Overview

Dataset statistics

Number of variables5
Number of observations215
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory42.6 B

Variable types

Numeric2
Text3

Dataset

Description경상북도교육청 안동도서관의 월별 희망도서 구입 목록입니다(서명, 저자, 발행자, 발행년 등의 정보를 제공합니다)
Author경상북도교육청 경상북도교육청안동도서관
URLhttps://www.data.go.kr/data/15099213/fileData.do

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:35:13.905796
Analysis finished2023-12-11 23:35:15.194783
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct215
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108
Minimum1
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T08:35:15.266920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.7
Q154.5
median108
Q3161.5
95-th percentile204.3
Maximum215
Range214
Interquartile range (IQR)107

Descriptive statistics

Standard deviation62.209324
Coefficient of variation (CV)0.57601226
Kurtosis-1.2
Mean108
Median Absolute Deviation (MAD)54
Skewness0
Sum23220
Variance3870
MonotonicityStrictly increasing
2023-12-12T08:35:15.431789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
149 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
143 1
 
0.5%
144 1
 
0.5%
145 1
 
0.5%
Other values (205) 205
95.3%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
215 1
0.5%
214 1
0.5%
213 1
0.5%
212 1
0.5%
211 1
0.5%
210 1
0.5%
209 1
0.5%
208 1
0.5%
207 1
0.5%
206 1
0.5%

서명
Text

Distinct214
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T08:35:15.853584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length11.348837
Min length2

Characters and Unicode

Total characters2440
Distinct characters431
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

Unique213 ?
Unique (%)99.1%

Sample

1st row앞으로의 경제학
2nd row우리 목을 밟고 있는 발을 치워달라
3rd row인권의 전선들
4th row시대예보
5th row부모의 말은 아이의 인생이 된다
ValueCountFrequency (%)
2 15
 
2.2%
1 14
 
2.0%
4 9
 
1.3%
5 7
 
1.0%
사이언스툰 7
 
1.0%
1등급 7
 
1.0%
고교학점제 6
 
0.9%
선택과목 6
 
0.9%
3 6
 
0.9%
주제탐구세특 6
 
0.9%
Other values (497) 605
87.9%
2023-12-12T08:35:16.373131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
473
 
19.4%
의 63
 
2.6%
이 52
 
2.1%
사 36
 
1.5%
학 34
 
1.4%
는 30
 
1.2%
1 30
 
1.2%
2 30
 
1.2%
리 29
 
1.2%
가 27
 
1.1%
Other values (421) 1636
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1798
73.7%
Space Separator 473
 
19.4%
Decimal Number 108
 
4.4%
Uppercase Letter 26
 
1.1%
Other Punctuation 22
 
0.9%
Lowercase Letter 7
 
0.3%
Dash Punctuation 4
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 63
 
3.5%
이 52
 
2.9%
사 36
 
2.0%
학 34
 
1.9%
는 30
 
1.7%
리 29
 
1.6%
가 27
 
1.5%
스 25
 
1.4%
다 24
 
1.3%
고 23
 
1.3%
Other values (384) 1455
80.9%
Uppercase Letter
ValueCountFrequency (%)
A 5
19.2%
P 4
15.4%
R 3
11.5%
T 3
11.5%
C 2
 
7.7%
G 2
 
7.7%
S 2
 
7.7%
F 1
 
3.8%
L 1
 
3.8%
D 1
 
3.8%
Other values (2) 2
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 30
27.8%
2 30
27.8%
3 14
13.0%
4 12
 
11.1%
5 10
 
9.3%
0 5
 
4.6%
6 4
 
3.7%
8 1
 
0.9%
7 1
 
0.9%
9 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 10
45.5%
! 4
 
18.2%
: 3
 
13.6%
? 2
 
9.1%
. 2
 
9.1%
/ 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
o 3
42.9%
t 1
 
14.3%
u 1
 
14.3%
d 1
 
14.3%
i 1
 
14.3%
Space Separator
ValueCountFrequency (%)
473
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1798
73.7%
Common 609
 
25.0%
Latin 33
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 63
 
3.5%
이 52
 
2.9%
사 36
 
2.0%
학 34
 
1.9%
는 30
 
1.7%
리 29
 
1.6%
가 27
 
1.5%
스 25
 
1.4%
다 24
 
1.3%
고 23
 
1.3%
Other values (384) 1455
80.9%
Common
ValueCountFrequency (%)
473
77.7%
1 30
 
4.9%
2 30
 
4.9%
3 14
 
2.3%
4 12
 
2.0%
, 10
 
1.6%
5 10
 
1.6%
0 5
 
0.8%
- 4
 
0.7%
! 4
 
0.7%
Other values (10) 17
 
2.8%
Latin
ValueCountFrequency (%)
A 5
15.2%
P 4
12.1%
o 3
9.1%
R 3
9.1%
T 3
9.1%
C 2
 
6.1%
G 2
 
6.1%
S 2
 
6.1%
F 1
 
3.0%
L 1
 
3.0%
Other values (7) 7
21.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1797
73.6%
ASCII 642
 
26.3%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
473
73.7%
1 30
 
4.7%
2 30
 
4.7%
3 14
 
2.2%
4 12
 
1.9%
, 10
 
1.6%
5 10
 
1.6%
0 5
 
0.8%
A 5
 
0.8%
- 4
 
0.6%
Other values (27) 49
 
7.6%
Hangul
ValueCountFrequency (%)
의 63
 
3.5%
이 52
 
2.9%
사 36
 
2.0%
학 34
 
1.9%
는 30
 
1.7%
리 29
 
1.6%
가 27
 
1.5%
스 25
 
1.4%
다 24
 
1.3%
고 23
 
1.3%
Other values (383) 1454
80.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

저자
Text

Distinct182
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T08:35:16.834107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length3
Mean length4.1209302
Min length2

Characters and Unicode

Total characters886
Distinct characters269
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)74.9%

Sample

1st row원용찬
2nd row이창신
3rd row정정훈
4th row송길영
5th row아자 부부
ValueCountFrequency (%)
욘 6
 
2.2%
포세 6
 
2.2%
김재훈 5
 
1.8%
편집부 4
 
1.4%
전민희 3
 
1.1%
싱숑 3
 
1.1%
마츠자카 3
 
1.1%
가즈오 3
 
1.1%
권라드 3
 
1.1%
고희정 3
 
1.1%
Other values (220) 239
86.0%
2023-12-12T08:35:17.421992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
7.1%
김 34
 
3.8%
이 21
 
2.4%
정 19
 
2.1%
리 17
 
1.9%
영 15
 
1.7%
희 15
 
1.7%
아 13
 
1.5%
민 12
 
1.4%
마 11
 
1.2%
Other values (259) 666
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 774
87.4%
Space Separator 63
 
7.1%
Lowercase Letter 30
 
3.4%
Uppercase Letter 13
 
1.5%
Other Punctuation 4
 
0.5%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 34
 
4.4%
이 21
 
2.7%
정 19
 
2.5%
리 17
 
2.2%
영 15
 
1.9%
희 15
 
1.9%
아 13
 
1.7%
민 12
 
1.6%
마 11
 
1.4%
박 10
 
1.3%
Other values (228) 607
78.4%
Lowercase Letter
ValueCountFrequency (%)
a 5
16.7%
i 3
10.0%
m 3
10.0%
r 3
10.0%
e 2
 
6.7%
o 2
 
6.7%
s 2
 
6.7%
y 1
 
3.3%
t 1
 
3.3%
h 1
 
3.3%
Other values (7) 7
23.3%
Uppercase Letter
ValueCountFrequency (%)
K 2
15.4%
S 2
15.4%
G 1
7.7%
T 1
7.7%
H 1
7.7%
J 1
7.7%
I 1
7.7%
E 1
7.7%
N 1
7.7%
P 1
7.7%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 774
87.4%
Common 69
 
7.8%
Latin 43
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 34
 
4.4%
이 21
 
2.7%
정 19
 
2.5%
리 17
 
2.2%
영 15
 
1.9%
희 15
 
1.9%
아 13
 
1.7%
민 12
 
1.6%
마 11
 
1.4%
박 10
 
1.3%
Other values (228) 607
78.4%
Latin
ValueCountFrequency (%)
a 5
 
11.6%
i 3
 
7.0%
m 3
 
7.0%
r 3
 
7.0%
e 2
 
4.7%
o 2
 
4.7%
K 2
 
4.7%
s 2
 
4.7%
S 2
 
4.7%
G 1
 
2.3%
Other values (18) 18
41.9%
Common
ValueCountFrequency (%)
63
91.3%
. 4
 
5.8%
- 2
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 774
87.4%
ASCII 112
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
56.2%
a 5
 
4.5%
. 4
 
3.6%
i 3
 
2.7%
m 3
 
2.7%
r 3
 
2.7%
- 2
 
1.8%
e 2
 
1.8%
o 2
 
1.8%
K 2
 
1.8%
Other values (21) 23
 
20.5%
Hangul
ValueCountFrequency (%)
김 34
 
4.4%
이 21
 
2.7%
정 19
 
2.5%
리 17
 
2.2%
영 15
 
1.9%
희 15
 
1.9%
아 13
 
1.7%
민 12
 
1.6%
마 11
 
1.4%
박 10
 
1.3%
Other values (228) 607
78.4%

발행자
Text

Distinct156
Distinct (%)72.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T08:35:17.786975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4
Min length1

Characters and Unicode

Total characters860
Distinct characters247
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

Unique122 ?
Unique (%)56.7%

Sample

1st row당대
2nd row당대
3rd row당대
4th row교보문고
5th row사람in
ValueCountFrequency (%)
문학동네 7
 
3.2%
예한 6
 
2.7%
휴머니스트 5
 
2.3%
아울북 4
 
1.8%
서울문화사 3
 
1.4%
당대 3
 
1.4%
학산문화사 3
 
1.4%
비채 3
 
1.4%
영컴 3
 
1.4%
한길사 3
 
1.4%
Other values (150) 179
81.7%
2023-12-12T08:35:18.374985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 38
 
4.4%
사 35
 
4.1%
북 27
 
3.1%
이 25
 
2.9%
문 24
 
2.8%
아 18
 
2.1%
한 15
 
1.7%
학 15
 
1.7%
어 14
 
1.6%
니 12
 
1.4%
Other values (237) 637
74.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 837
97.3%
Uppercase Letter 10
 
1.2%
Lowercase Letter 6
 
0.7%
Space Separator 5
 
0.6%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 38
 
4.5%
사 35
 
4.2%
북 27
 
3.2%
이 25
 
3.0%
문 24
 
2.9%
아 18
 
2.2%
한 15
 
1.8%
학 15
 
1.8%
어 14
 
1.7%
니 12
 
1.4%
Other values (222) 614
73.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
20.0%
B 2
20.0%
S 2
20.0%
O 2
20.0%
K 1
10.0%
N 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
r 1
16.7%
t 1
16.7%
e 1
16.7%
a 1
16.7%
n 1
16.7%
i 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 837
97.3%
Latin 16
 
1.9%
Common 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 38
 
4.5%
사 35
 
4.2%
북 27
 
3.2%
이 25
 
3.0%
문 24
 
2.9%
아 18
 
2.2%
한 15
 
1.8%
학 15
 
1.8%
어 14
 
1.7%
니 12
 
1.4%
Other values (222) 614
73.4%
Latin
ValueCountFrequency (%)
E 2
12.5%
B 2
12.5%
S 2
12.5%
O 2
12.5%
r 1
6.2%
t 1
6.2%
e 1
6.2%
a 1
6.2%
K 1
6.2%
n 1
6.2%
Other values (2) 2
12.5%
Common
ValueCountFrequency (%)
5
71.4%
1 1
 
14.3%
2 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 837
97.3%
ASCII 23
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 38
 
4.5%
사 35
 
4.2%
북 27
 
3.2%
이 25
 
3.0%
문 24
 
2.9%
아 18
 
2.2%
한 15
 
1.8%
학 15
 
1.8%
어 14
 
1.7%
니 12
 
1.4%
Other values (222) 614
73.4%
ASCII
ValueCountFrequency (%)
5
21.7%
E 2
 
8.7%
B 2
 
8.7%
S 2
 
8.7%
O 2
 
8.7%
r 1
 
4.3%
t 1
 
4.3%
e 1
 
4.3%
a 1
 
4.3%
K 1
 
4.3%
Other values (5) 5
21.7%

발행년
Real number (ℝ)

Distinct7
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2022.293
Minimum2015
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T08:35:18.515610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2019
Q12022
median2023
Q32023
95-th percentile2023
Maximum2023
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3984964
Coefficient of variation (CV)0.00069153995
Kurtosis4.5442956
Mean2022.293
Median Absolute Deviation (MAD)0
Skewness-2.1699874
Sum434793
Variance1.9557922
MonotonicityNot monotonic
2023-12-12T08:35:18.630805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2023 156
72.6%
2022 19
 
8.8%
2019 17
 
7.9%
2021 15
 
7.0%
2020 4
 
1.9%
2018 3
 
1.4%
2015 1
 
0.5%
ValueCountFrequency (%)
2015 1
 
0.5%
2018 3
 
1.4%
2019 17
 
7.9%
2020 4
 
1.9%
2021 15
 
7.0%
2022 19
 
8.8%
2023 156
72.6%
ValueCountFrequency (%)
2023 156
72.6%
2022 19
 
8.8%
2021 15
 
7.0%
2020 4
 
1.9%
2019 17
 
7.9%
2018 3
 
1.4%
2015 1
 
0.5%

Interactions

2023-12-12T08:35:14.565823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.381691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.678224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.467473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:35:18.718107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번발행년
순번1.0000.392
발행년0.3921.000
2023-12-12T08:35:18.810811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번발행년
순번1.000-0.068
발행년-0.0681.000

Missing values

2023-12-12T08:35:14.813980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:35:15.159013image/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

순번서명저자발행자발행년
01앞으로의 경제학원용찬당대2022
12우리 목을 밟고 있는 발을 치워달라이창신당대2023
23인권의 전선들정정훈당대2023
34시대예보송길영교보문고2023
45부모의 말은 아이의 인생이 된다아자 부부사람in2023
56돈을 부르는 매너민경남데이원2023
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