Overview

Dataset statistics

Number of variables9
Number of observations56
Missing cells191
Missing cells (%)37.9%
Duplicate rows2
Duplicate rows (%)3.6%
Total size in memory4.1 KiB
Average record size in memory74.4 B

Variable types

Unsupported3
Categorical2
Text4

Alerts

Dataset has 2 (3.6%) duplicate rowsDuplicates
Unnamed: 1 is highly overall correlated with Unnamed: 8High correlation
Unnamed: 8 is highly overall correlated with Unnamed: 1High correlation
전문예술법인 및 단체 지정현황 –25개소/2015.12월기준-  has 30 (53.6%) missing valuesMissing
Unnamed: 2 has 30 (53.6%) missing valuesMissing
Unnamed: 3 has 19 (33.9%) missing valuesMissing
Unnamed: 4 has 29 (51.8%) missing valuesMissing
Unnamed: 5 has 25 (44.6%) missing valuesMissing
Unnamed: 6 has 30 (53.6%) missing valuesMissing
Unnamed: 7 has 28 (50.0%) missing valuesMissing
전문예술법인 및 단체 지정현황 –25개소/2015.12월기준-  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

Reproduction

Analysis started2024-03-14 02:48:10.356721
Analysis finished2024-03-14 02:48:11.018598
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전문예술법인 및 단체 지정현황 –25개소/2015.12월기준- 
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)53.6%
Memory size580.0 B

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
29 
전문예술법인
14 
전문예술단체
11 
지 정
 
1
형 태
 
1

Length

Max length6
Median length4
Mean length4.8571429
Min length3

Unique

Unique2 ?
Unique (%)3.6%

Sample

1st row지 정
2nd row형 태
3rd row<NA>
4th row전문예술법인
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 29
51.8%
전문예술법인 14
25.0%
전문예술단체 11
 
19.6%
지 정 1
 
1.8%
형 태 1
 
1.8%

Length

2024-03-14T11:48:11.111266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:11.211700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
50.0%
전문예술법인 14
24.1%
전문예술단체 11
 
19.0%
지 1
 
1.7%
정 1
 
1.7%
형 1
 
1.7%
태 1
 
1.7%

Unnamed: 2
Text

MISSING 

Distinct15
Distinct (%)57.7%
Missing30
Missing (%)53.6%
Memory size580.0 B
2024-03-14T11:48:11.331114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5
Min length2

Characters and Unicode

Total characters91
Distinct characters33
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

Unique11 ?
Unique (%)42.3%

Sample

1st row유 형
2nd row오페라단
3rd row종합예술단
4th row전통예술단
5th row전통예술단
ValueCountFrequency (%)
전통예술단 5
18.5%
연극단 4
14.8%
음악 4
14.8%
문화단체 2
 
7.4%
유 1
 
3.7%
형 1
 
3.7%
오페라단 1
 
3.7%
종합예술단 1
 
3.7%
국악공연단 1
 
3.7%
서예전시 1
 
3.7%
Other values (6) 6
22.2%
2024-03-14T11:48:11.578125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
단 15
16.5%
예 8
 
8.8%
전 7
 
7.7%
술 7
 
7.7%
악 7
 
7.7%
통 6
 
6.6%
연 5
 
5.5%
극 4
 
4.4%
음 4
 
4.4%
국 2
 
2.2%
Other values (23) 26
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
98.9%
Space Separator 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 15
16.7%
예 8
 
8.9%
전 7
 
7.8%
술 7
 
7.8%
악 7
 
7.8%
통 6
 
6.7%
연 5
 
5.6%
극 4
 
4.4%
음 4
 
4.4%
국 2
 
2.2%
Other values (22) 25
27.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
98.9%
Common 1
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 15
16.7%
예 8
 
8.9%
전 7
 
7.8%
술 7
 
7.8%
악 7
 
7.8%
통 6
 
6.7%
연 5
 
5.6%
극 4
 
4.4%
음 4
 
4.4%
국 2
 
2.2%
Other values (22) 25
27.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
98.9%
ASCII 1
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
단 15
16.7%
예 8
 
8.9%
전 7
 
7.8%
술 7
 
7.8%
악 7
 
7.8%
통 6
 
6.7%
연 5
 
5.6%
극 4
 
4.4%
음 4
 
4.4%
국 2
 
2.2%
Other values (22) 25
27.8%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 3
Text

MISSING 

Distinct36
Distinct (%)97.3%
Missing19
Missing (%)33.9%
Memory size580.0 B
2024-03-14T11:48:11.764994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length6.7027027
Min length2

Characters and Unicode

Total characters248
Distinct characters117
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)94.6%

Sample

1st row법 인 명
2nd row(단 체)
3rd row사)호남
4th row오페라단
5th row사)예술기획 예루
ValueCountFrequency (%)
문화재단 2
 
3.5%
사)세계서예전북비엔날레조직위원회 1
 
1.8%
고창 1
 
1.8%
재)익산 1
 
1.8%
법 1
 
1.8%
인 1
 
1.8%
명 1
 
1.8%
미디어 1
 
1.8%
연구소 1
 
1.8%
사)전주세계 1
 
1.8%
Other values (46) 46
80.7%
2024-03-14T11:48:12.132000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
8.5%
) 15
 
6.0%
사 14
 
5.6%
단 8
 
3.2%
전 7
 
2.8%
예 7
 
2.8%
회 6
 
2.4%
문 5
 
2.0%
연 5
 
2.0%
화 5
 
2.0%
Other values (107) 155
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
80.6%
Space Separator 21
 
8.5%
Close Punctuation 15
 
6.0%
Lowercase Letter 5
 
2.0%
Open Punctuation 4
 
1.6%
Uppercase Letter 2
 
0.8%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 14
 
7.0%
단 8
 
4.0%
전 7
 
3.5%
예 7
 
3.5%
회 6
 
3.0%
문 5
 
2.5%
연 5
 
2.5%
화 5
 
2.5%
악 5
 
2.5%
소 4
 
2.0%
Other values (96) 134
67.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
20.0%
c 1
20.0%
i 1
20.0%
t 1
20.0%
s 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 199
80.2%
Common 41
 
16.5%
Latin 7
 
2.8%
Han 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 14
 
7.0%
단 8
 
4.0%
전 7
 
3.5%
예 7
 
3.5%
회 6
 
3.0%
문 5
 
2.5%
연 5
 
2.5%
화 5
 
2.5%
악 5
 
2.5%
소 4
 
2.0%
Other values (95) 133
66.8%
Latin
ValueCountFrequency (%)
B 1
14.3%
T 1
14.3%
k 1
14.3%
c 1
14.3%
i 1
14.3%
t 1
14.3%
s 1
14.3%
Common
ValueCountFrequency (%)
21
51.2%
) 15
36.6%
( 4
 
9.8%
& 1
 
2.4%
Han
ValueCountFrequency (%)
打 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 199
80.2%
ASCII 48
 
19.4%
CJK 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
43.8%
) 15
31.2%
( 4
 
8.3%
B 1
 
2.1%
& 1
 
2.1%
T 1
 
2.1%
k 1
 
2.1%
c 1
 
2.1%
i 1
 
2.1%
t 1
 
2.1%
Hangul
ValueCountFrequency (%)
사 14
 
7.0%
단 8
 
4.0%
전 7
 
3.5%
예 7
 
3.5%
회 6
 
3.0%
문 5
 
2.5%
연 5
 
2.5%
화 5
 
2.5%
악 5
 
2.5%
소 4
 
2.0%
Other values (95) 133
66.8%
CJK
ValueCountFrequency (%)
打 1
100.0%

Unnamed: 4
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing29
Missing (%)51.8%
Memory size580.0 B
2024-03-14T11:48:12.334071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0740741
Min length3

Characters and Unicode

Total characters83
Distinct characters52
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row성 명
2nd row(대표자)
3rd row강홍규
4th row이종례
5th row최기춘
ValueCountFrequency (%)
성 1
 
3.4%
전춘근 1
 
3.4%
양진성 1
 
3.4%
이병열 1
 
3.4%
선기현 1
 
3.4%
김재원 1
 
3.4%
정기주 1
 
3.4%
이은희 1
 
3.4%
김선식 1
 
3.4%
박승환 1
 
3.4%
Other values (19) 19
65.5%
2024-03-14T11:48:12.611675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 6
 
7.2%
성 4
 
4.8%
진 4
 
4.8%
이 4
 
4.8%
박 3
 
3.6%
기 3
 
3.6%
재 2
 
2.4%
선 2
 
2.4%
2
 
2.4%
자 2
 
2.4%
Other values (42) 51
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79
95.2%
Space Separator 2
 
2.4%
Open Punctuation 1
 
1.2%
Close Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 6
 
7.6%
성 4
 
5.1%
진 4
 
5.1%
이 4
 
5.1%
박 3
 
3.8%
기 3
 
3.8%
재 2
 
2.5%
선 2
 
2.5%
자 2
 
2.5%
대 2
 
2.5%
Other values (39) 47
59.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79
95.2%
Common 4
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 6
 
7.6%
성 4
 
5.1%
진 4
 
5.1%
이 4
 
5.1%
박 3
 
3.8%
기 3
 
3.8%
재 2
 
2.5%
선 2
 
2.5%
자 2
 
2.5%
대 2
 
2.5%
Other values (39) 47
59.5%
Common
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79
95.2%
ASCII 4
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 6
 
7.6%
성 4
 
5.1%
진 4
 
5.1%
이 4
 
5.1%
박 3
 
3.8%
기 3
 
3.8%
재 2
 
2.5%
선 2
 
2.5%
자 2
 
2.5%
대 2
 
2.5%
Other values (39) 47
59.5%
ASCII
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing25
Missing (%)44.6%
Memory size580.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)53.6%
Memory size580.0 B

Unnamed: 7
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing28
Missing (%)50.0%
Memory size580.0 B
2024-03-14T11:48:12.842313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length26
Mean length20.392857
Min length4

Characters and Unicode

Total characters571
Distinct characters139
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row목적사업
2nd row오페라를 통한 한국음악의 세계화, 지역 문화의 세계화
3rd row지역 사회의 문화, 예술 향상과 지역 간의 문화교류
4th row공연활동, 전통예술분야 의 교육, 체험 진행,
5th row전통문화 전승 및 보급사업
ValueCountFrequency (%)
및 9
 
6.4%
지역 4
 
2.9%
다양한 3
 
2.1%
연극 3
 
2.1%
전승 3
 
2.1%
보급 3
 
2.1%
통해 3
 
2.1%
문화 2
 
1.4%
등 2
 
1.4%
문화예술진흥 2
 
1.4%
Other values (100) 106
75.7%
2024-03-14T11:48:13.218771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
19.8%
화 23
 
4.0%
문 19
 
3.3%
전 16
 
2.8%
예 15
 
2.6%
, 15
 
2.6%
술 14
 
2.5%
의 12
 
2.1%
연 11
 
1.9%
통 10
 
1.8%
Other values (129) 323
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 441
77.2%
Space Separator 113
 
19.8%
Other Punctuation 15
 
2.6%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 23
 
5.2%
문 19
 
4.3%
전 16
 
3.6%
예 15
 
3.4%
술 14
 
3.2%
의 12
 
2.7%
연 11
 
2.5%
통 10
 
2.3%
공 9
 
2.0%
및 9
 
2.0%
Other values (125) 303
68.7%
Space Separator
ValueCountFrequency (%)
113
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 441
77.2%
Common 130
 
22.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 23
 
5.2%
문 19
 
4.3%
전 16
 
3.6%
예 15
 
3.4%
술 14
 
3.2%
의 12
 
2.7%
연 11
 
2.5%
통 10
 
2.3%
공 9
 
2.0%
및 9
 
2.0%
Other values (125) 303
68.7%
Common
ValueCountFrequency (%)
113
86.9%
, 15
 
11.5%
) 1
 
0.8%
( 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 441
77.2%
ASCII 130
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
86.9%
, 15
 
11.5%
) 1
 
0.8%
( 1
 
0.8%
Hangul
ValueCountFrequency (%)
화 23
 
5.2%
문 19
 
4.3%
전 16
 
3.6%
예 15
 
3.4%
술 14
 
3.2%
의 12
 
2.7%
연 11
 
2.5%
통 10
 
2.3%
공 9
 
2.0%
및 9
 
2.0%
Other values (125) 303
68.7%

Unnamed: 8
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
28 
 
24 
변경내용
 
1
및
 
1
변경일자
 
1

Length

Max length9
Median length4
Mean length3.1785714
Min length1

Unique

Unique4 ?
Unique (%)7.1%

Sample

1st row변경내용
2nd row및
3rd row변경일자
4th row 
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 28
50.0%
  24
42.9%
변경내용 1
 
1.8%
및 1
 
1.8%
변경일자 1
 
1.8%
‘12년 법인전환 1
 
1.8%

Length

2024-03-14T11:48:13.406997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:48:13.496507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
84.8%
변경내용 1
 
3.0%
및 1
 
3.0%
변경일자 1
 
3.0%
‘12년 1
 
3.0%
법인전환 1
 
3.0%

Correlations

2024-03-14T11:48:13.558865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 7Unnamed: 8
Unnamed: 11.0000.9181.0001.0001.0000.978
Unnamed: 20.9181.0001.0001.0001.0000.565
Unnamed: 31.0001.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.0001.000
Unnamed: 71.0001.0001.0001.0001.0001.000
Unnamed: 80.9780.5651.0001.0001.0001.000
2024-03-14T11:48:13.640233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 8
Unnamed: 11.0000.797
Unnamed: 80.7971.000
2024-03-14T11:48:13.706709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 8
Unnamed: 11.0000.797
Unnamed: 80.7971.000

Missing values

2024-03-14T11:48:10.682319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:48:10.787957image/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.
2024-03-14T11:48:10.896320image/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

전문예술법인 및 단체 지정현황 –25개소/2015.12월기준-Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0연번지 정유 형법 인 명성 명소 재 지회원수목적사업변경내용
1NaN형 태<NA>(단 체)(대표자)NaNNaN<NA>및
2NaN<NA><NA><NA><NA>NaNNaN<NA>변경일자
31전문예술법인오페라단사)호남강홍규전주시 완산구 서노송동 568-134 성지빌딩 5층200오페라를 통한 한국음악의 세계화, 지역 문화의 세계화
4NaN<NA><NA>오페라단<NA>NaNNaN<NA><NA>
52전문예술법인종합예술단사)예술기획 예루이종례전주시 완산구 중앙동 1가 55-3번지154지역 사회의 문화, 예술 향상과 지역 간의 문화교류
63전문예술법인전통예술단사)전통예술원 모악최기춘전주시 완산구 현무3길 77-15, 4층 (경원동 3가)72공연활동, 전통예술분야 의 교육, 체험 진행,‘12년 법인전환
7NaN<NA><NA><NA><NA>NaNNaN<NA><NA>
84전문예술법인전통예술단사)전통문화김진형전주시 완산구 동문길 115-540전통문화 전승 및 보급사업
9NaN<NA><NA>마을<NA>NaNNaN<NA><NA>
전문예술법인 및 단체 지정현황 –25개소/2015.12월기준-Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
4621전문예술단체음악프로인데정기주전주시 완산구 용머리로12문화예술향유 확대를 위한 음악활동
47NaN<NA><NA>성악 연구회<NA>73(효자동1가)NaN<NA><NA>
48NaN<NA><NA><NA><NA>NaNNaN<NA><NA>
4922전문예술법인음악사단법인 드림필김재원전주시 용머리로 203, 2층(서완산동 2가)45전북지역 음악공연문화 활성화
50NaN<NA><NA><NA><NA>NaNNaN<NA><NA>
5123전문예술단체기타(사)한국예총 전라북도연합회선기현전주시 덕진구 소리로 3110000향토예술의 창달로 예술문화 발전에 기여
52NaN<NA><NA><NA><NA>(덕진동1가)NaN<NA><NA>
5324전문예술단체국악국악예술단 고창이병열고창군 고창읍 읍내리 456-1100지역 고유문화의 개발, 보급 보존, 전승 및 선향
54NaN<NA><NA><NA><NA>NaNNaN<NA><NA>
5525전문예술단체무용포스댄스 컴퍼니오해룡전주시 완산구 중화산동 2가 596-1315복합적인 예술활동을 통해 문화적 공공성 확대

Duplicate rows

Most frequently occurring

Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 7Unnamed: 8# duplicates
1<NA><NA><NA><NA><NA><NA>16
0<NA><NA>문화재단<NA><NA><NA>2