Overview

Dataset statistics

Number of variables7
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory64.4 B

Variable types

Text2
Categorical1
Numeric4

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/2d22fcf9-459f-4328-8593-b2617e724b94

Alerts

참여영상수집일자 has constant value ""Constant
수 is highly overall correlated with 참여영상좋아요수 and 2 other fieldsHigh correlation
참여영상좋아요수 is highly overall correlated with 수 and 2 other fieldsHigh correlation
참여영상싫어요수 is highly overall correlated with 수 and 2 other fieldsHigh correlation
참여영상시청수 is highly overall correlated with 수 and 2 other fieldsHigh correlation
참여영상경로명 has unique valuesUnique
참여영상시청수 has unique valuesUnique
수 has 9 (30.0%) zerosZeros
참여영상좋아요수 has 7 (23.3%) zerosZeros
참여영상싫어요수 has 13 (43.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:16:27.464146
Analysis finished2023-12-10 14:16:31.389106
Duration3.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

참여영상경로명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:16:31.713509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters1290
Distinct characters69
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

Unique30 ?
Unique (%)100.0%

Sample

1st rowhttps://www.youtube.com/watch?v=3kfO9PJX6Bc
2nd rowhttps://www.youtube.com/watch?v=zQ7lF1wEZEk
3rd rowhttps://www.youtube.com/watch?v=6lZhmyhCf4o
4th rowhttps://www.youtube.com/watch?v=S31j0lVWW_Y
5th rowhttps://www.youtube.com/watch?v=B7Mt6YdVwOU
ValueCountFrequency (%)
https://www.youtube.com/watch?v=3kfo9pjx6bc 1
 
3.3%
https://www.youtube.com/watch?v=zq7lf1wezek 1
 
3.3%
https://www.youtube.com/watch?v=wnw93on8i9g 1
 
3.3%
https://www.youtube.com/watch?v=kasciujr1ha 1
 
3.3%
https://www.youtube.com/watch?v=dok8qprt4gm 1
 
3.3%
https://www.youtube.com/watch?v=hecruthly4i 1
 
3.3%
https://www.youtube.com/watch?v=3memou_s14i 1
 
3.3%
https://www.youtube.com/watch?v=igdturrw_wy 1
 
3.3%
https://www.youtube.com/watch?v=e8os9iwqexa 1
 
3.3%
https://www.youtube.com/watch?v=3a9onermvo4 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:16:32.498026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 128
 
9.9%
t 123
 
9.5%
/ 90
 
7.0%
h 68
 
5.3%
o 67
 
5.2%
c 66
 
5.1%
u 62
 
4.8%
. 60
 
4.7%
s 37
 
2.9%
e 35
 
2.7%
Other values (59) 554
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 843
65.3%
Other Punctuation 210
 
16.3%
Uppercase Letter 144
 
11.2%
Decimal Number 56
 
4.3%
Math Symbol 30
 
2.3%
Connector Punctuation 6
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 128
15.2%
t 123
14.6%
h 68
 
8.1%
o 67
 
7.9%
c 66
 
7.8%
u 62
 
7.4%
s 37
 
4.4%
e 35
 
4.2%
a 34
 
4.0%
m 34
 
4.0%
Other values (16) 189
22.4%
Uppercase Letter
ValueCountFrequency (%)
E 13
 
9.0%
W 10
 
6.9%
A 9
 
6.2%
M 9
 
6.2%
O 8
 
5.6%
I 7
 
4.9%
Y 7
 
4.9%
C 7
 
4.9%
D 6
 
4.2%
Z 6
 
4.2%
Other values (16) 62
43.1%
Decimal Number
ValueCountFrequency (%)
4 10
17.9%
3 9
16.1%
1 7
12.5%
9 7
12.5%
8 5
8.9%
2 5
8.9%
6 5
8.9%
7 3
 
5.4%
0 3
 
5.4%
5 2
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
: 30
 
14.3%
? 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 987
76.5%
Common 303
 
23.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 128
 
13.0%
t 123
 
12.5%
h 68
 
6.9%
o 67
 
6.8%
c 66
 
6.7%
u 62
 
6.3%
s 37
 
3.7%
e 35
 
3.5%
a 34
 
3.4%
m 34
 
3.4%
Other values (42) 333
33.7%
Common
ValueCountFrequency (%)
/ 90
29.7%
. 60
19.8%
= 30
 
9.9%
: 30
 
9.9%
? 30
 
9.9%
4 10
 
3.3%
3 9
 
3.0%
1 7
 
2.3%
9 7
 
2.3%
_ 6
 
2.0%
Other values (7) 24
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 128
 
9.9%
t 123
 
9.5%
/ 90
 
7.0%
h 68
 
5.3%
o 67
 
5.2%
c 66
 
5.1%
u 62
 
4.8%
. 60
 
4.7%
s 37
 
2.9%
e 35
 
2.7%
Other values (59) 554
42.9%

참여영상수집일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-02-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-01
2nd row2021-02-01
3rd row2021-02-01
4th row2021-02-01
5th row2021-02-01

Common Values

ValueCountFrequency (%)
2021-02-01 30
100.0%

Length

2023-12-10T23:16:32.747074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:16:32.959024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-01 30
100.0%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.3
Minimum0
Maximum775
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:33.138213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median13.5
Q393.5
95-th percentile555.15
Maximum775
Range775
Interquartile range (IQR)93.5

Descriptive statistics

Standard deviation194.0322
Coefficient of variation (CV)2.0360146
Kurtosis7.8673664
Mean95.3
Median Absolute Deviation (MAD)13.5
Skewness2.8665966
Sum2859
Variance37648.493
MonotonicityNot monotonic
2023-12-10T23:16:33.345788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 9
30.0%
9 2
 
6.7%
4 2
 
6.7%
110 1
 
3.3%
8 1
 
3.3%
34 1
 
3.3%
723 1
 
3.3%
43 1
 
3.3%
12 1
 
3.3%
15 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
0 9
30.0%
4 2
 
6.7%
8 1
 
3.3%
9 2
 
6.7%
12 1
 
3.3%
15 1
 
3.3%
24 1
 
3.3%
31 1
 
3.3%
34 1
 
3.3%
43 1
 
3.3%
ValueCountFrequency (%)
775 1
3.3%
723 1
3.3%
350 1
3.3%
227 1
3.3%
132 1
3.3%
114 1
3.3%
110 1
3.3%
100 1
3.3%
74 1
3.3%
61 1
3.3%

참여영상좋아요수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean880.9
Minimum0
Maximum10088
Zeros7
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:33.594059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.75
median56.5
Q31309.5
95-th percentile3158.8
Maximum10088
Range10088
Interquartile range (IQR)1306.75

Descriptive statistics

Standard deviation1978.2598
Coefficient of variation (CV)2.2457258
Kurtosis16.750569
Mean880.9
Median Absolute Deviation (MAD)56.5
Skewness3.7913217
Sum26427
Variance3913512
MonotonicityNot monotonic
2023-12-10T23:16:33.797323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 7
23.3%
12 2
 
6.7%
3247 1
 
3.3%
101 1
 
3.3%
84 1
 
3.3%
24 1
 
3.3%
10088 1
 
3.3%
1664 1
 
3.3%
2 1
 
3.3%
98 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
0 7
23.3%
2 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%
12 2
 
6.7%
16 1
 
3.3%
24 1
 
3.3%
29 1
 
3.3%
84 1
 
3.3%
87 1
 
3.3%
ValueCountFrequency (%)
10088 1
3.3%
3247 1
3.3%
3051 1
3.3%
1824 1
3.3%
1788 1
3.3%
1699 1
3.3%
1664 1
3.3%
1616 1
3.3%
390 1
3.3%
334 1
3.3%

참여영상싫어요수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.7
Minimum0
Maximum381
Zeros13
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:34.012386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315.75
95-th percentile213.15
Maximum381
Range381
Interquartile range (IQR)15.75

Descriptive statistics

Standard deviation91.138451
Coefficient of variation (CV)2.7044051
Kurtosis11.39582
Mean33.7
Median Absolute Deviation (MAD)2
Skewness3.4828704
Sum1011
Variance8306.2172
MonotonicityNot monotonic
2023-12-10T23:16:34.235266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 13
43.3%
52 2
 
6.7%
5 2
 
6.7%
2 2
 
6.7%
49 1
 
3.3%
381 1
 
3.3%
19 1
 
3.3%
11 1
 
3.3%
15 1
 
3.3%
16 1
 
3.3%
Other values (5) 5
 
16.7%
ValueCountFrequency (%)
0 13
43.3%
1 1
 
3.3%
2 2
 
6.7%
5 2
 
6.7%
6 1
 
3.3%
7 1
 
3.3%
11 1
 
3.3%
15 1
 
3.3%
16 1
 
3.3%
19 1
 
3.3%
ValueCountFrequency (%)
381 1
3.3%
345 1
3.3%
52 2
6.7%
49 1
3.3%
43 1
3.3%
19 1
3.3%
16 1
3.3%
15 1
3.3%
11 1
3.3%
7 1
3.3%

참여영상시청수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118585.47
Minimum30
Maximum1395428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:34.465988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile72.15
Q11040.5
median4406
Q353614.75
95-th percentile795481.9
Maximum1395428
Range1395398
Interquartile range (IQR)52574.25

Descriptive statistics

Standard deviation319566.82
Coefficient of variation (CV)2.6948228
Kurtosis11.246587
Mean118585.47
Median Absolute Deviation (MAD)4333.5
Skewness3.4137443
Sum3557564
Variance1.0212296 × 1011
MonotonicityNot monotonic
2023-12-10T23:16:35.057809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
427434 1
 
3.3%
126447 1
 
3.3%
4623 1
 
3.3%
4189 1
 
3.3%
1395428 1
 
3.3%
3278 1
 
3.3%
80738 1
 
3.3%
111 1
 
3.3%
3715 1
 
3.3%
110 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
30 1
3.3%
69 1
3.3%
76 1
3.3%
110 1
3.3%
111 1
3.3%
259 1
3.3%
382 1
3.3%
875 1
3.3%
1537 1
3.3%
2625 1
3.3%
ValueCountFrequency (%)
1395428 1
3.3%
1096612 1
3.3%
427434 1
3.3%
126447 1
3.3%
109193 1
3.3%
94709 1
3.3%
80738 1
3.3%
55849 1
3.3%
46912 1
3.3%
26534 1
3.3%

영상영상채널명
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:16:35.430191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length11.166667
Min length3

Characters and Unicode

Total characters335
Distinct characters91
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

Unique26 ?
Unique (%)86.7%

Sample

1st row런닝맨 - 스브스 공식 채널
2nd rowSBS NOW SBS 공식 채널
3rd rowMBN Entertainment
4th row모비딕 Mobidic
5th row트박스 Twitch clips box
ValueCountFrequency (%)
kbs 6
 
9.0%
채널 3
 
4.5%
entertainment 3
 
4.5%
news 3
 
4.5%
jtbc 2
 
3.0%
2
 
3.0%
sbs 2
 
3.0%
tv 2
 
3.0%
공식 2
 
3.0%
mbckpop 2
 
3.0%
Other values (40) 40
59.7%
2023-12-10T23:16:36.418168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
11.3%
B 17
 
5.1%
S 13
 
3.9%
e 13
 
3.9%
o 11
 
3.3%
i 10
 
3.0%
t 10
 
3.0%
n 10
 
3.0%
T 9
 
2.7%
r 9
 
2.7%
Other values (81) 195
58.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 117
34.9%
Uppercase Letter 114
34.0%
Other Letter 61
18.2%
Space Separator 38
 
11.3%
Dash Punctuation 3
 
0.9%
Other Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
널 4
 
6.6%
채 4
 
6.6%
스 4
 
6.6%
마 2
 
3.3%
브 2
 
3.3%
공 2
 
3.3%
트 2
 
3.3%
식 2
 
3.3%
선 2
 
3.3%
파 2
 
3.3%
Other values (35) 35
57.4%
Lowercase Letter
ValueCountFrequency (%)
e 13
11.1%
o 11
 
9.4%
i 10
 
8.5%
t 10
 
8.5%
n 10
 
8.5%
r 9
 
7.7%
a 8
 
6.8%
p 8
 
6.8%
s 5
 
4.3%
m 5
 
4.3%
Other values (12) 28
23.9%
Uppercase Letter
ValueCountFrequency (%)
B 17
14.9%
S 13
11.4%
T 9
 
7.9%
K 8
 
7.0%
C 8
 
7.0%
M 7
 
6.1%
L 7
 
6.1%
A 6
 
5.3%
N 6
 
5.3%
E 5
 
4.4%
Other values (10) 28
24.6%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 231
69.0%
Hangul 61
 
18.2%
Common 43
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
널 4
 
6.6%
채 4
 
6.6%
스 4
 
6.6%
마 2
 
3.3%
브 2
 
3.3%
공 2
 
3.3%
트 2
 
3.3%
식 2
 
3.3%
선 2
 
3.3%
파 2
 
3.3%
Other values (35) 35
57.4%
Latin
ValueCountFrequency (%)
B 17
 
7.4%
S 13
 
5.6%
e 13
 
5.6%
o 11
 
4.8%
i 10
 
4.3%
t 10
 
4.3%
n 10
 
4.3%
T 9
 
3.9%
r 9
 
3.9%
K 8
 
3.5%
Other values (32) 121
52.4%
Common
ValueCountFrequency (%)
38
88.4%
- 3
 
7.0%
& 1
 
2.3%
· 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 273
81.5%
Hangul 61
 
18.2%
None 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
 
13.9%
B 17
 
6.2%
S 13
 
4.8%
e 13
 
4.8%
o 11
 
4.0%
i 10
 
3.7%
t 10
 
3.7%
n 10
 
3.7%
T 9
 
3.3%
r 9
 
3.3%
Other values (35) 133
48.7%
Hangul
ValueCountFrequency (%)
널 4
 
6.6%
채 4
 
6.6%
스 4
 
6.6%
마 2
 
3.3%
브 2
 
3.3%
공 2
 
3.3%
트 2
 
3.3%
식 2
 
3.3%
선 2
 
3.3%
파 2
 
3.3%
Other values (35) 35
57.4%
None
ValueCountFrequency (%)
· 1
100.0%

Interactions

2023-12-10T23:16:30.292917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:27.934121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.839385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.594499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:30.465339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.127699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.055983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.787663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:30.623663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.384537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.201272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.939049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:30.811149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.598305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.384064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:30.099793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:16:36.576914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
참여영상경로명수참여영상좋아요수참여영상싫어요수참여영상시청수영상영상채널명
참여영상경로명1.0001.0001.0001.0001.0001.000
수1.0001.0000.6880.6940.7601.000
참여영상좋아요수1.0000.6881.0000.6670.9520.957
참여영상싫어요수1.0000.6940.6671.0000.7140.737
참여영상시청수1.0000.7600.9520.7141.0001.000
영상영상채널명1.0001.0000.9570.7371.0001.000
2023-12-10T23:16:36.746274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수참여영상좋아요수참여영상싫어요수참여영상시청수
수1.0000.8390.8700.947
참여영상좋아요수0.8391.0000.8840.886
참여영상싫어요수0.8700.8841.0000.865
참여영상시청수0.9470.8860.8651.000

Missing values

2023-12-10T23:16:31.099185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:16:31.298683image/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

참여영상경로명참여영상수집일자수참여영상좋아요수참여영상싫어요수참여영상시청수영상영상채널명
0https://www.youtube.com/watch?v=3kfO9PJX6Bc2021-02-01110324749427434런닝맨 - 스브스 공식 채널
1https://www.youtube.com/watch?v=zQ7lF1wEZEk2021-02-0135018243811096612SBS NOW SBS 공식 채널
2https://www.youtube.com/watch?v=6lZhmyhCf4o2021-02-01090875MBN Entertainment
3https://www.youtube.com/watch?v=S31j0lVWW_Y2021-02-019003794모비딕 Mobidic
4https://www.youtube.com/watch?v=B7Mt6YdVwOU2021-02-0122716161994709트박스 Twitch clips box
5https://www.youtube.com/watch?v=2DW9MrrEpoc2021-02-01313341123370MBCdrama
6https://www.youtube.com/watch?v=IMr3dc4LAsA2021-02-01775305152109193정선호
7https://www.youtube.com/watch?v=biaH0bEKmeQ2021-02-01050259MPLAY
8https://www.youtube.com/watch?v=LFaCWcFwjOY2021-02-01612471546912KBS News
9https://www.youtube.com/watch?v=sTqD_LRs10w2021-02-0110017881655849BELLA&LUCAS 벨라앤루카스
참여영상경로명참여영상수집일자수참여영상좋아요수참여영상싫어요수참여영상시청수영상영상채널명
20https://www.youtube.com/watch?v=xhbDCZ45_1o2021-02-0100030KBS 교양
21https://www.youtube.com/watch?v=3A9ONErMvO42021-02-0100076MBClife
22https://www.youtube.com/watch?v=E8Os9IwqExA2021-02-01001110Arirang TV
23https://www.youtube.com/watch?v=iGDTurrW_wY2021-02-01129823715KBS Kpop
24https://www.youtube.com/watch?v=3mEMoU_s14I2021-02-01020111으뜸전남튜브
25https://www.youtube.com/watch?v=hECruThLY4I2021-02-014316644380738MBCkpop
26https://www.youtube.com/watch?v=DOk8QPrt4GM2021-02-0101203278채널A Entertainment
27https://www.youtube.com/watch?v=KaSCiUJr1HA2021-02-01723100883451395428마플 마인크래프트 채널
28https://www.youtube.com/watch?v=WNW93on8I9g2021-02-01342424189KBS News
29https://www.youtube.com/watch?v=SzPO6itEW382021-02-0198454623ALL THE K-POP