Overview

Dataset statistics

Number of variables6
Number of observations906
Missing cells17
Missing cells (%)0.3%
Duplicate rows3
Duplicate rows (%)0.3%
Total size in memory42.6 KiB
Average record size in memory48.1 B

Variable types

Categorical2
Text4

Dataset

Description한국남부발전(주)_본사 북카페 도서 현황에 대한 데이터로 카테고리, 도서명, 저자명, 출판사, 출판일 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15095377/fileData.do

Alerts

Dataset has 3 (0.3%) duplicate rowsDuplicates
저자명 has 13 (1.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 20:35:10.305624
Analysis finished2023-12-12 20:35:11.354330
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

카테고리
Categorical

Distinct23
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
문학
251 
경제/경영
201 
자기계발
137 
취미/생활/건강
60 
인문/역사
52 
Other values (18)
205 

Length

Max length8
Median length7
Mean length3.8907285
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row경제/경영
2nd row인문/역사
3rd row자기계발
4th row경제/경영
5th row문학

Common Values

ValueCountFrequency (%)
문학 251
27.7%
경제/경영 201
22.2%
자기계발 137
15.1%
취미/생활/건강 60
 
6.6%
인문/역사 52
 
5.7%
외국어/외국도서 25
 
2.8%
인문 25
 
2.8%
사회 25
 
2.8%
만화 24
 
2.6%
과학 18
 
2.0%
Other values (13) 88
 
9.7%

Length

2023-12-13T05:35:11.437771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
문학 251
27.7%
경제/경영 201
22.2%
자기계발 137
15.1%
취미/생활/건강 60
 
6.6%
인문/역사 52
 
5.7%
외국어/외국도서 25
 
2.8%
인문 25
 
2.8%
사회 25
 
2.8%
만화 24
 
2.6%
과학 18
 
2.0%
Other values (13) 88
 
9.7%

도서명
Text

Distinct886
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-13T05:35:11.742850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length30
Mean length11.717439
Min length1

Characters and Unicode

Total characters10616
Distinct characters742
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique866 ?
Unique (%)95.6%

Sample

1st row스티브 잡스
2nd row행복해질 용기
3rd row몰입 : 인생을 바꾸는 자기 혁명
4th row4개의 통장
5th row언어의 온도
ValueCountFrequency (%)
34
 
1.1%
식객 24
 
0.8%
2 19
 
0.6%
1 19
 
0.6%
나는 18
 
0.6%
기념 15
 
0.5%
수업 15
 
0.5%
나의 14
 
0.5%
에디션 14
 
0.5%
아리랑 12
 
0.4%
Other values (1956) 2844
93.9%
2023-12-13T05:35:12.180284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2122
 
20.0%
의 304
 
2.9%
는 181
 
1.7%
이 166
 
1.6%
기 131
 
1.2%
다 130
 
1.2%
하 117
 
1.1%
사 116
 
1.1%
리 112
 
1.1%
지 99
 
0.9%
Other values (732) 7138
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7702
72.6%
Space Separator 2122
 
20.0%
Decimal Number 353
 
3.3%
Uppercase Letter 131
 
1.2%
Other Punctuation 116
 
1.1%
Lowercase Letter 81
 
0.8%
Open Punctuation 48
 
0.5%
Close Punctuation 48
 
0.5%
Dash Punctuation 9
 
0.1%
Final Punctuation 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 304
 
3.9%
는 181
 
2.4%
이 166
 
2.2%
기 131
 
1.7%
다 130
 
1.7%
하 117
 
1.5%
사 116
 
1.5%
리 112
 
1.5%
지 99
 
1.3%
한 99
 
1.3%
Other values (664) 6247
81.1%
Uppercase Letter
ValueCountFrequency (%)
T 24
18.3%
G 15
11.5%
I 11
 
8.4%
P 10
 
7.6%
H 9
 
6.9%
N 8
 
6.1%
O 6
 
4.6%
R 6
 
4.6%
W 6
 
4.6%
E 6
 
4.6%
Other values (12) 30
22.9%
Lowercase Letter
ValueCountFrequency (%)
h 9
11.1%
i 8
9.9%
e 8
9.9%
o 7
8.6%
s 7
8.6%
t 6
 
7.4%
n 6
 
7.4%
g 5
 
6.2%
c 4
 
4.9%
a 4
 
4.9%
Other values (10) 17
21.0%
Decimal Number
ValueCountFrequency (%)
0 88
24.9%
1 77
21.8%
2 77
21.8%
3 30
 
8.5%
5 24
 
6.8%
4 15
 
4.2%
6 14
 
4.0%
8 11
 
3.1%
9 10
 
2.8%
7 7
 
2.0%
Other Punctuation
ValueCountFrequency (%)
: 39
33.6%
, 37
31.9%
. 19
16.4%
! 7
 
6.0%
? 6
 
5.2%
· 5
 
4.3%
& 1
 
0.9%
/ 1
 
0.9%
% 1
 
0.9%
Space Separator
ValueCountFrequency (%)
2122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7700
72.5%
Common 2702
 
25.5%
Latin 212
 
2.0%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 304
 
3.9%
는 181
 
2.4%
이 166
 
2.2%
기 131
 
1.7%
다 130
 
1.7%
하 117
 
1.5%
사 116
 
1.5%
리 112
 
1.5%
지 99
 
1.3%
한 99
 
1.3%
Other values (662) 6245
81.1%
Latin
ValueCountFrequency (%)
T 24
 
11.3%
G 15
 
7.1%
I 11
 
5.2%
P 10
 
4.7%
H 9
 
4.2%
h 9
 
4.2%
i 8
 
3.8%
e 8
 
3.8%
N 8
 
3.8%
o 7
 
3.3%
Other values (32) 103
48.6%
Common
ValueCountFrequency (%)
2122
78.5%
0 88
 
3.3%
1 77
 
2.8%
2 77
 
2.8%
( 48
 
1.8%
) 48
 
1.8%
: 39
 
1.4%
, 37
 
1.4%
3 30
 
1.1%
5 24
 
0.9%
Other values (16) 112
 
4.1%
Han
ValueCountFrequency (%)
乙 1
50.0%
神 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7700
72.5%
ASCII 2905
 
27.4%
None 5
 
< 0.1%
Punctuation 4
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2122
73.0%
0 88
 
3.0%
1 77
 
2.7%
2 77
 
2.7%
( 48
 
1.7%
) 48
 
1.7%
: 39
 
1.3%
, 37
 
1.3%
3 30
 
1.0%
5 24
 
0.8%
Other values (55) 315
 
10.8%
Hangul
ValueCountFrequency (%)
의 304
 
3.9%
는 181
 
2.4%
이 166
 
2.2%
기 131
 
1.7%
다 130
 
1.7%
하 117
 
1.5%
사 116
 
1.5%
리 112
 
1.5%
지 99
 
1.3%
한 99
 
1.3%
Other values (662) 6245
81.1%
None
ValueCountFrequency (%)
· 5
100.0%
Punctuation
ValueCountFrequency (%)
’ 2
50.0%
‘ 2
50.0%
CJK
ValueCountFrequency (%)
乙 1
50.0%
神 1
50.0%

저자명
Text

MISSING 

Distinct711
Distinct (%)79.6%
Missing13
Missing (%)1.4%
Memory size7.2 KiB
2023-12-13T05:35:12.508796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length5.5475924
Min length1

Characters and Unicode

Total characters4954
Distinct characters511
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique624 ?
Unique (%)69.9%

Sample

1st row월터 아이작슨
2nd row기시미 이치로
3rd row황농문
4th row고경호
5th row이기주
ValueCountFrequency (%)
허영만 27
 
1.9%
조정래 24
 
1.7%
존 17
 
1.2%
히가시노 10
 
0.7%
게이고 10
 
0.7%
그리샴 9
 
0.6%
채사장 9
 
0.6%
마이클 8
 
0.6%
로버트 6
 
0.4%
마케마케 6
 
0.4%
Other values (1051) 1302
91.2%
2023-12-13T05:35:12.951084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
535
 
10.8%
이 180
 
3.6%
, 131
 
2.6%
김 120
 
2.4%
스 105
 
2.1%
리 93
 
1.9%
정 88
 
1.8%
영 79
 
1.6%
조 54
 
1.1%
드 53
 
1.1%
Other values (501) 3516
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4133
83.4%
Space Separator 535
 
10.8%
Other Punctuation 157
 
3.2%
Uppercase Letter 43
 
0.9%
Lowercase Letter 29
 
0.6%
Open Punctuation 23
 
0.5%
Close Punctuation 20
 
0.4%
Math Symbol 12
 
0.2%
Dash Punctuation 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 180
 
4.4%
김 120
 
2.9%
스 105
 
2.5%
리 93
 
2.3%
정 88
 
2.1%
영 79
 
1.9%
조 54
 
1.3%
드 53
 
1.3%
마 51
 
1.2%
미 46
 
1.1%
Other values (456) 3264
79.0%
Uppercase Letter
ValueCountFrequency (%)
N 6
14.0%
J 4
 
9.3%
M 4
 
9.3%
D 3
 
7.0%
A 3
 
7.0%
S 3
 
7.0%
H 3
 
7.0%
R 3
 
7.0%
T 2
 
4.7%
F 2
 
4.7%
Other values (9) 10
23.3%
Lowercase Letter
ValueCountFrequency (%)
t 4
13.8%
i 4
13.8%
r 3
10.3%
v 3
10.3%
u 2
6.9%
a 2
6.9%
e 2
6.9%
n 2
6.9%
l 2
6.9%
y 1
 
3.4%
Other values (4) 4
13.8%
Math Symbol
ValueCountFrequency (%)
| 9
75.0%
< 2
 
16.7%
> 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 131
83.4%
. 26
 
16.6%
Open Punctuation
ValueCountFrequency (%)
( 21
91.3%
〈 2
 
8.7%
Close Punctuation
ValueCountFrequency (%)
) 18
90.0%
〉 2
 
10.0%
Space Separator
ValueCountFrequency (%)
535
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4133
83.4%
Common 749
 
15.1%
Latin 72
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 180
 
4.4%
김 120
 
2.9%
스 105
 
2.5%
리 93
 
2.3%
정 88
 
2.1%
영 79
 
1.9%
조 54
 
1.3%
드 53
 
1.3%
마 51
 
1.2%
미 46
 
1.1%
Other values (456) 3264
79.0%
Latin
ValueCountFrequency (%)
N 6
 
8.3%
t 4
 
5.6%
i 4
 
5.6%
J 4
 
5.6%
M 4
 
5.6%
D 3
 
4.2%
A 3
 
4.2%
S 3
 
4.2%
H 3
 
4.2%
r 3
 
4.2%
Other values (23) 35
48.6%
Common
ValueCountFrequency (%)
535
71.4%
, 131
 
17.5%
. 26
 
3.5%
( 21
 
2.8%
) 18
 
2.4%
| 9
 
1.2%
〉 2
 
0.3%
〈 2
 
0.3%
< 2
 
0.3%
- 1
 
0.1%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4133
83.4%
ASCII 817
 
16.5%
None 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
535
65.5%
, 131
 
16.0%
. 26
 
3.2%
( 21
 
2.6%
) 18
 
2.2%
| 9
 
1.1%
N 6
 
0.7%
t 4
 
0.5%
i 4
 
0.5%
J 4
 
0.5%
Other values (33) 59
 
7.2%
Hangul
ValueCountFrequency (%)
이 180
 
4.4%
김 120
 
2.9%
스 105
 
2.5%
리 93
 
2.3%
정 88
 
2.1%
영 79
 
1.9%
조 54
 
1.3%
드 53
 
1.3%
마 51
 
1.2%
미 46
 
1.1%
Other values (456) 3264
79.0%
None
ValueCountFrequency (%)
〉 2
50.0%
〈 2
50.0%

출판사
Text

Distinct384
Distinct (%)42.5%
Missing2
Missing (%)0.2%
Memory size7.2 KiB
2023-12-13T05:35:13.192898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length4.7201327
Min length1

Characters and Unicode

Total characters4267
Distinct characters389
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)25.3%

Sample

1st row민음사
2nd row더좋은책
3rd row랜덤하우스
4th row다산북스
5th row말글터
ValueCountFrequency (%)
김영사 46
 
5.1%
해냄출판사 22
 
2.4%
문학동네 19
 
2.1%
민음사 17
 
1.9%
다산북스 17
 
1.9%
알에이치코리아(rhk 15
 
1.7%
위즈덤하우스 14
 
1.5%
창비 14
 
1.5%
쌤앤파커스 11
 
1.2%
웅진지식하우스 11
 
1.2%
Other values (374) 719
79.4%
2023-12-13T05:35:14.058499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 279
 
6.5%
북 170
 
4.0%
사 151
 
3.5%
이 106
 
2.5%
( 85
 
2.0%
) 85
 
2.0%
리 69
 
1.6%
다 60
 
1.4%
어 59
 
1.4%
문 56
 
1.3%
Other values (379) 3147
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3834
89.9%
Lowercase Letter 116
 
2.7%
Uppercase Letter 109
 
2.6%
Open Punctuation 85
 
2.0%
Close Punctuation 85
 
2.0%
Decimal Number 28
 
0.7%
Other Punctuation 7
 
0.2%
Space Separator 1
 
< 0.1%
Other Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 279
 
7.3%
북 170
 
4.4%
사 151
 
3.9%
이 106
 
2.8%
리 69
 
1.8%
다 60
 
1.6%
어 59
 
1.5%
문 56
 
1.5%
트 55
 
1.4%
비 53
 
1.4%
Other values (329) 2776
72.4%
Uppercase Letter
ValueCountFrequency (%)
K 21
19.3%
R 21
19.3%
H 15
13.8%
B 7
 
6.4%
T 6
 
5.5%
I 6
 
5.5%
F 5
 
4.6%
A 5
 
4.6%
N 3
 
2.8%
P 3
 
2.8%
Other values (14) 17
15.6%
Lowercase Letter
ValueCountFrequency (%)
o 19
16.4%
e 16
13.8%
a 13
11.2%
i 11
9.5%
r 7
 
6.0%
n 6
 
5.2%
b 6
 
5.2%
k 6
 
5.2%
s 6
 
5.2%
m 5
 
4.3%
Other values (8) 21
18.1%
Decimal Number
ValueCountFrequency (%)
2 18
64.3%
1 10
35.7%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3835
89.9%
Latin 225
 
5.3%
Common 207
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 279
 
7.3%
북 170
 
4.4%
사 151
 
3.9%
이 106
 
2.8%
리 69
 
1.8%
다 60
 
1.6%
어 59
 
1.5%
문 56
 
1.5%
트 55
 
1.4%
비 53
 
1.4%
Other values (330) 2777
72.4%
Latin
ValueCountFrequency (%)
K 21
 
9.3%
R 21
 
9.3%
o 19
 
8.4%
e 16
 
7.1%
H 15
 
6.7%
a 13
 
5.8%
i 11
 
4.9%
B 7
 
3.1%
r 7
 
3.1%
n 6
 
2.7%
Other values (32) 89
39.6%
Common
ValueCountFrequency (%)
( 85
41.1%
) 85
41.1%
2 18
 
8.7%
1 10
 
4.8%
. 7
 
3.4%
1
 
0.5%
- 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3834
89.9%
ASCII 432
 
10.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 279
 
7.3%
북 170
 
4.4%
사 151
 
3.9%
이 106
 
2.8%
리 69
 
1.8%
다 60
 
1.6%
어 59
 
1.5%
문 56
 
1.5%
트 55
 
1.4%
비 53
 
1.4%
Other values (329) 2776
72.4%
ASCII
ValueCountFrequency (%)
( 85
19.7%
) 85
19.7%
K 21
 
4.9%
R 21
 
4.9%
o 19
 
4.4%
2 18
 
4.2%
e 16
 
3.7%
H 15
 
3.5%
a 13
 
3.0%
i 11
 
2.5%
Other values (39) 128
29.6%
None
ValueCountFrequency (%)
㈜ 1
100.0%

출판일
Text

Distinct591
Distinct (%)65.4%
Missing2
Missing (%)0.2%
Memory size7.2 KiB
2023-12-13T05:35:14.362174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9889381
Min length5

Characters and Unicode

Total characters9030
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique440 ?
Unique (%)48.7%

Sample

1st row2011-10-24
2nd row2015-07-20
3rd row2007-12-10
4th row2009-01-10
5th row2016-08-19
ValueCountFrequency (%)
2007-01-30 19
 
2.1%
2023-03-30 12
 
1.3%
2023-04-28 12
 
1.3%
2023-04-26 10
 
1.1%
2023-04-14 9
 
1.0%
2023-04-05 9
 
1.0%
2023-05-10 9
 
1.0%
2023-05-01 8
 
0.9%
2023-03-24 8
 
0.9%
2023-04-20 8
 
0.9%
Other values (581) 800
88.5%
2023-12-13T05:35:14.775947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2375
26.3%
2 2139
23.7%
- 1804
20.0%
1 948
 
10.5%
3 551
 
6.1%
5 271
 
3.0%
4 248
 
2.7%
9 191
 
2.1%
8 187
 
2.1%
7 181
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7226
80.0%
Dash Punctuation 1804
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2375
32.9%
2 2139
29.6%
1 948
 
13.1%
3 551
 
7.6%
5 271
 
3.8%
4 248
 
3.4%
9 191
 
2.6%
8 187
 
2.6%
7 181
 
2.5%
6 135
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 1804
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9030
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2375
26.3%
2 2139
23.7%
- 1804
20.0%
1 948
 
10.5%
3 551
 
6.1%
5 271
 
3.0%
4 248
 
2.7%
9 191
 
2.1%
8 187
 
2.1%
7 181
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2375
26.3%
2 2139
23.7%
- 1804
20.0%
1 948
 
10.5%
3 551
 
6.1%
5 271
 
3.0%
4 248
 
2.7%
9 191
 
2.1%
8 187
 
2.1%
7 181
 
2.0%

소유
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
자체
748 
대여
158 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자체 748
82.6%
대여 158
 
17.4%

Length

2023-12-13T05:35:14.950474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:35:15.069745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자체 748
82.6%
대여 158
 
17.4%

Correlations

2023-12-13T05:35:15.147373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카테고리소유
카테고리1.0000.229
소유0.2291.000
2023-12-13T05:35:15.252798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카테고리소유
카테고리1.0000.197
소유0.1971.000
2023-12-13T05:35:15.364263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카테고리소유
카테고리1.0000.197
소유0.1971.000

Missing values

2023-12-13T05:35:11.115191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:35:11.210703image/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.
2023-12-13T05:35:11.301338image/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

카테고리도서명저자명출판사출판일소유
0경제/경영스티브 잡스월터 아이작슨민음사2011-10-24대여
1인문/역사행복해질 용기기시미 이치로더좋은책2015-07-20대여
2자기계발몰입 : 인생을 바꾸는 자기 혁명황농문랜덤하우스2007-12-10대여
3경제/경영4개의 통장고경호다산북스2009-01-10대여
4문학언어의 온도이기주말글터2016-08-19대여
5문학위험한 비너스히가시노 게이고현대문학2017-06-30대여
6경제/경영나는 월세 받아 세계여행 간다청목머니플러스2017-08-20대여
7자기계발횡설수설하지 않고 정확하게 설명하는 법고구레 다이치갈매나무2017-08-28대여
8인문/역사말의 품격이기주황소북스2017-05-29대여
9사회검사내전김웅부키2018-01-19대여
카테고리도서명저자명출판사출판일소유
896자기계발관점을 디자인하라박용후프롬북스2013-07-12자체
897자기계발사람은 무엇으로 성장하는가존 맥스웰비즈니스북스2012-10-05자체
898자기계발생각 버리기 연습코이케 류노스케21세기북스2010-09-10자체
899자기계발(시골의사 박경철의) 자기혁명박경철리더스북2011-10-05자체
900자기계발원씽(The One Thing)게리 켈러비즈니스북스2013-08-30자체
901경제/경영권력과 부오루크에코리브르2015-07-24자체
902자기계발린토크앨런 파머처음북스2014-04-28자체
903자기계발태클김흥기갈라북스2014-11-25자체
904역사/문화세상을 바꾼 음식 이야기홍익희세종서적2017-01-06자체
905자기계발그릿(Grit)앤절라 더크워스비즈니스북스2016-10-28자체

Duplicate rows

Most frequently occurring

카테고리도서명저자명출판사출판일소유# duplicates
0경제/경영챗GPT 기회를 잡는 사람들장민알투스2023-03-08자체2
1문학구의 증명최진영은행나무2023-04-26자체2
2문학한강 10조정래해냄출판사2007-01-30자체2