Overview

Dataset statistics

Number of variables8
Number of observations30
Missing cells29
Missing cells (%)12.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory69.4 B

Variable types

Text5
Categorical1
DateTime1
Numeric1

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/131708ef-c280-47ae-9905-ef85b029e9c9

Alerts

재생목록수집일자 has constant value ""Constant
재생목록설명 has constant value ""Constant
재생목록설명 has 29 (96.7%) missing valuesMissing
재생목록ID has unique valuesUnique
재생목록명 has unique valuesUnique
영상목록 has 6 (20.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:12:32.906298
Analysis finished2023-12-10 14:12:34.106237
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

재생목록ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:12:34.400153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length31.866667
Min length18

Characters and Unicode

Total characters956
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowPLtqYizcPqxZRNiHp5sTwZCXO3Uk4HqW3K
2nd rowPLzy-AsQeybxOSl7Z-GbsfXGv_KX1L4oWc
3rd rowPLtqYizcPqxZQO-BOwdHxNKhTaeu3iUblV
4th rowPLDF47ADFB62745F56
5th rowPLzy-AsQeybxPPs-qq4ioKqVolEJ8HgKVZ
ValueCountFrequency (%)
pltqyizcpqxzrnihp5stwzcxo3uk4hqw3k 1
 
3.3%
plzy-asqeybxosl7z-gbsfxgv_kx1l4owc 1
 
3.3%
pl-53pe4iuswctgdjcxayrqgmcukewmpoh 1
 
3.3%
pl82ee71f67c52159a 1
 
3.3%
pltk5qv4ow2-pdcfaneqqgfmywiditylhz 1
 
3.3%
pl9o4fkn5dfjnh_owrqcx1eys5wu20wssb 1
 
3.3%
plk3bmu3g-ixupjrpvpe9909obgcprr9pn 1
 
3.3%
pl0f0a5e91ac37efd5 1
 
3.3%
pltqyizcpqxzt1lsjrswso3sxevv_srm4y 1
 
3.3%
plpjzfoosnf-nmfxucfrzzo1ohurkbewfi 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:12:35.105832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 53
 
5.5%
L 39
 
4.1%
F 23
 
2.4%
9 22
 
2.3%
o 22
 
2.3%
W 22
 
2.3%
q 21
 
2.2%
4 21
 
2.2%
3 21
 
2.2%
Q 20
 
2.1%
Other values (54) 692
72.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 431
45.1%
Lowercase Letter 320
33.5%
Decimal Number 174
18.2%
Dash Punctuation 17
 
1.8%
Connector Punctuation 14
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 53
 
12.3%
L 39
 
9.0%
F 23
 
5.3%
W 22
 
5.1%
Q 20
 
4.6%
E 19
 
4.4%
X 19
 
4.4%
V 17
 
3.9%
A 16
 
3.7%
K 16
 
3.7%
Other values (16) 187
43.4%
Lowercase Letter
ValueCountFrequency (%)
o 22
 
6.9%
q 21
 
6.6%
x 20
 
6.2%
c 19
 
5.9%
s 18
 
5.6%
z 16
 
5.0%
i 14
 
4.4%
w 14
 
4.4%
e 13
 
4.1%
r 13
 
4.1%
Other values (16) 150
46.9%
Decimal Number
ValueCountFrequency (%)
9 22
12.6%
4 21
12.1%
3 21
12.1%
1 20
11.5%
7 18
10.3%
5 17
9.8%
2 17
9.8%
6 13
7.5%
0 13
7.5%
8 12
6.9%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 751
78.6%
Common 205
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 53
 
7.1%
L 39
 
5.2%
F 23
 
3.1%
o 22
 
2.9%
W 22
 
2.9%
q 21
 
2.8%
Q 20
 
2.7%
x 20
 
2.7%
c 19
 
2.5%
E 19
 
2.5%
Other values (42) 493
65.6%
Common
ValueCountFrequency (%)
9 22
10.7%
4 21
10.2%
3 21
10.2%
1 20
9.8%
7 18
8.8%
5 17
8.3%
2 17
8.3%
- 17
8.3%
_ 14
6.8%
6 13
6.3%
Other values (2) 25
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 53
 
5.5%
L 39
 
4.1%
F 23
 
2.4%
9 22
 
2.3%
o 22
 
2.3%
W 22
 
2.3%
q 21
 
2.2%
4 21
 
2.2%
3 21
 
2.2%
Q 20
 
2.1%
Other values (54) 692
72.4%

재생목록채널ID
Text

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:12:35.526963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters720
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)53.3%

Sample

1st rowUCiBr0bK06imaMbLc8sAEz0A
2nd rowUCHsK9gl5aU0F3umrU4Zn_sA
3rd rowUCiBr0bK06imaMbLc8sAEz0A
4th rowUCHlSeJxRIXZWMARC2oMwmcQ
5th rowUCHsK9gl5aU0F3umrU4Zn_sA
ValueCountFrequency (%)
ucibr0bk06imamblc8saez0a 4
 
13.3%
uc7lb15p-hux7a5gbuhcxtuq 4
 
13.3%
uchpjiaegwtdztmwekzfulsa 4
 
13.3%
uchsk9gl5au0f3umru4zn_sa 2
 
6.7%
ucg5bassl2h0wjlg4bev5scq 1
 
3.3%
uci-czvbfyfggzccqjnyf16g 1
 
3.3%
ucv7hx-7ctqth4cxxt1nfrig 1
 
3.3%
ucfycczczxbrdbznf1fgd5ma 1
 
3.3%
ucnmbn-pnx1m9tlf0s-sedeq 1
 
3.3%
uce52oeb7xv_kajsezckxjjg 1
 
3.3%
Other values (10) 10
33.3%
2023-12-10T23:12:36.198003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 42
 
5.8%
U 36
 
5.0%
A 25
 
3.5%
0 20
 
2.8%
5 19
 
2.6%
u 19
 
2.6%
g 19
 
2.6%
s 17
 
2.4%
x 17
 
2.4%
E 16
 
2.2%
Other values (54) 490
68.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 304
42.2%
Lowercase Letter 298
41.4%
Decimal Number 98
 
13.6%
Dash Punctuation 12
 
1.7%
Connector Punctuation 8
 
1.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 42
 
13.8%
U 36
 
11.8%
A 25
 
8.2%
E 16
 
5.3%
H 15
 
4.9%
Q 15
 
4.9%
F 13
 
4.3%
Z 13
 
4.3%
B 12
 
3.9%
M 11
 
3.6%
Other values (16) 106
34.9%
Lowercase Letter
ValueCountFrequency (%)
u 19
 
6.4%
g 19
 
6.4%
s 17
 
5.7%
x 17
 
5.7%
l 16
 
5.4%
b 16
 
5.4%
a 16
 
5.4%
m 15
 
5.0%
t 15
 
5.0%
w 15
 
5.0%
Other values (16) 133
44.6%
Decimal Number
ValueCountFrequency (%)
0 20
20.4%
5 19
19.4%
7 12
12.2%
1 11
11.2%
6 10
10.2%
9 6
 
6.1%
4 6
 
6.1%
8 5
 
5.1%
3 5
 
5.1%
2 4
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 602
83.6%
Common 118
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 42
 
7.0%
U 36
 
6.0%
A 25
 
4.2%
u 19
 
3.2%
g 19
 
3.2%
s 17
 
2.8%
x 17
 
2.8%
E 16
 
2.7%
l 16
 
2.7%
b 16
 
2.7%
Other values (42) 379
63.0%
Common
ValueCountFrequency (%)
0 20
16.9%
5 19
16.1%
- 12
10.2%
7 12
10.2%
1 11
9.3%
6 10
8.5%
_ 8
 
6.8%
9 6
 
5.1%
4 6
 
5.1%
8 5
 
4.2%
Other values (2) 9
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 42
 
5.8%
U 36
 
5.0%
A 25
 
3.5%
0 20
 
2.8%
5 19
 
2.6%
u 19
 
2.6%
g 19
 
2.6%
s 17
 
2.4%
x 17
 
2.4%
E 16
 
2.2%
Other values (54) 490
68.1%

재생목록수집일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-03-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-01
2nd row2021-03-01
3rd row2021-03-01
4th row2021-03-01
5th row2021-03-01

Common Values

ValueCountFrequency (%)
2021-03-01 30
100.0%

Length

2023-12-10T23:12:36.483265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:12:36.708001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 30
100.0%

재생목록업로드일자
Date

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2012-06-11 00:00:00
Maximum2020-11-19 00:00:00
2023-12-10T23:12:36.878126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:37.108267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

재생목록명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:12:37.458163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length23.5
Mean length24.366667
Min length4

Characters and Unicode

Total characters731
Distinct characters193
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row행복 주식회사: Season 236
2nd row고전게임
3rd row아빠! 어디가?: Season 1273
4th rowTalk Show YeoYouManMan 20070226
5th row형 어디있냐고
ValueCountFrequency (%)
season 6
 
4.2%
5
 
3.5%
the 3
 
2.1%
of 3
 
2.1%
hot 3
 
2.1%
diary 2
 
1.4%
pretty 2
 
1.4%
clips 2
 
1.4%
힘내요 1
 
0.7%
즐거워 1
 
0.7%
Other values (116) 116
80.6%
2023-12-10T23:12:38.065851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
16.0%
0 30
 
4.1%
o 24
 
3.3%
e 22
 
3.0%
2 21
 
2.9%
1 19
 
2.6%
i 17
 
2.3%
a 17
 
2.3%
n 14
 
1.9%
s 14
 
1.9%
Other values (183) 436
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
25.9%
Lowercase Letter 182
24.9%
Space Separator 117
16.0%
Decimal Number 110
15.0%
Uppercase Letter 84
11.5%
Other Punctuation 26
 
3.6%
Open Punctuation 9
 
1.2%
Close Punctuation 9
 
1.2%
Dash Punctuation 4
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 6
 
3.2%
사 5
 
2.6%
스 5
 
2.6%
일 5
 
2.6%
이 5
 
2.6%
회 4
 
2.1%
의 4
 
2.1%
요 3
 
1.6%
모 3
 
1.6%
어 3
 
1.6%
Other values (117) 146
77.2%
Lowercase Letter
ValueCountFrequency (%)
o 24
13.2%
e 22
12.1%
i 17
9.3%
a 17
9.3%
n 14
 
7.7%
s 14
 
7.7%
r 13
 
7.1%
l 8
 
4.4%
t 7
 
3.8%
y 7
 
3.8%
Other values (13) 39
21.4%
Uppercase Letter
ValueCountFrequency (%)
S 10
11.9%
O 9
10.7%
T 9
10.7%
P 7
 
8.3%
H 6
 
7.1%
Y 5
 
6.0%
L 5
 
6.0%
M 5
 
6.0%
G 4
 
4.8%
E 4
 
4.8%
Other values (9) 20
23.8%
Decimal Number
ValueCountFrequency (%)
0 30
27.3%
2 21
19.1%
1 19
17.3%
7 9
 
8.2%
3 8
 
7.3%
9 7
 
6.4%
6 5
 
4.5%
4 4
 
3.6%
5 4
 
3.6%
8 3
 
2.7%
Other Punctuation
ValueCountFrequency (%)
: 6
23.1%
! 6
23.1%
. 5
19.2%
; 4
15.4%
' 3
11.5%
& 1
 
3.8%
? 1
 
3.8%
Open Punctuation
ValueCountFrequency (%)
[ 6
66.7%
( 3
33.3%
Close Punctuation
ValueCountFrequency (%)
] 6
66.7%
) 3
33.3%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
37.8%
Latin 266
36.4%
Hangul 189
25.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 6
 
3.2%
사 5
 
2.6%
스 5
 
2.6%
일 5
 
2.6%
이 5
 
2.6%
회 4
 
2.1%
의 4
 
2.1%
요 3
 
1.6%
모 3
 
1.6%
어 3
 
1.6%
Other values (117) 146
77.2%
Latin
ValueCountFrequency (%)
o 24
 
9.0%
e 22
 
8.3%
i 17
 
6.4%
a 17
 
6.4%
n 14
 
5.3%
s 14
 
5.3%
r 13
 
4.9%
S 10
 
3.8%
O 9
 
3.4%
T 9
 
3.4%
Other values (32) 117
44.0%
Common
ValueCountFrequency (%)
117
42.4%
0 30
 
10.9%
2 21
 
7.6%
1 19
 
6.9%
7 9
 
3.3%
3 8
 
2.9%
9 7
 
2.5%
[ 6
 
2.2%
] 6
 
2.2%
: 6
 
2.2%
Other values (14) 47
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 542
74.1%
Hangul 189
 
25.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
21.6%
0 30
 
5.5%
o 24
 
4.4%
e 22
 
4.1%
2 21
 
3.9%
1 19
 
3.5%
i 17
 
3.1%
a 17
 
3.1%
n 14
 
2.6%
s 14
 
2.6%
Other values (56) 247
45.6%
Hangul
ValueCountFrequency (%)
고 6
 
3.2%
사 5
 
2.6%
스 5
 
2.6%
일 5
 
2.6%
이 5
 
2.6%
회 4
 
2.1%
의 4
 
2.1%
요 3
 
1.6%
모 3
 
1.6%
어 3
 
1.6%
Other values (117) 146
77.2%

재생목록설명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing29
Missing (%)96.7%
Memory size372.0 B
2023-12-10T23:12:38.394700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters73
Distinct characters51
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row안녕 여러분! 한달 동안 클레버TV에서 가장 많은 조회수와 좋아요 수를 받았던 영상 모음입니다! 우리 같이 몰아볼까요? 고고싱~♡
ValueCountFrequency (%)
안녕 1
 
5.9%
수를 1
 
5.9%
몰아볼까요 1
 
5.9%
같이 1
 
5.9%
우리 1
 
5.9%
모음입니다 1
 
5.9%
영상 1
 
5.9%
받았던 1
 
5.9%
좋아요 1
 
5.9%
여러분 1
 
5.9%
Other values (7) 7
41.2%
2023-12-10T23:12:38.808017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
23.3%
안 2
 
2.7%
! 2
 
2.7%
아 2
 
2.7%
수 2
 
2.7%
요 2
 
2.7%
고 2
 
2.7%
? 1
 
1.4%
~ 1
 
1.4%
받 1
 
1.4%
Other values (41) 41
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49
67.1%
Space Separator 17
 
23.3%
Other Punctuation 3
 
4.1%
Uppercase Letter 2
 
2.7%
Math Symbol 1
 
1.4%
Other Symbol 1
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 2
 
4.1%
아 2
 
4.1%
수 2
 
4.1%
요 2
 
4.1%
고 2
 
4.1%
받 1
 
2.0%
았 1
 
2.0%
싱 1
 
2.0%
던 1
 
2.0%
영 1
 
2.0%
Other values (34) 34
69.4%
Other Punctuation
ValueCountFrequency (%)
! 2
66.7%
? 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
V 1
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Symbol
ValueCountFrequency (%)
♡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49
67.1%
Common 22
30.1%
Latin 2
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 2
 
4.1%
아 2
 
4.1%
수 2
 
4.1%
요 2
 
4.1%
고 2
 
4.1%
받 1
 
2.0%
았 1
 
2.0%
싱 1
 
2.0%
던 1
 
2.0%
영 1
 
2.0%
Other values (34) 34
69.4%
Common
ValueCountFrequency (%)
17
77.3%
! 2
 
9.1%
? 1
 
4.5%
~ 1
 
4.5%
♡ 1
 
4.5%
Latin
ValueCountFrequency (%)
T 1
50.0%
V 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49
67.1%
ASCII 23
31.5%
Misc Symbols 1
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
73.9%
! 2
 
8.7%
? 1
 
4.3%
~ 1
 
4.3%
T 1
 
4.3%
V 1
 
4.3%
Hangul
ValueCountFrequency (%)
안 2
 
4.1%
아 2
 
4.1%
수 2
 
4.1%
요 2
 
4.1%
고 2
 
4.1%
받 1
 
2.0%
았 1
 
2.0%
싱 1
 
2.0%
던 1
 
2.0%
영 1
 
2.0%
Other values (34) 34
69.4%
Misc Symbols
ValueCountFrequency (%)
♡ 1
100.0%

재생목록아이콘
Text

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:12:39.253268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length46
Mean length44.8
Min length40

Characters and Unicode

Total characters1344
Distinct characters65
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st rowhttps://i.ytimg.com/vi/zv2hupy9B_Y/default.jpg
2nd rowhttps://i.ytimg.com/vi/YTH88pmB1wY/default.jpg
3rd rowhttps://i.ytimg.com/img/no_thumbnail.jpg
4th rowhttps://i.ytimg.com/img/no_thumbnail.jpg
5th rowhttps://i.ytimg.com/vi/vP4169nvq4Q/default.jpg
ValueCountFrequency (%)
https://i.ytimg.com/img/no_thumbnail.jpg 6
 
20.0%
https://i.ytimg.com/vi/zv2hupy9b_y/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/yimjb5omh-m/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/z_wkytkh3lo/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/a_5gpn6rp3c/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/iqbafeglpgg/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/280nprs3qww/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/h9mjbtln3la/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/19kj0wcf98e/default.jpg 1
 
3.3%
https://i.ytimg.com/vi/yfooca6xw08/default.jpg 1
 
3.3%
Other values (15) 15
50.0%
2023-12-10T23:12:39.764793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 144
 
10.7%
t 123
 
9.2%
i 99
 
7.4%
. 90
 
6.7%
m 75
 
5.6%
g 73
 
5.4%
p 65
 
4.8%
o 42
 
3.1%
h 41
 
3.1%
y 37
 
2.8%
Other values (55) 555
41.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 921
68.5%
Other Punctuation 264
 
19.6%
Uppercase Letter 99
 
7.4%
Decimal Number 46
 
3.4%
Connector Punctuation 10
 
0.7%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 123
13.4%
i 99
 
10.7%
m 75
 
8.1%
g 73
 
7.9%
p 65
 
7.1%
o 42
 
4.6%
h 41
 
4.5%
y 37
 
4.0%
c 36
 
3.9%
s 35
 
3.8%
Other values (16) 295
32.0%
Uppercase Letter
ValueCountFrequency (%)
P 7
 
7.1%
M 7
 
7.1%
B 7
 
7.1%
I 6
 
6.1%
E 6
 
6.1%
W 6
 
6.1%
A 6
 
6.1%
J 5
 
5.1%
C 5
 
5.1%
Y 5
 
5.1%
Other values (15) 39
39.4%
Decimal Number
ValueCountFrequency (%)
9 8
17.4%
2 6
13.0%
8 6
13.0%
3 5
10.9%
1 5
10.9%
4 4
8.7%
5 4
8.7%
0 4
8.7%
6 4
8.7%
Other Punctuation
ValueCountFrequency (%)
/ 144
54.5%
. 90
34.1%
: 30
 
11.4%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1020
75.9%
Common 324
 
24.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 123
 
12.1%
i 99
 
9.7%
m 75
 
7.4%
g 73
 
7.2%
p 65
 
6.4%
o 42
 
4.1%
h 41
 
4.0%
y 37
 
3.6%
c 36
 
3.5%
s 35
 
3.4%
Other values (41) 394
38.6%
Common
ValueCountFrequency (%)
/ 144
44.4%
. 90
27.8%
: 30
 
9.3%
_ 10
 
3.1%
9 8
 
2.5%
2 6
 
1.9%
8 6
 
1.9%
3 5
 
1.5%
1 5
 
1.5%
- 4
 
1.2%
Other values (4) 16
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 144
 
10.7%
t 123
 
9.2%
i 99
 
7.4%
. 90
 
6.7%
m 75
 
5.6%
g 73
 
5.4%
p 65
 
4.8%
o 42
 
3.1%
h 41
 
3.1%
y 37
 
2.8%
Other values (55) 555
41.3%

영상목록
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.466667
Minimum0
Maximum2141
Zeros6
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:12:39.910482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6.5
Q314.75
95-th percentile169.7
Maximum2141
Range2141
Interquartile range (IQR)12.75

Descriptive statistics

Standard deviation389.79895
Coefficient of variation (CV)4.3569182
Kurtosis29.212734
Mean89.466667
Median Absolute Deviation (MAD)6.5
Skewness5.3778779
Sum2684
Variance151943.22
MonotonicityNot monotonic
2023-12-10T23:12:40.054720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 6
20.0%
3 4
13.3%
14 2
 
6.7%
15 2
 
6.7%
2 2
 
6.7%
9 2
 
6.7%
4 1
 
3.3%
7 1
 
3.3%
36 1
 
3.3%
10 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
0 6
20.0%
1 1
 
3.3%
2 2
 
6.7%
3 4
13.3%
4 1
 
3.3%
6 1
 
3.3%
7 1
 
3.3%
9 2
 
6.7%
10 1
 
3.3%
11 1
 
3.3%
ValueCountFrequency (%)
2141 1
3.3%
212 1
3.3%
118 1
3.3%
36 1
3.3%
25 1
3.3%
21 1
3.3%
15 2
6.7%
14 2
6.7%
11 1
3.3%
10 1
3.3%

Interactions

2023-12-10T23:12:33.625199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:12:40.263400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재생목록ID재생목록채널ID재생목록업로드일자재생목록명재생목록아이콘영상목록
재생목록ID1.0001.0001.0001.0001.0001.000
재생목록채널ID1.0001.0000.9691.0000.8601.000
재생목록업로드일자1.0000.9691.0001.0000.9821.000
재생목록명1.0001.0001.0001.0001.0001.000
재생목록아이콘1.0000.8600.9821.0001.0001.000
영상목록1.0001.0001.0001.0001.0001.000

Missing values

2023-12-10T23:12:33.801926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:12:34.017108image/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

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