Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells49
Missing cells (%)51.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory900.0 B
Average record size in memory37.5 B

Variable types

Text4

Alerts

Unnamed: 3 has constant value ""Constant
전라북도 예술문화단체 현황 has 12 (50.0%) missing valuesMissing
Unnamed: 1 has 13 (54.2%) missing valuesMissing
Unnamed: 2 has 1 (4.2%) missing valuesMissing
Unnamed: 3 has 23 (95.8%) missing valuesMissing

Reproduction

Analysis started2024-03-14 03:06:03.788498
Analysis finished2024-03-14 03:06:04.202736
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 예술문화단체 현황
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing12
Missing (%)50.0%
Memory size324.0 B
2024-03-14T12:06:04.394625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.25
Min length4

Characters and Unicode

Total characters63
Distinct characters29
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

Unique12 ?
Unique (%)100.0%

Sample

1st row소 속
2nd row전북예총연합회
3rd row건축가협회
4th row국악협회
5th row무용협회
ValueCountFrequency (%)
소 1
 
7.7%
속 1
 
7.7%
전북예총연합회 1
 
7.7%
건축가협회 1
 
7.7%
국악협회 1
 
7.7%
무용협회 1
 
7.7%
문인협회 1
 
7.7%
미술협회 1
 
7.7%
사진작가협회 1
 
7.7%
연극협회 1
 
7.7%
Other values (3) 3
23.1%
2024-03-14T12:06:04.682946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 11
17.5%
협 10
15.9%
7
 
11.1%
예 3
 
4.8%
연 3
 
4.8%
인 3
 
4.8%
술 2
 
3.2%
가 2
 
3.2%
악 2
 
3.2%
작 1
 
1.6%
Other values (19) 19
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56
88.9%
Space Separator 7
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 11
19.6%
협 10
17.9%
예 3
 
5.4%
연 3
 
5.4%
인 3
 
5.4%
술 2
 
3.6%
가 2
 
3.6%
악 2
 
3.6%
작 1
 
1.8%
극 1
 
1.8%
Other values (18) 18
32.1%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56
88.9%
Common 7
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 11
19.6%
협 10
17.9%
예 3
 
5.4%
연 3
 
5.4%
인 3
 
5.4%
술 2
 
3.6%
가 2
 
3.6%
악 2
 
3.6%
작 1
 
1.8%
극 1
 
1.8%
Other values (18) 18
32.1%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56
88.9%
ASCII 7
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 11
19.6%
협 10
17.9%
예 3
 
5.4%
연 3
 
5.4%
인 3
 
5.4%
술 2
 
3.6%
가 2
 
3.6%
악 2
 
3.6%
작 1
 
1.8%
극 1
 
1.8%
Other values (18) 18
32.1%
ASCII
ValueCountFrequency (%)
7
100.0%

Unnamed: 1
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing13
Missing (%)54.2%
Memory size324.0 B
2024-03-14T12:06:04.820116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters44
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row전주지회
2nd row군산지회
3rd row익산지회
4th row정읍지회
5th row남원지회
ValueCountFrequency (%)
전주지회 1
9.1%
군산지회 1
9.1%
익산지회 1
9.1%
정읍지회 1
9.1%
남원지회 1
9.1%
김제지회 1
9.1%
완주지회 1
9.1%
진안지회 1
9.1%
임실지회 1
9.1%
고창지회 1
9.1%
2024-03-14T12:06:05.057940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 11
25.0%
회 11
25.0%
산 2
 
4.5%
안 2
 
4.5%
주 2
 
4.5%
전 1
 
2.3%
완 1
 
2.3%
창 1
 
2.3%
고 1
 
2.3%
실 1
 
2.3%
Other values (11) 11
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 11
25.0%
회 11
25.0%
산 2
 
4.5%
안 2
 
4.5%
주 2
 
4.5%
전 1
 
2.3%
완 1
 
2.3%
창 1
 
2.3%
고 1
 
2.3%
실 1
 
2.3%
Other values (11) 11
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 11
25.0%
회 11
25.0%
산 2
 
4.5%
안 2
 
4.5%
주 2
 
4.5%
전 1
 
2.3%
완 1
 
2.3%
창 1
 
2.3%
고 1
 
2.3%
실 1
 
2.3%
Other values (11) 11
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 11
25.0%
회 11
25.0%
산 2
 
4.5%
안 2
 
4.5%
주 2
 
4.5%
전 1
 
2.3%
완 1
 
2.3%
창 1
 
2.3%
고 1
 
2.3%
실 1
 
2.3%
Other values (11) 11
25.0%

Unnamed: 2
Text

MISSING 

Distinct13
Distinct (%)56.5%
Missing1
Missing (%)4.2%
Memory size324.0 B
2024-03-14T12:06:05.257847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length25
Mean length23.478261
Min length6

Characters and Unicode

Total characters540
Distinct characters79
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

Unique12 ?
Unique (%)52.2%

Sample

1st row사무실 주소
2nd row전주시 완산구 소리로 31 한국소리문화의전당내
3rd row전주시 덕진구 덕진동 1가 1220
4th row군산시 백토로 203 군산예술의 전당 내
5th row익산시 선화1로 106 솜리문화예술회관 3층
ValueCountFrequency (%)
전주시 12
 
10.3%
완산구 11
 
9.5%
소리로 11
 
9.5%
31 11
 
9.5%
한국소리문화의전당내 11
 
9.5%
내 3
 
2.6%
2층 2
 
1.7%
11 2
 
1.7%
진안군 2
 
1.7%
진안읍 1
 
0.9%
Other values (50) 50
43.1%
2024-03-14T12:06:05.575566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
 
18.9%
전 25
 
4.6%
리 25
 
4.6%
소 24
 
4.4%
1 23
 
4.3%
시 18
 
3.3%
로 16
 
3.0%
3 15
 
2.8%
화 15
 
2.8%
주 14
 
2.6%
Other values (69) 263
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 373
69.1%
Space Separator 102
 
18.9%
Decimal Number 60
 
11.1%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 25
 
6.7%
리 25
 
6.7%
소 24
 
6.4%
시 18
 
4.8%
로 16
 
4.3%
화 15
 
4.0%
주 14
 
3.8%
내 14
 
3.8%
산 14
 
3.8%
구 13
 
3.5%
Other values (56) 195
52.3%
Decimal Number
ValueCountFrequency (%)
1 23
38.3%
3 15
25.0%
2 7
 
11.7%
5 6
 
10.0%
0 5
 
8.3%
4 1
 
1.7%
6 1
 
1.7%
8 1
 
1.7%
7 1
 
1.7%
Space Separator
ValueCountFrequency (%)
102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 373
69.1%
Common 167
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 25
 
6.7%
리 25
 
6.7%
소 24
 
6.4%
시 18
 
4.8%
로 16
 
4.3%
화 15
 
4.0%
주 14
 
3.8%
내 14
 
3.8%
산 14
 
3.8%
구 13
 
3.5%
Other values (56) 195
52.3%
Common
ValueCountFrequency (%)
102
61.1%
1 23
 
13.8%
3 15
 
9.0%
2 7
 
4.2%
5 6
 
3.6%
0 5
 
3.0%
) 2
 
1.2%
( 2
 
1.2%
4 1
 
0.6%
- 1
 
0.6%
Other values (3) 3
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 373
69.1%
ASCII 167
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
61.1%
1 23
 
13.8%
3 15
 
9.0%
2 7
 
4.2%
5 6
 
3.6%
0 5
 
3.0%
) 2
 
1.2%
( 2
 
1.2%
4 1
 
0.6%
- 1
 
0.6%
Other values (3) 3
 
1.8%
Hangul
ValueCountFrequency (%)
전 25
 
6.7%
리 25
 
6.7%
소 24
 
6.4%
시 18
 
4.8%
로 16
 
4.3%
화 15
 
4.0%
주 14
 
3.8%
내 14
 
3.8%
산 14
 
3.8%
구 13
 
3.5%
Other values (56) 195
52.3%

Unnamed: 3
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing23
Missing (%)95.8%
Memory size324.0 B
2024-03-14T12:06:05.651644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2024-03-14T12:06:05.831970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Correlations

2024-03-14T12:06:05.921045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 예술문화단체 현황Unnamed: 1Unnamed: 2
전라북도 예술문화단체 현황1.000NaN1.000
Unnamed: 1NaN1.0001.000
Unnamed: 21.0001.0001.000

Missing values

2024-03-14T12:06:03.935349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:06:04.003917image/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.
2024-03-14T12:06:04.125597image/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

전라북도 예술문화단체 현황Unnamed: 1Unnamed: 2Unnamed: 3
0<NA><NA><NA><NA>
1소 속<NA>사무실 주소비고
2전북예총연합회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
3<NA>전주지회전주시 덕진구 덕진동 1가 1220<NA>
4<NA>군산지회군산시 백토로 203 군산예술의 전당 내<NA>
5<NA>익산지회익산시 선화1로 106 솜리문화예술회관 3층<NA>
6<NA>정읍지회정읍시 시기4길 13번지 정읍사예술회관 1층<NA>
7<NA>남원지회남원시 관한북로 57 (구 의회청사 2층)<NA>
8<NA>김제지회김제시 서암 5길 5 김제문화예술회관 내<NA>
9<NA>완주지회완주군 봉동읍 과학로 850-15 전북근로자종합복지관 2층<NA>
전라북도 예술문화단체 현황Unnamed: 1Unnamed: 2Unnamed: 3
14건축가협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
15국악협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
16무용협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
17문인협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
18미술협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
19사진작가협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
20연극협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
21연예예술인협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
22영화인협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>
23음악협회<NA>전주시 완산구 소리로 31 한국소리문화의전당내<NA>