Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells125
Missing cells (%)13.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory74.3 B

Variable types

Categorical4
Text4
Numeric1

Alerts

art_grp_se is highly overall correlated with archv_artst_nm and 2 other fieldsHigh correlation
archv_artst_nm is highly overall correlated with art_grp_se and 2 other fieldsHigh correlation
realm_cl is highly overall correlated with art_grp_se and 2 other fieldsHigh correlation
act_relm_cn is highly overall correlated with art_grp_se and 2 other fieldsHigh correlation
vrit_mark_cn has 10 (10.0%) missing valuesMissing
birth_year has 21 (21.0%) missing valuesMissing
rsrch_man_nm has 94 (94.0%) missing valuesMissing
nm has unique valuesUnique
url has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:46:11.103323
Analysis finished2023-12-10 09:46:13.370406
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

art_grp_se
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
ARTST
69 
FARTST
18 
ARTGR
7 
DIC
 
6

Length

Max length6
Median length5
Mean length5.06
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowARTST
2nd rowARTST
3rd rowARTST
4th rowARTST
5th rowARTGR

Common Values

ValueCountFrequency (%)
ARTST 69
69.0%
FARTST 18
 
18.0%
ARTGR 7
 
7.0%
DIC 6
 
6.0%

Length

2023-12-10T18:46:13.509561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:46:13.842184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
artst 69
69.0%
fartst 18
 
18.0%
artgr 7
 
7.0%
dic 6
 
6.0%

archv_artst_nm
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
예술인
69 
미술작가
18 
예술단체
7 
구술채록
 
6

Length

Max length4
Median length3
Mean length3.31
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row예술인
2nd row예술인
3rd row예술인
4th row예술인
5th row예술단체

Common Values

ValueCountFrequency (%)
예술인 69
69.0%
미술작가 18
 
18.0%
예술단체 7
 
7.0%
구술채록 6
 
6.0%

Length

2023-12-10T18:46:14.112387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:46:14.341365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
예술인 69
69.0%
미술작가 18
 
18.0%
예술단체 7
 
7.0%
구술채록 6
 
6.0%

nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:46:14.861146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length3.43
Min length2

Characters and Unicode

Total characters343
Distinct characters137
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

Unique100 ?
Unique (%)100.0%

Sample

1st row심옥식
2nd row오수환
3rd row홍현숙
4th row계낙영
5th row극단 산으로 간 어부
ValueCountFrequency (%)
극단 2
 
1.9%
심옥식 1
 
0.9%
이성자 1
 
0.9%
최미레 1
 
0.9%
공석준 1
 
0.9%
정현도 1
 
0.9%
이영학 1
 
0.9%
홍순모 1
 
0.9%
박수정 1
 
0.9%
이용백 1
 
0.9%
Other values (96) 96
89.7%
2023-12-10T18:46:15.733752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 19
 
5.5%
김 18
 
5.2%
영 9
 
2.6%
수 8
 
2.3%
정 8
 
2.3%
7
 
2.0%
옥 7
 
2.0%
인 7
 
2.0%
홍 7
 
2.0%
현 7
 
2.0%
Other values (127) 246
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 332
96.8%
Space Separator 7
 
2.0%
Open Punctuation 2
 
0.6%
Close Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 19
 
5.7%
김 18
 
5.4%
영 9
 
2.7%
수 8
 
2.4%
정 8
 
2.4%
옥 7
 
2.1%
인 7
 
2.1%
홍 7
 
2.1%
현 7
 
2.1%
성 7
 
2.1%
Other values (124) 235
70.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 332
96.8%
Common 11
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 19
 
5.7%
김 18
 
5.4%
영 9
 
2.7%
수 8
 
2.4%
정 8
 
2.4%
옥 7
 
2.1%
인 7
 
2.1%
홍 7
 
2.1%
현 7
 
2.1%
성 7
 
2.1%
Other values (124) 235
70.8%
Common
ValueCountFrequency (%)
7
63.6%
( 2
 
18.2%
) 2
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 332
96.8%
ASCII 11
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 19
 
5.7%
김 18
 
5.4%
영 9
 
2.7%
수 8
 
2.4%
정 8
 
2.4%
옥 7
 
2.1%
인 7
 
2.1%
홍 7
 
2.1%
현 7
 
2.1%
성 7
 
2.1%
Other values (124) 235
70.8%
ASCII
ValueCountFrequency (%)
7
63.6%
( 2
 
18.2%
) 2
 
18.2%

vrit_mark_cn
Text

MISSING 

Distinct90
Distinct (%)100.0%
Missing10
Missing (%)10.0%
Memory size932.0 B
2023-12-10T18:46:16.430623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length10.055556
Min length3

Characters and Unicode

Total characters905
Distinct characters125
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)100.0%

Sample

1st rowSHIM Okshik
2nd rowOh su fan
3rd rowHong hyun sook
4th rowKye nak young
5th rowKim bo hie
ValueCountFrequency (%)
lee 11
 
5.2%
kim 10
 
4.7%
young 6
 
2.8%
hong 6
 
2.8%
kang 4
 
1.9%
park 4
 
1.9%
mo 4
 
1.9%
joo 3
 
1.4%
shim 3
 
1.4%
sun 3
 
1.4%
Other values (132) 157
74.4%
2023-12-10T18:46:17.418939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
13.4%
n 87
 
9.6%
o 79
 
8.7%
e 59
 
6.5%
g 47
 
5.2%
u 46
 
5.1%
h 31
 
3.4%
a 30
 
3.3%
i 30
 
3.3%
k 28
 
3.1%
Other values (115) 347
38.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 558
61.7%
Space Separator 121
 
13.4%
Uppercase Letter 111
 
12.3%
Other Letter 104
 
11.5%
Other Punctuation 8
 
0.9%
Dash Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
李 7
 
6.7%
金 5
 
4.8%
子 3
 
2.9%
玉 3
 
2.9%
宋 2
 
1.9%
趙 2
 
1.9%
昌 2
 
1.9%
錫 2
 
1.9%
成 2
 
1.9%
慶 2
 
1.9%
Other values (70) 74
71.2%
Lowercase Letter
ValueCountFrequency (%)
n 87
15.6%
o 79
14.2%
e 59
10.6%
g 47
8.4%
u 46
8.2%
h 31
 
5.6%
a 30
 
5.4%
i 30
 
5.4%
k 28
 
5.0%
y 27
 
4.8%
Other values (12) 94
16.8%
Uppercase Letter
ValueCountFrequency (%)
K 20
18.0%
L 14
12.6%
S 12
10.8%
H 11
9.9%
C 8
 
7.2%
J 7
 
6.3%
O 5
 
4.5%
E 5
 
4.5%
N 4
 
3.6%
R 4
 
3.6%
Other values (8) 21
18.9%
Space Separator
ValueCountFrequency (%)
121
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 669
73.9%
Common 132
 
14.6%
Han 95
 
10.5%
Hangul 9
 
1.0%

Most frequent character per script

Han
ValueCountFrequency (%)
李 7
 
7.4%
金 5
 
5.3%
子 3
 
3.2%
玉 3
 
3.2%
宋 2
 
2.1%
趙 2
 
2.1%
昌 2
 
2.1%
錫 2
 
2.1%
成 2
 
2.1%
慶 2
 
2.1%
Other values (63) 65
68.4%
Latin
ValueCountFrequency (%)
n 87
13.0%
o 79
 
11.8%
e 59
 
8.8%
g 47
 
7.0%
u 46
 
6.9%
h 31
 
4.6%
a 30
 
4.5%
i 30
 
4.5%
k 28
 
4.2%
y 27
 
4.0%
Other values (30) 205
30.6%
Hangul
ValueCountFrequency (%)
명 2
22.2%
본 2
22.2%
옥 1
11.1%
경 1
11.1%
이 1
11.1%
유 1
11.1%
백 1
11.1%
Common
ValueCountFrequency (%)
121
91.7%
, 8
 
6.1%
- 1
 
0.8%
( 1
 
0.8%
) 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 801
88.5%
CJK 82
 
9.1%
CJK Compat Ideographs 13
 
1.4%
Hangul 9
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
15.1%
n 87
 
10.9%
o 79
 
9.9%
e 59
 
7.4%
g 47
 
5.9%
u 46
 
5.7%
h 31
 
3.9%
a 30
 
3.7%
i 30
 
3.7%
k 28
 
3.5%
Other values (35) 243
30.3%
CJK Compat Ideographs
ValueCountFrequency (%)
李 7
53.8%
金 5
38.5%
羅 1
 
7.7%
CJK
ValueCountFrequency (%)
子 3
 
3.7%
玉 3
 
3.7%
宋 2
 
2.4%
趙 2
 
2.4%
昌 2
 
2.4%
錫 2
 
2.4%
成 2
 
2.4%
慶 2
 
2.4%
金 2
 
2.4%
邊 2
 
2.4%
Other values (60) 60
73.2%
Hangul
ValueCountFrequency (%)
명 2
22.2%
본 2
22.2%
옥 1
11.1%
경 1
11.1%
이 1
11.1%
유 1
11.1%
백 1
11.1%

realm_cl
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
시각예술
38 
창작음악
15 
공연예술
15 
회화
7 
공연단체
6 
Other values (8)
19 

Length

Max length4
Median length4
Mean length3.54
Min length2

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row창작음악
2nd row시각예술
3rd row시각예술
4th row시각예술
5th row공연단체

Common Values

ValueCountFrequency (%)
시각예술 38
38.0%
창작음악 15
 
15.0%
공연예술 15
 
15.0%
회화 7
 
7.0%
공연단체 6
 
6.0%
문학 6
 
6.0%
조각 5
 
5.0%
사진 2
 
2.0%
설치 2
 
2.0%
<NA> 1
 
1.0%
Other values (3) 3
 
3.0%

Length

2023-12-10T18:46:17.714563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시각예술 38
38.0%
창작음악 15
 
15.0%
공연예술 15
 
15.0%
회화 7
 
7.0%
공연단체 6
 
6.0%
문학 6
 
6.0%
조각 5
 
5.0%
사진 2
 
2.0%
설치 2
 
2.0%
na 1
 
1.0%
Other values (3) 3
 
3.0%

act_relm_cn
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
미술작가
32 
<NA>
25 
한국현대음악
15 
문학
4 
연극
4 
Other values (16)
20 

Length

Max length8
Median length4
Mean length4.03
Min length1

Unique

Unique13 ?
Unique (%)13.0%

Sample

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

Common Values

ValueCountFrequency (%)
미술작가 32
32.0%
<NA> 25
25.0%
한국현대음악 15
15.0%
문학 4
 
4.0%
연극 4
 
4.0%
서양화 3
 
3.0%
작곡 2
 
2.0%
무용 2
 
2.0%
한국민속무용 1
 
1.0%
시 1
 
1.0%
Other values (11) 11
 
11.0%

Length

2023-12-10T18:46:18.045465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미술작가 32
31.4%
na 25
24.5%
한국현대음악 15
14.7%
문학 4
 
3.9%
연극 4
 
3.9%
서양화 4
 
3.9%
작곡 2
 
2.0%
무용 2
 
2.0%
경기민요 1
 
1.0%
한국무용 1
 
1.0%
Other values (12) 12
 
11.8%

birth_year
Real number (ℝ)

MISSING 

Distinct53
Distinct (%)67.1%
Missing21
Missing (%)21.0%
Infinite0
Infinite (%)0.0%
Mean1945.8734
Minimum1912
Maximum1994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:46:18.304858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1912
5-th percentile1917.9
Q11931.5
median1945
Q31959.5
95-th percentile1979
Maximum1994
Range82
Interquartile range (IQR)28

Descriptive statistics

Standard deviation18.940099
Coefficient of variation (CV)0.0097334694
Kurtosis-0.61170981
Mean1945.8734
Median Absolute Deviation (MAD)14
Skewness0.27799089
Sum153724
Variance358.72736
MonotonicityNot monotonic
2023-12-10T18:46:18.656144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1952 3
 
3.0%
1972 3
 
3.0%
1960 3
 
3.0%
1936 3
 
3.0%
1922 2
 
2.0%
1956 2
 
2.0%
1949 2
 
2.0%
1938 2
 
2.0%
1979 2
 
2.0%
1966 2
 
2.0%
Other values (43) 55
55.0%
(Missing) 21
 
21.0%
ValueCountFrequency (%)
1912 1
1.0%
1913 1
1.0%
1914 1
1.0%
1917 1
1.0%
1918 1
1.0%
1919 1
1.0%
1921 1
1.0%
1922 2
2.0%
1923 1
1.0%
1924 1
1.0%
ValueCountFrequency (%)
1994 1
 
1.0%
1983 1
 
1.0%
1981 1
 
1.0%
1979 2
2.0%
1978 1
 
1.0%
1972 3
3.0%
1969 1
 
1.0%
1968 1
 
1.0%
1967 1
 
1.0%
1966 2
2.0%

rsrch_man_nm
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing94
Missing (%)94.0%
Memory size932.0 B
2023-12-10T18:46:18.932905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters18
Distinct characters17
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

Unique6 ?
Unique (%)100.0%

Sample

1st row박선애
2nd row김성수
3rd row서지영
4th row장미영
5th row이인순
ValueCountFrequency (%)
박선애 1
16.7%
김성수 1
16.7%
서지영 1
16.7%
장미영 1
16.7%
이인순 1
16.7%
한진일 1
16.7%
2023-12-10T18:46:19.424553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
영 2
 
11.1%
장 1
 
5.6%
진 1
 
5.6%
한 1
 
5.6%
순 1
 
5.6%
인 1
 
5.6%
이 1
 
5.6%
미 1
 
5.6%
박 1
 
5.6%
선 1
 
5.6%
Other values (7) 7
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 2
 
11.1%
장 1
 
5.6%
진 1
 
5.6%
한 1
 
5.6%
순 1
 
5.6%
인 1
 
5.6%
이 1
 
5.6%
미 1
 
5.6%
박 1
 
5.6%
선 1
 
5.6%
Other values (7) 7
38.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 2
 
11.1%
장 1
 
5.6%
진 1
 
5.6%
한 1
 
5.6%
순 1
 
5.6%
인 1
 
5.6%
이 1
 
5.6%
미 1
 
5.6%
박 1
 
5.6%
선 1
 
5.6%
Other values (7) 7
38.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
영 2
 
11.1%
장 1
 
5.6%
진 1
 
5.6%
한 1
 
5.6%
순 1
 
5.6%
인 1
 
5.6%
이 1
 
5.6%
미 1
 
5.6%
박 1
 
5.6%
선 1
 
5.6%
Other values (7) 7
38.9%

url
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:46:19.856023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length43
Mean length42.95
Min length42

Characters and Unicode

Total characters4295
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowhttps://www.daarts.or.kr/handle/11080/67675
2nd rowhttps://www.daarts.or.kr/handle/11080/19462
3rd rowhttps://www.daarts.or.kr/handle/11080/19678
4th rowhttps://www.daarts.or.kr/handle/11080/19222
5th rowhttps://www.daarts.or.kr/handle/11080/51181
ValueCountFrequency (%)
https://www.daarts.or.kr/handle/11080/67675 1
 
1.0%
https://www.daarts.or.kr/handle/11080/19519 1
 
1.0%
https://www.daarts.or.kr/handle/11080/65696 1
 
1.0%
https://www.daarts.or.kr/handle/11080/19606 1
 
1.0%
https://www.daarts.or.kr/handle/11080/19531 1
 
1.0%
https://www.daarts.or.kr/handle/11080/19671 1
 
1.0%
https://www.daarts.or.kr/handle/11080/106595 1
 
1.0%
https://www.daarts.or.kr/handle/11080/19533 1
 
1.0%
https://www.daarts.or.kr/handle/11080/119447 1
 
1.0%
https://www.daarts.or.kr/handle/11080/19336 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:46:20.510951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 500
 
11.6%
w 300
 
7.0%
. 300
 
7.0%
a 300
 
7.0%
r 300
 
7.0%
t 300
 
7.0%
1 296
 
6.9%
0 228
 
5.3%
h 200
 
4.7%
s 200
 
4.7%
Other values (16) 1371
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2400
55.9%
Decimal Number 995
23.2%
Other Punctuation 900
 
21.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 300
12.5%
a 300
12.5%
r 300
12.5%
t 300
12.5%
h 200
8.3%
s 200
8.3%
d 200
8.3%
l 100
 
4.2%
e 100
 
4.2%
n 100
 
4.2%
Other values (3) 300
12.5%
Decimal Number
ValueCountFrequency (%)
1 296
29.7%
0 228
22.9%
8 131
13.2%
9 78
 
7.8%
6 59
 
5.9%
5 59
 
5.9%
3 47
 
4.7%
4 37
 
3.7%
2 34
 
3.4%
7 26
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/ 500
55.6%
. 300
33.3%
: 100
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2400
55.9%
Common 1895
44.1%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 500
26.4%
. 300
15.8%
1 296
15.6%
0 228
12.0%
8 131
 
6.9%
: 100
 
5.3%
9 78
 
4.1%
6 59
 
3.1%
5 59
 
3.1%
3 47
 
2.5%
Other values (3) 97
 
5.1%
Latin
ValueCountFrequency (%)
w 300
12.5%
a 300
12.5%
r 300
12.5%
t 300
12.5%
h 200
8.3%
s 200
8.3%
d 200
8.3%
l 100
 
4.2%
e 100
 
4.2%
n 100
 
4.2%
Other values (3) 300
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 500
 
11.6%
w 300
 
7.0%
. 300
 
7.0%
a 300
 
7.0%
r 300
 
7.0%
t 300
 
7.0%
1 296
 
6.9%
0 228
 
5.3%
h 200
 
4.7%
s 200
 
4.7%
Other values (16) 1371
31.9%

Interactions

2023-12-10T18:46:12.512347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:46:20.692605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
art_grp_searchv_artst_nmnmvrit_mark_cnrealm_clact_relm_cnbirth_yearrsrch_man_nmurl
art_grp_se1.0001.0001.0001.0000.9930.9720.280NaN1.000
archv_artst_nm1.0001.0001.0001.0000.9930.9720.280NaN1.000
nm1.0001.0001.0001.0001.0001.0001.0001.0001.000
vrit_mark_cn1.0001.0001.0001.0001.0001.0001.0001.0001.000
realm_cl0.9930.9931.0001.0001.0001.0000.5631.0001.000
act_relm_cn0.9720.9721.0001.0001.0001.0000.7221.0001.000
birth_year0.2800.2801.0001.0000.5630.7221.0001.0001.000
rsrch_man_nmNaNNaN1.0001.0001.0001.0001.0001.0001.000
url1.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-10T18:46:20.886695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
act_relm_cnrealm_clart_grp_searchv_artst_nm
act_relm_cn1.0000.8860.7550.755
realm_cl0.8861.0000.8510.851
art_grp_se0.7550.8511.0001.000
archv_artst_nm0.7550.8511.0001.000
2023-12-10T18:46:21.075190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
birth_yearart_grp_searchv_artst_nmrealm_clact_relm_cn
birth_year1.0000.1630.1630.2810.272
art_grp_se0.1631.0001.0000.8510.755
archv_artst_nm0.1631.0001.0000.8510.755
realm_cl0.2810.8510.8511.0000.886
act_relm_cn0.2720.7550.7550.8861.000

Missing values

2023-12-10T18:46:12.710828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:46:13.000258image/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.
2023-12-10T18:46:13.230905image/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

art_grp_searchv_artst_nmnmvrit_mark_cnrealm_clact_relm_cnbirth_yearrsrch_man_nmurl
0ARTST예술인심옥식SHIM Okshik창작음악한국현대음악1959<NA>https://www.daarts.or.kr/handle/11080/67675
1ARTST예술인오수환Oh su fan시각예술미술작가1946<NA>https://www.daarts.or.kr/handle/11080/19462
2ARTST예술인홍현숙Hong hyun sook시각예술미술작가1958<NA>https://www.daarts.or.kr/handle/11080/19678
3ARTST예술인계낙영Kye nak young시각예술미술작가1948<NA>https://www.daarts.or.kr/handle/11080/19222
4ARTGR예술단체극단 산으로 간 어부<NA>공연단체<NA><NA><NA>https://www.daarts.or.kr/handle/11080/51181
5FARTST미술작가김보희Kim bo hie회화<NA>1952<NA>https://www.daarts.or.kr/handle/11080/19273
6ARTST예술인변시지邊時志시각예술서양화1926<NA>https://www.daarts.or.kr/handle/11080/6034
7ARTST예술인임영미LYMN Youngmee창작음악한국현대음악1960<NA>https://www.daarts.or.kr/handle/11080/58477
8ARTST예술인이재삼Lee jae sam시각예술미술작가1960<NA>https://www.daarts.or.kr/handle/11080/19540
9ARTST예술인김춘옥Kim chun ok시각예술미술작가1946<NA>https://www.daarts.or.kr/handle/11080/19330
art_grp_searchv_artst_nmnmvrit_mark_cnrealm_clact_relm_cnbirth_yearrsrch_man_nmurl
90DIC구술채록김우옥金雨玉공연예술연극1934이인순https://www.daarts.or.kr/handle/11080/16194
91ARTGR예술단체공연배달서비스 간다<NA>공연단체<NA><NA><NA>https://www.daarts.or.kr/handle/11080/33954
92ARTST예술인강정완Kang jeong wan시각예술미술작가<NA><NA>https://www.daarts.or.kr/handle/11080/19214
93ARTST예술인김선두Kim sun doo시각예술미술작가<NA><NA>https://www.daarts.or.kr/handle/11080/19281
94ARTST예술인김의경金義卿공연예술극작가1936<NA>https://www.daarts.or.kr/handle/11080/6157
95ARTST예술인김남조金南祚문학시1927<NA>https://www.daarts.or.kr/handle/11080/5778
96DIC구술채록성찬경成贊慶문학문학1930한진일https://www.daarts.or.kr/handle/11080/16415
97FARTST미술작가최민식Choi min sick사진<NA>1928<NA>https://www.daarts.or.kr/handle/11080/19635
98ARTST예술인조수호趙守鎬시각예술서예1924<NA>https://www.daarts.or.kr/handle/11080/5926
99FARTST미술작가강진모Kang jin mo조각<NA>1956<NA>https://www.daarts.or.kr/handle/11080/19215