Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory52.3 B

Variable types

Numeric3
Text2
Categorical1

Dataset

Description대전광역시 유성구 관평도서관의 대출실적을 기준으로 선정한 베스트 도서대출 100선에 대한 데이터로 순위, 도서명, 저자, 출판사, 출판년, 대출횟수 등의 항목을 제공합니다.
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15053379/fileData.do

Alerts

순위 is highly overall correlated with 대출건수High correlation
대출건수 is highly overall correlated with 순위High correlation
순위 has unique valuesUnique
서명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:14:10.206767
Analysis finished2023-12-12 15:14:11.896926
Duration1.69 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
2023-12-13T00:14:11.970837image/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
2023-12-13T00:14:12.108822image/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

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-13T00:14:12.410949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length35.5
Mean length20.54
Min length3

Characters and Unicode

Total characters2054
Distinct characters328
Distinct categories9 ?
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 row추리 천재 엉덩이 탐정 . 1 보라 부인의 암호 사건
2nd row추리 천재 엉덩이 탐정 .4 괴도 VS 탐정 대결 사건
3rd row추리 천재 엉덩이 탐정 .2 어둠 속으로 사라진 거인 사건
4th row(추리 천재) 엉덩이 탐정 .3 불멸의 절도단 사건
5th row마인드 스쿨 .1 자신감이 필요해!
ValueCountFrequency (%)
보물찾기 22
 
4.1%
16
 
3.0%
탐정 11
 
2.1%
추리 10
 
1.9%
엉덩이 10
 
1.9%
내일은 10
 
1.9%
천재 9
 
1.7%
사건 9
 
1.7%
마인드 8
 
1.5%
과학 8
 
1.5%
Other values (294) 423
78.9%
2023-12-13T00:14:12.967975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
448
 
21.8%
. 54
 
2.6%
이 40
 
1.9%
기 38
 
1.9%
서 31
 
1.5%
에 29
 
1.4%
의 28
 
1.4%
학 27
 
1.3%
! 26
 
1.3%
아 26
 
1.3%
Other values (318) 1307
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1303
63.4%
Space Separator 448
 
21.8%
Other Punctuation 95
 
4.6%
Decimal Number 87
 
4.2%
Lowercase Letter 56
 
2.7%
Uppercase Letter 21
 
1.0%
Close Punctuation 20
 
1.0%
Open Punctuation 20
 
1.0%
Math Symbol 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 40
 
3.1%
기 38
 
2.9%
서 31
 
2.4%
에 29
 
2.2%
의 28
 
2.1%
학 27
 
2.1%
아 26
 
2.0%
과 26
 
2.0%
보 25
 
1.9%
물 25
 
1.9%
Other values (270) 1008
77.4%
Lowercase Letter
ValueCountFrequency (%)
o 6
 
10.7%
r 5
 
8.9%
i 5
 
8.9%
c 4
 
7.1%
h 4
 
7.1%
l 4
 
7.1%
v 4
 
7.1%
m 3
 
5.4%
u 3
 
5.4%
a 3
 
5.4%
Other values (9) 15
26.8%
Decimal Number
ValueCountFrequency (%)
1 15
17.2%
2 14
16.1%
3 12
13.8%
5 12
13.8%
4 9
10.3%
6 8
9.2%
0 6
 
6.9%
8 5
 
5.7%
7 4
 
4.6%
9 2
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
S 9
42.9%
I 4
19.0%
C 4
19.0%
V 1
 
4.8%
O 1
 
4.8%
W 1
 
4.8%
M 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 54
56.8%
! 26
27.4%
: 12
 
12.6%
, 2
 
2.1%
? 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 19
95.0%
] 1
 
5.0%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
[ 1
 
5.0%
Math Symbol
ValueCountFrequency (%)
= 3
75.0%
~ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1303
63.4%
Common 674
32.8%
Latin 77
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 40
 
3.1%
기 38
 
2.9%
서 31
 
2.4%
에 29
 
2.2%
의 28
 
2.1%
학 27
 
2.1%
아 26
 
2.0%
과 26
 
2.0%
보 25
 
1.9%
물 25
 
1.9%
Other values (270) 1008
77.4%
Latin
ValueCountFrequency (%)
S 9
 
11.7%
o 6
 
7.8%
r 5
 
6.5%
i 5
 
6.5%
c 4
 
5.2%
h 4
 
5.2%
l 4
 
5.2%
I 4
 
5.2%
C 4
 
5.2%
v 4
 
5.2%
Other values (16) 28
36.4%
Common
ValueCountFrequency (%)
448
66.5%
. 54
 
8.0%
! 26
 
3.9%
) 19
 
2.8%
( 19
 
2.8%
1 15
 
2.2%
2 14
 
2.1%
: 12
 
1.8%
3 12
 
1.8%
5 12
 
1.8%
Other values (12) 43
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1303
63.4%
ASCII 751
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
448
59.7%
. 54
 
7.2%
! 26
 
3.5%
) 19
 
2.5%
( 19
 
2.5%
1 15
 
2.0%
2 14
 
1.9%
: 12
 
1.6%
3 12
 
1.6%
5 12
 
1.6%
Other values (38) 120
 
16.0%
Hangul
ValueCountFrequency (%)
이 40
 
3.1%
기 38
 
2.9%
서 31
 
2.4%
에 29
 
2.2%
의 28
 
2.1%
학 27
 
2.1%
아 26
 
2.0%
과 26
 
2.0%
보 25
 
1.9%
물 25
 
1.9%
Other values (270) 1008
77.4%

저자
Text

Distinct50
Distinct (%)50.5%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-13T00:14:13.184500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.7575758
Min length2

Characters and Unicode

Total characters372
Distinct characters114
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)32.3%

Sample

1st row트롤
2nd row트롤
3rd row트롤
4th row트롤
5th row천근아
ValueCountFrequency (%)
강경효 17
 
14.7%
트롤 8
 
6.9%
곰돌이 5
 
4.3%
co 5
 
4.3%
한현동 4
 
3.4%
강경호 3
 
2.6%
스토리 3
 
2.6%
a 3
 
2.6%
천근아 3
 
2.6%
올댓스토리 3
 
2.6%
Other values (50) 62
53.4%
2023-12-13T00:14:13.563939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
강 22
 
5.9%
경 22
 
5.9%
효 18
 
4.8%
17
 
4.6%
이 14
 
3.8%
스 9
 
2.4%
리 9
 
2.4%
트 8
 
2.2%
롤 8
 
2.2%
토 8
 
2.2%
Other values (104) 237
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
83.6%
Lowercase Letter 35
 
9.4%
Space Separator 17
 
4.6%
Other Punctuation 5
 
1.3%
Uppercase Letter 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 22
 
7.1%
경 22
 
7.1%
효 18
 
5.8%
이 14
 
4.5%
스 9
 
2.9%
리 9
 
2.9%
트 8
 
2.6%
롤 8
 
2.6%
토 8
 
2.6%
김 7
 
2.3%
Other values (88) 186
59.8%
Lowercase Letter
ValueCountFrequency (%)
c 5
14.3%
o 5
14.3%
f 4
11.4%
i 4
11.4%
a 3
8.6%
d 2
 
5.7%
y 2
 
5.7%
n 2
 
5.7%
r 2
 
5.7%
s 2
 
5.7%
Other values (2) 4
11.4%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
G 2
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
83.6%
Latin 39
 
10.5%
Common 22
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 22
 
7.1%
경 22
 
7.1%
효 18
 
5.8%
이 14
 
4.5%
스 9
 
2.9%
리 9
 
2.9%
트 8
 
2.6%
롤 8
 
2.6%
토 8
 
2.6%
김 7
 
2.3%
Other values (88) 186
59.8%
Latin
ValueCountFrequency (%)
c 5
12.8%
o 5
12.8%
f 4
10.3%
i 4
10.3%
a 3
 
7.7%
d 2
 
5.1%
y 2
 
5.1%
n 2
 
5.1%
r 2
 
5.1%
A 2
 
5.1%
Other values (4) 8
20.5%
Common
ValueCountFrequency (%)
17
77.3%
, 5
 
22.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
83.6%
ASCII 61
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
강 22
 
7.1%
경 22
 
7.1%
효 18
 
5.8%
이 14
 
4.5%
스 9
 
2.9%
리 9
 
2.9%
트 8
 
2.6%
롤 8
 
2.6%
토 8
 
2.6%
김 7
 
2.3%
Other values (88) 186
59.8%
ASCII
ValueCountFrequency (%)
17
27.9%
, 5
 
8.2%
c 5
 
8.2%
o 5
 
8.2%
f 4
 
6.6%
i 4
 
6.6%
a 3
 
4.9%
d 2
 
3.3%
y 2
 
3.3%
n 2
 
3.3%
Other values (6) 12
19.7%

발행처
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
아이세움
37 
고릴라박스
9 
글송이
8 
MiraeN·아이세움
7 
재미북스
7 
Other values (21)
32 

Length

Max length12
Median length11
Mean length4.64
Min length2

Unique

Unique14 ?
Unique (%)14.0%

Sample

1st rowMiraeN·아이세움
2nd row미래엔
3rd row아이세움
4th rowMiraeN·아이세움
5th row고릴라박스

Common Values

ValueCountFrequency (%)
아이세움 37
37.0%
고릴라박스 9
 
9.0%
글송이 8
 
8.0%
MiraeN·아이세움 7
 
7.0%
재미북스 7
 
7.0%
시공주니어 3
 
3.0%
가나출판사 3
 
3.0%
학산문화사 3
 
3.0%
아울북 3
 
3.0%
창비 2
 
2.0%
Other values (16) 18
18.0%

Length

2023-12-13T00:14:13.714861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아이세움 37
36.6%
고릴라박스 9
 
8.9%
글송이 8
 
7.9%
miraen·아이세움 7
 
6.9%
재미북스 7
 
6.9%
시공주니어 3
 
3.0%
가나출판사 3
 
3.0%
학산문화사 3
 
3.0%
아울북 3
 
3.0%
민음사 2
 
2.0%
Other values (17) 19
18.8%

발행년
Real number (ℝ)

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.11
Minimum2011
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:14:13.818488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2013
Q12014
median2015
Q32016
95-th percentile2018
Maximum2019
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4276844
Coefficient of variation (CV)0.00070848958
Kurtosis1.0097953
Mean2015.11
Median Absolute Deviation (MAD)1
Skewness0.41892803
Sum201511
Variance2.0382828
MonotonicityNot monotonic
2023-12-13T00:14:13.959600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2014 30
30.0%
2015 30
30.0%
2016 20
20.0%
2017 8
 
8.0%
2019 3
 
3.0%
2018 3
 
3.0%
2013 3
 
3.0%
2012 2
 
2.0%
2011 1
 
1.0%
ValueCountFrequency (%)
2011 1
 
1.0%
2012 2
 
2.0%
2013 3
 
3.0%
2014 30
30.0%
2015 30
30.0%
2016 20
20.0%
2017 8
 
8.0%
2018 3
 
3.0%
2019 3
 
3.0%
ValueCountFrequency (%)
2019 3
 
3.0%
2018 3
 
3.0%
2017 8
 
8.0%
2016 20
20.0%
2015 30
30.0%
2014 30
30.0%
2013 3
 
3.0%
2012 2
 
2.0%
2011 1
 
1.0%

대출건수
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.31
Minimum145
Maximum355
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:14:14.127664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum145
5-th percentile146
Q1153.75
median166
Q3182.25
95-th percentile220.05
Maximum355
Range210
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation27.697024
Coefficient of variation (CV)0.1616778
Kurtosis18.737114
Mean171.31
Median Absolute Deviation (MAD)14
Skewness3.3291545
Sum17131
Variance767.12515
MonotonicityDecreasing
2023-12-13T00:14:14.308296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
166 7
 
7.0%
145 4
 
4.0%
146 4
 
4.0%
155 4
 
4.0%
154 4
 
4.0%
153 3
 
3.0%
168 3
 
3.0%
186 3
 
3.0%
156 3
 
3.0%
175 3
 
3.0%
Other values (42) 62
62.0%
ValueCountFrequency (%)
145 4
4.0%
146 4
4.0%
147 2
2.0%
148 3
3.0%
149 3
3.0%
150 2
2.0%
151 2
2.0%
152 2
2.0%
153 3
3.0%
154 4
4.0%
ValueCountFrequency (%)
355 1
1.0%
231 1
1.0%
230 1
1.0%
222 1
1.0%
221 1
1.0%
220 1
1.0%
212 1
1.0%
204 1
1.0%
201 1
1.0%
198 1
1.0%

Interactions

2023-12-13T00:14:11.439295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:10.887914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:11.163551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:11.548383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:10.978420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:11.257529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:11.634160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:11.082268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:11.353558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:14:14.396008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위서명저자발행처발행년대출건수
순위1.0001.0000.6570.4360.4110.817
서명1.0001.0001.0001.0001.0001.000
저자0.6571.0001.0000.9970.8330.000
발행처0.4361.0000.9971.0000.7260.000
발행년0.4111.0000.8330.7261.0000.524
대출건수0.8171.0000.0000.0000.5241.000
2023-12-13T00:14:14.508468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위발행년대출건수발행처
순위1.000-0.236-1.0000.148
발행년-0.2361.0000.2330.320
대출건수-1.0000.2331.0000.000
발행처0.1480.3200.0001.000

Missing values

2023-12-13T00:14:11.743212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:14:11.860611image/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

순위서명저자발행처발행년대출건수
01추리 천재 엉덩이 탐정 . 1 보라 부인의 암호 사건트롤MiraeN·아이세움2019355
12추리 천재 엉덩이 탐정 .4 괴도 VS 탐정 대결 사건트롤미래엔2017231
23추리 천재 엉덩이 탐정 .2 어둠 속으로 사라진 거인 사건트롤아이세움2017230
34(추리 천재) 엉덩이 탐정 .3 불멸의 절도단 사건트롤MiraeN·아이세움2017222
45마인드 스쿨 .1 자신감이 필요해!천근아고릴라박스2014221
56추리 천재 엉덩이 탐정 .5 유적에서 날아온 SOS 사건다나카 요코아이세움2017220
67마인드 스쿨 .3 너도 같이 놀자!천근아고릴라박스2014212
78나미야 잡화점의 기적 :히가시노 게이고 장편소설히가시노 게이고현대문학2015204
89추리 천재 엉덩이 탐정 . 6 수상한 탐정 사무소 사건트롤MiraeN·아이세움2018201
910나이트 사파리에서 살아남기 .2한현동아이세움2014198
순위서명저자발행처발행년대출건수
9091이라크에서 보물찾기강경호아이세움2014147
919213층 나무집Griffiths, Andy시공주니어2015147
9293테푸할아버지의 요술테이프박은경고래이야기2016146
9394(쿠키런) 엽기 과학 상식조주희서울문화사2016146
9495저는 주식투자가 처음인데요 :레알 생초보의 주식투자 입문기강병욱한빛비즈2015146
9596어린이 과학 형사대 CSI :과학 추리만화 .5 서서히 드러나는 범인의 정체양선모가나출판사2013146
9697지하 100층짜리 집이와이 도시오북뱅크2016145
9798내일은 실험왕 .20 바다의 대결곰돌이 co아이세움2013145
9899이유가 있어요요시타케 신스케봄나무2016145
9910052층 나무집 .[4]그리피스, 앤디시공주니어2016145