Letter
ValueCountFrequency (%)
응 1
33.3%
답 1
33.3%
률 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100
97.1%
Hangul 3
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
. 26
26.0%
1 18
18.0%
3 9
 
9.0%
7 9
 
9.0%
4 8
 
8.0%
2 8
 
8.0%
6 7
 
7.0%
9 5
 
5.0%
5 4
 
4.0%
8 4
 
4.0%
Hangul
ValueCountFrequency (%)
응 1
33.3%
답 1
33.3%
률 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100
97.1%
Hangul 3
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 26
26.0%
1 18
18.0%
3 9
 
9.0%
7 9
 
9.0%
4 8
 
8.0%
2 8
 
8.0%
6 7
 
7.0%
9 5
 
5.0%
5 4
 
4.0%
8 4
 
4.0%
Hangul
ValueCountFrequency (%)
응 1
33.3%
답 1
33.3%
률 1
33.3%

Unnamed: 3
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing24
Missing (%)80.0%
Memory size372.0 B
2024-03-14T09:28:58.814193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3333333
Min length2

Characters and Unicode

Total characters14
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row비고
2nd row신규항목
3rd row?
4th row?
5th row?
ValueCountFrequency (%)
4
66.7%
비고 1
 
16.7%
신규항목 1
 
16.7%
2024-03-14T09:28:58.998546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 4
28.6%
4
28.6%
비 1
 
7.1%
고 1
 
7.1%
신 1
 
7.1%
규 1
 
7.1%
항 1
 
7.1%
목 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
42.9%
Other Punctuation 4
28.6%
Space Separator 4
28.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
16.7%
고 1
16.7%
신 1
16.7%
규 1
16.7%
항 1
16.7%
목 1
16.7%
Other Punctuation
ValueCountFrequency (%)
? 4
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8
57.1%
Hangul 6
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
16.7%
고 1
16.7%
신 1
16.7%
규 1
16.7%
항 1
16.7%
목 1
16.7%
Common
ValueCountFrequency (%)
? 4
50.0%
4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
57.1%
Hangul 6
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 4
50.0%
4
50.0%
Hangul
ValueCountFrequency (%)
비 1
16.7%
고 1
16.7%
신 1
16.7%
규 1
16.7%
항 1
16.7%
목 1
16.7%

Correlations

2024-03-14T09:28:59.064048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2014 소통 체감도 조사결과Unnamed: 1Unnamed: 2Unnamed: 3
2014 소통 체감도 조사결과1.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.000

Missing values

2024-03-14T09:28:56.865008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:28:57.053991image/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.
2024-03-14T09:28:57.212942image/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

2014 소통 체감도 조사결과Unnamed: 1Unnamed: 2Unnamed: 3
0설문항목응답내용응답률비고
1<NA><NA><NA><NA>
2도정 소식 인지 경로TV·신문63.4<NA>
3<NA>인터넷16.1<NA>
4<NA>공무원5.9<NA>
5<NA>가족·친구8.7<NA>
6<NA>홍보책자5.9<NA>
7소통 체감도매우 그렇다8.1<NA>
8<NA>그렇다35.4<NA>
9<NA>보 통41.7<NA>
2014 소통 체감도 조사결과Unnamed: 1Unnamed: 2Unnamed: 3
20도민 참여기회 확대 방법페이스북, 인터넷22.7<NA>
21<NA>전화 또는 방문13.1<NA>
22<NA>설명회·토론회50.7<NA>
23<NA>여론조사13.6<NA>
24민선6기 핵심과제 중농업농촌분야30.7신규항목
25소통이 필요한 분야관광분야13.7?
26<NA>탄소산업분야4.7?
27<NA>복지·환경분야37.9?
28<NA>새만금개발분야13.1?
29<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

2014 소통 체감도 조사결과Unnamed: 1Unnamed: 2Unnamed: 3# duplicates
0<NA><NA><NA><NA>2