Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells6243
Missing cells (%)5.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory957.0 KiB
Average record size in memory98.0 B

Variable types

Numeric2
Text5
Categorical4

Dataset

Description서울특별시 동작구립도서관에서 보유 중인 전자 도서 목록 현황으로 제목, 저자, 출판사명, 보유수량, 유형 등의 정보를 제공합니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15112685/fileData.do

Alerts

콘텐츠 유형 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
입고일 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
태블릿사용여부 is highly overall correlated with 보유수 and 3 other fieldsHigh correlation
스마트폰사용여부 is highly overall correlated with 보유수 and 3 other fieldsHigh correlation
연번 is highly overall correlated with 콘텐츠 유형 and 1 other fieldsHigh correlation
보유수 is highly overall correlated with 콘텐츠 유형 and 3 other fieldsHigh correlation
콘텐츠 유형 is highly imbalanced (99.9%)Imbalance
스마트폰사용여부 is highly imbalanced (83.4%)Imbalance
태블릿사용여부 is highly imbalanced (83.4%)Imbalance
국제표준도서번호 has 6225 (62.3%) missing valuesMissing
보유수 is highly skewed (γ1 = 99.99927288)Skewed

Reproduction

Analysis started2024-03-14 15:59:04.637196
Analysis finished2024-03-14 15:59:10.293209
Duration5.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct9999
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5722.1508
Minimum1
Maximum11425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:59:10.506330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile574.9
Q12863.5
median5729
Q38576.5
95-th percentile10848.1
Maximum11425
Range11424
Interquartile range (IQR)5713

Descriptive statistics

Standard deviation3299.3306
Coefficient of variation (CV)0.57658924
Kurtosis-1.2012668
Mean5722.1508
Median Absolute Deviation (MAD)2857
Skewness-0.0038090571
Sum57215786
Variance10885582
MonotonicityNot monotonic
2024-03-15T00:59:10.899467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1908 1
 
< 0.1%
10030 1
 
< 0.1%
10055 1
 
< 0.1%
9859 1
 
< 0.1%
5724 1
 
< 0.1%
9425 1
 
< 0.1%
5860 1
 
< 0.1%
6883 1
 
< 0.1%
6002 1
 
< 0.1%
5466 1
 
< 0.1%
Other values (9989) 9989
99.9%
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 (%)
11425 1
< 0.1%
11424 1
< 0.1%
11423 1
< 0.1%
11422 1
< 0.1%
11420 1
< 0.1%
11419 1
< 0.1%
11418 1
< 0.1%
11417 1
< 0.1%
11416 1
< 0.1%
11415 1
< 0.1%

국제표준도서번호
Text

MISSING 

Distinct3775
Distinct (%)100.0%
Missing6225
Missing (%)62.3%
Memory size156.2 KiB
2024-03-15T00:59:11.959781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters37750
Distinct characters12
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

Unique3775 ?
Unique (%)100.0%

Sample

1st rowD131213730
2nd row1185903062
3rd row8970135103
4th row1189584867
5th row1130627985
ValueCountFrequency (%)
d131205880 1
 
< 0.1%
9050157230 1
 
< 0.1%
8965961955 1
 
< 0.1%
115992225x 1
 
< 0.1%
8963791815 1
 
< 0.1%
1190710056 1
 
< 0.1%
1162541393 1
 
< 0.1%
1156759528 1
 
< 0.1%
1190313774 1
 
< 0.1%
9050157440 1
 
< 0.1%
Other values (3765) 3765
99.7%
2024-03-15T00:59:13.239707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7785
20.6%
0 4811
12.7%
9 3740
9.9%
8 3702
9.8%
5 3025
 
8.0%
6 2977
 
7.9%
2 2953
 
7.8%
3 2718
 
7.2%
7 2685
 
7.1%
4 2257
 
6.0%
Other values (2) 1097
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36653
97.1%
Uppercase Letter 1097
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7785
21.2%
0 4811
13.1%
9 3740
10.2%
8 3702
10.1%
5 3025
 
8.3%
6 2977
 
8.1%
2 2953
 
8.1%
3 2718
 
7.4%
7 2685
 
7.3%
4 2257
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
D 854
77.8%
X 243
 
22.2%

Most occurring scripts

ValueCountFrequency (%)
Common 36653
97.1%
Latin 1097
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7785
21.2%
0 4811
13.1%
9 3740
10.2%
8 3702
10.1%
5 3025
 
8.3%
6 2977
 
8.1%
2 2953
 
8.1%
3 2718
 
7.4%
7 2685
 
7.3%
4 2257
 
6.2%
Latin
ValueCountFrequency (%)
D 854
77.8%
X 243
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7785
20.6%
0 4811
12.7%
9 3740
9.9%
8 3702
9.8%
5 3025
 
8.0%
6 2977
 
7.9%
2 2953
 
7.8%
3 2718
 
7.2%
7 2685
 
7.1%
4 2257
 
6.0%
Other values (2) 1097
 
2.9%

제목
Text

Distinct9944
Distinct (%)99.4%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-15T00:59:14.884504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length106
Median length78
Mean length23.157816
Min length1

Characters and Unicode

Total characters231555
Distinct characters1495
Distinct categories16 ?
Distinct scripts6 ?
Distinct blocks13 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9901 ?
Unique (%)99.0%

Sample

1st row한국사가 죽어야 나라가 산다 : 한국사를 은폐하고 조작한 주류 역사학자들을 고발한다
2nd rowThe Life of Stork
3rd row(앱북) 펭귄
4th row(위기를 ‘절대희망‘으로 바꾼) 행복나눔 125
5th row우리도 철학이 필요해
ValueCountFrequency (%)
2659
 
4.7%
the 655
 
1.1%
앱북 429
 
0.8%
2 312
 
0.5%
1 303
 
0.5%
이야기 295
 
0.5%
위한 284
 
0.5%
읽는 234
 
0.4%
and 202
 
0.4%
of 202
 
0.4%
Other values (19989) 51514
90.2%
2024-03-15T00:59:17.539881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47090
 
20.3%
e 3728
 
1.6%
이 3589
 
1.5%
의 3476
 
1.5%
는 3109
 
1.3%
: 2642
 
1.1%
a 2357
 
1.0%
o 2087
 
0.9%
한 2085
 
0.9%
리 2080
 
0.9%
Other values (1485) 159312
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131674
56.9%
Space Separator 47090
 
20.3%
Lowercase Letter 25717
 
11.1%
Uppercase Letter 7646
 
3.3%
Decimal Number 6242
 
2.7%
Other Punctuation 5102
 
2.2%
Close Punctuation 3669
 
1.6%
Open Punctuation 3667
 
1.6%
Dash Punctuation 317
 
0.1%
Math Symbol 233
 
0.1%
Other values (6) 198
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3589
 
2.7%
의 3476
 
2.6%
는 3109
 
2.4%
한 2085
 
1.6%
리 2080
 
1.6%
기 1993
 
1.5%
다 1817
 
1.4%
지 1810
 
1.4%
사 1758
 
1.3%
가 1729
 
1.3%
Other values (1361) 108228
82.2%
Lowercase Letter
ValueCountFrequency (%)
e 3728
14.5%
a 2357
 
9.2%
o 2087
 
8.1%
t 1920
 
7.5%
i 1841
 
7.2%
n 1821
 
7.1%
s 1777
 
6.9%
r 1736
 
6.8%
h 1349
 
5.2%
l 1156
 
4.5%
Other values (16) 5945
23.1%
Uppercase Letter
ValueCountFrequency (%)
T 1045
 
13.7%
S 716
 
9.4%
B 464
 
6.1%
L 424
 
5.5%
P 379
 
5.0%
A 369
 
4.8%
E 360
 
4.7%
O 349
 
4.6%
C 344
 
4.5%
M 335
 
4.4%
Other values (16) 2861
37.4%
Other Punctuation
ValueCountFrequency (%)
: 2642
51.8%
, 890
 
17.4%
! 479
 
9.4%
. 319
 
6.3%
? 300
 
5.9%
& 157
 
3.1%
; 133
 
2.6%
· 90
 
1.8%
＆ 19
 
0.4%
% 17
 
0.3%
Other values (10) 56
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 1500
24.0%
0 1176
18.8%
2 1040
16.7%
3 654
10.5%
5 454
 
7.3%
4 419
 
6.7%
6 325
 
5.2%
9 238
 
3.8%
8 228
 
3.7%
7 208
 
3.3%
Math Symbol
ValueCountFrequency (%)
｜ 154
66.1%
~ 34
 
14.6%
+ 22
 
9.4%
| 17
 
7.3%
< 1
 
0.4%
> 1
 
0.4%
÷ 1
 
0.4%
∞ 1
 
0.4%
∼ 1
 
0.4%
= 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
] 1889
51.5%
) 1738
47.4%
》 14
 
0.4%
｝ 11
 
0.3%
』 7
 
0.2%
〉 6
 
0.2%
］ 3
 
0.1%
」 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 1887
51.5%
( 1738
47.4%
《 14
 
0.4%
｛ 11
 
0.3%
『 7
 
0.2%
〈 6
 
0.2%
［ 3
 
0.1%
「 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 29
40.8%
Ⅰ 26
36.6%
Ⅲ 10
 
14.1%
Ⅳ 5
 
7.0%
Ⅴ 1
 
1.4%
Other Symbol
ValueCountFrequency (%)
│ 1
33.3%
♂ 1
33.3%
♀ 1
33.3%
Final Punctuation
ValueCountFrequency (%)
’ 59
96.7%
” 2
 
3.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 49
96.1%
“ 2
 
3.9%
Space Separator
ValueCountFrequency (%)
47090
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 317
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131229
56.7%
Common 66447
28.7%
Latin 33434
 
14.4%
Han 399
 
0.2%
Hiragana 43
 
< 0.1%
Katakana 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3589
 
2.7%
의 3476
 
2.6%
는 3109
 
2.4%
한 2085
 
1.6%
리 2080
 
1.6%
기 1993
 
1.5%
다 1817
 
1.4%
지 1810
 
1.4%
사 1758
 
1.3%
가 1729
 
1.3%
Other values (1219) 107783
82.1%
Han
ValueCountFrequency (%)
志 31
 
7.8%
國 29
 
7.3%
傳 25
 
6.3%
三 22
 
5.5%
曹 22
 
5.5%
操 22
 
5.5%
新 16
 
4.0%
風 7
 
1.8%
史 6
 
1.5%
詩 6
 
1.5%
Other values (113) 213
53.4%
Common
ValueCountFrequency (%)
47090
70.9%
: 2642
 
4.0%
] 1889
 
2.8%
[ 1887
 
2.8%
) 1738
 
2.6%
( 1738
 
2.6%
1 1500
 
2.3%
0 1176
 
1.8%
2 1040
 
1.6%
, 890
 
1.3%
Other values (57) 4857
 
7.3%
Latin
ValueCountFrequency (%)
e 3728
 
11.2%
a 2357
 
7.0%
o 2087
 
6.2%
t 1920
 
5.7%
i 1841
 
5.5%
n 1821
 
5.4%
s 1777
 
5.3%
r 1736
 
5.2%
h 1349
 
4.0%
l 1156
 
3.5%
Other values (47) 13662
40.9%
Hiragana
ValueCountFrequency (%)
き 8
18.6%
ど 8
18.6%
よ 4
9.3%
う 4
9.3%
こ 4
9.3%
そ 4
9.3%
に 2
 
4.7%
も 1
 
2.3%
て 1
 
2.3%
っ 1
 
2.3%
Other values (6) 6
14.0%
Katakana
ValueCountFrequency (%)
マ 1
33.3%
チ 1
33.3%
ネ 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131218
56.7%
ASCII 99319
42.9%
CJK 391
 
0.2%
None 364
 
0.2%
Punctuation 122
 
0.1%
Number Forms 71
 
< 0.1%
Hiragana 43
 
< 0.1%
Compat Jamo 11
 
< 0.1%
CJK Compat Ideographs 8
 
< 0.1%
Katakana 3
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47090
47.4%
e 3728
 
3.8%
: 2642
 
2.7%
a 2357
 
2.4%
o 2087
 
2.1%
t 1920
 
1.9%
] 1889
 
1.9%
[ 1887
 
1.9%
i 1841
 
1.9%
n 1821
 
1.8%
Other values (78) 32057
32.3%
Hangul
ValueCountFrequency (%)
이 3589
 
2.7%
의 3476
 
2.6%
는 3109
 
2.4%
한 2085
 
1.6%
리 2080
 
1.6%
기 1993
 
1.5%
다 1817
 
1.4%
지 1810
 
1.4%
사 1758
 
1.3%
가 1729
 
1.3%
Other values (1218) 107772
82.1%
None
ValueCountFrequency (%)
｜ 154
42.3%
· 90
24.7%
＆ 19
 
5.2%
》 14
 
3.8%
《 14
 
3.8%
｝ 11
 
3.0%
｛ 11
 
3.0%
／ 9
 
2.5%
』 7
 
1.9%
『 7
 
1.9%
Other values (11) 28
 
7.7%
Punctuation
ValueCountFrequency (%)
’ 59
48.4%
‘ 49
40.2%
… 10
 
8.2%
” 2
 
1.6%
“ 2
 
1.6%
CJK
ValueCountFrequency (%)
志 31
 
7.9%
國 29
 
7.4%
傳 25
 
6.4%
三 22
 
5.6%
曹 22
 
5.6%
操 22
 
5.6%
新 16
 
4.1%
風 7
 
1.8%
史 6
 
1.5%
詩 6
 
1.5%
Other values (110) 205
52.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 29
40.8%
Ⅰ 26
36.6%
Ⅲ 10
 
14.1%
Ⅳ 5
 
7.0%
Ⅴ 1
 
1.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
100.0%
Hiragana
ValueCountFrequency (%)
き 8
18.6%
ど 8
18.6%
よ 4
9.3%
う 4
9.3%
こ 4
9.3%
そ 4
9.3%
に 2
 
4.7%
も 1
 
2.3%
て 1
 
2.3%
っ 1
 
2.3%
Other values (6) 6
14.0%
CJK Compat Ideographs
ValueCountFrequency (%)
列 6
75.0%
烈 1
 
12.5%
戀 1
 
12.5%
Box Drawing
ValueCountFrequency (%)
│ 1
100.0%
Misc Symbols
ValueCountFrequency (%)
♂ 1
50.0%
♀ 1
50.0%
Math Operators
ValueCountFrequency (%)
∞ 1
50.0%
∼ 1
50.0%
Katakana
ValueCountFrequency (%)
マ 1
33.3%
チ 1
33.3%
ネ 1
33.3%

저자
Text

Distinct5698
Distinct (%)57.0%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-03-15T00:59:19.020787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length62
Mean length5.9601562
Min length2

Characters and Unicode

Total characters59536
Distinct characters843
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4548 ?
Unique (%)45.5%

Sample

1st row이주한
2nd row유스쿨넷 편집부
3rd row윤무부, 전미숙, 강은경
4th row이명진
5th row김병규
ValueCountFrequency (%)
외 1104
 
6.8%
편집부 872
 
5.4%
유스쿨넷 412
 
2.5%
블루앤트리 250
 
1.5%
편집국 117
 
0.7%
안데르센 89
 
0.5%
이원호 80
 
0.5%
한스 76
 
0.5%
크리스티안 76
 
0.5%
ybm/si-sa 71
 
0.4%
Other values (6798) 13131
80.7%
2024-03-15T00:59:20.854211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6289
 
10.6%
이 1740
 
2.9%
스 1426
 
2.4%
김 1126
 
1.9%
외 1116
 
1.9%
집 1057
 
1.8%
편 1043
 
1.8%
리 991
 
1.7%
부 943
 
1.6%
a 782
 
1.3%
Other values (833) 43023
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44058
74.0%
Space Separator 6289
 
10.6%
Lowercase Letter 5588
 
9.4%
Uppercase Letter 2283
 
3.8%
Other Punctuation 883
 
1.5%
Open Punctuation 150
 
0.3%
Close Punctuation 149
 
0.3%
Dash Punctuation 81
 
0.1%
Decimal Number 49
 
0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1740
 
3.9%
스 1426
 
3.2%
김 1126
 
2.6%
외 1116
 
2.5%
집 1057
 
2.4%
편 1043
 
2.4%
리 991
 
2.2%
부 943
 
2.1%
유 713
 
1.6%
정 674
 
1.5%
Other values (756) 33229
75.4%
Lowercase Letter
ValueCountFrequency (%)
a 782
14.0%
e 708
12.7%
n 575
10.3%
r 476
8.5%
o 432
 
7.7%
i 387
 
6.9%
l 308
 
5.5%
s 296
 
5.3%
t 286
 
5.1%
d 188
 
3.4%
Other values (16) 1150
20.6%
Uppercase Letter
ValueCountFrequency (%)
S 290
12.7%
M 267
11.7%
B 187
 
8.2%
A 141
 
6.2%
J 141
 
6.2%
D 132
 
5.8%
C 127
 
5.6%
Y 122
 
5.3%
L 118
 
5.2%
K 110
 
4.8%
Other values (14) 648
28.4%
Decimal Number
ValueCountFrequency (%)
1 14
28.6%
2 12
24.5%
8 6
12.2%
0 5
 
10.2%
6 3
 
6.1%
4 3
 
6.1%
5 3
 
6.1%
3 2
 
4.1%
7 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 452
51.2%
. 339
38.4%
/ 77
 
8.7%
& 8
 
0.9%
; 4
 
0.5%
' 2
 
0.2%
· 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 145
96.7%
〈 4
 
2.7%
『 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 144
96.6%
〉 4
 
2.7%
』 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
< 3
60.0%
> 2
40.0%
Space Separator
ValueCountFrequency (%)
6289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44044
74.0%
Latin 7871
 
13.2%
Common 7607
 
12.8%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1740
 
4.0%
스 1426
 
3.2%
김 1126
 
2.6%
외 1116
 
2.5%
집 1057
 
2.4%
편 1043
 
2.4%
리 991
 
2.3%
부 943
 
2.1%
유 713
 
1.6%
정 674
 
1.5%
Other values (748) 33215
75.4%
Latin
ValueCountFrequency (%)
a 782
 
9.9%
e 708
 
9.0%
n 575
 
7.3%
r 476
 
6.0%
o 432
 
5.5%
i 387
 
4.9%
l 308
 
3.9%
s 296
 
3.8%
S 290
 
3.7%
t 286
 
3.6%
Other values (40) 3331
42.3%
Common
ValueCountFrequency (%)
6289
82.7%
, 452
 
5.9%
. 339
 
4.5%
( 145
 
1.9%
) 144
 
1.9%
- 81
 
1.1%
/ 77
 
1.0%
1 14
 
0.2%
2 12
 
0.2%
& 8
 
0.1%
Other values (17) 46
 
0.6%
Han
ValueCountFrequency (%)
人 4
28.6%
民 4
28.6%
劉 1
 
7.1%
起 1
 
7.1%
釪 1
 
7.1%
牟 1
 
7.1%
鑒 1
 
7.1%
鐘 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44044
74.0%
ASCII 15467
 
26.0%
CJK 14
 
< 0.1%
None 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6289
40.7%
a 782
 
5.1%
e 708
 
4.6%
n 575
 
3.7%
r 476
 
3.1%
, 452
 
2.9%
o 432
 
2.8%
i 387
 
2.5%
. 339
 
2.2%
l 308
 
2.0%
Other values (62) 4719
30.5%
Hangul
ValueCountFrequency (%)
이 1740
 
4.0%
스 1426
 
3.2%
김 1126
 
2.6%
외 1116
 
2.5%
집 1057
 
2.4%
편 1043
 
2.4%
리 991
 
2.3%
부 943
 
2.1%
유 713
 
1.6%
정 674
 
1.5%
Other values (748) 33215
75.4%
None
ValueCountFrequency (%)
〈 4
36.4%
〉 4
36.4%
『 1
 
9.1%
』 1
 
9.1%
· 1
 
9.1%
CJK
ValueCountFrequency (%)
人 4
28.6%
民 4
28.6%
劉 1
 
7.1%
起 1
 
7.1%
釪 1
 
7.1%
牟 1
 
7.1%
鑒 1
 
7.1%
鐘 1
 
7.1%

출판사
Text

Distinct1090
Distinct (%)10.9%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-15T00:59:22.062891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length4.6492649
Min length1

Characters and Unicode

Total characters46488
Distinct characters570
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

Unique405 ?
Unique (%)4.1%

Sample

1st row역사의아침
2nd row유스쿨넷
3rd row삼성비엔씨(주)
4th row모아북스
5th row좋은꿈
ValueCountFrequency (%)
유스쿨넷 412
 
4.0%
도서출판 276
 
2.7%
삼성비엔씨(주 271
 
2.6%
블루앤트리 250
 
2.4%
아이들영어 234
 
2.2%
청어 197
 
1.9%
위즈덤하우스 193
 
1.9%
다락원 168
 
1.6%
와이비엠 160
 
1.5%
한국아문센 149
 
1.4%
Other values (1090) 8099
77.8%
2024-03-15T00:59:23.659339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 2625
 
5.6%
이 1619
 
3.5%
북 1481
 
3.2%
아 973
 
2.1%
리 913
 
2.0%
어 857
 
1.8%
비 771
 
1.7%
다 662
 
1.4%
사 641
 
1.4%
문 589
 
1.3%
Other values (560) 35357
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42665
91.8%
Uppercase Letter 1533
 
3.3%
Lowercase Letter 814
 
1.8%
Space Separator 410
 
0.9%
Open Punctuation 366
 
0.8%
Close Punctuation 366
 
0.8%
Decimal Number 257
 
0.6%
Other Punctuation 76
 
0.2%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 2625
 
6.2%
이 1619
 
3.8%
북 1481
 
3.5%
아 973
 
2.3%
리 913
 
2.1%
어 857
 
2.0%
비 771
 
1.8%
다 662
 
1.6%
사 641
 
1.5%
문 589
 
1.4%
Other values (496) 31534
73.9%
Uppercase Letter
ValueCountFrequency (%)
O 267
17.4%
K 179
11.7%
M 121
7.9%
D 120
7.8%
B 115
7.5%
S 105
 
6.8%
A 103
 
6.7%
R 98
 
6.4%
I 89
 
5.8%
N 72
 
4.7%
Other values (15) 264
17.2%
Lowercase Letter
ValueCountFrequency (%)
o 113
13.9%
e 107
13.1%
s 77
9.5%
t 70
8.6%
r 70
8.6%
a 56
 
6.9%
b 47
 
5.8%
n 42
 
5.2%
l 38
 
4.7%
k 37
 
4.5%
Other values (13) 157
19.3%
Decimal Number
ValueCountFrequency (%)
2 102
39.7%
1 89
34.6%
0 19
 
7.4%
3 17
 
6.6%
6 11
 
4.3%
4 10
 
3.9%
5 7
 
2.7%
8 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 55
72.4%
& 16
 
21.1%
# 4
 
5.3%
／ 1
 
1.3%
Space Separator
ValueCountFrequency (%)
410
100.0%
Open Punctuation
ValueCountFrequency (%)
( 366
100.0%
Close Punctuation
ValueCountFrequency (%)
) 366
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42666
91.8%
Latin 2347
 
5.0%
Common 1475
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 2625
 
6.2%
이 1619
 
3.8%
북 1481
 
3.5%
아 973
 
2.3%
리 913
 
2.1%
어 857
 
2.0%
비 771
 
1.8%
다 662
 
1.6%
사 641
 
1.5%
문 589
 
1.4%
Other values (497) 31535
73.9%
Latin
ValueCountFrequency (%)
O 267
 
11.4%
K 179
 
7.6%
M 121
 
5.2%
D 120
 
5.1%
B 115
 
4.9%
o 113
 
4.8%
e 107
 
4.6%
S 105
 
4.5%
A 103
 
4.4%
R 98
 
4.2%
Other values (38) 1019
43.4%
Common
ValueCountFrequency (%)
410
27.8%
( 366
24.8%
) 366
24.8%
2 102
 
6.9%
1 89
 
6.0%
. 55
 
3.7%
0 19
 
1.3%
3 17
 
1.2%
& 16
 
1.1%
6 11
 
0.7%
Other values (5) 24
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42665
91.8%
ASCII 3821
 
8.2%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 2625
 
6.2%
이 1619
 
3.8%
북 1481
 
3.5%
아 973
 
2.3%
리 913
 
2.1%
어 857
 
2.0%
비 771
 
1.8%
다 662
 
1.6%
사 641
 
1.5%
문 589
 
1.4%
Other values (496) 31534
73.9%
ASCII
ValueCountFrequency (%)
410
 
10.7%
( 366
 
9.6%
) 366
 
9.6%
O 267
 
7.0%
K 179
 
4.7%
M 121
 
3.2%
D 120
 
3.1%
B 115
 
3.0%
o 113
 
3.0%
e 107
 
2.8%
Other values (52) 1657
43.4%
None
ValueCountFrequency (%)
／ 1
50.0%
㈜ 1
50.0%

보유수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2152
Minimum1
Maximum22479
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:59:24.023386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile2
Maximum22479
Range22478
Interquartile range (IQR)0

Descriptive statistics

Standard deviation224.77087
Coefficient of variation (CV)53.323892
Kurtosis9999.903
Mean4.2152
Median Absolute Deviation (MAD)0
Skewness99.999273
Sum42152
Variance50521.944
MonotonicityNot monotonic
2024-03-15T00:59:24.350724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 8933
89.3%
1 871
 
8.7%
5 170
 
1.7%
3 14
 
0.1%
4 11
 
0.1%
22479 1
 
< 0.1%
ValueCountFrequency (%)
1 871
 
8.7%
2 8933
89.3%
3 14
 
0.1%
4 11
 
0.1%
5 170
 
1.7%
22479 1
 
< 0.1%
ValueCountFrequency (%)
22479 1
 
< 0.1%
5 170
 
1.7%
4 11
 
0.1%
3 14
 
0.1%
2 8933
89.3%
1 871
 
8.7%

카테고리
Text

Distinct243
Distinct (%)2.4%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-15T00:59:25.146323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length11.82523
Min length3

Characters and Unicode

Total characters118205
Distinct characters255
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)0.3%

Sample

1st row역사/문화 > 역사일반
2nd row외국도서 > 아동/청소년
3rd row아동 > 어린이문학
4th row경제경영 > 경영일반
5th row아동 > 철학/심리
ValueCountFrequency (%)
9950
33.1%
아동 1906
 
6.3%
소설 1306
 
4.4%
국어/외국어 1216
 
4.1%
인문 1078
 
3.6%
자기계발 820
 
2.7%
어린이문학 707
 
2.4%
어린이영어 665
 
2.2%
경제경영 597
 
2.0%
시/에세이 548
 
1.8%
Other values (250) 11224
37.4%
2024-03-15T00:59:26.104599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20021
 
16.9%
> 9950
 
8.4%
/ 7121
 
6.0%
어 5529
 
4.7%
국 3890
 
3.3%
문 3283
 
2.8%
동 3270
 
2.8%
소 3148
 
2.7%
이 3096
 
2.6%
아 3086
 
2.6%
Other values (245) 55811
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80849
68.4%
Space Separator 20021
 
16.9%
Math Symbol 9978
 
8.4%
Other Punctuation 7121
 
6.0%
Uppercase Letter 178
 
0.2%
Decimal Number 56
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 5529
 
6.8%
국 3890
 
4.8%
문 3283
 
4.1%
동 3270
 
4.0%
소 3148
 
3.9%
이 3096
 
3.8%
아 3086
 
3.8%
설 2443
 
3.0%
영 2251
 
2.8%
학 2187
 
2.7%
Other values (227) 48666
60.2%
Uppercase Letter
ValueCountFrequency (%)
I 59
33.1%
T 59
33.1%
S 29
16.3%
F 26
14.6%
O 4
 
2.2%
A 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
3 25
44.6%
4 25
44.6%
6 2
 
3.6%
5 2
 
3.6%
2 1
 
1.8%
1 1
 
1.8%
Math Symbol
ValueCountFrequency (%)
> 9950
99.7%
~ 28
 
0.3%
Space Separator
ValueCountFrequency (%)
20021
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 7121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80849
68.4%
Common 37178
31.5%
Latin 178
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 5529
 
6.8%
국 3890
 
4.8%
문 3283
 
4.1%
동 3270
 
4.0%
소 3148
 
3.9%
이 3096
 
3.8%
아 3086
 
3.8%
설 2443
 
3.0%
영 2251
 
2.8%
학 2187
 
2.7%
Other values (227) 48666
60.2%
Common
ValueCountFrequency (%)
20021
53.9%
> 9950
26.8%
/ 7121
 
19.2%
~ 28
 
0.1%
3 25
 
0.1%
4 25
 
0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
2 1
 
< 0.1%
1 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Latin
ValueCountFrequency (%)
I 59
33.1%
T 59
33.1%
S 29
16.3%
F 26
14.6%
O 4
 
2.2%
A 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80849
68.4%
ASCII 37356
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20021
53.6%
> 9950
26.6%
/ 7121
 
19.1%
I 59
 
0.2%
T 59
 
0.2%
S 29
 
0.1%
~ 28
 
0.1%
F 26
 
0.1%
3 25
 
0.1%
4 25
 
0.1%
Other values (8) 13
 
< 0.1%
Hangul
ValueCountFrequency (%)
어 5529
 
6.8%
국 3890
 
4.8%
문 3283
 
4.1%
동 3270
 
4.0%
소 3148
 
3.9%
이 3096
 
3.8%
아 3086
 
3.8%
설 2443
 
3.0%
영 2251
 
2.8%
학 2187
 
2.7%
Other values (227) 48666
60.2%

콘텐츠 유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전자책
9999 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0001
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
전자책 9999
> 99.9%
<NA> 1
 
< 0.1%

Length

2024-03-15T00:59:26.568952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:59:26.778187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전자책 9999
> 99.9%
na 1
 
< 0.1%

스마트폰사용여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제공
9556 
미제공
 
443
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0445
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row제공
2nd row제공
3rd row미제공
4th row제공
5th row제공

Common Values

ValueCountFrequency (%)
제공 9556
95.6%
미제공 443
 
4.4%
<NA> 1
 
< 0.1%

Length

2024-03-15T00:59:26.970889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:59:27.379248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제공 9556
95.6%
미제공 443
 
4.4%
na 1
 
< 0.1%

태블릿사용여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제공
9556 
미제공
 
443
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0445
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row제공
2nd row제공
3rd row미제공
4th row제공
5th row제공

Common Values

ValueCountFrequency (%)
제공 9556
95.6%
미제공 443
 
4.4%
<NA> 1
 
< 0.1%

Length

2024-03-15T00:59:27.726980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:59:27.914158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제공 9556
95.6%
미제공 443
 
4.4%
na 1
 
< 0.1%

입고일
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-11-12
976 
2021-07-08
971 
2020-09-10
962 
2013-12-19
875 
2023-07-26
674 
Other values (20)
5542 

Length

Max length10
Median length10
Mean length9.9994
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2014-12-11
2nd row2020-11-12
3rd row2018-11-06
4th row2013-12-19
5th row2020-11-12

Common Values

ValueCountFrequency (%)
2020-11-12 976
 
9.8%
2021-07-08 971
 
9.7%
2020-09-10 962
 
9.6%
2013-12-19 875
 
8.8%
2023-07-26 674
 
6.7%
2014-08-01 650
 
6.5%
2018-06-26 564
 
5.6%
2016-08-18 523
 
5.2%
2017-04-28 522
 
5.2%
2019-07-17 522
 
5.2%
Other values (15) 2761
27.6%

Length

2024-03-15T00:59:28.133573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-11-12 976
 
9.8%
2021-07-08 971
 
9.7%
2020-09-10 962
 
9.6%
2013-12-19 875
 
8.8%
2023-07-26 674
 
6.7%
2014-08-01 650
 
6.5%
2018-06-26 564
 
5.6%
2016-08-18 523
 
5.2%
2017-04-28 522
 
5.2%
2019-07-17 522
 
5.2%
Other values (15) 2761
27.6%

Interactions

2024-03-15T00:59:08.722871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:59:08.162065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:59:09.000240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:59:08.440092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:59:28.325254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번보유수스마트폰사용여부태블릿사용여부입고일
연번1.000NaN0.5740.5740.981
보유수NaN1.000NaNNaNNaN
스마트폰사용여부0.574NaN1.0001.0000.997
태블릿사용여부0.574NaN1.0001.0000.997
입고일0.981NaN0.9970.9971.000
2024-03-15T00:59:28.606580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
콘텐츠 유형입고일태블릿사용여부스마트폰사용여부
콘텐츠 유형1.0001.0001.0001.000
입고일1.0001.0000.9540.954
태블릿사용여부1.0000.9541.0000.999
스마트폰사용여부1.0000.9540.9991.000
2024-03-15T00:59:28.803717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번보유수콘텐츠 유형스마트폰사용여부태블릿사용여부입고일
연번1.0000.2681.0000.4430.4430.884
보유수0.2681.0001.0001.0001.0001.000
콘텐츠 유형1.0001.0001.0001.0001.0001.000
스마트폰사용여부0.4431.0001.0001.0000.9990.954
태블릿사용여부0.4431.0001.0000.9991.0000.954
입고일0.8841.0001.0000.9540.9541.000

Missing values

2024-03-15T00:59:09.361309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:59:09.650608image/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.
2024-03-15T00:59:10.021419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

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23222323<NA>마법천자문 4 : 울려라! 소리 음스튜디오 시리얼아울북2아동 > 아동만화전자책제공제공2015-11-17
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