Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory68.3 B

Variable types

Numeric2
Text4
DateTime1
Categorical1

Dataset

Description대구도시개발공사 전자도서관에서 제공하는 대출 순위 100위권 도서 현황(컨텐츠명,출판사,저자,등록일,권수,누적대출)을 제공합니다.
Author대구도시개발공사
URLhttps://www.data.go.kr/data/15049662/fileData.do

Alerts

번호 is highly overall correlated with 누적대출High correlation
누적대출 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
컨텐츠번호 has unique valuesUnique
컨텐츠명 has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:20:00.637777
Analysis finished2023-12-16 15:20:07.147558
Duration6.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-16T15:20:07.576772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-16T15:20:08.349709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

컨텐츠번호
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-16T15:20:09.377605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters900
Distinct characters11
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

Unique100 ?
Unique (%)100.0%

Sample

1st row110500213
2nd row190600029
3rd row090400034
4th row190202508
5th row110500214
ValueCountFrequency (%)
110500213 1
 
1.0%
191006069 1
 
1.0%
191203393 1
 
1.0%
a07100195 1
 
1.0%
090600189 1
 
1.0%
110400816 1
 
1.0%
170605930 1
 
1.0%
190302671 1
 
1.0%
a06070832 1
 
1.0%
090500293 1
 
1.0%
Other values (90) 90
90.0%
2023-12-16T15:20:11.882669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 304
33.8%
1 164
18.2%
2 85
 
9.4%
9 68
 
7.6%
6 50
 
5.6%
5 49
 
5.4%
3 49
 
5.4%
8 44
 
4.9%
4 40
 
4.4%
7 37
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 890
98.9%
Uppercase Letter 10
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 304
34.2%
1 164
18.4%
2 85
 
9.6%
9 68
 
7.6%
6 50
 
5.6%
5 49
 
5.5%
3 49
 
5.5%
8 44
 
4.9%
4 40
 
4.5%
7 37
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 890
98.9%
Latin 10
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 304
34.2%
1 164
18.4%
2 85
 
9.6%
9 68
 
7.6%
6 50
 
5.6%
5 49
 
5.5%
3 49
 
5.5%
8 44
 
4.9%
4 40
 
4.5%
7 37
 
4.2%
Latin
ValueCountFrequency (%)
A 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 304
33.8%
1 164
18.2%
2 85
 
9.4%
9 68
 
7.6%
6 50
 
5.6%
5 49
 
5.4%
3 49
 
5.4%
8 44
 
4.9%
4 40
 
4.4%
7 37
 
4.1%

컨텐츠명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-16T15:20:13.446850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length11.74
Min length2

Characters and Unicode

Total characters1174
Distinct characters305
Distinct categories8 ?
Distinct scripts3 ?
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 row그리스 로마 신화 1
2nd row여행의 이유
3rd row관계의 심리학
4th row아주 작은 습관의 힘
5th row그리스 로마 신화 2
ValueCountFrequency (%)
1 8
 
2.4%
그리스 7
 
2.1%
신화 7
 
2.1%
로마 7
 
2.1%
세계사 4
 
1.2%
3
 
0.9%
읽는 3
 
0.9%
나는 3
 
0.9%
심리학 3
 
0.9%
할 2
 
0.6%
Other values (277) 292
86.1%
2023-12-16T15:20:15.794359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
 
20.4%
의 28
 
2.4%
리 21
 
1.8%
는 21
 
1.8%
이 19
 
1.6%
아 18
 
1.5%
로 17
 
1.4%
사 16
 
1.4%
기 15
 
1.3%
지 15
 
1.3%
Other values (295) 765
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 866
73.8%
Space Separator 239
 
20.4%
Decimal Number 46
 
3.9%
Other Punctuation 11
 
0.9%
Uppercase Letter 5
 
0.4%
Dash Punctuation 3
 
0.3%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 28
 
3.2%
리 21
 
2.4%
는 21
 
2.4%
이 19
 
2.2%
아 18
 
2.1%
로 17
 
2.0%
사 16
 
1.8%
기 15
 
1.7%
지 15
 
1.7%
한 12
 
1.4%
Other values (274) 684
79.0%
Decimal Number
ValueCountFrequency (%)
1 14
30.4%
0 11
23.9%
2 8
17.4%
3 4
 
8.7%
6 3
 
6.5%
5 3
 
6.5%
4 2
 
4.3%
7 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 1
20.0%
G 1
20.0%
R 1
20.0%
I 1
20.0%
T 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 7
63.6%
' 2
 
18.2%
% 1
 
9.1%
: 1
 
9.1%
Space Separator
ValueCountFrequency (%)
239
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 866
73.8%
Common 303
 
25.8%
Latin 5
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 28
 
3.2%
리 21
 
2.4%
는 21
 
2.4%
이 19
 
2.2%
아 18
 
2.1%
로 17
 
2.0%
사 16
 
1.8%
기 15
 
1.7%
지 15
 
1.7%
한 12
 
1.4%
Other values (274) 684
79.0%
Common
ValueCountFrequency (%)
239
78.9%
1 14
 
4.6%
0 11
 
3.6%
2 8
 
2.6%
, 7
 
2.3%
3 4
 
1.3%
- 3
 
1.0%
6 3
 
1.0%
5 3
 
1.0%
' 2
 
0.7%
Other values (6) 9
 
3.0%
Latin
ValueCountFrequency (%)
B 1
20.0%
G 1
20.0%
R 1
20.0%
I 1
20.0%
T 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 866
73.8%
ASCII 308
 
26.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
77.6%
1 14
 
4.5%
0 11
 
3.6%
2 8
 
2.6%
, 7
 
2.3%
3 4
 
1.3%
- 3
 
1.0%
6 3
 
1.0%
5 3
 
1.0%
' 2
 
0.6%
Other values (11) 14
 
4.5%
Hangul
ValueCountFrequency (%)
의 28
 
3.2%
리 21
 
2.4%
는 21
 
2.4%
이 19
 
2.2%
아 18
 
2.1%
로 17
 
2.0%
사 16
 
1.8%
기 15
 
1.7%
지 15
 
1.7%
한 12
 
1.4%
Other values (274) 684
79.0%

출판사
Text

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-16T15:20:16.741437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.37
Min length1

Characters and Unicode

Total characters437
Distinct characters163
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)51.0%

Sample

1st row마므레북
2nd row문학동네
3rd row경향미디어
4th row비즈니스북스
5th row마므레북
ValueCountFrequency (%)
마므레북 7
 
6.9%
비즈니스북스 5
 
5.0%
인플루엔셜 5
 
5.0%
위즈덤하우스 4
 
4.0%
다연 4
 
4.0%
다산북스 3
 
3.0%
애플북스 3
 
3.0%
미래의창 2
 
2.0%
원앤원북스 2
 
2.0%
rhk 2
 
2.0%
Other values (58) 64
63.4%
2023-12-16T15:20:18.523175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 32
 
7.3%
북 27
 
6.2%
다 11
 
2.5%
마 10
 
2.3%
즈 9
 
2.1%
플 8
 
1.8%
산 8
 
1.8%
레 8
 
1.8%
비 8
 
1.8%
므 7
 
1.6%
Other values (153) 309
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 403
92.2%
Uppercase Letter 14
 
3.2%
Lowercase Letter 4
 
0.9%
Decimal Number 4
 
0.9%
Open Punctuation 3
 
0.7%
Close Punctuation 3
 
0.7%
Other Punctuation 3
 
0.7%
Other Symbol 2
 
0.5%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 32
 
7.9%
북 27
 
6.7%
다 11
 
2.7%
마 10
 
2.5%
즈 9
 
2.2%
플 8
 
2.0%
산 8
 
2.0%
레 8
 
2.0%
비 8
 
2.0%
므 7
 
1.7%
Other values (132) 275
68.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
21.4%
C 2
14.3%
R 2
14.3%
H 2
14.3%
K 2
14.3%
M 2
14.3%
I 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
t 1
25.0%
r 1
25.0%
a 1
25.0%
Decimal Number
ValueCountFrequency (%)
4 1
25.0%
0 1
25.0%
1 1
25.0%
2 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 405
92.7%
Latin 18
 
4.1%
Common 14
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 32
 
7.9%
북 27
 
6.7%
다 11
 
2.7%
마 10
 
2.5%
즈 9
 
2.2%
플 8
 
2.0%
산 8
 
2.0%
레 8
 
2.0%
비 8
 
2.0%
므 7
 
1.7%
Other values (133) 277
68.4%
Latin
ValueCountFrequency (%)
B 3
16.7%
C 2
11.1%
R 2
11.1%
H 2
11.1%
K 2
11.1%
M 2
11.1%
e 1
 
5.6%
t 1
 
5.6%
r 1
 
5.6%
a 1
 
5.6%
Common
ValueCountFrequency (%)
( 3
21.4%
) 3
21.4%
& 2
14.3%
1
 
7.1%
4 1
 
7.1%
. 1
 
7.1%
0 1
 
7.1%
1 1
 
7.1%
2 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
92.2%
ASCII 32
 
7.3%
None 2
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 32
 
7.9%
북 27
 
6.7%
다 11
 
2.7%
마 10
 
2.5%
즈 9
 
2.2%
플 8
 
2.0%
산 8
 
2.0%
레 8
 
2.0%
비 8
 
2.0%
므 7
 
1.7%
Other values (132) 275
68.2%
ASCII
ValueCountFrequency (%)
B 3
 
9.4%
( 3
 
9.4%
) 3
 
9.4%
C 2
 
6.2%
& 2
 
6.2%
R 2
 
6.2%
H 2
 
6.2%
K 2
 
6.2%
M 2
 
6.2%
e 1
 
3.1%
Other values (10) 10
31.2%
None
ValueCountFrequency (%)
㈜ 2
100.0%

저자
Text

Distinct84
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-16T15:20:19.605613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length22
Mean length5.35
Min length2

Characters and Unicode

Total characters535
Distinct characters198
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)81.0%

Sample

1st row홍은영
2nd row김영하
3rd row이철우
4th row제임스 클리어
5th row홍은영
ValueCountFrequency (%)
기타 10
 
6.1%
홍은영 7
 
4.3%
kbs 2
 
1.2%
마크 2
 
1.2%
존 2
 
1.2%
권정윤 2
 
1.2%
서유현 2
 
1.2%
이준영 2
 
1.2%
이향은 2
 
1.2%
최지혜 2
 
1.2%
Other values (125) 130
79.8%
2023-12-16T15:20:21.815336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
11.8%
, 22
 
4.1%
이 17
 
3.2%
영 16
 
3.0%
김 15
 
2.8%
리 14
 
2.6%
기 13
 
2.4%
타 11
 
2.1%
은 9
 
1.7%
스 8
 
1.5%
Other values (188) 347
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 438
81.9%
Space Separator 63
 
11.8%
Other Punctuation 24
 
4.5%
Uppercase Letter 8
 
1.5%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 17
 
3.9%
영 16
 
3.7%
김 15
 
3.4%
리 14
 
3.2%
기 13
 
3.0%
타 11
 
2.5%
은 9
 
2.1%
스 8
 
1.8%
홍 8
 
1.8%
현 7
 
1.6%
Other values (179) 320
73.1%
Uppercase Letter
ValueCountFrequency (%)
S 3
37.5%
K 2
25.0%
B 2
25.0%
D 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 22
91.7%
. 2
 
8.3%
Space Separator
ValueCountFrequency (%)
63
100.0%
Open Punctuation
ValueCountFrequency (%)
〈 1
100.0%
Close Punctuation
ValueCountFrequency (%)
〉 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 438
81.9%
Common 89
 
16.6%
Latin 8
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 17
 
3.9%
영 16
 
3.7%
김 15
 
3.4%
리 14
 
3.2%
기 13
 
3.0%
타 11
 
2.5%
은 9
 
2.1%
스 8
 
1.8%
홍 8
 
1.8%
현 7
 
1.6%
Other values (179) 320
73.1%
Common
ValueCountFrequency (%)
63
70.8%
, 22
 
24.7%
. 2
 
2.2%
〈 1
 
1.1%
〉 1
 
1.1%
Latin
ValueCountFrequency (%)
S 3
37.5%
K 2
25.0%
B 2
25.0%
D 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 438
81.9%
ASCII 95
 
17.8%
None 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
66.3%
, 22
 
23.2%
S 3
 
3.2%
K 2
 
2.1%
. 2
 
2.1%
B 2
 
2.1%
D 1
 
1.1%
Hangul
ValueCountFrequency (%)
이 17
 
3.9%
영 16
 
3.7%
김 15
 
3.4%
리 14
 
3.2%
기 13
 
3.0%
타 11
 
2.5%
은 9
 
2.1%
스 8
 
1.8%
홍 8
 
1.8%
현 7
 
1.6%
Other values (179) 320
73.1%
None
ValueCountFrequency (%)
〈 1
50.0%
〉 1
50.0%

등록일
Date

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2008-11-05 00:00:00
Maximum2022-09-20 00:00:00
2023-12-16T15:20:22.532533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:20:23.459668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

권수
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3
68 
5
32 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row5
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 68
68.0%
5 32
32.0%

Length

2023-12-16T15:20:24.155842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:20:25.015117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 68
68.0%
5 32
32.0%

누적대출
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.95
Minimum42
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-16T15:20:25.660059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile43
Q150
median62
Q398.25
95-th percentile145.05
Maximum206
Range164
Interquartile range (IQR)48.25

Descriptive statistics

Standard deviation35.237542
Coefficient of variation (CV)0.45792777
Kurtosis1.4694844
Mean76.95
Median Absolute Deviation (MAD)17
Skewness1.3092771
Sum7695
Variance1241.6843
MonotonicityDecreasing
2023-12-16T15:20:26.576752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44 7
 
7.0%
52 5
 
5.0%
43 4
 
4.0%
75 3
 
3.0%
57 3
 
3.0%
56 3
 
3.0%
55 3
 
3.0%
104 3
 
3.0%
54 3
 
3.0%
48 3
 
3.0%
Other values (49) 63
63.0%
ValueCountFrequency (%)
42 2
 
2.0%
43 4
4.0%
44 7
7.0%
45 2
 
2.0%
46 2
 
2.0%
47 2
 
2.0%
48 3
3.0%
49 2
 
2.0%
50 2
 
2.0%
51 1
 
1.0%
ValueCountFrequency (%)
206 1
1.0%
189 1
1.0%
152 1
1.0%
150 1
1.0%
146 1
1.0%
145 1
1.0%
144 1
1.0%
137 1
1.0%
134 1
1.0%
133 1
1.0%

Interactions

2023-12-16T15:20:05.268329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:20:04.500457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:20:05.686457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:20:04.962033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:20:27.185278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호컨텐츠번호컨텐츠명출판사저자등록일권수누적대출
번호1.0001.0001.0000.0830.6800.1470.4710.895
컨텐츠번호1.0001.0001.0001.0001.0001.0001.0001.000
컨텐츠명1.0001.0001.0001.0001.0001.0001.0001.000
출판사0.0831.0001.0001.0000.9720.7630.9710.000
저자0.6801.0001.0000.9721.0000.9981.0000.000
등록일0.1471.0001.0000.7630.9981.0000.9960.000
권수0.4711.0001.0000.9711.0000.9961.0000.000
누적대출0.8951.0001.0000.0000.0000.0000.0001.000
2023-12-16T15:20:28.004859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호누적대출권수
번호1.000-1.0000.346
누적대출-1.0001.0000.000
권수0.3460.0001.000

Missing values

2023-12-16T15:20:06.288905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:20:06.937685image/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

번호컨텐츠번호컨텐츠명출판사저자등록일권수누적대출
01110500213그리스 로마 신화 1마므레북홍은영2011-09-293206
12190600029여행의 이유문학동네김영하2019-02-015189
23090400034관계의 심리학경향미디어이철우2009-06-235152
34190202508아주 작은 습관의 힘비즈니스북스제임스 클리어2019-02-013150
45110500214그리스 로마 신화 2마므레북홍은영2011-09-293146
56A08020006꿈꾸는 다락방 - 생생하게 꿈꾸면 이루어진다국일미디어기타2008-11-055145
671911040391일 1페이지, 세상에서 가장 짧은 교양 수업 365위즈덤하우스데이비드 S. 키더, 노아 D. 오펜하임2020-05-193144
78200701496돈의 속성스노우폭스북스김승호2020-09-223137
89090900337유재석처럼 말하고 강호동처럼 행동하라두리미디어서병기2009-12-075134
910090600537바람의 딸 걸어서 지구 세 바퀴 반 1푸른숲한비야2009-12-075133
번호컨텐츠번호컨텐츠명출판사저자등록일권수누적대출
9091120401326우주에서 제일 쉬운 영문법잉크레오짱2012-12-05544
9192111000424실전에 바로 써먹는 주식투자 레슨 60원앤원북스박용선2011-12-22344
92930904001141% 다른 스피치비전코리아박정길2009-06-23544
9394A02100194영혼을 위한 닭고기 수프 1(주)도서출판푸른숲기타2008-11-05544
9495200604447성숙한 어른이 갖춰야 할 좋은 심리 습관다연류쉬안2020-06-01343
9596091100376한권으로 읽는 삼국지대교출판나관중2009-12-07543
9697A08100010왕사슴 아델칸휴먼비전기타2008-11-05543
9798A02100074사고력을 키우는 수학책을지외국어기타2008-11-05543
9899091000018몰입㈜알에이치코리아황농문2009-12-07542
99100090400128라이벌 한국사애플북스김갑동2009-12-28542