Overview

Dataset statistics

Number of variables14
Number of observations28
Missing cells5
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory113.7 B

Variable types

Text6
DateTime2
Categorical2
Numeric3
Boolean1

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/eb7f4994-28e1-47ab-b35c-ae923b18923e

Alerts

COLCT_DAY has constant value ""Constant
READER_CO_CLSDR_AT has constant value ""Constant
CTGRY is highly overall correlated with ANALS_CHNNL_NATIONHigh correlation
ANALS_CHNNL_NATION is highly overall correlated with CO and 3 other fieldsHigh correlation
CO is highly overall correlated with CHNNL_ANALS_RDCNT and 1 other fieldsHigh correlation
VIDO is highly overall correlated with ANALS_CHNNL_NATIONHigh correlation
CHNNL_ANALS_RDCNT is highly overall correlated with CO and 1 other fieldsHigh correlation
KWRD has 3 (10.7%) missing valuesMissing
VIDO_ID has 2 (7.1%) missing valuesMissing
PATH has unique valuesUnique
CREAT_DAY has unique valuesUnique
ICON_NM has unique valuesUnique
DC has unique valuesUnique
CHNNL_NM has unique valuesUnique
CO has unique valuesUnique
VIDO has unique valuesUnique
CHNNL_ANALS_RDCNT has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:57:43.597907
Analysis finished2023-12-10 13:57:47.177767
Duration3.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

PATH
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T22:57:47.510924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length56
Mean length56
Min length56

Characters and Unicode

Total characters1568
Distinct characters67
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

Unique28 ?
Unique (%)100.0%

Sample

1st rowhttps://www.youtube.com/channel/UCnfwIKyFYRuqZzzKBDt6JOA
2nd rowhttps://www.youtube.com/channel/UCQPPzb7y4aJz6VV1F3v066g
3rd rowhttps://www.youtube.com/channel/UCmcd3r7AsHjm3deMgx1ZPiw
4th rowhttps://www.youtube.com/channel/UCIBoeAMqlic3emU6_crV9Vw
5th rowhttps://www.youtube.com/channel/UCNjQBiTSdoj2tCQLBGXFksw
ValueCountFrequency (%)
https://www.youtube.com/channel/ucnfwikyfyruqzzzkbdt6joa 1
 
3.6%
https://www.youtube.com/channel/ucqppzb7y4ajz6vv1f3v066g 1
 
3.6%
https://www.youtube.com/channel/ucficvvy-jrtqh1epppntpfw 1
 
3.6%
https://www.youtube.com/channel/uc2tgwq3bczudagnh965ym-a 1
 
3.6%
https://www.youtube.com/channel/ucfnsbw9u_i1zktt86zjlewg 1
 
3.6%
https://www.youtube.com/channel/uc7bcrlidterrb_mkrhpvsnw 1
 
3.6%
https://www.youtube.com/channel/uctzpzo3xuw5k6rkhlvaj0jq 1
 
3.6%
https://www.youtube.com/channel/uciipmdpvk7nznheushmvkug 1
 
3.6%
https://www.youtube.com/channel/ucem8l1w4owhkqpoog1sb4_w 1
 
3.6%
https://www.youtube.com/channel/uc31gc42xzclooi5gp1xipzw 1
 
3.6%
Other values (18) 18
64.3%
2023-12-10T22:57:48.402609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 112
 
7.1%
w 101
 
6.4%
t 97
 
6.2%
e 72
 
4.6%
o 67
 
4.3%
n 64
 
4.1%
c 64
 
4.1%
u 62
 
4.0%
h 61
 
3.9%
. 56
 
3.6%
Other values (57) 812
51.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 950
60.6%
Uppercase Letter 316
 
20.2%
Other Punctuation 196
 
12.5%
Decimal Number 92
 
5.9%
Connector Punctuation 8
 
0.5%
Dash Punctuation 6
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 101
 
10.6%
t 97
 
10.2%
e 72
 
7.6%
o 67
 
7.1%
n 64
 
6.7%
c 64
 
6.7%
u 62
 
6.5%
h 61
 
6.4%
p 43
 
4.5%
m 40
 
4.2%
Other values (16) 279
29.4%
Uppercase Letter
ValueCountFrequency (%)
U 40
 
12.7%
C 38
 
12.0%
A 15
 
4.7%
R 15
 
4.7%
P 15
 
4.7%
B 15
 
4.7%
Q 15
 
4.7%
Z 14
 
4.4%
S 12
 
3.8%
G 10
 
3.2%
Other values (16) 127
40.2%
Decimal Number
ValueCountFrequency (%)
3 14
15.2%
1 14
15.2%
6 12
13.0%
7 10
10.9%
8 9
9.8%
5 9
9.8%
9 8
8.7%
4 7
7.6%
0 5
 
5.4%
2 4
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/ 112
57.1%
. 56
28.6%
: 28
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1266
80.7%
Common 302
 
19.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 101
 
8.0%
t 97
 
7.7%
e 72
 
5.7%
o 67
 
5.3%
n 64
 
5.1%
c 64
 
5.1%
u 62
 
4.9%
h 61
 
4.8%
p 43
 
3.4%
m 40
 
3.2%
Other values (42) 595
47.0%
Common
ValueCountFrequency (%)
/ 112
37.1%
. 56
18.5%
: 28
 
9.3%
3 14
 
4.6%
1 14
 
4.6%
6 12
 
4.0%
7 10
 
3.3%
8 9
 
3.0%
5 9
 
3.0%
_ 8
 
2.6%
Other values (5) 30
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 112
 
7.1%
w 101
 
6.4%
t 97
 
6.2%
e 72
 
4.6%
o 67
 
4.3%
n 64
 
4.1%
c 64
 
4.1%
u 62
 
4.0%
h 61
 
3.9%
. 56
 
3.6%
Other values (57) 812
51.8%

COLCT_DAY
Date

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2020-10-01 00:00:00
Maximum2020-10-01 00:00:00
2023-12-10T22:57:48.935575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:49.221949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

CREAT_DAY
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2009-07-21 00:00:00
Maximum2019-03-15 00:00:00
2023-12-10T22:57:49.491554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:49.805501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

ICON_NM
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T22:57:50.416615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length99
Median length99
Mean length98.714286
Min length97

Characters and Unicode

Total characters2764
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st rowhttps://yt3.ggpht.com/a/AATXAJxaDVlUPqZHSbhlU2JqHDqjvnvK7PGRMQmhjCqy7A=s88-c-k-c0xffffffff-no-rj-mo
2nd rowhttps://yt3.ggpht.com/a/AATXAJwJlecYgVbv4-omj1nRSiz6XUc2LULY9oxpgetGVQ=s88-c-k-c0xffffffff-no-rj-mo
3rd rowhttps://yt3.ggpht.com/a/AATXAJxUhvFQjRfD_AIF8lklez0oCCQ3JmYTtLXAOWlpQQ=s88-c-k-c0xffffffff-no-rj-mo
4th rowhttps://yt3.ggpht.com/a/AATXAJwBWZ-AIFsDSePhB9p5Uv_gmrB-MQB-TL_H9vzexA=s88-c-k-c0xffffffff-no-rj-mo
5th rowhttps://yt3.ggpht.com/a/AATXAJyKRd6UvxHfnugFJN-CaVYq9drEy0lRuwZvrK_QOQ=s88-c-k-c0xffffffff-no-rj-mo
ValueCountFrequency (%)
https://yt3.ggpht.com/a/aatxajxadvlupqzhsbhlu2jqhdqjvnvk7pgrmqmhjcqy7a=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajwjlecygvbv4-omj1nrsiz6xuc2luly9oxpgetgvq=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajywhsb0moro9cow13p0dejmobc13fnozfnqu71cqg=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajwzaam82wehkouzh9f6kvrfxl2uxl-abkhik7yygq=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajwm2iw701x-l_udwnqs1hnenm1sujpnr47m_5a2iw=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajyigtqp-egi9f63pwnglx2f3iofkhenglbcbpxsla=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajyj2o3tj0onqbx3uxpbiqu9o6djh2t-8kzdht2wda=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajx0xzoccod9pb2nzynopiy8jqh-yjt8nbtndsjbqq=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajw0he0hwd7clxvv87a3o2oeceqsqjh738dpeeh9ta=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
https://yt3.ggpht.com/a/aatxajy-xmi69kqqr2-qkhonhcifbeopxdi0qiq0loc0ng=s88-c-k-c0xffffffff-no-rj-mo 1
 
3.6%
Other values (18) 18
64.3%
2023-12-10T22:57:51.257176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 239
 
8.6%
- 187
 
6.8%
t 126
 
4.6%
/ 112
 
4.1%
o 105
 
3.8%
A 103
 
3.7%
c 100
 
3.6%
8 78
 
2.8%
m 77
 
2.8%
g 75
 
2.7%
Other values (58) 1562
56.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1439
52.1%
Uppercase Letter 620
22.4%
Decimal Number 278
 
10.1%
Other Punctuation 196
 
7.1%
Dash Punctuation 187
 
6.8%
Math Symbol 28
 
1.0%
Connector Punctuation 16
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
f 239
16.6%
t 126
 
8.8%
o 105
 
7.3%
c 100
 
6.9%
m 77
 
5.4%
g 75
 
5.2%
h 74
 
5.1%
p 74
 
5.1%
s 67
 
4.7%
n 50
 
3.5%
Other values (16) 452
31.4%
Uppercase Letter
ValueCountFrequency (%)
A 103
16.6%
J 50
 
8.1%
X 39
 
6.3%
T 35
 
5.6%
Q 32
 
5.2%
O 26
 
4.2%
P 25
 
4.0%
I 23
 
3.7%
F 20
 
3.2%
U 20
 
3.2%
Other values (16) 247
39.8%
Decimal Number
ValueCountFrequency (%)
8 78
28.1%
3 47
16.9%
0 43
15.5%
2 23
 
8.3%
7 18
 
6.5%
9 17
 
6.1%
1 16
 
5.8%
6 15
 
5.4%
5 11
 
4.0%
4 10
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 112
57.1%
. 56
28.6%
: 28
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 187
100.0%
Math Symbol
ValueCountFrequency (%)
= 28
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2059
74.5%
Common 705
 
25.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
f 239
 
11.6%
t 126
 
6.1%
o 105
 
5.1%
A 103
 
5.0%
c 100
 
4.9%
m 77
 
3.7%
g 75
 
3.6%
h 74
 
3.6%
p 74
 
3.6%
s 67
 
3.3%
Other values (42) 1019
49.5%
Common
ValueCountFrequency (%)
- 187
26.5%
/ 112
15.9%
8 78
11.1%
. 56
 
7.9%
3 47
 
6.7%
0 43
 
6.1%
= 28
 
4.0%
: 28
 
4.0%
2 23
 
3.3%
7 18
 
2.6%
Other values (6) 85
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 239
 
8.6%
- 187
 
6.8%
t 126
 
4.6%
/ 112
 
4.1%
o 105
 
3.8%
A 103
 
3.7%
c 100
 
3.6%
8 78
 
2.8%
m 77
 
2.8%
g 75
 
2.7%
Other values (58) 1562
56.5%

DC
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T22:57:51.748033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length396
Median length85.5
Mean length107.21429
Min length6

Characters and Unicode

Total characters3002
Distinct characters444
Distinct categories16 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row매일경제TV는 매일경제신문은 물론 MBN; 매경닷컴 등 매경미디어그룹의 경제; 경영 금융; 증권 부동산; 창업 등 다양한 분야의 명품 콘텐츠를 제공함과 동시에 단순히 돈을 버는 것으로 끝나는 게 아니라 삶의 질을 높이는 방송이 될 것입니다. http:www.mktv.co.kr
2nd row안녕하세요 트위치에서 방송하고 있는 백설양입니다; 더빙; 게임; 라디오를 진행하고있습니다. YouTube 백설양 채널을 구독하시면 새로 업데이트 되는 동영상의 안내를 바로 받아보실 수 있습니다 ^^
3rd row유튜브 시작 날짜 2012 . 01 . 10 96년 6월 11일생 문의 : apple3203@naver.com 여러분을 미친듯이 웃길 입담은 없지만 즐겁게 볼수있는 영상을 만들기위해 노력하겠습니다. [컴퓨터 사양] CPU i7 8700 커피레이크 RAM 32기가 VGA RTX2060
4th row모두들 개모링~★ LOL 서폿 방송 1위! 그랩;운영;한타 등등 여러가지를 알려드립니다!! 감사합니다 따랑해여~♥
5th row책 읽어주는 라디오 + 외국어 라디오 (서울 수도권 104.5MHz) 한국교육방송 EBS 라디오 공식 운영 채널 입니다
ValueCountFrequency (%)
13
 
2.2%
홀릭 6
 
1.0%
채널입니다 5
 
0.8%
사사건건 5
 
0.8%
유튜브 5
 
0.8%
다양한 5
 
0.8%
등 4
 
0.7%
전문 4
 
0.7%
안녕하세요 4
 
0.7%
ebs 4
 
0.7%
Other values (479) 535
90.7%
2023-12-10T22:57:52.680115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
621
 
20.7%
. 59
 
2.0%
다 51
 
1.7%
; 48
 
1.6%
니 41
 
1.4%
o 38
 
1.3%
e 37
 
1.2%
하 32
 
1.1%
는 30
 
1.0%
t 30
 
1.0%
Other values (434) 2015
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1564
52.1%
Space Separator 621
 
20.7%
Lowercase Letter 387
 
12.9%
Other Punctuation 154
 
5.1%
Uppercase Letter 123
 
4.1%
Decimal Number 84
 
2.8%
Other Symbol 28
 
0.9%
Open Punctuation 10
 
0.3%
Close Punctuation 10
 
0.3%
Math Symbol 7
 
0.2%
Other values (6) 14
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 51
 
3.3%
니 41
 
2.6%
하 32
 
2.0%
는 30
 
1.9%
이 29
 
1.9%
의 29
 
1.9%
한 22
 
1.4%
로 21
 
1.3%
사 20
 
1.3%
입 17
 
1.1%
Other values (348) 1272
81.3%
Lowercase Letter
ValueCountFrequency (%)
o 38
 
9.8%
e 37
 
9.6%
t 30
 
7.8%
r 27
 
7.0%
n 26
 
6.7%
a 22
 
5.7%
c 22
 
5.7%
s 21
 
5.4%
i 18
 
4.7%
w 17
 
4.4%
Other values (15) 129
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 21
17.1%
B 9
 
7.3%
S 9
 
7.3%
N 8
 
6.5%
A 8
 
6.5%
I 7
 
5.7%
K 7
 
5.7%
R 6
 
4.9%
V 6
 
4.9%
D 5
 
4.1%
Other values (14) 37
30.1%
Decimal Number
ValueCountFrequency (%)
0 23
27.4%
1 19
22.6%
2 12
14.3%
5 6
 
7.1%
3 5
 
6.0%
6 5
 
6.0%
7 4
 
4.8%
8 4
 
4.8%
4 4
 
4.8%
9 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 59
38.3%
; 48
31.2%
! 22
 
14.3%
: 12
 
7.8%
@ 7
 
4.5%
' 3
 
1.9%
? 2
 
1.3%
& 1
 
0.6%
Other Symbol
ValueCountFrequency (%)
★ 16
57.1%
☆ 10
35.7%
ⓒ 1
 
3.6%
♥ 1
 
3.6%
Math Symbol
ValueCountFrequency (%)
~ 4
57.1%
▷ 2
28.6%
+ 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 6
60.0%
[ 4
40.0%
Close Punctuation
ValueCountFrequency (%)
) 6
60.0%
] 4
40.0%
Other Number
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%
Space Separator
ValueCountFrequency (%)
621
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 6
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1564
52.1%
Common 928
30.9%
Latin 510
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 51
 
3.3%
니 41
 
2.6%
하 32
 
2.0%
는 30
 
1.9%
이 29
 
1.9%
의 29
 
1.9%
한 22
 
1.4%
로 21
 
1.3%
사 20
 
1.3%
입 17
 
1.1%
Other values (348) 1272
81.3%
Latin
ValueCountFrequency (%)
o 38
 
7.5%
e 37
 
7.3%
t 30
 
5.9%
r 27
 
5.3%
n 26
 
5.1%
a 22
 
4.3%
c 22
 
4.3%
s 21
 
4.1%
T 21
 
4.1%
i 18
 
3.5%
Other values (39) 248
48.6%
Common
ValueCountFrequency (%)
621
66.9%
. 59
 
6.4%
; 48
 
5.2%
0 23
 
2.5%
! 22
 
2.4%
1 19
 
2.0%
★ 16
 
1.7%
: 12
 
1.3%
2 12
 
1.3%
☆ 10
 
1.1%
Other values (27) 86
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1561
52.0%
ASCII 1402
46.7%
Misc Symbols 27
 
0.9%
Punctuation 4
 
0.1%
Compat Jamo 3
 
0.1%
Enclosed Alphanum 3
 
0.1%
Geometric Shapes 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
621
44.3%
. 59
 
4.2%
; 48
 
3.4%
o 38
 
2.7%
e 37
 
2.6%
t 30
 
2.1%
r 27
 
1.9%
n 26
 
1.9%
0 23
 
1.6%
a 22
 
1.6%
Other values (67) 471
33.6%
Hangul
ValueCountFrequency (%)
다 51
 
3.3%
니 41
 
2.6%
하 32
 
2.0%
는 30
 
1.9%
이 29
 
1.9%
의 29
 
1.9%
한 22
 
1.4%
로 21
 
1.3%
사 20
 
1.3%
입 17
 
1.1%
Other values (346) 1269
81.3%
Misc Symbols
ValueCountFrequency (%)
★ 16
59.3%
☆ 10
37.0%
♥ 1
 
3.7%
Punctuation
ValueCountFrequency (%)
’ 2
50.0%
‘ 2
50.0%
Geometric Shapes
ValueCountFrequency (%)
▷ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅎ 2
66.7%
ㅁ 1
33.3%
Enclosed Alphanum
ValueCountFrequency (%)
ⓒ 1
33.3%
① 1
33.3%
② 1
33.3%

CTGRY
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
M
21 
T
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowT
2nd rowM
3rd rowM
4th rowM
5th rowT

Common Values

ValueCountFrequency (%)
M 21
75.0%
T 7
 
25.0%

Length

2023-12-10T22:57:52.895131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:53.103612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 21
75.0%
t 7
 
25.0%

CHNNL_NM
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T22:57:53.405310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length7.4642857
Min length2

Characters and Unicode

Total characters209
Distinct characters97
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row매일경제TV
2nd row백설양
3rd rowYT Apple
4th row개인팟
5th rowEBS 라디오 공식 채널
ValueCountFrequency (%)
tv 3
 
7.0%
채널a 2
 
4.7%
매일경제tv 1
 
2.3%
로이조 1
 
2.3%
윰댕(yum-cast 1
 
2.3%
엠빅뉴스 1
 
2.3%
talk 1
 
2.3%
to 1
 
2.3%
me 1
 
2.3%
in 1
 
2.3%
Other values (30) 30
69.8%
2023-12-10T22:57:54.054867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
7.2%
T 12
 
5.7%
e 10
 
4.8%
n 9
 
4.3%
V 7
 
3.3%
a 7
 
3.3%
t 6
 
2.9%
B 5
 
2.4%
A 5
 
2.4%
o 5
 
2.4%
Other values (87) 128
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70
33.5%
Lowercase Letter 66
31.6%
Uppercase Letter 51
24.4%
Space Separator 15
 
7.2%
Close Punctuation 2
 
1.0%
Decimal Number 2
 
1.0%
Open Punctuation 2
 
1.0%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 4
 
5.7%
널 3
 
4.3%
채 3
 
4.3%
뉴 3
 
4.3%
비 2
 
2.9%
건 2
 
2.9%
이 2
 
2.9%
사 2
 
2.9%
빅 2
 
2.9%
디 2
 
2.9%
Other values (45) 45
64.3%
Uppercase Letter
ValueCountFrequency (%)
T 12
23.5%
V 7
13.7%
B 5
9.8%
A 5
9.8%
S 3
 
5.9%
E 3
 
5.9%
F 3
 
5.9%
O 2
 
3.9%
N 2
 
3.9%
G 2
 
3.9%
Other values (7) 7
13.7%
Lowercase Letter
ValueCountFrequency (%)
e 10
15.2%
n 9
13.6%
a 7
10.6%
t 6
9.1%
o 5
7.6%
r 5
7.6%
l 4
 
6.1%
u 3
 
4.5%
m 3
 
4.5%
i 3
 
4.5%
Other values (7) 11
16.7%
Close Punctuation
ValueCountFrequency (%)
) 1
50.0%
」 1
50.0%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 1
50.0%
「 1
50.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 117
56.0%
Hangul 70
33.5%
Common 22
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 4
 
5.7%
널 3
 
4.3%
채 3
 
4.3%
뉴 3
 
4.3%
비 2
 
2.9%
건 2
 
2.9%
이 2
 
2.9%
사 2
 
2.9%
빅 2
 
2.9%
디 2
 
2.9%
Other values (45) 45
64.3%
Latin
ValueCountFrequency (%)
T 12
 
10.3%
e 10
 
8.5%
n 9
 
7.7%
V 7
 
6.0%
a 7
 
6.0%
t 6
 
5.1%
B 5
 
4.3%
A 5
 
4.3%
o 5
 
4.3%
r 5
 
4.3%
Other values (24) 46
39.3%
Common
ValueCountFrequency (%)
15
68.2%
) 1
 
4.5%
0 1
 
4.5%
1 1
 
4.5%
- 1
 
4.5%
( 1
 
4.5%
「 1
 
4.5%
」 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137
65.6%
Hangul 70
33.5%
None 2
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
 
10.9%
T 12
 
8.8%
e 10
 
7.3%
n 9
 
6.6%
V 7
 
5.1%
a 7
 
5.1%
t 6
 
4.4%
B 5
 
3.6%
A 5
 
3.6%
o 5
 
3.6%
Other values (30) 56
40.9%
Hangul
ValueCountFrequency (%)
스 4
 
5.7%
널 3
 
4.3%
채 3
 
4.3%
뉴 3
 
4.3%
비 2
 
2.9%
건 2
 
2.9%
이 2
 
2.9%
사 2
 
2.9%
빅 2
 
2.9%
디 2
 
2.9%
Other values (45) 45
64.3%
None
ValueCountFrequency (%)
「 1
50.0%
」 1
50.0%

CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1669530
Minimum5840
Maximum37500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T22:57:54.436570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5840
5-th percentile16520
Q1102550
median240500
Q3592500
95-th percentile1147000
Maximum37500000
Range37494160
Interquartile range (IQR)489950

Descriptive statistics

Standard deviation7030011.2
Coefficient of variation (CV)4.2107726
Kurtosis27.859777
Mean1669530
Median Absolute Deviation (MAD)180000
Skewness5.272445
Sum46746840
Variance4.9421057 × 1013
MonotonicityNot monotonic
2023-12-10T22:57:54.723650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
90700 1
 
3.6%
645000 1
 
3.6%
222000 1
 
3.6%
259000 1
 
3.6%
5840 1
 
3.6%
30300 1
 
3.6%
351000 1
 
3.6%
217000 1
 
3.6%
650000 1
 
3.6%
1210000 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
5840 1
3.6%
13300 1
3.6%
22500 1
3.6%
28000 1
3.6%
30300 1
3.6%
90700 1
3.6%
98200 1
3.6%
104000 1
3.6%
106000 1
3.6%
116000 1
3.6%
ValueCountFrequency (%)
37500000 1
3.6%
1210000 1
3.6%
1030000 1
3.6%
971000 1
3.6%
781000 1
3.6%
650000 1
3.6%
645000 1
3.6%
575000 1
3.6%
476000 1
3.6%
351000 1
3.6%

READER_CO_CLSDR_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size188.0 B
False
28 
ValueCountFrequency (%)
False 28
100.0%
2023-12-10T22:57:54.973742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

ANALS_CHNNL_NATION
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
KR
23 
<NA>
5 

Length

Max length4
Median length2
Mean length2.3571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKR
2nd rowKR
3rd row<NA>
4th rowKR
5th rowKR

Common Values

ValueCountFrequency (%)
KR 23
82.1%
<NA> 5
 
17.9%

Length

2023-12-10T22:57:55.175732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:55.363524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kr 23
82.1%
na 5
 
17.9%

KWRD
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing3
Missing (%)10.7%
Memory size356.0 B
2023-12-10T22:57:55.796780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length133
Median length50
Mean length41.84
Min length5

Characters and Unicode

Total characters1046
Distinct characters282
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row매일경제TV 매일경제 MBN 특강 경제 주식 강좌 MBN골드 와우넷 한국경제 매경 투자 시황 펀드 재테크 부동산 주식투자
2nd row백설양 롤 라디오 트위치
3rd rowYT 애플
4th row모닝스페셜 ebs ebs라디오생방송 한준희의축구축구 ebs태국어 ebs라디오 야구야구 englishgogo 인도네시아어 잉글리쉬고고
5th row건담 홀릭 Gundam Holic)
ValueCountFrequency (%)
먹방 5
 
2.3%
korean 3
 
1.4%
트위치 2
 
0.9%
채널a 2
 
0.9%
채널에이 2
 
0.9%
시사 2
 
0.9%
사회 2
 
0.9%
ebs 2
 
0.9%
tekken 2
 
0.9%
뉴스 2
 
0.9%
Other values (189) 192
88.9%
2023-12-10T22:57:56.572712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
191
 
18.3%
o 32
 
3.1%
e 23
 
2.2%
a 19
 
1.8%
r 17
 
1.6%
n 17
 
1.6%
g 14
 
1.3%
스 13
 
1.2%
T 13
 
1.2%
방 13
 
1.2%
Other values (272) 694
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 526
50.3%
Lowercase Letter 207
 
19.8%
Space Separator 191
 
18.3%
Uppercase Letter 104
 
9.9%
Decimal Number 11
 
1.1%
Other Punctuation 6
 
0.6%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 13
 
2.5%
방 13
 
2.5%
이 12
 
2.3%
사 12
 
2.3%
시 12
 
2.3%
오 8
 
1.5%
송 7
 
1.3%
치 7
 
1.3%
라 7
 
1.3%
뉴 6
 
1.1%
Other values (217) 429
81.6%
Uppercase Letter
ValueCountFrequency (%)
T 13
12.5%
K 11
 
10.6%
B 8
 
7.7%
N 8
 
7.7%
E 8
 
7.7%
S 7
 
6.7%
V 6
 
5.8%
L 5
 
4.8%
A 5
 
4.8%
G 5
 
4.8%
Other values (13) 28
26.9%
Lowercase Letter
ValueCountFrequency (%)
o 32
15.5%
e 23
11.1%
a 19
 
9.2%
r 17
 
8.2%
n 17
 
8.2%
g 14
 
6.8%
s 12
 
5.8%
m 9
 
4.3%
k 8
 
3.9%
t 8
 
3.9%
Other values (12) 48
23.2%
Decimal Number
ValueCountFrequency (%)
1 3
27.3%
9 3
27.3%
8 2
18.2%
3 2
18.2%
0 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 4
66.7%
! 1
 
16.7%
' 1
 
16.7%
Space Separator
ValueCountFrequency (%)
191
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 524
50.1%
Latin 311
29.7%
Common 209
 
20.0%
Han 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 13
 
2.5%
방 13
 
2.5%
이 12
 
2.3%
사 12
 
2.3%
시 12
 
2.3%
오 8
 
1.5%
송 7
 
1.3%
치 7
 
1.3%
라 7
 
1.3%
뉴 6
 
1.1%
Other values (215) 427
81.5%
Latin
ValueCountFrequency (%)
o 32
 
10.3%
e 23
 
7.4%
a 19
 
6.1%
r 17
 
5.5%
n 17
 
5.5%
g 14
 
4.5%
T 13
 
4.2%
s 12
 
3.9%
K 11
 
3.5%
m 9
 
2.9%
Other values (35) 144
46.3%
Common
ValueCountFrequency (%)
191
91.4%
. 4
 
1.9%
1 3
 
1.4%
9 3
 
1.4%
8 2
 
1.0%
3 2
 
1.0%
0 1
 
0.5%
! 1
 
0.5%
) 1
 
0.5%
' 1
 
0.5%
Han
ValueCountFrequency (%)
拳 1
50.0%
鐵 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 524
50.1%
ASCII 520
49.7%
CJK 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191
36.7%
o 32
 
6.2%
e 23
 
4.4%
a 19
 
3.7%
r 17
 
3.3%
n 17
 
3.3%
g 14
 
2.7%
T 13
 
2.5%
s 12
 
2.3%
K 11
 
2.1%
Other values (45) 171
32.9%
Hangul
ValueCountFrequency (%)
스 13
 
2.5%
방 13
 
2.5%
이 12
 
2.3%
사 12
 
2.3%
시 12
 
2.3%
오 8
 
1.5%
송 7
 
1.3%
치 7
 
1.3%
라 7
 
1.3%
뉴 6
 
1.1%
Other values (215) 427
81.5%
CJK
ValueCountFrequency (%)
拳 1
50.0%
鐵 1
50.0%

VIDO_ID
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing2
Missing (%)7.1%
Memory size356.0 B
2023-12-10T22:57:56.919794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters286
Distinct characters63
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

Unique26 ?
Unique (%)100.0%

Sample

1st rowF-msd6tV5_M
2nd rowriATxq431k4
3rd rowOx_BNMphZ8U
4th row3Jl1RCE2PaA
5th rowFgNYsrZ6VQw
ValueCountFrequency (%)
gdzli9ownzg 1
 
3.8%
ox_bnmphz8u 1
 
3.8%
pdxfkae7s4y 1
 
3.8%
0smwnunrgc 1
 
3.8%
4yi2jdt__yk 1
 
3.8%
cqgiaioofsw 1
 
3.8%
n3biichtoz4 1
 
3.8%
vkd1wnqx_eg 1
 
3.8%
bil0x4c_g0o 1
 
3.8%
bptbmwlhxju 1
 
3.8%
Other values (16) 16
61.5%
2023-12-10T22:57:57.808537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
 
3.8%
g 9
 
3.1%
U 9
 
3.1%
k 9
 
3.1%
W 8
 
2.8%
0 8
 
2.8%
i 7
 
2.4%
o 7
 
2.4%
N 7
 
2.4%
_ 7
 
2.4%
Other values (53) 204
71.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 125
43.7%
Lowercase Letter 107
37.4%
Decimal Number 44
 
15.4%
Connector Punctuation 7
 
2.4%
Dash Punctuation 3
 
1.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 9
 
7.2%
W 8
 
6.4%
N 7
 
5.6%
M 7
 
5.6%
Z 7
 
5.6%
S 6
 
4.8%
R 6
 
4.8%
G 6
 
4.8%
E 6
 
4.8%
L 6
 
4.8%
Other values (16) 57
45.6%
Lowercase Letter
ValueCountFrequency (%)
g 9
 
8.4%
k 9
 
8.4%
i 7
 
6.5%
o 7
 
6.5%
b 5
 
4.7%
y 5
 
4.7%
w 5
 
4.7%
j 5
 
4.7%
s 5
 
4.7%
p 4
 
3.7%
Other values (15) 46
43.0%
Decimal Number
ValueCountFrequency (%)
4 11
25.0%
0 8
18.2%
6 5
11.4%
1 5
11.4%
5 4
 
9.1%
2 4
 
9.1%
3 3
 
6.8%
7 2
 
4.5%
9 1
 
2.3%
8 1
 
2.3%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 232
81.1%
Common 54
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 9
 
3.9%
U 9
 
3.9%
k 9
 
3.9%
W 8
 
3.4%
i 7
 
3.0%
o 7
 
3.0%
N 7
 
3.0%
M 7
 
3.0%
Z 7
 
3.0%
S 6
 
2.6%
Other values (41) 156
67.2%
Common
ValueCountFrequency (%)
4 11
20.4%
0 8
14.8%
_ 7
13.0%
6 5
9.3%
1 5
9.3%
5 4
 
7.4%
2 4
 
7.4%
3 3
 
5.6%
- 3
 
5.6%
7 2
 
3.7%
Other values (2) 2
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11
 
3.8%
g 9
 
3.1%
U 9
 
3.1%
k 9
 
3.1%
W 8
 
2.8%
0 8
 
2.8%
i 7
 
2.4%
o 7
 
2.4%
N 7
 
2.4%
_ 7
 
2.4%
Other values (53) 204
71.3%

VIDO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4019.1786
Minimum993
Maximum36061
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T22:57:58.056255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum993
5-th percentile1048.15
Q11382.5
median2063.5
Q33316.25
95-th percentile11624.6
Maximum36061
Range35068
Interquartile range (IQR)1933.75

Descriptive statistics

Standard deviation6821.3853
Coefficient of variation (CV)1.6972088
Kurtosis19.407526
Mean4019.1786
Median Absolute Deviation (MAD)929.5
Skewness4.2338012
Sum112537
Variance46531298
MonotonicityNot monotonic
2023-12-10T22:57:58.315313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3482 1
 
3.6%
2405 1
 
3.6%
1067 1
 
3.6%
2887 1
 
3.6%
1284 1
 
3.6%
4035 1
 
3.6%
1461 1
 
3.6%
1100 1
 
3.6%
14195 1
 
3.6%
1038 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
993 1
3.6%
1038 1
3.6%
1067 1
3.6%
1100 1
3.6%
1119 1
3.6%
1284 1
3.6%
1306 1
3.6%
1408 1
3.6%
1461 1
3.6%
1470 1
3.6%
ValueCountFrequency (%)
36061 1
3.6%
14195 1
3.6%
6851 1
3.6%
6195 1
3.6%
4035 1
3.6%
3597 1
3.6%
3482 1
3.6%
3261 1
3.6%
3126 1
3.6%
2978 1
3.6%

CHNNL_ANALS_RDCNT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7427663 × 108
Minimum1641805
Maximum5.2469891 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T22:57:58.578902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1641805
5-th percentile4727908.5
Q135587767
median1.1181399 × 108
Q33.5403408 × 108
95-th percentile8.4983289 × 108
Maximum5.2469891 × 109
Range5.2453473 × 109
Interquartile range (IQR)3.1844632 × 108

Descriptive statistics

Standard deviation9.8303102 × 108
Coefficient of variation (CV)2.6264825
Kurtosis24.584856
Mean3.7427663 × 108
Median Absolute Deviation (MAD)92397050
Skewness4.8433563
Sum1.0479746 × 1010
Variance9.6634999 × 1017
MonotonicityNot monotonic
2023-12-10T22:57:58.817729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
7914792 1
 
3.6%
437039222 1
 
3.6%
107336949 1
 
3.6%
129165036 1
 
3.6%
4329353 1
 
3.6%
27347658 1
 
3.6%
116291034 1
 
3.6%
81107028 1
 
3.6%
502891410 1
 
3.6%
556762863 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1641805 1
3.6%
4329353 1
3.6%
5468083 1
3.6%
7914792 1
3.6%
12049923 1
3.6%
27347658 1
3.6%
29811072 1
3.6%
37513332 1
3.6%
45310065 1
3.6%
48559642 1
3.6%
ValueCountFrequency (%)
5246989095 1
3.6%
1007639835 1
3.6%
556762863 1
3.6%
511711756 1
3.6%
502891410 1
3.6%
437039222 1
3.6%
360278976 1
3.6%
351952451 1
3.6%
223842569 1
3.6%
196844024 1
3.6%

Interactions

2023-12-10T22:57:46.002584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:44.760642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:45.291566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:46.162130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:44.905925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:45.585088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:46.320783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:45.066053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:45.870498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:57:58.981274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
PATHCREAT_DAYICON_NMDCCTGRYCHNNL_NMCOKWRDVIDO_IDVIDOCHNNL_ANALS_RDCNT
PATH1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
CREAT_DAY1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
ICON_NM1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
DC1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
CTGRY1.0001.0001.0001.0001.0001.0000.0001.0001.0000.5670.000
CHNNL_NM1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
CO1.0001.0001.0001.0000.0001.0001.0001.0001.0000.0001.000
KWRD1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
VIDO_ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
VIDO1.0001.0001.0001.0000.5671.0000.0001.0001.0001.0000.000
CHNNL_ANALS_RDCNT1.0001.0001.0001.0000.0001.0001.0001.0001.0000.0001.000
2023-12-10T22:57:59.406053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CTGRYANALS_CHNNL_NATION
CTGRY1.0001.000
ANALS_CHNNL_NATION1.0001.000
2023-12-10T22:57:59.553675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
COVIDOCHNNL_ANALS_RDCNTCTGRYANALS_CHNNL_NATION
CO1.000-0.0210.8810.0001.000
VIDO-0.0211.0000.1800.3741.000
CHNNL_ANALS_RDCNT0.8810.1801.0000.0001.000
CTGRY0.0000.3740.0001.0001.000
ANALS_CHNNL_NATION1.0001.0001.0001.0001.000

Missing values

2023-12-10T22:57:46.535261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:57:46.879692image/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.
2023-12-10T22:57:47.078458image/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

PATHCOLCT_DAYCREAT_DAYICON_NMDCCTGRYCHNNL_NMCOREADER_CO_CLSDR_ATANALS_CHNNL_NATIONKWRDVIDO_IDVIDOCHNNL_ANALS_RDCNT
0https://www.youtube.com/channel/UCnfwIKyFYRuqZzzKBDt6JOA2020-10-012018-10-23https://yt3.ggpht.com/a/AATXAJxaDVlUPqZHSbhlU2JqHDqjvnvK7PGRMQmhjCqy7A=s88-c-k-c0xffffffff-no-rj-mo매일경제TV는 매일경제신문은 물론 MBN; 매경닷컴 등 매경미디어그룹의 경제; 경영 금융; 증권 부동산; 창업 등 다양한 분야의 명품 콘텐츠를 제공함과 동시에 단순히 돈을 버는 것으로 끝나는 게 아니라 삶의 질을 높이는 방송이 될 것입니다. http:www.mktv.co.krT매일경제TV90700FalseKR매일경제TV 매일경제 MBN 특강 경제 주식 강좌 MBN골드 와우넷 한국경제 매경 투자 시황 펀드 재테크 부동산 주식투자F-msd6tV5_M34827914792
1https://www.youtube.com/channel/UCQPPzb7y4aJz6VV1F3v066g2020-10-012011-09-25https://yt3.ggpht.com/a/AATXAJwJlecYgVbv4-omj1nRSiz6XUc2LULY9oxpgetGVQ=s88-c-k-c0xffffffff-no-rj-mo안녕하세요 트위치에서 방송하고 있는 백설양입니다; 더빙; 게임; 라디오를 진행하고있습니다. YouTube 백설양 채널을 구독하시면 새로 업데이트 되는 동영상의 안내를 바로 받아보실 수 있습니다 ^^M백설양106000FalseKR백설양 롤 라디오 트위치riATxq431k4140851968420
2https://www.youtube.com/channel/UCmcd3r7AsHjm3deMgx1ZPiw2020-10-012011-12-30https://yt3.ggpht.com/a/AATXAJxUhvFQjRfD_AIF8lklez0oCCQ3JmYTtLXAOWlpQQ=s88-c-k-c0xffffffff-no-rj-mo유튜브 시작 날짜 2012 . 01 . 10 96년 6월 11일생 문의 : apple3203@naver.com 여러분을 미친듯이 웃길 입담은 없지만 즐겁게 볼수있는 영상을 만들기위해 노력하겠습니다. [컴퓨터 사양] CPU i7 8700 커피레이크 RAM 32기가 VGA RTX2060MYT Apple329000False<NA>YT 애플Ox_BNMphZ8U2254152320111
3https://www.youtube.com/channel/UCIBoeAMqlic3emU6_crV9Vw2020-10-012013-05-25https://yt3.ggpht.com/a/AATXAJwBWZ-AIFsDSePhB9p5Uv_gmrB-MQB-TL_H9vzexA=s88-c-k-c0xffffffff-no-rj-mo모두들 개모링~★ LOL 서폿 방송 1위! 그랩;운영;한타 등등 여러가지를 알려드립니다!! 감사합니다 따랑해여~♥M개인팟117000FalseKR<NA>3Jl1RCE2PaA156629811072
4https://www.youtube.com/channel/UCNjQBiTSdoj2tCQLBGXFksw2020-10-012019-03-15https://yt3.ggpht.com/a/AATXAJyKRd6UvxHfnugFJN-CaVYq9drEy0lRuwZvrK_QOQ=s88-c-k-c0xffffffff-no-rj-mo책 읽어주는 라디오 + 외국어 라디오 (서울 수도권 104.5MHz) 한국교육방송 EBS 라디오 공식 운영 채널 입니다TEBS 라디오 공식 채널22500FalseKR모닝스페셜 ebs ebs라디오생방송 한준희의축구축구 ebs태국어 ebs라디오 야구야구 englishgogo 인도네시아어 잉글리쉬고고FgNYsrZ6VQw11191641805
5https://www.youtube.com/channel/UC1MQ-3B7gRmyeAzBtt-GAUA2020-10-012013-02-27https://yt3.ggpht.com/a/AATXAJwQay6pcL7LYoJjpUmiLP7GZLiWAv-mgwF9l21lPw=s88-c-k-c0xffffffff-no-rj-mo취미 전문 스타트업 원티비넷 (OneTvNet) 에서 제공하는 하비 전문 방송 서비스 채널 입니다. 건담비건담 (레고또봇 포함) 프라모델에서 완성품까지 여러 신제품기존 제품 리뷰; 한정판 리뷰; 3D 스핀; LBX 커스터 마이징 등 다양한 컨텐츠를 재미있고 알차게 준비하여 꾸준히 업로드 하도록 하겠습니다. 또한; 저희 건담 홀릭 패밀리 채널인 슈퍼 히어로 홀릭; 피규어 홀릭; 페이퍼 홀릭; 펫 홀릭 (반려 동물) 등 다양한 취미 관련 방송 채널도 많은 관심과 성원; 구독 부탁 드립니다. 감사합니다.. ^^ 2015년 722(수) 건담 홀릭 구독자 27;000명 달성..!! 진심으로 감사의 말씀 올립니다. 앞으로도 겸허한 마음과 초심을 잃지 않는 최상의 서비스를 만들고자 최선을 다 하겠습니다.MGundam Holic TV173000FalseKR건담 홀릭 Gundam Holic)aI6q0QmR2GM6851143616237
6https://www.youtube.com/channel/UCB-ogYCX9Me8nP9gEGpMjUg2020-10-012012-05-17https://yt3.ggpht.com/a/AATXAJwYhu7Uo1P6HAx-HjOBo2znsZgDhw2l8K_Nm3-jIQ=s88-c-k-c0xffffffff-no-rj-mo동아미디어그룹 종합편성 TV 채널A 예능 프로그램T채널A Entertainment315000False<NA>채널A 채널에이 채널A예능 개밥남 개밥주는남자 오쾌남 오!쾌남 이만갑 이제만나러갑니다 아빠본색 하트시그널 밥한번먹자 풍문으로들었쇼 외부자들 나는몸신이다oFUboVESHhM36061360278976
7https://www.youtube.com/channel/UCN3RfsR18gsH8PLI6R6PYSQ2020-10-012014-07-15https://yt3.ggpht.com/a/AATXAJw1-N_gdMjSvNBb4WVY9JF2QmqUUmTJy46NIDpaZA=s88-c-k-c0xffffffff-no-rj-mo한국교육방송공사 EBS 뉴스 채널입니다. EBS 뉴스의 TV 방송시간은 월~금 낮 12시; 저녁 5시입니다. Republic of Korea's station EBS; NewsT뉴스EBS13300FalseKREBS NEWSKgFr6ULl7ag359712049923
8https://www.youtube.com/channel/UCL784ga_3vTDUpEZxgveRNQ2020-10-012014-03-26https://yt3.ggpht.com/a/AATXAJyYXrPmYZy8D3ozOmQ1XWdsbkI2g6IfdwP2_3Iu=s88-c-k-c0xffffffff-no-rj-mo맛집을 비롯해서 편의점; 대형마트; 인터넷 쇼핑몰; 전통시장; 배달음식; 패스트푸드; 집에서 만들어 먹는 음식; 어머니가 해주시는 음식 등의 정보를 소개하는 채널입니다. 먹방은 조카가 맛있게 먹는 모습 정도는 보여드리지만; 먹방은 아니고; 평소의 일상생활속에서 제가 구입해서 먹는 다양한 음식의 정보를 소개하면서 개인적인 평가를 내리는데; 참고하셔서 다양한 식품 음식 선택에 조금이나마 도움이 되셨으면 좋겠습니다. 별점으로 개인적인 평가도 내리는데; 주관적이고 개인적인 취향의 평가이니 참고만 하시길 바라겠습니다. ★★★★★ 강력추천 ★★★★☆ 괜찮고; 재구매 의사 있음 ★★★☆☆ 괜찮지만; 재구매 의사는 없음 ★★☆☆☆ 별로 ★☆☆☆☆ 아주 마음에 안듬M단비스 Food104000FalseKR단비스푸드 단비스Food 단비스 먹방 연서 먹방LkyHe0ETGzs619582042986
9https://www.youtube.com/channel/UCWMK0idJDBqwpueUiEXStCQ2020-10-012014-12-16https://yt3.ggpht.com/a/AATXAJwHovOwoydz1W7dE-6nOs_jGgAwZN-C0OKzs5yP3A=s88-c-k-c0xffffffff-no-rj-mo전역....M저펄이116000FalseKR저스트펄슨 저펄 게리모드 Gmod JustPerson Garry's Mod 울산큰고래MNusWQQvj4g99345310065
PATHCOLCT_DAYCREAT_DAYICON_NMDCCTGRYCHNNL_NMCOREADER_CO_CLSDR_ATANALS_CHNNL_NATIONKWRDVIDO_IDVIDOCHNNL_ANALS_RDCNT
18https://www.youtube.com/channel/UC5r3WHrX4Z7peSYpDlgktGw2020-10-012009-07-21https://yt3.ggpht.com/a/AATXAJyBKartVqnC4OS3SS7zPDcsWjJbwcQw0ukFMhtPKA=s88-c-k-c0xffffffff-no-rj-moWe connect people through Korean lessons and cultural videos. Check out our Korean lessons at http:TalkToMeInKorean.com !!!MTalk To Me In Korean971000FalseKR한국 한국말 배우기 학습 교재 Learn Korean Korean Language Korean South Korea0KnUyy6pH-U164148559642
19https://www.youtube.com/channel/UC31Gc42xzclOOi5Gp1xIpZw2020-10-012014-02-04https://yt3.ggpht.com/a/AATXAJy-xMI69kqqR2-qkHONHcIfBeopxDI0qIQ0loc0ng=s88-c-k-c0xffffffff-no-rj-mo‘책으로 여는IT세상’을 모토로 IT전문가를 위한 프로그래밍; 컴퓨터공학; IT 에세이; eBook 리얼타임(전자책)과 일반 독자를 위한 IT활용서; 실용서를 출간하고 있습니다.M한빛미디어28000FalseKR책 technology IT book programming 개발자 프로그래머 programmer techBptbmwLHXjU16305468083
20https://www.youtube.com/channel/UCem8l1w4OWhkqpoOg1SB4_w2020-10-012014-05-19https://yt3.ggpht.com/a/AATXAJw0He0hwD7ClxvV87A3O2OecEQsqJh738DpeEh9tA=s88-c-k-c0xffffffff-no-rj-mo걍 구독한번하고 영상 하나만보세요 오늘 제 영상 다봅니다 마약같은 재넌 유튜브 구독하면 개이득이??! 알리미 설정 꼭하삼 5분이하면 슬픈 재넌영상 10분이상은 컨텐츠 노잼영상M재넌Jaenune1210000FalseKR재넌 작비 공대생 꽈뚜룹 참교육 투보 악녀 먹방 몰카 몰래카메라 웃긴영상 웃음 개그 보물섬 보따 송대익 조재원 김유이bIl0x4c_g0o1038556762863
21https://www.youtube.com/channel/UCIIpmDPVk7nzNHEUSHmvkUg2020-10-012014-02-26https://yt3.ggpht.com/a/AATXAJx0xZocCOd9Pb2NZynOPiy8jQH-YJt8nbtnDSjBqQ=s88-c-k-c0xffffffff-no-rj-mo매일 오후 5시 40분; 채널A '뉴스TOP10' 공식 유튜브T채널A 뉴스TOP10650000False<NA>채널에이 채널A 뉴스탑텐 뉴스TOP10 뉴스 사회 정치 시사 스포츠 김승련앵커 앵커 김승련 박종진 쾌도난마 대담vkD1WNqx_Eg14195502891410
22https://www.youtube.com/channel/UCTZPZo3xuW5k6RkhlVaJ0jQ2020-10-012014-07-31https://yt3.ggpht.com/a/AATXAJyJ2O3tJ0OnQBX3UXPBIqU9o6DJh2T-8KzdhT2WdA=s88-c-k-c0xffffffff-no-rj-mo안녕하세요. 조용한돌아이 김뚜띠의 유튜브 채널입니다 매일 업로드됩니다! 좋아요 구독버튼눌러주세요!M김뚜띠217000False<NA><NA>N3bIiCHTOZ4110081107028
23https://www.youtube.com/channel/UC7bcRlidTERRb_MKRHPVSnw2020-10-012014-10-30https://yt3.ggpht.com/a/AATXAJyiGtQP-egi9f63PwnglX2F3iOfkHENglbCBPxSlA=s88-c-k-c0xffffffff-no-rj-mo세상의 모든걸 대신 공략해주는 남자 푸린입니다^ㅁ^ 개인메일:kmb1000@naver.com 광고문의:biz@pixelnetwork.co.kr ▷ 생방송 https:www.twitch.tvrngudwnswkd ▷ 인스타그램 https:www.instagram.compurin_26M푸린351000FalseKR고인물 공략 공포게임 SPEED RUN 공포CqGiAIoOFSw1461116291034
24https://www.youtube.com/channel/UCfnSBW9u_I1ZKtT86zjLewg2020-10-012011-12-19https://yt3.ggpht.com/a/AATXAJwm2IW701x-L_UdwnqS1hNenm1sUjpnR47m_5A2Iw=s88-c-k-c0xffffffff-no-rj-moTAKTAK1893;JDCR;SAINT;JEONDDING의 철권관련 유투브 채널입니다.MBattleFinger30300FalseKRTEKKEN. taktak1893. 탁탁1893. 철권. 鐵拳4yI2jDT__Yk403527347658
25https://www.youtube.com/channel/UC2tGWq3BCZUDAgNh965yM-A2020-10-012013-08-19https://yt3.ggpht.com/a/AATXAJwzAaM82WEhkouZH9F6kvRFxL2UxL-AbKHik7YygQ=s88-c-k-c0xffffffff-no-rj-mo철권 관련 영상 채널입니다.M파쇄축5840FalseKR파쇄축 TEKKEN 철권 풍신류 9RKLK vkthocnr-0SMWnUnRgc12844329353
26https://www.youtube.com/channel/UCfiCVvy-jRTQH1EpPPntpfw2020-10-012013-05-27https://yt3.ggpht.com/a/AATXAJyWHsB0Moro9Cow13P0deJMOBC13FNOZFNqU71Cqg=s88-c-k-c0xffffffff-no-rj-mo즐거움과 감동이 넘치는 건강한 콘텐츠를 통해 보다 풍요로운 내일을 만들어 가는 No.1 미디어그룹 berrymedia.co.krMBerryTV259000FalseKRGTV DreamTV CookTV 생활체육TV 베리미디어 베리TV<NA>2887129165036
27https://www.youtube.com/channel/UCQreDC73rqiw1wSc_ZYwgHA2020-10-012013-06-13https://yt3.ggpht.com/a/AATXAJwA1KFeI0Fw5GqroiBl58OwytwaWME5KOMlIg-mqg=s88-c-k-c0xffffffff-no-rj-mo한국 마인크래프트 괴담; 정보 전문 유튜버 블루위키!! 구독과 좋아요 감사합니다!MTV블루위키222000FalseKR<NA>tkWrv4MSuWw1067107336949