Overview

Dataset statistics

Number of variables5
Number of observations234
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory42.6 B

Variable types

Numeric2
Text3

Dataset

Description중소기업은행 도서실의 '16년도 3분기 신규 도서 DB 제공
Author중소기업은행
URLhttps://www.data.go.kr/data/15047843/fileData.do

Alerts

연번 has unique valuesUnique
서명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:03:18.016198
Analysis finished2023-12-12 22:03:19.221935
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct234
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.5
Minimum1
Maximum234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:03:19.322699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.65
Q159.25
median117.5
Q3175.75
95-th percentile222.35
Maximum234
Range233
Interquartile range (IQR)116.5

Descriptive statistics

Standard deviation67.694165
Coefficient of variation (CV)0.57612055
Kurtosis-1.2
Mean117.5
Median Absolute Deviation (MAD)58.5
Skewness0
Sum27495
Variance4582.5
MonotonicityStrictly increasing
2023-12-13T07:03:19.469520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
162 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
153 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
Other values (224) 224
95.7%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
234 1
0.4%
233 1
0.4%
232 1
0.4%
231 1
0.4%
230 1
0.4%
229 1
0.4%
228 1
0.4%
227 1
0.4%
226 1
0.4%
225 1
0.4%

서명
Text

UNIQUE 

Distinct234
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T07:03:19.761089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length112
Median length60
Mean length25.320513
Min length4

Characters and Unicode

Total characters5925
Distinct characters571
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique234 ?
Unique (%)100.0%

Sample

1st row(2013) 외부연구지원 공모논문집 : 통권 제10호
2nd row한ㆍ유라시아 주요국 산업협력을 위한 전략적 제휴방안 연구
3rd row기업구조조정 제도의 이해 : 워크아웃과 법정관리
4th row전자금융과 핀테크의 이해 : 금융사고와 범죄 방지 및 소비자보호를 중심으로
5th row대규모 기업집단 소유지배 괴리지표 동향 및 경제분석
ValueCountFrequency (%)
134
 
9.4%
2 10
 
0.7%
1 10
 
0.7%
of 9
 
0.6%
위한 9
 
0.6%
장편소설 7
 
0.5%
및 7
 
0.5%
파운데이션 7
 
0.5%
한 7
 
0.5%
않는 6
 
0.4%
Other values (988) 1218
85.5%
2023-12-13T07:03:20.254712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1190
 
20.1%
의 116
 
2.0%
: 102
 
1.7%
e 89
 
1.5%
t 77
 
1.3%
i 75
 
1.3%
o 74
 
1.2%
이 73
 
1.2%
a 73
 
1.2%
n 70
 
1.2%
Other values (561) 3986
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3436
58.0%
Space Separator 1190
 
20.1%
Lowercase Letter 815
 
13.8%
Other Punctuation 189
 
3.2%
Uppercase Letter 91
 
1.5%
Decimal Number 85
 
1.4%
Open Punctuation 43
 
0.7%
Close Punctuation 43
 
0.7%
Math Symbol 31
 
0.5%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 116
 
3.4%
이 73
 
2.1%
한 62
 
1.8%
는 59
 
1.7%
가 56
 
1.6%
지 48
 
1.4%
기 48
 
1.4%
사 47
 
1.4%
리 45
 
1.3%
제 42
 
1.2%
Other values (484) 2840
82.7%
Lowercase Letter
ValueCountFrequency (%)
e 89
10.9%
t 77
 
9.4%
i 75
 
9.2%
o 74
 
9.1%
a 73
 
9.0%
n 70
 
8.6%
r 49
 
6.0%
s 45
 
5.5%
l 29
 
3.6%
u 29
 
3.6%
Other values (15) 205
25.2%
Uppercase Letter
ValueCountFrequency (%)
I 10
 
11.0%
C 8
 
8.8%
K 8
 
8.8%
M 8
 
8.8%
D 6
 
6.6%
S 6
 
6.6%
A 6
 
6.6%
T 5
 
5.5%
P 5
 
5.5%
F 4
 
4.4%
Other values (13) 25
27.5%
Other Punctuation
ValueCountFrequency (%)
: 102
54.0%
. 33
 
17.5%
, 29
 
15.3%
· 8
 
4.2%
& 6
 
3.2%
? 4
 
2.1%
; 2
 
1.1%
! 2
 
1.1%
' 2
 
1.1%
% 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 24
28.2%
2 16
18.8%
0 14
16.5%
3 11
12.9%
5 9
 
10.6%
4 6
 
7.1%
7 3
 
3.5%
9 1
 
1.2%
6 1
 
1.2%
Math Symbol
ValueCountFrequency (%)
= 27
87.1%
+ 3
 
9.7%
~ 1
 
3.2%
Open Punctuation
ValueCountFrequency (%)
( 41
95.3%
[ 2
 
4.7%
Close Punctuation
ValueCountFrequency (%)
) 41
95.3%
] 2
 
4.7%
Space Separator
ValueCountFrequency (%)
1190
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3404
57.5%
Common 1582
26.7%
Latin 907
 
15.3%
Han 32
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 116
 
3.4%
이 73
 
2.1%
한 62
 
1.8%
는 59
 
1.7%
가 56
 
1.6%
지 48
 
1.4%
기 48
 
1.4%
사 47
 
1.4%
리 45
 
1.3%
제 42
 
1.2%
Other values (457) 2808
82.5%
Latin
ValueCountFrequency (%)
e 89
 
9.8%
t 77
 
8.5%
i 75
 
8.3%
o 74
 
8.2%
a 73
 
8.0%
n 70
 
7.7%
r 49
 
5.4%
s 45
 
5.0%
l 29
 
3.2%
u 29
 
3.2%
Other values (39) 297
32.7%
Common
ValueCountFrequency (%)
1190
75.2%
: 102
 
6.4%
( 41
 
2.6%
) 41
 
2.6%
. 33
 
2.1%
, 29
 
1.8%
= 27
 
1.7%
1 24
 
1.5%
2 16
 
1.0%
0 14
 
0.9%
Other values (18) 65
 
4.1%
Han
ValueCountFrequency (%)
法 2
 
6.2%
明 2
 
6.2%
見 2
 
6.2%
萬 2
 
6.2%
里 2
 
6.2%
白 1
 
3.1%
幹 1
 
3.1%
頭 1
 
3.1%
大 1
 
3.1%
商 1
 
3.1%
Other values (17) 17
53.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3393
57.3%
ASCII 2480
41.9%
CJK 32
 
0.5%
Compat Jamo 11
 
0.2%
None 8
 
0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1190
48.0%
: 102
 
4.1%
e 89
 
3.6%
t 77
 
3.1%
i 75
 
3.0%
o 74
 
3.0%
a 73
 
2.9%
n 70
 
2.8%
r 49
 
2.0%
s 45
 
1.8%
Other values (65) 636
25.6%
Hangul
ValueCountFrequency (%)
의 116
 
3.4%
이 73
 
2.2%
한 62
 
1.8%
는 59
 
1.7%
가 56
 
1.7%
지 48
 
1.4%
기 48
 
1.4%
사 47
 
1.4%
리 45
 
1.3%
제 42
 
1.2%
Other values (456) 2797
82.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
100.0%
None
ValueCountFrequency (%)
· 8
100.0%
CJK
ValueCountFrequency (%)
法 2
 
6.2%
明 2
 
6.2%
見 2
 
6.2%
萬 2
 
6.2%
里 2
 
6.2%
白 1
 
3.1%
幹 1
 
3.1%
頭 1
 
3.1%
大 1
 
3.1%
商 1
 
3.1%
Other values (17) 17
53.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

저자
Text

Distinct204
Distinct (%)87.6%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
2023-12-13T07:03:20.612209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length3
Mean length6.5193133
Min length2

Characters and Unicode

Total characters1519
Distinct characters259
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)79.8%

Sample

1st row예금보험공사
2nd row한홍열
3rd row김동환
4th row이충열
5th row김현종
ValueCountFrequency (%)
asimov 7
 
2.2%
issac 7
 
2.2%
한기찬 5
 
1.6%
mark 3
 
0.9%
eco 3
 
0.9%
umberto 3
 
0.9%
paris 3
 
0.9%
review 3
 
0.9%
김은덕 3
 
0.9%
paul 3
 
0.9%
Other values (260) 279
87.5%
2023-12-13T07:03:21.161994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
5.7%
a 69
 
4.5%
e 66
 
4.3%
, 60
 
3.9%
i 57
 
3.8%
s 50
 
3.3%
r 49
 
3.2%
l 48
 
3.2%
o 44
 
2.9%
n 37
 
2.4%
Other values (249) 953
62.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 620
40.8%
Other Letter 593
39.0%
Uppercase Letter 144
 
9.5%
Space Separator 86
 
5.7%
Other Punctuation 70
 
4.6%
Math Symbol 4
 
0.3%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 29
 
4.9%
김 25
 
4.2%
경 12
 
2.0%
성 12
 
2.0%
한 9
 
1.5%
현 9
 
1.5%
조 9
 
1.5%
신 9
 
1.5%
박 9
 
1.5%
재 9
 
1.5%
Other values (193) 461
77.7%
Lowercase Letter
ValueCountFrequency (%)
a 69
11.1%
e 66
10.6%
i 57
 
9.2%
s 50
 
8.1%
r 49
 
7.9%
l 48
 
7.7%
o 44
 
7.1%
n 37
 
6.0%
t 29
 
4.7%
c 20
 
3.2%
Other values (15) 151
24.4%
Uppercase Letter
ValueCountFrequency (%)
A 16
 
11.1%
E 13
 
9.0%
K 12
 
8.3%
R 11
 
7.6%
B 11
 
7.6%
M 11
 
7.6%
P 9
 
6.2%
S 7
 
4.9%
I 7
 
4.9%
D 6
 
4.2%
Other values (13) 41
28.5%
Other Punctuation
ValueCountFrequency (%)
, 60
85.7%
. 9
 
12.9%
? 1
 
1.4%
Math Symbol
ValueCountFrequency (%)
< 2
50.0%
> 2
50.0%
Decimal Number
ValueCountFrequency (%)
8 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 764
50.3%
Hangul 548
36.1%
Common 162
 
10.7%
Han 45
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 29
 
5.3%
김 25
 
4.6%
경 12
 
2.2%
성 12
 
2.2%
한 9
 
1.6%
현 9
 
1.6%
조 9
 
1.6%
신 9
 
1.6%
박 9
 
1.6%
재 9
 
1.6%
Other values (153) 416
75.9%
Latin
ValueCountFrequency (%)
a 69
 
9.0%
e 66
 
8.6%
i 57
 
7.5%
s 50
 
6.5%
r 49
 
6.4%
l 48
 
6.3%
o 44
 
5.8%
n 37
 
4.8%
t 29
 
3.8%
c 20
 
2.6%
Other values (38) 295
38.6%
Han
ValueCountFrequency (%)
藤 2
 
4.4%
村 2
 
4.4%
樹 2
 
4.4%
上 2
 
4.4%
春 2
 
4.4%
宋 1
 
2.2%
烈 1
 
2.2%
草 1
 
2.2%
沃 1
 
2.2%
龍 1
 
2.2%
Other values (30) 30
66.7%
Common
ValueCountFrequency (%)
86
53.1%
, 60
37.0%
. 9
 
5.6%
< 2
 
1.2%
> 2
 
1.2%
? 1
 
0.6%
8 1
 
0.6%
2 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 926
61.0%
Hangul 548
36.1%
CJK 43
 
2.8%
CJK Compat Ideographs 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
 
9.3%
a 69
 
7.5%
e 66
 
7.1%
, 60
 
6.5%
i 57
 
6.2%
s 50
 
5.4%
r 49
 
5.3%
l 48
 
5.2%
o 44
 
4.8%
n 37
 
4.0%
Other values (46) 360
38.9%
Hangul
ValueCountFrequency (%)
이 29
 
5.3%
김 25
 
4.6%
경 12
 
2.2%
성 12
 
2.2%
한 9
 
1.6%
현 9
 
1.6%
조 9
 
1.6%
신 9
 
1.6%
박 9
 
1.6%
재 9
 
1.6%
Other values (153) 416
75.9%
CJK
ValueCountFrequency (%)
藤 2
 
4.7%
村 2
 
4.7%
樹 2
 
4.7%
上 2
 
4.7%
春 2
 
4.7%
宋 1
 
2.3%
烈 1
 
2.3%
草 1
 
2.3%
沃 1
 
2.3%
瞬 1
 
2.3%
Other values (28) 28
65.1%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 1
50.0%
良 1
50.0%

출판사
Text

Distinct157
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T07:03:21.460098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length5.542735
Min length2

Characters and Unicode

Total characters1297
Distinct characters269
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)50.9%

Sample

1st row예금보험공사
2nd row대외경제정책연구원
3rd row한국금융연구원
4th row한국금융연구원
5th row한국경제연구원
ValueCountFrequency (%)
한국경제연구원 11
 
4.5%
황금가지:민음인 7
 
2.9%
김영사 7
 
2.9%
한국개발연구원 6
 
2.5%
대외경제정책연구원 5
 
2.1%
한빛미디어 5
 
2.1%
위키북스 4
 
1.6%
열린책들 4
 
1.6%
위즈덤하우스 4
 
1.6%
해냄 3
 
1.2%
Other values (153) 187
77.0%
2023-12-13T07:03:22.013888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 47
 
3.6%
한 39
 
3.0%
경 34
 
2.6%
사 34
 
2.6%
원 33
 
2.5%
북 33
 
2.5%
연 32
 
2.5%
구 31
 
2.4%
문 29
 
2.2%
국 29
 
2.2%
Other values (259) 956
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1202
92.7%
Other Punctuation 32
 
2.5%
Uppercase Letter 28
 
2.2%
Lowercase Letter 22
 
1.7%
Space Separator 9
 
0.7%
Decimal Number 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 47
 
3.9%
한 39
 
3.2%
경 34
 
2.8%
사 34
 
2.8%
원 33
 
2.7%
북 33
 
2.7%
연 32
 
2.7%
구 31
 
2.6%
문 29
 
2.4%
국 29
 
2.4%
Other values (225) 861
71.6%
Lowercase Letter
ValueCountFrequency (%)
o 6
27.3%
i 2
 
9.1%
e 2
 
9.1%
s 2
 
9.1%
n 2
 
9.1%
r 1
 
4.5%
a 1
 
4.5%
c 1
 
4.5%
m 1
 
4.5%
y 1
 
4.5%
Other values (3) 3
13.6%
Uppercase Letter
ValueCountFrequency (%)
K 5
17.9%
B 4
14.3%
I 3
10.7%
A 3
10.7%
S 3
10.7%
P 3
10.7%
T 2
 
7.1%
F 1
 
3.6%
J 1
 
3.6%
C 1
 
3.6%
Other values (2) 2
 
7.1%
Other Punctuation
ValueCountFrequency (%)
: 28
87.5%
. 2
 
6.2%
# 1
 
3.1%
& 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
1 1
25.0%
0 1
25.0%
3 1
25.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1187
91.5%
Latin 50
 
3.9%
Common 45
 
3.5%
Han 15
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 47
 
4.0%
한 39
 
3.3%
경 34
 
2.9%
사 34
 
2.9%
원 33
 
2.8%
북 33
 
2.8%
연 32
 
2.7%
구 31
 
2.6%
문 29
 
2.4%
국 29
 
2.4%
Other values (218) 846
71.3%
Latin
ValueCountFrequency (%)
o 6
 
12.0%
K 5
 
10.0%
B 4
 
8.0%
I 3
 
6.0%
A 3
 
6.0%
S 3
 
6.0%
P 3
 
6.0%
T 2
 
4.0%
i 2
 
4.0%
e 2
 
4.0%
Other values (15) 17
34.0%
Common
ValueCountFrequency (%)
: 28
62.2%
9
 
20.0%
. 2
 
4.4%
2 1
 
2.2%
# 1
 
2.2%
1 1
 
2.2%
& 1
 
2.2%
0 1
 
2.2%
3 1
 
2.2%
Han
ValueCountFrequency (%)
社 4
26.7%
文 4
26.7%
法 2
13.3%
弘 2
13.3%
事 1
 
6.7%
英 1
 
6.7%
博 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1187
91.5%
ASCII 95
 
7.3%
CJK 15
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 47
 
4.0%
한 39
 
3.3%
경 34
 
2.9%
사 34
 
2.9%
원 33
 
2.8%
북 33
 
2.8%
연 32
 
2.7%
구 31
 
2.6%
문 29
 
2.4%
국 29
 
2.4%
Other values (218) 846
71.3%
ASCII
ValueCountFrequency (%)
: 28
29.5%
9
 
9.5%
o 6
 
6.3%
K 5
 
5.3%
B 4
 
4.2%
I 3
 
3.2%
A 3
 
3.2%
S 3
 
3.2%
P 3
 
3.2%
. 2
 
2.1%
Other values (24) 29
30.5%
CJK
ValueCountFrequency (%)
社 4
26.7%
文 4
26.7%
法 2
13.3%
弘 2
13.3%
事 1
 
6.7%
英 1
 
6.7%
博 1
 
6.7%

출판년도
Real number (ℝ)

Distinct12
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.7692
Minimum1996
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:03:22.164050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1996
5-th percentile2009
Q12015
median2015
Q32016
95-th percentile2016
Maximum2016
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.3869625
Coefficient of variation (CV)0.0011847325
Kurtosis20.29742
Mean2014.7692
Median Absolute Deviation (MAD)1
Skewness-3.9100028
Sum471456
Variance5.69759
MonotonicityNot monotonic
2023-12-13T07:03:22.310678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2016 114
48.7%
2015 74
31.6%
2014 17
 
7.3%
2013 12
 
5.1%
2007 4
 
1.7%
2009 4
 
1.7%
2012 2
 
0.9%
2006 2
 
0.9%
2010 2
 
0.9%
2008 1
 
0.4%
Other values (2) 2
 
0.9%
ValueCountFrequency (%)
1996 1
 
0.4%
2004 1
 
0.4%
2006 2
 
0.9%
2007 4
 
1.7%
2008 1
 
0.4%
2009 4
 
1.7%
2010 2
 
0.9%
2012 2
 
0.9%
2013 12
5.1%
2014 17
7.3%
ValueCountFrequency (%)
2016 114
48.7%
2015 74
31.6%
2014 17
 
7.3%
2013 12
 
5.1%
2012 2
 
0.9%
2010 2
 
0.9%
2009 4
 
1.7%
2008 1
 
0.4%
2007 4
 
1.7%
2006 2
 
0.9%

Interactions

2023-12-13T07:03:18.788601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:03:18.610333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:03:18.909628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:03:18.692451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:03:22.418574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번출판년도
연번1.0000.272
출판년도0.2721.000
2023-12-13T07:03:22.517270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번출판년도
연번1.0000.018
출판년도0.0181.000

Missing values

2023-12-13T07:03:19.060779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:03:19.168891image/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

연번서명저자출판사출판년도
01(2013) 외부연구지원 공모논문집 : 통권 제10호예금보험공사예금보험공사2016
12한ㆍ유라시아 주요국 산업협력을 위한 전략적 제휴방안 연구한홍열대외경제정책연구원2015
23기업구조조정 제도의 이해 : 워크아웃과 법정관리김동환한국금융연구원2016
34전자금융과 핀테크의 이해 : 금융사고와 범죄 방지 및 소비자보호를 중심으로이충열한국금융연구원2016
45대규모 기업집단 소유지배 괴리지표 동향 및 경제분석김현종한국경제연구원2015
56미국 기준금리 인상에 따른 한국 제조업의 수출영향 전망 및 시사점차경수한국경제연구원2016
67세무조사의 경제적 영향과 제도개선 방향조경엽한국경제연구원2016
78규제개혁과제의 입법효율성 분석 및 경제활력 제고방안양금승한국경제연구원2016
89IMF의 한국경제 보고서 = A study on the economic development of Korea from the Perspetive of IMF. 1윤여봉KAIST 금융공학연구센터2016
910IMF의 한국경제 보고서 = A study on the economic development of Korea from the Perspetive of IMF. 2윤여봉KAIST 금융공학연구센터2016
연번서명저자출판사출판년도
224225숨결이 바람 될 때 : 서른여섯 젊은 의사의 마지막 순간Kalanithi, Paul흐름2016
225226(자신만만 세계여행) 캐나다 : Canada곽정란삼성2016
226227(알고리즘으로 배우는) 인공지능, 머신러닝, 딥러닝 입문김의중위키북스2016
227228목돈사회 : 대한민국은 어떻게 헬조선이 되었는가정우성에이콘2015
228229사업의 길이병욱프리이코노미북스:에프케이아이미디어2016
229230(대박땅꾼 전은규 훔쳐서라도 배워야 할) 부동산 투자 교과서 : 소액 편전은규한국경제신문i2016
230231나는 왜 괜찮은 아이디어가 없을까?오상진비즈니스북스2016
231232포트레이트 인 재즈 = Portrait in jazz村上春樹문학사상2013
232233(우리말 한글) 훈민정음 제자 원리이성진한솜미디어2015
233234한국 공기업의 이해이상철대영문화사2016