Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory60.3 B

Variable types

Numeric3
Text1
Categorical3

Dataset

Description원신흥도서관의 1년간 대출실적을 기준으로 선정한 베스트 도서대출 100선(순위, 도서명, 저자, 출판사, 출판년, 대출횟수)
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15085837/fileData.do

Alerts

순위 is highly overall correlated with 대출건수High correlation
발행년 is highly overall correlated with 저자 and 1 other fieldsHigh correlation
대출건수 is highly overall correlated with 순위High correlation
저자 is highly overall correlated with 발행년 and 1 other fieldsHigh correlation
발행처 is highly overall correlated with 발행년 and 1 other fieldsHigh correlation
순위 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:31:55.201034
Analysis finished2023-12-12 18:31:57.008713
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순위
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
2023-12-13T03:31:57.110196image/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
2023-12-13T03:31:57.325382image/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%

서명
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-13T03:31:57.607656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length42
Mean length30.56
Min length8

Characters and Unicode

Total characters3056
Distinct characters328
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row(신비아파트)고스트 탐험대 . 1 , 서유럽 5개국
2nd row내일은 발명왕 : 본격 대결 과학발명 만화 . 14 , 상상력 발명 게임
3rd row쿠키런 서바이벌 대작전 : 안전상식 학습만화 . 11 , 전기편
4th row(백종원의) 도전 요리왕 . 3 , 이탈리아
5th row(신비아파트) 한자귀신 . 11 , 악귀의 노래
ValueCountFrequency (%)
203
 
23.0%
쿠키런 19
 
2.2%
신비아파트 12
 
1.4%
서바이벌 12
 
1.4%
대작전 12
 
1.4%
학습만화 12
 
1.4%
메이플스토리 11
 
1.2%
수학도둑 11
 
1.2%
코믹 11
 
1.2%
편 10
 
1.1%
Other values (313) 570
64.6%
2023-12-13T03:31:58.082011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
786
25.7%
. 91
 
3.0%
, 76
 
2.5%
( 56
 
1.8%
) 56
 
1.8%
신 50
 
1.6%
이 45
 
1.5%
의 42
 
1.4%
대 41
 
1.3%
1 41
 
1.3%
Other values (318) 1772
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1721
56.3%
Space Separator 786
25.7%
Other Punctuation 222
 
7.3%
Decimal Number 153
 
5.0%
Open Punctuation 56
 
1.8%
Close Punctuation 56
 
1.8%
Lowercase Letter 42
 
1.4%
Uppercase Letter 17
 
0.6%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 50
 
2.9%
이 45
 
2.6%
의 42
 
2.4%
대 41
 
2.4%
학 40
 
2.3%
리 34
 
2.0%
아 34
 
2.0%
스 34
 
2.0%
한 31
 
1.8%
전 30
 
1.7%
Other values (278) 1340
77.9%
Lowercase Letter
ValueCountFrequency (%)
o 12
28.6%
a 5
11.9%
r 5
11.9%
i 3
 
7.1%
e 3
 
7.1%
l 2
 
4.8%
t 2
 
4.8%
s 2
 
4.8%
u 2
 
4.8%
n 2
 
4.8%
Other values (3) 4
 
9.5%
Decimal Number
ValueCountFrequency (%)
1 41
26.8%
4 19
12.4%
2 17
11.1%
3 17
11.1%
7 16
 
10.5%
6 11
 
7.2%
0 11
 
7.2%
8 8
 
5.2%
5 8
 
5.2%
9 5
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
G 8
47.1%
X 3
 
17.6%
T 2
 
11.8%
P 1
 
5.9%
H 1
 
5.9%
A 1
 
5.9%
K 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 91
41.0%
, 76
34.2%
: 36
 
16.2%
! 16
 
7.2%
＆ 2
 
0.9%
· 1
 
0.5%
Space Separator
ValueCountFrequency (%)
786
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1712
56.0%
Common 1276
41.8%
Latin 59
 
1.9%
Han 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 50
 
2.9%
이 45
 
2.6%
의 42
 
2.5%
대 41
 
2.4%
학 40
 
2.3%
리 34
 
2.0%
아 34
 
2.0%
스 34
 
2.0%
한 31
 
1.8%
전 30
 
1.8%
Other values (269) 1331
77.7%
Common
ValueCountFrequency (%)
786
61.6%
. 91
 
7.1%
, 76
 
6.0%
( 56
 
4.4%
) 56
 
4.4%
1 41
 
3.2%
: 36
 
2.8%
4 19
 
1.5%
2 17
 
1.3%
3 17
 
1.3%
Other values (10) 81
 
6.3%
Latin
ValueCountFrequency (%)
o 12
20.3%
G 8
13.6%
a 5
 
8.5%
r 5
 
8.5%
i 3
 
5.1%
X 3
 
5.1%
e 3
 
5.1%
l 2
 
3.4%
t 2
 
3.4%
s 2
 
3.4%
Other values (10) 14
23.7%
Han
ValueCountFrequency (%)
小 1
11.1%
說 1
11.1%
河 1
11.1%
大 1
11.1%
來 1
11.1%
夜 1
11.1%
廷 1
11.1%
趙 1
11.1%
善 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1712
56.0%
ASCII 1332
43.6%
CJK 9
 
0.3%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
786
59.0%
. 91
 
6.8%
, 76
 
5.7%
( 56
 
4.2%
) 56
 
4.2%
1 41
 
3.1%
: 36
 
2.7%
4 19
 
1.4%
2 17
 
1.3%
3 17
 
1.3%
Other values (28) 137
 
10.3%
Hangul
ValueCountFrequency (%)
신 50
 
2.9%
이 45
 
2.6%
의 42
 
2.5%
대 41
 
2.4%
학 40
 
2.3%
리 34
 
2.0%
아 34
 
2.0%
스 34
 
2.0%
한 31
 
1.8%
전 30
 
1.8%
Other values (269) 1331
77.7%
None
ValueCountFrequency (%)
＆ 2
66.7%
· 1
33.3%
CJK
ValueCountFrequency (%)
小 1
11.1%
說 1
11.1%
河 1
11.1%
大 1
11.1%
來 1
11.1%
夜 1
11.1%
廷 1
11.1%
趙 1
11.1%
善 1
11.1%

권호기호
Categorical

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
v.1
7 
v.3
 
6
v.4
 
6
v.2
 
6
v.6
 
6
Other values (38)
69 

Length

Max length4
Median length4
Mean length3.54
Min length3

Unique

Unique24 ?
Unique (%)24.0%

Sample

1st rowv.1
2nd rowv.14
3rd rowv.11
4th rowv.3
5th rowv.11

Common Values

ValueCountFrequency (%)
v.1 7
 
7.0%
v.3 6
 
6.0%
v.4 6
 
6.0%
v.2 6
 
6.0%
v.6 6
 
6.0%
v.11 5
 
5.0%
v.8 5
 
5.0%
v.17 4
 
4.0%
v.7 4
 
4.0%
v.13 4
 
4.0%
Other values (33) 47
47.0%

Length

2023-12-13T03:31:58.260137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
v.1 7
 
7.0%
v.4 6
 
6.0%
v.2 6
 
6.0%
v.6 6
 
6.0%
v.3 6
 
6.0%
v.11 5
 
5.0%
v.8 5
 
5.0%
v.17 4
 
4.0%
v.7 4
 
4.0%
v.13 4
 
4.0%
Other values (33) 47
47.0%

저자
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
김강현
18 
송도수
18 
임우영
 
5
백종원
 
4
김기수
 
4
Other values (31)
51 

Length

Max length11
Median length3
Mean length3.46
Min length3

Unique

Unique18 ?
Unique (%)18.0%

Sample

1st row임우영
2nd row곰돌이 co
3rd row김강현
4th row백종원
5th row김강현

Common Values

ValueCountFrequency (%)
김강현 18
18.0%
송도수 18
18.0%
임우영 5
 
5.0%
백종원 4
 
4.0%
김기수 4
 
4.0%
곰돌이 co 4
 
4.0%
흔한남매 4
 
4.0%
김미영 4
 
4.0%
신태훈 3
 
3.0%
이봉기 2
 
2.0%
Other values (26) 34
34.0%

Length

2023-12-13T03:31:58.417147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김강현 18
16.5%
송도수 18
16.5%
임우영 5
 
4.6%
백종원 4
 
3.7%
김기수 4
 
3.7%
곰돌이 4
 
3.7%
co 4
 
3.7%
흔한남매 4
 
3.7%
김미영 4
 
3.7%
신태훈 3
 
2.8%
Other values (32) 41
37.6%

발행처
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울문화사
48 
아이세움
8 
아울북
7 
위즈덤하우스
6 
재미북스
6 
Other values (13)
25 

Length

Max length12
Median length5
Mean length4.79
Min length2

Unique

Unique7 ?
Unique (%)7.0%

Sample

1st row서울문화사
2nd row아이세움
3rd row서울문화사
4th row위즈덤하우스
5th row서울문화사

Common Values

ValueCountFrequency (%)
서울문화사 48
48.0%
아이세움 8
 
8.0%
아울북 7
 
7.0%
위즈덤하우스 6
 
6.0%
재미북스 6
 
6.0%
고릴라박스 5
 
5.0%
미래엔 4
 
4.0%
주니어김영사 3
 
3.0%
대원키즈 2
 
2.0%
메가스터디 2
 
2.0%
Other values (8) 9
 
9.0%

Length

2023-12-13T03:31:58.588010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울문화사 48
46.6%
아이세움 9
 
8.7%
아울북 8
 
7.8%
위즈덤하우스 7
 
6.8%
재미북스 6
 
5.8%
고릴라박스 5
 
4.9%
미래엔 5
 
4.9%
주니어김영사 3
 
2.9%
학산문화사 2
 
1.9%
대원키즈 2
 
1.9%
Other values (7) 8
 
7.8%

발행년
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.51
Minimum2003
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T03:31:58.732889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2015
Q12018
median2019
Q32020
95-th percentile2020.05
Maximum2021
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3202882
Coefficient of variation (CV)0.0011495054
Kurtosis23.321736
Mean2018.51
Median Absolute Deviation (MAD)1
Skewness-4.1071931
Sum201851
Variance5.3837374
MonotonicityNot monotonic
2023-12-13T03:31:58.908975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2018 30
30.0%
2020 28
28.0%
2019 25
25.0%
2017 5
 
5.0%
2021 5
 
5.0%
2015 3
 
3.0%
2014 1
 
1.0%
2016 1
 
1.0%
2008 1
 
1.0%
2003 1
 
1.0%
ValueCountFrequency (%)
2003 1
 
1.0%
2008 1
 
1.0%
2014 1
 
1.0%
2015 3
 
3.0%
2016 1
 
1.0%
2017 5
 
5.0%
2018 30
30.0%
2019 25
25.0%
2020 28
28.0%
2021 5
 
5.0%
ValueCountFrequency (%)
2021 5
 
5.0%
2020 28
28.0%
2019 25
25.0%
2018 30
30.0%
2017 5
 
5.0%
2016 1
 
1.0%
2015 3
 
3.0%
2014 1
 
1.0%
2008 1
 
1.0%
2003 1
 
1.0%

대출건수
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.41
Minimum32
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T03:31:59.059115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile33
Q133
median34
Q335
95-th percentile37.05
Maximum41
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6702688
Coefficient of variation (CV)0.048540216
Kurtosis2.3236803
Mean34.41
Median Absolute Deviation (MAD)1
Skewness1.4342297
Sum3441
Variance2.789798
MonotonicityDecreasing
2023-12-13T03:31:59.195416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
33 37
37.0%
34 27
27.0%
35 12
 
12.0%
36 11
 
11.0%
37 7
 
7.0%
38 3
 
3.0%
41 1
 
1.0%
40 1
 
1.0%
32 1
 
1.0%
ValueCountFrequency (%)
32 1
 
1.0%
33 37
37.0%
34 27
27.0%
35 12
 
12.0%
36 11
 
11.0%
37 7
 
7.0%
38 3
 
3.0%
40 1
 
1.0%
41 1
 
1.0%
ValueCountFrequency (%)
41 1
 
1.0%
40 1
 
1.0%
38 3
 
3.0%
37 7
 
7.0%
36 11
 
11.0%
35 12
 
12.0%
34 27
27.0%
33 37
37.0%
32 1
 
1.0%

Interactions

2023-12-13T03:31:56.465045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.796225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.083862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.548692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.879666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.215194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.671822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.988608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.366779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:31:59.286622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위서명권호기호저자발행처발행년대출건수
순위1.0000.9400.4180.1560.2610.0000.828
서명0.9401.0001.0000.9981.0001.0000.887
권호기호0.4181.0001.0000.0000.0000.0000.000
저자0.1560.9980.0001.0000.9970.9170.000
발행처0.2611.0000.0000.9971.0000.7560.000
발행년0.0001.0000.0000.9170.7561.0000.417
대출건수0.8280.8870.0000.0000.0000.4171.000
2023-12-13T03:31:59.406291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권호기호발행처저자
권호기호1.0000.0000.000
발행처0.0001.0000.761
저자0.0000.7611.000
2023-12-13T03:31:59.512205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위발행년대출건수권호기호저자발행처
순위1.0000.086-0.9620.1050.0000.088
발행년0.0861.000-0.0940.0000.6110.595
대출건수-0.962-0.0941.0000.0000.0000.000
권호기호0.1050.0000.0001.0000.0000.000
저자0.0000.6110.0000.0001.0000.761
발행처0.0880.5950.0000.0000.7611.000

Missing values

2023-12-13T03:31:56.790847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:31:56.948331image/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

순위서명권호기호저자발행처발행년대출건수
01(신비아파트)고스트 탐험대 . 1 , 서유럽 5개국v.1임우영서울문화사201741
12내일은 발명왕 : 본격 대결 과학발명 만화 . 14 , 상상력 발명 게임v.14곰돌이 co아이세움201540
23쿠키런 서바이벌 대작전 : 안전상식 학습만화 . 11 , 전기편v.11김강현서울문화사201838
34(백종원의) 도전 요리왕 . 3 , 이탈리아v.3백종원위즈덤하우스201938
45(신비아파트) 한자귀신 . 11 , 악귀의 노래v.11김강현서울문화사202038
56(허팝) 과학 파워 . 5 , 소금 용암＆신발 자전거v.5유경원서울문화사201937
67(코믹 메이플스토리) 수학도둑 : 종합편 . 80v.80송도수서울문화사202037
78쿠키런 서바이벌 대작전 : 안전상식 학습만화 . 28 , 최후의 생존자편v.28김강현서울문화사201937
89쿠키런 서바이벌 대작전 : 안전상식 학습만화 . 9 , 지진 편v.9김강현서울문화사201837
910(신비아파트) 한자 귀신 . 3 , 새로운 봉인 카드v.3김기수서울문화사201937
순위서명권호기호저자발행처발행년대출건수
9091(코믹 메이플스토리) 수학도둑 . 46v.46송도수서울문화사201733
9192(신비아파트)고스트 탐험대 . 9 , 아프리카 4개국v.9임우영서울문화사201933
9293(신비아파트 고스트볼 더블X) 수상한 의뢰 . 2v.2서울문화사 . 편집부서울문화사202033
9394쿠키런 어드벤처 : 쿠키들의 신나는 세계여행 . 14 , 토론토(Toronto)v.14송도수서울문화사201933
9495(신비아파트)한자귀신 . 6 , 명령의 힘v.6김강현서울문화사201933
9596쿠키런 서바이벌 대작전 : 안전상식 학습만화 . 27 , 로봇의 심장편v.27김강현서울문화사201933
9697(코믹 메이플스토리) 수학도둑 : 종합편 . 65v.65송도수서울문화사201833
9798(이상한 과자 가게) 전천당 . 8v.8히로시마 레이코길벗스쿨202033
9899(빈대 가족의) 덜렁이는 유튜브 스타v.35임창호재미북스201933
99100신비아파트 교과서 위인 100 . 4v.4임우영서울문화사202032