Overview

Dataset statistics

Number of variables7
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory60.6 B

Variable types

Numeric1
Text5
Categorical1

Dataset

Description대구광역시교육청 대구광역시교육청삼국유사군위도서관_인기도서목록(2024년 1월 삼국유사군위도서관 TOP50)
Author대구광역시교육청 대구광역시교육청삼국유사군위도서관
URLhttps://www.data.go.kr/data/15127146/fileData.do

Alerts

대출횟수 is highly imbalanced (59.8%)Imbalance
순위 has unique valuesUnique
등록번호 has unique valuesUnique
서명 has unique valuesUnique
청구기호 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:16:41.866731
Analysis finished2024-03-16 04:16:43.352889
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순위
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-16T13:16:43.495896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2024-03-16T13:16:43.778520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

등록번호
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-16T13:16:44.119990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters600
Distinct characters13
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

Unique50 ?
Unique (%)100.0%

Sample

1st rowEDA000135512
2nd rowEDA000135940
3rd rowEDA000134757
4th rowEDA000135240
5th rowEDA000135720
ValueCountFrequency (%)
eda000135512 1
 
2.0%
eda000135806 1
 
2.0%
eda000135145 1
 
2.0%
eda000135908 1
 
2.0%
eda000127359 1
 
2.0%
eda000127361 1
 
2.0%
eda000136014 1
 
2.0%
eda000134393 1
 
2.0%
eda000130237 1
 
2.0%
eda000130892 1
 
2.0%
Other values (40) 40
80.0%
2024-03-16T13:16:44.657274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 178
29.7%
1 58
 
9.7%
3 52
 
8.7%
E 50
 
8.3%
D 50
 
8.3%
A 50
 
8.3%
5 46
 
7.7%
2 26
 
4.3%
4 22
 
3.7%
7 18
 
3.0%
Other values (3) 50
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 450
75.0%
Uppercase Letter 150
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 178
39.6%
1 58
 
12.9%
3 52
 
11.6%
5 46
 
10.2%
2 26
 
5.8%
4 22
 
4.9%
7 18
 
4.0%
8 17
 
3.8%
6 17
 
3.8%
9 16
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
E 50
33.3%
D 50
33.3%
A 50
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 450
75.0%
Latin 150
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 178
39.6%
1 58
 
12.9%
3 52
 
11.6%
5 46
 
10.2%
2 26
 
5.8%
4 22
 
4.9%
7 18
 
4.0%
8 17
 
3.8%
6 17
 
3.8%
9 16
 
3.6%
Latin
ValueCountFrequency (%)
E 50
33.3%
D 50
33.3%
A 50
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 178
29.7%
1 58
 
9.7%
3 52
 
8.7%
E 50
 
8.3%
D 50
 
8.3%
A 50
 
8.3%
5 46
 
7.7%
2 26
 
4.3%
4 22
 
3.7%
7 18
 
3.0%
Other values (3) 50
 
8.3%

서명
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-16T13:16:45.553937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length39
Mean length27.22
Min length5

Characters and Unicode

Total characters1361
Distinct characters325
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row흔한남매. 14
2nd row의사 어벤저스 : 어린의 의학 동화. 15, 눈 질환, 보이는 게 전부는 아니야!
3rd row당뇨병·대사·내분비의 구조
4th row(흔한남매) 이무기 : 이해하면 무서운 이야기. 1
5th row(우리 아기 오감발달) 산타와 꼬마 요정 사운드북
ValueCountFrequency (%)
26
 
7.4%
2 10
 
2.8%
1 8
 
2.3%
흔한남매 6
 
1.7%
3 4
 
1.1%
친구들 2
 
0.6%
쓴 2
 
0.6%
go 2
 
0.6%
질환 2
 
0.6%
의사 2
 
0.6%
Other values (264) 288
81.8%
2024-03-16T13:16:46.358002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
 
22.8%
. 34
 
2.5%
의 31
 
2.3%
사 24
 
1.8%
한 22
 
1.6%
1 21
 
1.5%
는 21
 
1.5%
: 20
 
1.5%
이 19
 
1.4%
2 17
 
1.2%
Other values (315) 842
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 854
62.7%
Space Separator 310
 
22.8%
Other Punctuation 84
 
6.2%
Decimal Number 64
 
4.7%
Open Punctuation 14
 
1.0%
Close Punctuation 14
 
1.0%
Lowercase Letter 9
 
0.7%
Uppercase Letter 9
 
0.7%
Dash Punctuation 1
 
0.1%
Initial Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 31
 
3.6%
사 24
 
2.8%
한 22
 
2.6%
는 21
 
2.5%
이 19
 
2.2%
기 17
 
2.0%
법 16
 
1.9%
가 14
 
1.6%
하 11
 
1.3%
어 11
 
1.3%
Other values (280) 668
78.2%
Decimal Number
ValueCountFrequency (%)
1 21
32.8%
2 17
26.6%
3 8
 
12.5%
4 7
 
10.9%
0 5
 
7.8%
7 2
 
3.1%
5 1
 
1.6%
8 1
 
1.6%
9 1
 
1.6%
6 1
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
o 2
22.2%
e 2
22.2%
w 1
11.1%
f 1
11.1%
l 1
11.1%
n 1
11.1%
s 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
G 2
22.2%
B 2
22.2%
I 1
11.1%
M 1
11.1%
T 1
11.1%
S 1
11.1%
E 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 34
40.5%
: 20
23.8%
, 14
16.7%
· 10
 
11.9%
! 6
 
7.1%
Space Separator
ValueCountFrequency (%)
310
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 845
62.1%
Common 489
35.9%
Latin 18
 
1.3%
Han 9
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 31
 
3.7%
사 24
 
2.8%
한 22
 
2.6%
는 21
 
2.5%
이 19
 
2.2%
기 17
 
2.0%
법 16
 
1.9%
가 14
 
1.7%
하 11
 
1.3%
어 11
 
1.3%
Other values (271) 659
78.0%
Common
ValueCountFrequency (%)
310
63.4%
. 34
 
7.0%
1 21
 
4.3%
: 20
 
4.1%
2 17
 
3.5%
( 14
 
2.9%
, 14
 
2.9%
) 14
 
2.9%
· 10
 
2.0%
3 8
 
1.6%
Other values (11) 27
 
5.5%
Latin
ValueCountFrequency (%)
o 2
11.1%
G 2
11.1%
e 2
11.1%
B 2
11.1%
I 1
 
5.6%
M 1
 
5.6%
T 1
 
5.6%
w 1
 
5.6%
f 1
 
5.6%
l 1
 
5.6%
Other values (4) 4
22.2%
Han
ValueCountFrequency (%)
大 1
11.1%
來 1
11.1%
廷 1
11.1%
趙 1
11.1%
設 1
11.1%
小 1
11.1%
河 1
11.1%
秘 1
11.1%
法 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 845
62.1%
ASCII 495
36.4%
None 10
 
0.7%
CJK 9
 
0.7%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
62.6%
. 34
 
6.9%
1 21
 
4.2%
: 20
 
4.0%
2 17
 
3.4%
( 14
 
2.8%
, 14
 
2.8%
) 14
 
2.8%
3 8
 
1.6%
4 7
 
1.4%
Other values (22) 36
 
7.3%
Hangul
ValueCountFrequency (%)
의 31
 
3.7%
사 24
 
2.8%
한 22
 
2.6%
는 21
 
2.5%
이 19
 
2.2%
기 17
 
2.0%
법 16
 
1.9%
가 14
 
1.7%
하 11
 
1.3%
어 11
 
1.3%
Other values (271) 659
78.0%
None
ValueCountFrequency (%)
· 10
100.0%
CJK
ValueCountFrequency (%)
大 1
11.1%
來 1
11.1%
廷 1
11.1%
趙 1
11.1%
設 1
11.1%
小 1
11.1%
河 1
11.1%
秘 1
11.1%
法 1
11.1%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

저자
Text

Distinct48
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-16T13:16:46.826682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length12.98
Min length2

Characters and Unicode

Total characters649
Distinct characters162
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)92.0%

Sample

1st row흔한남매 원작 ; 백난도 글 ; 유난희 그림
2nd row 고희정 ; 조승연
3rd row오다와라 마사토 감수 ; 김병준 감역 ; 김선숙 옮김
4th row흔한남매 원작 ; 이종혁 글 ; 도니패밀리 그림
5th row샘 태플린 지음 ; 바이올레타 다비자 그림 ; 조남주 옮김
ValueCountFrequency (%)
32
 
15.8%
지음 24
 
11.9%
그림 14
 
6.9%
원작 11
 
5.4%
글 10
 
5.0%
흔한남매 7
 
3.5%
옮김 6
 
3.0%
파뿌리 2
 
1.0%
말이야와 2
 
1.0%
조승연 2
 
1.0%
Other values (85) 92
45.5%
2024-03-16T13:16:47.482686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
25.0%
; 32
 
4.9%
지 28
 
4.3%
음 25
 
3.9%
림 16
 
2.5%
그 15
 
2.3%
김 15
 
2.3%
이 13
 
2.0%
작 12
 
1.8%
원 11
 
1.7%
Other values (152) 320
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 443
68.3%
Space Separator 162
 
25.0%
Other Punctuation 37
 
5.7%
Uppercase Letter 3
 
0.5%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 28
 
6.3%
음 25
 
5.6%
림 16
 
3.6%
그 15
 
3.4%
김 15
 
3.4%
이 13
 
2.9%
작 12
 
2.7%
원 11
 
2.5%
글 11
 
2.5%
정 10
 
2.3%
Other values (140) 287
64.8%
Other Punctuation
ValueCountFrequency (%)
; 32
86.5%
, 2
 
5.4%
. 2
 
5.4%
· 1
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
B 1
33.3%
E 1
33.3%
Open Punctuation
ValueCountFrequency (%)
[ 1
50.0%
〈 1
50.0%
Close Punctuation
ValueCountFrequency (%)
] 1
50.0%
〉 1
50.0%
Space Separator
ValueCountFrequency (%)
162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 442
68.1%
Common 203
31.3%
Latin 3
 
0.5%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 28
 
6.3%
음 25
 
5.7%
림 16
 
3.6%
그 15
 
3.4%
김 15
 
3.4%
이 13
 
2.9%
작 12
 
2.7%
원 11
 
2.5%
글 11
 
2.5%
정 10
 
2.3%
Other values (139) 286
64.7%
Common
ValueCountFrequency (%)
162
79.8%
; 32
 
15.8%
, 2
 
1.0%
. 2
 
1.0%
[ 1
 
0.5%
] 1
 
0.5%
· 1
 
0.5%
〉 1
 
0.5%
〈 1
 
0.5%
Latin
ValueCountFrequency (%)
S 1
33.3%
B 1
33.3%
E 1
33.3%
Han
ValueCountFrequency (%)
著 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 442
68.1%
ASCII 203
31.3%
None 3
 
0.5%
CJK 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
79.8%
; 32
 
15.8%
, 2
 
1.0%
. 2
 
1.0%
[ 1
 
0.5%
] 1
 
0.5%
S 1
 
0.5%
B 1
 
0.5%
E 1
 
0.5%
Hangul
ValueCountFrequency (%)
지 28
 
6.3%
음 25
 
5.7%
림 16
 
3.6%
그 15
 
3.4%
김 15
 
3.4%
이 13
 
2.9%
작 12
 
2.7%
원 11
 
2.5%
글 11
 
2.5%
정 10
 
2.3%
Other values (139) 286
64.7%
None
ValueCountFrequency (%)
· 1
33.3%
〉 1
33.3%
〈 1
33.3%
CJK
ValueCountFrequency (%)
著 1
100.0%

발행자
Text

Distinct40
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-16T13:16:47.782224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length4.4
Min length2

Characters and Unicode

Total characters220
Distinct characters102
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)62.0%

Sample

1st row미래엔
2nd row가나
3rd rowBM성안당
4th row미래엔아이세움
5th rowUsborne Korea
ValueCountFrequency (%)
아이세움 3
 
5.6%
퀘스트 2
 
3.7%
아울북 2
 
3.7%
미래엔 2
 
3.7%
법문북스 2
 
3.7%
겜툰 2
 
3.7%
더 2
 
3.7%
해냄 2
 
3.7%
가나 2
 
3.7%
주니어김영사 2
 
3.7%
Other values (33) 33
61.1%
2024-03-16T13:16:48.372299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 12
 
5.5%
아 8
 
3.6%
북 8
 
3.6%
사 8
 
3.6%
이 7
 
3.2%
어 5
 
2.3%
산 5
 
2.3%
다 5
 
2.3%
세 5
 
2.3%
움 5
 
2.3%
Other values (92) 152
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 190
86.4%
Lowercase Letter 16
 
7.3%
Uppercase Letter 6
 
2.7%
Space Separator 4
 
1.8%
Other Punctuation 2
 
0.9%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 12
 
6.3%
아 8
 
4.2%
북 8
 
4.2%
사 8
 
4.2%
이 7
 
3.7%
어 5
 
2.6%
산 5
 
2.6%
다 5
 
2.6%
세 5
 
2.6%
움 5
 
2.6%
Other values (74) 122
64.2%
Lowercase Letter
ValueCountFrequency (%)
r 3
18.8%
e 3
18.8%
i 2
12.5%
a 2
12.5%
n 2
12.5%
o 2
12.5%
s 1
 
6.2%
b 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
M 2
33.3%
N 1
16.7%
U 1
16.7%
K 1
16.7%
B 1
16.7%
Other Punctuation
ValueCountFrequency (%)
; 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 190
86.4%
Latin 22
 
10.0%
Common 8
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 12
 
6.3%
아 8
 
4.2%
북 8
 
4.2%
사 8
 
4.2%
이 7
 
3.7%
어 5
 
2.6%
산 5
 
2.6%
다 5
 
2.6%
세 5
 
2.6%
움 5
 
2.6%
Other values (74) 122
64.2%
Latin
ValueCountFrequency (%)
r 3
13.6%
e 3
13.6%
i 2
9.1%
a 2
9.1%
M 2
9.1%
n 2
9.1%
o 2
9.1%
N 1
 
4.5%
U 1
 
4.5%
s 1
 
4.5%
Other values (3) 3
13.6%
Common
ValueCountFrequency (%)
4
50.0%
; 1
 
12.5%
( 1
 
12.5%
) 1
 
12.5%
· 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 190
86.4%
ASCII 29
 
13.2%
None 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 12
 
6.3%
아 8
 
4.2%
북 8
 
4.2%
사 8
 
4.2%
이 7
 
3.7%
어 5
 
2.6%
산 5
 
2.6%
다 5
 
2.6%
세 5
 
2.6%
움 5
 
2.6%
Other values (74) 122
64.2%
ASCII
ValueCountFrequency (%)
4
13.8%
r 3
10.3%
e 3
10.3%
i 2
 
6.9%
a 2
 
6.9%
M 2
 
6.9%
n 2
 
6.9%
o 2
 
6.9%
; 1
 
3.4%
( 1
 
3.4%
Other values (7) 7
24.1%
None
ValueCountFrequency (%)
· 1
100.0%

청구기호
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-16T13:16:48.678960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length12.16
Min length8

Characters and Unicode

Total characters608
Distinct characters58
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row아 813.8-흔91ㅎ-14
2nd row아 510.4-고98ㅇ-15
3rd row513.46-오221ㄷ
4th row아 813.7-흔91ㅇ-1
5th row유 375.1-태848ㅅ
ValueCountFrequency (%)
아 24
32.0%
375.1-태848ㅅ 2
 
2.7%
364-김73ㅎ 1
 
1.3%
193-샌223ㅈ 1
 
1.3%
843-시219ㅁ-1 1
 
1.3%
813.8-파47ㅍ-1 1
 
1.3%
813.8-파47ㅍ-3 1
 
1.3%
813.8-캐239ㅋ-2 1
 
1.3%
813.8-흔91ㅎ-2 1
 
1.3%
813.8-흔91ㅎ-11 1
 
1.3%
Other values (41) 41
54.7%
2024-03-16T13:16:49.331146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 75
12.3%
3 60
 
9.9%
1 57
 
9.4%
8 45
 
7.4%
4 39
 
6.4%
. 37
 
6.1%
7 32
 
5.3%
5 26
 
4.3%
2 25
 
4.1%
25
 
4.1%
Other values (48) 187
30.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 345
56.7%
Other Letter 125
 
20.6%
Dash Punctuation 75
 
12.3%
Other Punctuation 37
 
6.1%
Space Separator 25
 
4.1%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 24
19.2%
ㅎ 7
 
5.6%
흔 7
 
5.6%
ㅅ 6
 
4.8%
이 6
 
4.8%
ㅇ 6
 
4.8%
ㅁ 5
 
4.0%
ㄱ 5
 
4.0%
ㅈ 4
 
3.2%
조 4
 
3.2%
Other values (34) 51
40.8%
Decimal Number
ValueCountFrequency (%)
3 60
17.4%
1 57
16.5%
8 45
13.0%
4 39
11.3%
7 32
9.3%
5 26
7.5%
2 25
7.2%
6 24
 
7.0%
9 23
 
6.7%
0 14
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Other Punctuation
ValueCountFrequency (%)
. 37
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 483
79.4%
Hangul 125
 
20.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 24
19.2%
ㅎ 7
 
5.6%
흔 7
 
5.6%
ㅅ 6
 
4.8%
이 6
 
4.8%
ㅇ 6
 
4.8%
ㅁ 5
 
4.0%
ㄱ 5
 
4.0%
ㅈ 4
 
3.2%
조 4
 
3.2%
Other values (34) 51
40.8%
Common
ValueCountFrequency (%)
- 75
15.5%
3 60
12.4%
1 57
11.8%
8 45
9.3%
4 39
8.1%
. 37
7.7%
7 32
6.6%
5 26
 
5.4%
2 25
 
5.2%
25
 
5.2%
Other values (4) 62
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 483
79.4%
Hangul 75
 
12.3%
Compat Jamo 50
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 75
15.5%
3 60
12.4%
1 57
11.8%
8 45
9.3%
4 39
8.1%
. 37
7.7%
7 32
6.6%
5 26
 
5.4%
2 25
 
5.2%
25
 
5.2%
Other values (4) 62
12.8%
Hangul
ValueCountFrequency (%)
아 24
32.0%
흔 7
 
9.3%
이 6
 
8.0%
조 4
 
5.3%
박 2
 
2.7%
고 2
 
2.7%
김 2
 
2.7%
신 2
 
2.7%
말 2
 
2.7%
파 2
 
2.7%
Other values (19) 22
29.3%
Compat Jamo
ValueCountFrequency (%)
ㅎ 7
14.0%
ㅅ 6
12.0%
ㅇ 6
12.0%
ㅁ 5
10.0%
ㄱ 5
10.0%
ㅈ 4
8.0%
ㄴ 4
8.0%
ㅂ 3
6.0%
ㄷ 3
6.0%
ㅍ 2
 
4.0%
Other values (5) 5
10.0%

대출횟수
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
3
42 
2
6 
5
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)4.0%

Sample

1st row5
2nd row4
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 42
84.0%
2 6
 
12.0%
5 1
 
2.0%
4 1
 
2.0%

Length

2024-03-16T13:16:49.646751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:16:49.805816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 42
84.0%
2 6
 
12.0%
5 1
 
2.0%
4 1
 
2.0%

Interactions

2024-03-16T13:16:42.933275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:16:49.909107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위등록번호서명저자발행자청구기호대출횟수
순위1.0001.0001.0000.9690.8811.0000.721
등록번호1.0001.0001.0001.0001.0001.0001.000
서명1.0001.0001.0001.0001.0001.0001.000
저자0.9691.0001.0001.0000.9961.0001.000
발행자0.8811.0001.0000.9961.0001.0000.000
청구기호1.0001.0001.0001.0001.0001.0001.000
대출횟수0.7211.0001.0001.0000.0001.0001.000
2024-03-16T13:16:50.139420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위대출횟수
순위1.0000.487
대출횟수0.4871.000

Missing values

2024-03-16T13:16:43.099290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:16:43.277609image/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

순위등록번호서명저자발행자청구기호대출횟수
01EDA000135512흔한남매. 14흔한남매 원작 ; 백난도 글 ; 유난희 그림미래엔아 813.8-흔91ㅎ-145
12EDA000135940의사 어벤저스 : 어린의 의학 동화. 15, 눈 질환, 보이는 게 전부는 아니야!고희정 ; 조승연가나아 510.4-고98ㅇ-154
23EDA000134757당뇨병·대사·내분비의 구조오다와라 마사토 감수 ; 김병준 감역 ; 김선숙 옮김BM성안당513.46-오221ㄷ3
34EDA000135240(흔한남매) 이무기 : 이해하면 무서운 이야기. 1흔한남매 원작 ; 이종혁 글 ; 도니패밀리 그림미래엔아이세움아 813.7-흔91ㅇ-13
45EDA000135720(우리 아기 오감발달) 산타와 꼬마 요정 사운드북샘 태플린 지음 ; 바이올레타 다비자 그림 ; 조남주 옮김Usborne Korea유 375.1-태848ㅅ3
56EDA000123966(흔한남매) 안 흔한 일기 . 3. 3흔한남매 원작MireaN·아이세움아 816.7-흔91ㅇ-33
67EDA000135845부동산 경매 무작정 따라하기이현정 지음길벗367.564-이94ㅂ3
78EDA000097309(EBS 다큐프라임) 자본주의 : 금융·소비·돈에 관한 33가지 비밀EBS〈자본주의〉제작팀 지음.가나출판사322.01-이49ㅈ3
89EDA000135892그리스 로마 신화 34박시연 지음 ; ; 최우빈 그림아울북아 219.21-불849ㄱ-343
910EDA000135840(사례중심 self) 지급명령신청서·이의신청서 작성장태동 지음남산367.5-장832ㅈ3
순위등록번호서명저자발행자청구기호대출횟수
4041EDA000135694대한민국에서 가장 쉽게 쓴 민법책 : 번호사가 알려주는, 민법으로 바라보는 세상 이야기오수현 지음시원북스365-오57ㄷ3
4142EDA000135683겸손한 공감 : 정신건강을 돌보는 이의 속 깊은 사람 탐구김병수 지음더 퀘스트185.3-김44ㄱ3
4243EDA000130245법정의 고수 : 신 변호사의 법조 인사이드 스토리신주영 지음솔(솔출판사)360.04-신77ㅂ3
4344EDA000136120뉴스 영어의 결정적 심화 표현들박종홍 지음사람in747-박75ㄴ3
4445EDA000135162수상한 이웃집 시노다. 1, 똑똑! 옆집 여우인데요도미야스 요코 글 ; 오바 켄야 그림 ; 송지현 옮김다산어린이;다산북스아 833.8-도39ㅅ-12
4546EDA000135155빨간내복야코. 1빨간내복야코 원작 ; 서후 지음샌드박스스토리 키즈아 813.8-빨11ㅃ-12
4647EDA000135024놓지 마 과학!. 18, 악마견의 숨겨진 진실신태훈,나승훈 [공]글·그림위즈덤하우스아 400-신832ㄴ-182
4748EDA000135154빗자루 타고 붕붕붕줄리아 도널드슨 지음 ; 악셀 셰플러 그림 ; 노은정 옮김비룡소아 843-도213ㅂ2
4849EDA000135145문어 팬티수지 시니어 글 ; 클레어 파월 그림 ; 한미숙 옮김천개의바람아 843-시219ㅁ-12
4950EDA000135025달콤 짭짤 코파츄 : 다영 과학동화. 1, 바람마을의 생태계를 지켜라다영 지음 ; 밤코 그림창비아 400-다64ㄷ-12