Overview

Dataset statistics

Number of variables11
Number of observations1833
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory170.2 KiB
Average record size in memory95.1 B

Variable types

Numeric6
Categorical2
Text3

Dataset

Description충청남도 보령시 죽정도서관의 희망도서 구입목록 데이터입니다. 구입연도, 구입 월, 구분(성인/아동), 분류, 도서명, 저자명, 발행자, 단가, 수량, 금액 정보를 제공합니다.
Author충청남도 보령시
URLhttps://www.data.go.kr/data/15104392/fileData.do

Alerts

연번 is highly overall correlated with 구입연도High correlation
구입월 is highly overall correlated with 구입연도High correlation
단가 is highly overall correlated with 금액High correlation
금액 is highly overall correlated with 단가High correlation
구입연도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
분류 has 27 (1.5%) zerosZeros

Reproduction

Analysis started2024-05-04 08:25:57.304722
Analysis finished2024-05-04 08:26:17.114602
Duration19.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1833
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean917
Minimum1
Maximum1833
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.2 KiB
2024-05-04T08:26:17.472791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile92.6
Q1459
median917
Q31375
95-th percentile1741.4
Maximum1833
Range1832
Interquartile range (IQR)916

Descriptive statistics

Standard deviation529.28584
Coefficient of variation (CV)0.57719285
Kurtosis-1.2
Mean917
Median Absolute Deviation (MAD)458
Skewness0
Sum1680861
Variance280143.5
MonotonicityStrictly increasing
2024-05-04T08:26:17.923928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1232 1
 
0.1%
1230 1
 
0.1%
1229 1
 
0.1%
1228 1
 
0.1%
1227 1
 
0.1%
1226 1
 
0.1%
1225 1
 
0.1%
1224 1
 
0.1%
1223 1
 
0.1%
Other values (1823) 1823
99.5%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1833 1
0.1%
1832 1
0.1%
1831 1
0.1%
1830 1
0.1%
1829 1
0.1%
1828 1
0.1%
1827 1
0.1%
1826 1
0.1%
1825 1
0.1%
1824 1
0.1%

구입연도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.4 KiB
2023
1322 
2024
511 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 1322
72.1%
2024 511
 
27.9%

Length

2024-05-04T08:26:18.407052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:26:18.812540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 1322
72.1%
2024 511
 
27.9%

구입월
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2553191
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.2 KiB
2024-05-04T08:26:19.176270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q38
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4721687
Coefficient of variation (CV)0.66069607
Kurtosis-1.0192885
Mean5.2553191
Median Absolute Deviation (MAD)3
Skewness0.48744141
Sum9633
Variance12.055956
MonotonicityNot monotonic
2024-05-04T08:26:19.556243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 293
16.0%
4 251
13.7%
3 231
12.6%
2 201
11.0%
9 150
8.2%
8 116
 
6.3%
6 109
 
5.9%
11 107
 
5.8%
5 104
 
5.7%
12 104
 
5.7%
Other values (2) 167
9.1%
ValueCountFrequency (%)
1 293
16.0%
2 201
11.0%
3 231
12.6%
4 251
13.7%
5 104
 
5.7%
6 109
 
5.9%
7 102
 
5.6%
8 116
 
6.3%
9 150
8.2%
10 65
 
3.5%
ValueCountFrequency (%)
12 104
5.7%
11 107
5.8%
10 65
 
3.5%
9 150
8.2%
8 116
6.3%
7 102
5.6%
6 109
5.9%
5 104
5.7%
4 251
13.7%
3 231
12.6%

구분
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.4 KiB
성인
1172 
아동
561 
유아
 
100

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성인
2nd row성인
3rd row유아
4th row성인
5th row성인

Common Values

ValueCountFrequency (%)
성인 1172
63.9%
아동 561
30.6%
유아 100
 
5.5%

Length

2024-05-04T08:26:19.951108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:26:20.256317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성인 1172
63.9%
아동 561
30.6%
유아 100
 
5.5%

분류
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean575.99564
Minimum0
Maximum900
Zeros27
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size16.2 KiB
2024-05-04T08:26:20.528609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100
Q1300
median800
Q3800
95-th percentile800
Maximum900
Range900
Interquartile range (IQR)500

Descriptive statistics

Standard deviation287.47869
Coefficient of variation (CV)0.49909874
Kurtosis-1.1649914
Mean575.99564
Median Absolute Deviation (MAD)0
Skewness-0.66322441
Sum1055800
Variance82644
MonotonicityNot monotonic
2024-05-04T08:26:20.827363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
800 927
50.6%
100 297
 
16.2%
300 154
 
8.4%
500 145
 
7.9%
400 118
 
6.4%
900 87
 
4.7%
600 38
 
2.1%
0 27
 
1.5%
200 21
 
1.1%
700 19
 
1.0%
ValueCountFrequency (%)
0 27
 
1.5%
100 297
 
16.2%
200 21
 
1.1%
300 154
 
8.4%
400 118
 
6.4%
500 145
 
7.9%
600 38
 
2.1%
700 19
 
1.0%
800 927
50.6%
900 87
 
4.7%
ValueCountFrequency (%)
900 87
 
4.7%
800 927
50.6%
700 19
 
1.0%
600 38
 
2.1%
500 145
 
7.9%
400 118
 
6.4%
300 154
 
8.4%
200 21
 
1.1%
100 297
 
16.2%
0 27
 
1.5%

도서명
Text

Distinct1802
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size14.4 KiB
2024-05-04T08:26:21.467161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length29
Mean length12.414075
Min length1

Characters and Unicode

Total characters22755
Distinct characters945
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1771 ?
Unique (%)96.6%

Sample

1st row탈무드
2nd row트렌드 코리아 2023
3rd row내가 말할 차례야
4th row신의진의 자녀교육 베스트 컬렉션
5th row시인
ValueCountFrequency (%)
2 100
 
1.5%
1 97
 
1.5%
3 46
 
0.7%
나는 34
 
0.5%
내 33
 
0.5%
4 31
 
0.5%
위한 29
 
0.4%
이야기 26
 
0.4%
대모험 25
 
0.4%
세계사 25
 
0.4%
Other values (3672) 6071
93.2%
2024-05-04T08:26:22.556703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4703
 
20.7%
의 497
 
2.2%
이 495
 
2.2%
는 363
 
1.6%
다 305
 
1.3%
기 274
 
1.2%
사 251
 
1.1%
한 236
 
1.0%
지 232
 
1.0%
하 228
 
1.0%
Other values (935) 15171
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16699
73.4%
Space Separator 4703
 
20.7%
Decimal Number 722
 
3.2%
Other Punctuation 281
 
1.2%
Uppercase Letter 139
 
0.6%
Lowercase Letter 99
 
0.4%
Close Punctuation 48
 
0.2%
Open Punctuation 48
 
0.2%
Dash Punctuation 8
 
< 0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 497
 
3.0%
이 495
 
3.0%
는 363
 
2.2%
다 305
 
1.8%
기 274
 
1.6%
사 251
 
1.5%
한 236
 
1.4%
지 232
 
1.4%
하 228
 
1.4%
가 225
 
1.3%
Other values (867) 13593
81.4%
Uppercase Letter
ValueCountFrequency (%)
G 24
17.3%
P 14
10.1%
T 12
 
8.6%
S 10
 
7.2%
B 10
 
7.2%
C 9
 
6.5%
O 9
 
6.5%
I 7
 
5.0%
E 6
 
4.3%
V 5
 
3.6%
Other values (14) 33
23.7%
Lowercase Letter
ValueCountFrequency (%)
o 31
31.3%
t 9
 
9.1%
i 8
 
8.1%
e 7
 
7.1%
h 7
 
7.1%
k 6
 
6.1%
y 6
 
6.1%
u 4
 
4.0%
l 4
 
4.0%
n 4
 
4.0%
Other values (7) 13
13.1%
Decimal Number
ValueCountFrequency (%)
1 212
29.4%
2 153
21.2%
3 73
 
10.1%
4 69
 
9.6%
0 63
 
8.7%
5 48
 
6.6%
6 36
 
5.0%
8 27
 
3.7%
7 22
 
3.0%
9 19
 
2.6%
Other Punctuation
ValueCountFrequency (%)
: 106
37.7%
, 98
34.9%
! 60
21.4%
. 4
 
1.4%
% 4
 
1.4%
& 3
 
1.1%
? 3
 
1.1%
· 2
 
0.7%
; 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 47
97.9%
] 1
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 47
97.9%
[ 1
 
2.1%
Math Symbol
ValueCountFrequency (%)
~ 6
75.0%
+ 2
 
25.0%
Space Separator
ValueCountFrequency (%)
4703
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16699
73.4%
Common 5818
 
25.6%
Latin 238
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 497
 
3.0%
이 495
 
3.0%
는 363
 
2.2%
다 305
 
1.8%
기 274
 
1.6%
사 251
 
1.5%
한 236
 
1.4%
지 232
 
1.4%
하 228
 
1.4%
가 225
 
1.3%
Other values (867) 13593
81.4%
Latin
ValueCountFrequency (%)
o 31
 
13.0%
G 24
 
10.1%
P 14
 
5.9%
T 12
 
5.0%
S 10
 
4.2%
B 10
 
4.2%
t 9
 
3.8%
C 9
 
3.8%
O 9
 
3.8%
i 8
 
3.4%
Other values (31) 102
42.9%
Common
ValueCountFrequency (%)
4703
80.8%
1 212
 
3.6%
2 153
 
2.6%
: 106
 
1.8%
, 98
 
1.7%
3 73
 
1.3%
4 69
 
1.2%
0 63
 
1.1%
! 60
 
1.0%
5 48
 
0.8%
Other values (17) 233
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16699
73.4%
ASCII 6054
 
26.6%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4703
77.7%
1 212
 
3.5%
2 153
 
2.5%
: 106
 
1.8%
, 98
 
1.6%
3 73
 
1.2%
4 69
 
1.1%
0 63
 
1.0%
! 60
 
1.0%
5 48
 
0.8%
Other values (57) 469
 
7.7%
Hangul
ValueCountFrequency (%)
의 497
 
3.0%
이 495
 
3.0%
는 363
 
2.2%
다 305
 
1.8%
기 274
 
1.6%
사 251
 
1.5%
한 236
 
1.4%
지 232
 
1.4%
하 228
 
1.4%
가 225
 
1.3%
Other values (867) 13593
81.4%
None
ValueCountFrequency (%)
· 2
100.0%

저자명
Text

Distinct1354
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size14.4 KiB
2024-05-04T08:26:23.197523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length4.4697218
Min length1

Characters and Unicode

Total characters8193
Distinct characters560
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

Unique1105 ?
Unique (%)60.3%

Sample

1st row노먼 솔로몬
2nd row김난도 외
3rd row크리스티나 테바르
4th row신의진
5th row마이클 코넬리
ValueCountFrequency (%)
외 157
 
6.0%
흔한남매 16
 
0.6%
편집부 15
 
0.6%
설민석 15
 
0.6%
채유리 11
 
0.4%
김진명 10
 
0.4%
단꿈아이 9
 
0.3%
최명희 9
 
0.3%
찰스 9
 
0.3%
디킨스 9
 
0.3%
Other values (1678) 2340
90.0%
2024-05-04T08:26:24.504643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
808
 
9.9%
이 334
 
4.1%
김 214
 
2.6%
스 177
 
2.2%
리 171
 
2.1%
외 160
 
2.0%
정 132
 
1.6%
미 107
 
1.3%
지 101
 
1.2%
영 94
 
1.1%
Other values (550) 5895
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7288
89.0%
Space Separator 808
 
9.9%
Lowercase Letter 35
 
0.4%
Uppercase Letter 34
 
0.4%
Other Punctuation 13
 
0.2%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Math Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 334
 
4.6%
김 214
 
2.9%
스 177
 
2.4%
리 171
 
2.3%
외 160
 
2.2%
정 132
 
1.8%
미 107
 
1.5%
지 101
 
1.4%
영 94
 
1.3%
라 81
 
1.1%
Other values (512) 5717
78.4%
Uppercase Letter
ValueCountFrequency (%)
S 8
23.5%
G 5
14.7%
J 3
 
8.8%
T 3
 
8.8%
N 2
 
5.9%
E 2
 
5.9%
B 2
 
5.9%
R 1
 
2.9%
V 1
 
2.9%
P 1
 
2.9%
Other values (6) 6
17.6%
Lowercase Letter
ValueCountFrequency (%)
a 7
20.0%
t 4
11.4%
e 4
11.4%
y 3
8.6%
m 3
8.6%
o 3
8.6%
r 3
8.6%
k 2
 
5.7%
u 1
 
2.9%
s 1
 
2.9%
Other values (4) 4
11.4%
Other Punctuation
ValueCountFrequency (%)
. 11
84.6%
, 2
 
15.4%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
808
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7288
89.0%
Common 836
 
10.2%
Latin 69
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 334
 
4.6%
김 214
 
2.9%
스 177
 
2.4%
리 171
 
2.3%
외 160
 
2.2%
정 132
 
1.8%
미 107
 
1.5%
지 101
 
1.4%
영 94
 
1.3%
라 81
 
1.1%
Other values (512) 5717
78.4%
Latin
ValueCountFrequency (%)
S 8
 
11.6%
a 7
 
10.1%
G 5
 
7.2%
t 4
 
5.8%
e 4
 
5.8%
J 3
 
4.3%
y 3
 
4.3%
m 3
 
4.3%
T 3
 
4.3%
o 3
 
4.3%
Other values (20) 26
37.7%
Common
ValueCountFrequency (%)
808
96.7%
. 11
 
1.3%
) 6
 
0.7%
( 6
 
0.7%
, 2
 
0.2%
< 1
 
0.1%
> 1
 
0.1%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7288
89.0%
ASCII 905
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
808
89.3%
. 11
 
1.2%
S 8
 
0.9%
a 7
 
0.8%
) 6
 
0.7%
( 6
 
0.7%
G 5
 
0.6%
t 4
 
0.4%
e 4
 
0.4%
J 3
 
0.3%
Other values (28) 43
 
4.8%
Hangul
ValueCountFrequency (%)
이 334
 
4.6%
김 214
 
2.9%
스 177
 
2.4%
리 171
 
2.3%
외 160
 
2.2%
정 132
 
1.8%
미 107
 
1.5%
지 101
 
1.4%
영 94
 
1.3%
라 81
 
1.1%
Other values (512) 5717
78.4%

발행자
Text

Distinct666
Distinct (%)36.3%
Missing0
Missing (%)0.0%
Memory size14.4 KiB
2024-05-04T08:26:25.099441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.2160393
Min length1

Characters and Unicode

Total characters7728
Distinct characters473
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)19.6%

Sample

1st row규장
2nd row미래의창
3rd row다봄
4th row랜덤하우스코리아
5th row알에이치코리아
ValueCountFrequency (%)
문학동네 34
 
1.8%
미래엔아이세움 34
 
1.8%
주니어김영사 31
 
1.7%
위즈덤하우스 31
 
1.7%
다산어린이 31
 
1.7%
창비 30
 
1.6%
아울북 28
 
1.5%
비룡소 24
 
1.3%
단꿈아이 23
 
1.2%
스푼북 17
 
0.9%
Other values (659) 1557
84.6%
2024-05-04T08:26:26.050581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 436
 
5.6%
북 374
 
4.8%
이 308
 
4.0%
사 237
 
3.1%
어 216
 
2.8%
아 175
 
2.3%
리 127
 
1.6%
미 113
 
1.5%
비 110
 
1.4%
문 103
 
1.3%
Other values (463) 5529
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7540
97.6%
Uppercase Letter 130
 
1.7%
Decimal Number 34
 
0.4%
Lowercase Letter 15
 
0.2%
Space Separator 7
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 436
 
5.8%
북 374
 
5.0%
이 308
 
4.1%
사 237
 
3.1%
어 216
 
2.9%
아 175
 
2.3%
리 127
 
1.7%
미 113
 
1.5%
비 110
 
1.5%
문 103
 
1.4%
Other values (425) 5341
70.8%
Uppercase Letter
ValueCountFrequency (%)
O 34
26.2%
B 19
14.6%
S 18
13.8%
K 18
13.8%
N 6
 
4.6%
I 5
 
3.8%
P 4
 
3.1%
E 4
 
3.1%
C 3
 
2.3%
M 3
 
2.3%
Other values (11) 16
12.3%
Lowercase Letter
ValueCountFrequency (%)
s 3
20.0%
d 2
13.3%
i 2
13.3%
r 2
13.3%
e 1
 
6.7%
n 1
 
6.7%
a 1
 
6.7%
t 1
 
6.7%
l 1
 
6.7%
o 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 17
50.0%
1 15
44.1%
6 1
 
2.9%
7 1
 
2.9%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7540
97.6%
Latin 145
 
1.9%
Common 43
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 436
 
5.8%
북 374
 
5.0%
이 308
 
4.1%
사 237
 
3.1%
어 216
 
2.9%
아 175
 
2.3%
리 127
 
1.7%
미 113
 
1.5%
비 110
 
1.5%
문 103
 
1.4%
Other values (425) 5341
70.8%
Latin
ValueCountFrequency (%)
O 34
23.4%
B 19
13.1%
S 18
12.4%
K 18
12.4%
N 6
 
4.1%
I 5
 
3.4%
P 4
 
2.8%
E 4
 
2.8%
s 3
 
2.1%
C 3
 
2.1%
Other values (21) 31
21.4%
Common
ValueCountFrequency (%)
2 17
39.5%
1 15
34.9%
7
16.3%
) 1
 
2.3%
( 1
 
2.3%
6 1
 
2.3%
7 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7540
97.6%
ASCII 188
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 436
 
5.8%
북 374
 
5.0%
이 308
 
4.1%
사 237
 
3.1%
어 216
 
2.9%
아 175
 
2.3%
리 127
 
1.7%
미 113
 
1.5%
비 110
 
1.5%
문 103
 
1.4%
Other values (425) 5341
70.8%
ASCII
ValueCountFrequency (%)
O 34
18.1%
B 19
10.1%
S 18
 
9.6%
K 18
 
9.6%
2 17
 
9.0%
1 15
 
8.0%
7
 
3.7%
N 6
 
3.2%
I 5
 
2.7%
P 4
 
2.1%
Other values (28) 45
23.9%

단가
Real number (ℝ)

HIGH CORRELATION 

Distinct87
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15838.325
Minimum6000
Maximum55000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.2 KiB
2024-05-04T08:26:26.466063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6000
5-th percentile11000
Q113000
median15000
Q317800
95-th percentile23000
Maximum55000
Range49000
Interquartile range (IQR)4800

Descriptive statistics

Standard deviation4383.328
Coefficient of variation (CV)0.27675452
Kurtosis10.941311
Mean15838.325
Median Absolute Deviation (MAD)2000
Skewness2.2978059
Sum29031650
Variance19213564
MonotonicityNot monotonic
2024-05-04T08:26:26.903405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13000 192
 
10.5%
15000 173
 
9.4%
12000 152
 
8.3%
14000 146
 
8.0%
18000 117
 
6.4%
16800 98
 
5.3%
16000 96
 
5.2%
17000 83
 
4.5%
11000 67
 
3.7%
22000 44
 
2.4%
Other values (77) 665
36.3%
ValueCountFrequency (%)
6000 3
 
0.2%
7000 4
 
0.2%
7200 1
 
0.1%
7700 1
 
0.1%
7800 1
 
0.1%
8000 6
0.3%
8500 2
 
0.1%
9000 11
0.6%
9500 8
0.4%
9800 5
0.3%
ValueCountFrequency (%)
55000 1
 
0.1%
49000 1
 
0.1%
48000 1
 
0.1%
42000 1
 
0.1%
40000 1
 
0.1%
38000 4
0.2%
35000 6
0.3%
34000 3
0.2%
33000 5
0.3%
32000 1
 
0.1%

수량
Real number (ℝ)

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0447354
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.2 KiB
2024-05-04T08:26:27.266008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.46862925
Coefficient of variation (CV)0.44856262
Kurtosis201.17851
Mean1.0447354
Median Absolute Deviation (MAD)0
Skewness13.145683
Sum1915
Variance0.21961337
MonotonicityNot monotonic
2024-05-04T08:26:27.709008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 1811
98.8%
4 7
 
0.4%
5 4
 
0.2%
3 4
 
0.2%
2 2
 
0.1%
6 2
 
0.1%
10 2
 
0.1%
8 1
 
0.1%
ValueCountFrequency (%)
1 1811
98.8%
2 2
 
0.1%
3 4
 
0.2%
4 7
 
0.4%
5 4
 
0.2%
6 2
 
0.1%
8 1
 
0.1%
10 2
 
0.1%
ValueCountFrequency (%)
10 2
 
0.1%
8 1
 
0.1%
6 2
 
0.1%
5 4
 
0.2%
4 7
 
0.4%
3 4
 
0.2%
2 2
 
0.1%
1 1811
98.8%

금액
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16400.873
Minimum6000
Maximum150000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.2 KiB
2024-05-04T08:26:28.103997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6000
5-th percentile11000
Q113000
median15000
Q317800
95-th percentile25000
Maximum150000
Range144000
Interquartile range (IQR)4800

Descriptive statistics

Standard deviation7493.9772
Coefficient of variation (CV)0.45692551
Kurtosis122.0873
Mean16400.873
Median Absolute Deviation (MAD)2000
Skewness8.6656713
Sum30062800
Variance56159694
MonotonicityNot monotonic
2024-05-04T08:26:28.557709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13000 189
 
10.3%
15000 168
 
9.2%
12000 150
 
8.2%
14000 143
 
7.8%
18000 117
 
6.4%
16800 99
 
5.4%
16000 96
 
5.2%
17000 83
 
4.5%
11000 67
 
3.7%
22000 44
 
2.4%
Other values (88) 677
36.9%
ValueCountFrequency (%)
6000 3
 
0.2%
7000 4
 
0.2%
7200 1
 
0.1%
7700 1
 
0.1%
7800 1
 
0.1%
8000 6
0.3%
8500 2
 
0.1%
9000 12
0.7%
9500 8
0.4%
9800 5
0.3%
ValueCountFrequency (%)
150000 1
 
0.1%
140000 1
 
0.1%
120000 1
 
0.1%
75000 1
 
0.1%
65000 2
0.1%
60000 3
0.2%
56000 1
 
0.1%
55000 1
 
0.1%
54000 3
0.2%
49000 1
 
0.1%

Interactions

2024-05-04T08:26:12.716581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:01.310650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:03.821492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:05.931803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:08.181698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:10.329368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:13.250376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:01.798760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:04.226413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:06.333688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:08.575285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:10.751458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:13.755505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:02.233244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:04.548361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:06.668706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:08.858992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:11.167137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:14.265062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:02.627861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:04.890191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:07.175207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:09.245876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:11.525019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:14.643370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:03.033365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:05.182766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:07.454481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:09.606113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:11.884942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:15.041080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:03.375522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:05.512228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:07.782865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:09.954998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:26:12.183375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T08:26:28.886188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구입연도구입월구분분류단가수량금액
연번1.0000.9980.9710.2950.3050.2260.0870.000
구입연도0.9981.0000.7440.0750.1280.1450.0280.025
구입월0.9710.7441.0000.2190.2380.1420.0000.000
구분0.2950.0750.2191.0000.4530.5270.1380.207
분류0.3050.1280.2380.4531.0000.5400.0730.235
단가0.2260.1450.1420.5270.5401.0000.0000.754
수량0.0870.0280.0000.1380.0730.0001.0000.903
금액0.0000.0250.0000.2070.2350.7540.9031.000
2024-05-04T08:26:29.250767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분구입연도
구분1.0000.124
구입연도0.1241.000
2024-05-04T08:26:29.519406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구입월분류단가수량금액구입연도구분
연번1.0000.168-0.0130.120-0.0520.1060.9550.184
구입월0.1681.0000.0530.003-0.057-0.0130.5830.133
분류-0.0130.0531.000-0.3470.049-0.3280.0980.305
단가0.1200.003-0.3471.000-0.0800.9630.1100.371
수량-0.052-0.0570.049-0.0801.0000.1780.0210.087
금액0.106-0.013-0.3280.9630.1781.0000.0260.141
구입연도0.9550.5830.0980.1100.0210.0261.0000.124
구분0.1840.1330.3050.3710.0870.1410.1241.000

Missing values

2024-05-04T08:26:15.963109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T08:26:16.851022image/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

연번구입연도구입월구분분류도서명저자명발행자단가수량금액
0120231성인200탈무드노먼 솔로몬규장48000148000
1220231성인300트렌드 코리아 2023김난도 외미래의창19000119000
2320231유아800내가 말할 차례야크리스티나 테바르다봄13000113000
3420231성인500신의진의 자녀교육 베스트 컬렉션신의진랜덤하우스코리아18000118000
4520231성인800시인마이클 코넬리알에이치코리아16800116800
5620231아동800비밀요원 레너드 13박설연아울북13000113000
6720231성인800노곤하개 6홍끼비아북12500112500
7820231성인800노곤하개 7홍끼비아북12500112500
8920231성인800노곤하개 8홍끼비아북12500112500
91020231아동100한 문장부터 열 문장까지 초등 글쓰기강승임소울키즈12000112000
연번구입연도구입월구분분류도서명저자명발행자단가수량금액
1823182420244성인100인문학과 손잡은 영어 공부 1강준만인물과사상사18000118000
1824182520244성인100인문학과 손잡은 영어 공부 2강준만인물과사상사18000118000
1825182620244성인100별일, 하고 산다박지윤프란북스18000118000
1826182720244성인500독특해도 괜찮아베리 프리전트 외예문아카이브18000118000
1827182820244성인800내 말이 그 말이에요김제동나무의마음17000117000
1828182920244아동800양반전 허생전 예덕 선생전강민경파란자전거11900111900
1829183020244아동800문방구TV 로블록스 최강 배틀 코믹툰최진규서울문화사12000112000
1830183120244아동800별의 커비 푸푸푸 히어로 3아오키 케이 외다산어린이11000111000
1831183220244아동900용선생 교과서 세계사 1사회평론 역사연구소사회평론16000116000
1832183320244아동900용선생 교과서 세계사 2사회평론 역사연구소사회평론16000116000