Overview

Dataset statistics

Number of variables8
Number of observations106
Missing cells104
Missing cells (%)12.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory66.2 B

Variable types

Text2
Categorical5
DateTime1

Dataset

Description국립중앙극장 공연예술자료 저작권에 대한 정보로 자료명, 최상위 코드명, 차상위 코드, 차상위 코드명, 레벨 등의 정보를 제공합니다.
Author문화체육관광부 국립중앙극장
URLhttps://www.data.go.kr/data/15090179/fileData.do

Alerts

최상위 코드명 is highly overall correlated with 최상위 코드 and 3 other fieldsHigh correlation
최상위 코드 is highly overall correlated with 최상위 코드명 and 2 other fieldsHigh correlation
차상위 코드명 is highly overall correlated with 최상위 코드 and 3 other fieldsHigh correlation
차상위 코드 is highly overall correlated with 최상위 코드 and 3 other fieldsHigh correlation
레벨 is highly overall correlated with 최상위 코드명 and 2 other fieldsHigh correlation
최종수정일 has 104 (98.1%) missing valuesMissing
자료유형코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:22:46.933194
Analysis finished2023-12-12 17:22:47.652566
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자료유형코드
Text

UNIQUE 

Distinct106
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-13T02:22:48.039413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.490566
Min length2

Characters and Unicode

Total characters476
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)100.0%

Sample

1st rowT1
2nd rowC0
3rd rowC1
4th rowC2
5th rowD0
ValueCountFrequency (%)
t1 1
 
0.9%
o00201 1
 
0.9%
t09902 1
 
0.9%
t09901 1
 
0.9%
t01202 1
 
0.9%
t01201 1
 
0.9%
t01102 1
 
0.9%
t01101 1
 
0.9%
t01002 1
 
0.9%
t01001 1
 
0.9%
Other values (96) 96
90.6%
2023-12-13T02:22:48.772397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 213
44.7%
1 56
 
11.8%
T 43
 
9.0%
2 32
 
6.7%
9 26
 
5.5%
O 21
 
4.4%
V 12
 
2.5%
C 9
 
1.9%
3 9
 
1.9%
A 8
 
1.7%
Other values (8) 47
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 370
77.7%
Uppercase Letter 106
 
22.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 213
57.6%
1 56
 
15.1%
2 32
 
8.6%
9 26
 
7.0%
3 9
 
2.4%
4 8
 
2.2%
5 7
 
1.9%
6 7
 
1.9%
8 6
 
1.6%
7 6
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
T 43
40.6%
O 21
19.8%
V 12
 
11.3%
C 9
 
8.5%
A 8
 
7.5%
I 6
 
5.7%
D 4
 
3.8%
Z 3
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 370
77.7%
Latin 106
 
22.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 213
57.6%
1 56
 
15.1%
2 32
 
8.6%
9 26
 
7.0%
3 9
 
2.4%
4 8
 
2.2%
5 7
 
1.9%
6 7
 
1.9%
8 6
 
1.6%
7 6
 
1.6%
Latin
ValueCountFrequency (%)
T 43
40.6%
O 21
19.8%
V 12
 
11.3%
C 9
 
8.5%
A 8
 
7.5%
I 6
 
5.7%
D 4
 
3.8%
Z 3
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 213
44.7%
1 56
 
11.8%
T 43
 
9.0%
2 32
 
6.7%
9 26
 
5.5%
O 21
 
4.4%
V 12
 
2.5%
C 9
 
1.9%
3 9
 
1.9%
A 8
 
1.7%
Other values (8) 47
 
9.9%

자료유형 전체명
Text

Distinct105
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-13T02:22:49.087262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.4339623
Min length2

Characters and Unicode

Total characters894
Distinct characters90
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)98.1%

Sample

1st row대본
2nd row포스터
3rd row프로그램북
4th row전단지
5th row무대디자인
ValueCountFrequency (%)
기타서지류 40
16.8%
실물 30
 
12.6%
디지털파일 21
 
8.8%
박물 21
 
8.8%
기타 13
 
5.5%
영상 12
 
5.0%
음향 8
 
3.4%
사진 6
 
2.5%
무대디자인 4
 
1.7%
일반도면 3
 
1.3%
Other values (41) 80
33.6%
2023-12-13T02:22:49.599508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
14.8%
지 67
 
7.5%
기 62
 
6.9%
물 53
 
5.9%
타 53
 
5.9%
류 52
 
5.8%
서 49
 
5.5%
실 30
 
3.4%
일 27
 
3.0%
디 25
 
2.8%
Other values (80) 344
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 709
79.3%
Space Separator 132
 
14.8%
Uppercase Letter 47
 
5.3%
Other Punctuation 3
 
0.3%
Lowercase Letter 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 67
 
9.4%
기 62
 
8.7%
물 53
 
7.5%
타 53
 
7.5%
류 52
 
7.3%
서 49
 
6.9%
실 30
 
4.2%
일 27
 
3.8%
디 25
 
3.5%
박 21
 
3.0%
Other values (61) 270
38.1%
Uppercase Letter
ValueCountFrequency (%)
D 9
19.1%
C 7
14.9%
A 6
12.8%
V 5
10.6%
M 4
8.5%
T 3
 
6.4%
E 3
 
6.4%
H 2
 
4.3%
L 2
 
4.3%
P 1
 
2.1%
Other values (5) 5
10.6%
Space Separator
ValueCountFrequency (%)
132
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 709
79.3%
Common 136
 
15.2%
Latin 49
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 67
 
9.4%
기 62
 
8.7%
물 53
 
7.5%
타 53
 
7.5%
류 52
 
7.3%
서 49
 
6.9%
실 30
 
4.2%
일 27
 
3.8%
디 25
 
3.5%
박 21
 
3.0%
Other values (61) 270
38.1%
Latin
ValueCountFrequency (%)
D 9
18.4%
C 7
14.3%
A 6
12.2%
V 5
10.2%
M 4
8.2%
T 3
 
6.1%
E 3
 
6.1%
H 2
 
4.1%
m 2
 
4.1%
L 2
 
4.1%
Other values (6) 6
12.2%
Common
ValueCountFrequency (%)
132
97.1%
, 3
 
2.2%
8 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 709
79.3%
ASCII 185
 
20.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
71.4%
D 9
 
4.9%
C 7
 
3.8%
A 6
 
3.2%
V 5
 
2.7%
M 4
 
2.2%
T 3
 
1.6%
, 3
 
1.6%
E 3
 
1.6%
H 2
 
1.1%
Other values (9) 11
 
5.9%
Hangul
ValueCountFrequency (%)
지 67
 
9.4%
기 62
 
8.7%
물 53
 
7.5%
타 53
 
7.5%
류 52
 
7.3%
서 49
 
6.9%
실 30
 
4.2%
일 27
 
3.8%
디 25
 
3.5%
박 21
 
3.0%
Other values (61) 270
38.1%

최상위 코드
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size980.0 B
T0
40 
O0
21 
V0
12 
A0
8 
I0
6 
Other values (6)
19 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowT1
2nd rowC0
3rd rowC1
4th rowC2
5th rowD0

Common Values

ValueCountFrequency (%)
T0 40
37.7%
O0 21
19.8%
V0 12
 
11.3%
A0 8
 
7.5%
I0 6
 
5.7%
D0 4
 
3.8%
T1 3
 
2.8%
C0 3
 
2.8%
C1 3
 
2.8%
C2 3
 
2.8%

Length

2023-12-13T02:22:49.819855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t0 40
37.7%
o0 21
19.8%
v0 12
 
11.3%
a0 8
 
7.5%
i0 6
 
5.7%
d0 4
 
3.8%
t1 3
 
2.8%
c0 3
 
2.8%
c1 3
 
2.8%
c2 3
 
2.8%

최상위 코드명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size980.0 B
실물
24 
기타 서지류
14 
디지털파일
14 
영상
12 
박물
11 
Other values (9)
31 

Length

Max length9
Median length2
Mean length3.245283
Min length2

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row대본
2nd row포스터
3rd row프로그램북
4th row전단지
5th row무대디자인

Common Values

ValueCountFrequency (%)
실물 24
22.6%
기타 서지류 14
13.2%
디지털파일 14
13.2%
영상 12
11.3%
박물 11
10.4%
음향 8
 
7.5%
사진 6
 
5.7%
무대디자인 4
 
3.8%
포스터 3
 
2.8%
프로그램북 3
 
2.8%
Other values (4) 7
 
6.6%

Length

2023-12-13T02:22:50.016961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
실물 24
19.7%
기타 17
13.9%
서지류 15
12.3%
디지털파일 14
11.5%
영상 12
9.8%
박물 11
9.0%
음향 8
 
6.6%
사진 6
 
4.9%
무대디자인 4
 
3.3%
포스터 3
 
2.5%
Other values (4) 8
 
6.6%

차상위 코드
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
T0
13 
V0
11 
<NA>
11 
O0
10 
A0
7 
Other values (31)
54 

Length

Max length4
Median length2
Mean length2.9056604
Min length2

Unique

Unique12 ?
Unique (%)11.3%

Sample

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

Common Values

ValueCountFrequency (%)
T0 13
 
12.3%
V0 11
 
10.4%
<NA> 11
 
10.4%
O0 10
 
9.4%
A0 7
 
6.6%
I0 5
 
4.7%
D0 3
 
2.8%
T009 2
 
1.9%
T011 2
 
1.9%
T010 2
 
1.9%
Other values (26) 40
37.7%

Length

2023-12-13T02:22:50.209663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t0 13
 
12.3%
na 11
 
10.4%
v0 11
 
10.4%
o0 10
 
9.4%
a0 7
 
6.6%
i0 5
 
4.7%
d0 3
 
2.8%
c0 2
 
1.9%
t002 2
 
1.9%
t008 2
 
1.9%
Other values (26) 40
37.7%

차상위 코드명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size980.0 B
실물
25 
디지털파일
14 
기타 서지류
13 
<NA>
11 
영상
11 
Other values (8)
32 

Length

Max length6
Median length2
Mean length3.2735849
Min length2

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
실물 25
23.6%
디지털파일 14
13.2%
기타 서지류 13
12.3%
<NA> 11
10.4%
영상 11
10.4%
박물 10
 
9.4%
음향 7
 
6.6%
사진 5
 
4.7%
무대디자인 3
 
2.8%
포스터 2
 
1.9%
Other values (3) 5
 
4.7%

Length

2023-12-13T02:22:50.376444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
실물 25
21.0%
디지털파일 14
11.8%
기타 14
11.8%
서지류 13
10.9%
na 11
9.2%
영상 11
9.2%
박물 10
 
8.4%
음향 7
 
5.9%
사진 5
 
4.2%
무대디자인 3
 
2.5%
Other values (3) 6
 
5.0%

레벨
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size980.0 B
2
58 
3
37 
1
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 58
54.7%
3 37
34.9%
1 11
 
10.4%

Length

2023-12-13T02:22:50.534884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:22:50.676471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 58
54.7%
3 37
34.9%
1 11
 
10.4%

최종수정일
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing104
Missing (%)98.1%
Memory size980.0 B
Minimum2004-08-21 00:00:00
Maximum2026-07-21 00:00:00
2023-12-13T02:22:50.793473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:22:50.929155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Correlations

2023-12-13T02:22:51.055614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최상위 코드최상위 코드명차상위 코드차상위 코드명레벨최종수정일
최상위 코드1.0000.9821.0000.9760.5470.000
최상위 코드명0.9821.0000.9911.0000.8290.000
차상위 코드1.0000.9911.0000.9951.0000.000
차상위 코드명0.9761.0000.9951.0000.9970.000
레벨0.5470.8291.0000.9971.000NaN
최종수정일0.0000.0000.0000.000NaN1.000
2023-12-13T02:22:51.210552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최상위 코드명최상위 코드레벨차상위 코드차상위 코드명
최상위 코드명1.0000.9020.6520.7810.994
최상위 코드0.9021.0000.3650.8450.880
레벨0.6520.3651.0000.8030.899
차상위 코드0.7810.8450.8031.0000.802
차상위 코드명0.9940.8800.8990.8021.000
2023-12-13T02:22:51.339922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최상위 코드최상위 코드명차상위 코드차상위 코드명레벨
최상위 코드1.0000.9020.8450.8800.365
최상위 코드명0.9021.0000.7810.9940.652
차상위 코드0.8450.7811.0000.8020.803
차상위 코드명0.8800.9940.8021.0000.899
레벨0.3650.6520.8030.8991.000

Missing values

2023-12-13T02:22:47.402323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:22:47.585333image/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.

Sample

자료유형코드자료유형 전체명최상위 코드최상위 코드명차상위 코드차상위 코드명레벨최종수정일
0T1대본T1대본<NA><NA>1<NA>
1C0포스터C0포스터<NA><NA>1<NA>
2C1프로그램북C1프로그램북<NA><NA>1<NA>
3C2전단지C2전단지<NA><NA>1<NA>
4D0무대디자인D0무대디자인<NA><NA>1<NA>
5V0영상V0영상<NA><NA>1<NA>
6A0음향A0음향<NA><NA>1<NA>
7I0사진I0사진<NA><NA>1<NA>
8T0기타서지류T0기타 서지류<NA><NA>1<NA>
9O0박물O0박물<NA><NA>1<NA>
자료유형코드자료유형 전체명최상위 코드최상위 코드명차상위 코드차상위 코드명레벨최종수정일
96T00501기타서지류 논문 실물T0실물T005실물3<NA>
97T00502기타서지류 논문 디지털파일T0디지털파일T005디지털파일3<NA>
98T00601기타서지류 잡지 실물T0실물T006실물3<NA>
99T00602기타서지류 잡지 디지털파일T0디지털파일T006디지털파일321/08/04
100T00701기타서지류 신문 실물T0기타 서지류 신문T007실물3<NA>
101T00702기타서지류 신문 디지털파일T0디지털파일T007디지털파일3<NA>
102T00801기타서지류 도서 실물T0실물T008실물3<NA>
103T00802기타서지류 도서 디지털파일T0디지털파일T008디지털파일3<NA>
104T00901기타서지류 일기,서신류 실물T0실물T009실물3<NA>
105T00902기타서지류 일기,서신류 디지털파일T0디지털파일T009디지털파일3<NA>