Overview

Dataset statistics

Number of variables4
Number of observations29
Missing cells46
Missing cells (%)39.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory36.6 B

Variable types

Text3
Unsupported1

Dataset

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

Alerts

2014 소통 체감도 조사결과 has 21 (72.4%) missing valuesMissing
Unnamed: 1 has 1 (3.4%) missing valuesMissing
Unnamed: 2 has 1 (3.4%) missing valuesMissing
Unnamed: 3 has 23 (79.3%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:28:59.895770
Analysis finished2024-03-14 00:29:00.225039
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct8
Distinct (%)100.0%
Missing21
Missing (%)72.4%
Memory size364.0 B
2024-03-14T09:29:00.318852image/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%
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%
2024-03-14T09:29:00.547249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
21.3%
5
 
6.7%
4
 
5.3%
3
 
4.0%
3
 
4.0%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
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 (%)
5
 
8.6%
4
 
6.9%
3
 
5.2%
3
 
5.2%
2
 
3.4%
2
 
3.4%
2
 
3.4%
2
 
3.4%
1
 
1.7%
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 (%)
5
 
8.6%
4
 
6.9%
3
 
5.2%
3
 
5.2%
2
 
3.4%
2
 
3.4%
2
 
3.4%
2
 
3.4%
1
 
1.7%
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 (%)
5
 
8.6%
4
 
6.9%
3
 
5.2%
3
 
5.2%
2
 
3.4%
2
 
3.4%
2
 
3.4%
2
 
3.4%
1
 
1.7%
1
 
1.7%
Other values (33) 33
56.9%

Unnamed: 1
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing1
Missing (%)3.4%
Memory size364.0 B
2024-03-14T09:29:00.735009image/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 (%)
대한 3
 
5.8%
도정에 3
 
5.8%
아니다 2
 
3.8%
확대 2
 
3.8%
부족 2
 
3.8%
참여기회 2
 
3.8%
도정 2
 
3.8%
홍보 2
 
3.8%
도민 2
 
3.8%
그렇다 2
 
3.8%
Other values (28) 30
57.7%
2024-03-14T09:29:01.096549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
12.8%
7
 
3.7%
5
 
2.7%
5
 
2.7%
5
 
2.7%
5
 
2.7%
4
 
2.1%
4
 
2.1%
4
 
2.1%
· 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 (%)
7
 
4.5%
5
 
3.2%
5
 
3.2%
5
 
3.2%
5
 
3.2%
4
 
2.6%
4
 
2.6%
4
 
2.6%
3
 
1.9%
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 (%)
7
 
4.5%
5
 
3.2%
5
 
3.2%
5
 
3.2%
5
 
3.2%
4
 
2.6%
4
 
2.6%
4
 
2.6%
3
 
1.9%
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%
, 1
 
3.7%
T 1
 
3.7%
V 1
 
3.7%
Hangul
ValueCountFrequency (%)
7
 
4.5%
5
 
3.2%
5
 
3.2%
5
 
3.2%
5
 
3.2%
4
 
2.6%
4
 
2.6%
4
 
2.6%
3
 
1.9%
3
 
1.9%
Other values (76) 111
71.2%
None
ValueCountFrequency (%)
· 4
100.0%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)3.4%
Memory size364.0 B

Unnamed: 3
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing23
Missing (%)79.3%
Memory size364.0 B
2024-03-14T09:29:01.206549image/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 categories2 ?
Distinct scripts2 ?
Distinct blocks3 ?
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 (%)
비고 1
50.0%
신규항목 1
50.0%
2024-03-14T09:29:01.449433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
  4
28.6%
4
28.6%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 8
57.1%
Other Letter 6
42.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Space Separator
ValueCountFrequency (%)
  4
50.0%
4
50.0%

Most occurring scripts

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

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Common
ValueCountFrequency (%)
  4
50.0%
4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
42.9%
None 4
28.6%
ASCII 4
28.6%

Most frequent character per block

None
ValueCountFrequency (%)
  4
100.0%
ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Correlations

2024-03-14T09:29:01.542117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2014 소통 체감도 조사결과Unnamed: 1Unnamed: 3
2014 소통 체감도 조사결과1.0001.0001.000
Unnamed: 11.0001.0001.000
Unnamed: 31.0001.0001.000

Missing values

2024-03-14T09:29:00.036111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:29:00.107004image/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.
2024-03-14T09:29:00.179682image/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>NaN<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
19<NA>도정에 대한 관심16.9<NA>
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