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/d6ffc100-a8f9-44c7-beb9-db7e7894b527

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 8 (26.7%) zerosZeros
참여영상좋아요수 has 2 (6.7%) zerosZeros
참여영상싫어요수 has 11 (36.7%) zerosZeros
참여영상시청수 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:15:12.669893
Analysis finished2023-12-10 14:15:16.011505
Duration3.34 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
2023-12-10T23:15:16.294351image/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=1FyFWWULqmM
2nd rowhttps://www.youtube.com/watch?v=h9hiHdjMogk
3rd rowhttps://www.youtube.com/watch?v=WZz5svTl76M
4th rowhttps://www.youtube.com/watch?v=qy6wOHWEApQ
5th rowhttps://www.youtube.com/watch?v=wxIjiVvJw6A
ValueCountFrequency (%)
https://www.youtube.com/watch?v=1fyfwwulqmm 1
 
3.3%
https://www.youtube.com/watch?v=h9hihdjmogk 1
 
3.3%
https://www.youtube.com/watch?v=h3cud5mucu0 1
 
3.3%
https://www.youtube.com/watch?v=q3chwu67gcc 1
 
3.3%
https://www.youtube.com/watch?v=vh3khjsxjg0 1
 
3.3%
https://www.youtube.com/watch?v=tqhu8jztg1o 1
 
3.3%
https://www.youtube.com/watch?v=1mlh7rulcxy 1
 
3.3%
https://www.youtube.com/watch?v=jlqa4pnqxyu 1
 
3.3%
https://www.youtube.com/watch?v=yo0scvfyhkq 1
 
3.3%
https://www.youtube.com/watch?v=ou-sdxttzy4 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:15:16.861882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 126
 
9.8%
t 123
 
9.5%
/ 90
 
7.0%
c 68
 
5.3%
h 67
 
5.2%
o 66
 
5.1%
u 63
 
4.9%
. 60
 
4.7%
y 36
 
2.8%
a 36
 
2.8%
Other values (59) 555
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 842
65.3%
Other Punctuation 210
 
16.3%
Uppercase Letter 141
 
10.9%
Decimal Number 62
 
4.8%
Math Symbol 30
 
2.3%
Connector Punctuation 4
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 126
15.0%
t 123
14.6%
c 68
 
8.1%
h 67
 
8.0%
o 66
 
7.8%
u 63
 
7.5%
y 36
 
4.3%
a 36
 
4.3%
v 35
 
4.2%
m 35
 
4.2%
Other values (16) 187
22.2%
Uppercase Letter
ValueCountFrequency (%)
U 11
 
7.8%
M 11
 
7.8%
W 9
 
6.4%
Y 8
 
5.7%
H 7
 
5.0%
X 7
 
5.0%
J 6
 
4.3%
V 6
 
4.3%
Q 6
 
4.3%
L 6
 
4.3%
Other values (16) 64
45.4%
Decimal Number
ValueCountFrequency (%)
6 10
16.1%
0 9
14.5%
1 7
11.3%
8 7
11.3%
7 6
9.7%
4 6
9.7%
5 6
9.7%
2 4
 
6.5%
3 4
 
6.5%
9 3
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
? 30
 
14.3%
: 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 983
76.2%
Common 307
 
23.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 126
 
12.8%
t 123
 
12.5%
c 68
 
6.9%
h 67
 
6.8%
o 66
 
6.7%
u 63
 
6.4%
y 36
 
3.7%
a 36
 
3.7%
v 35
 
3.6%
m 35
 
3.6%
Other values (42) 328
33.4%
Common
ValueCountFrequency (%)
/ 90
29.3%
. 60
19.5%
? 30
 
9.8%
: 30
 
9.8%
= 30
 
9.8%
6 10
 
3.3%
0 9
 
2.9%
1 7
 
2.3%
8 7
 
2.3%
7 6
 
2.0%
Other values (7) 28
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 126
 
9.8%
t 123
 
9.5%
/ 90
 
7.0%
c 68
 
5.3%
h 67
 
5.2%
o 66
 
5.1%
u 63
 
4.9%
. 60
 
4.7%
y 36
 
2.8%
a 36
 
2.8%
Other values (59) 555
43.0%

참여영상수집일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-07-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-07-01
2nd row2021-07-01
3rd row2021-07-01
4th row2021-07-01
5th row2021-07-01

Common Values

ValueCountFrequency (%)
2021-07-01 30
100.0%

Length

2023-12-10T23:15:17.102549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:17.259578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-07-01 30
100.0%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.83333
Minimum0
Maximum656
Zeros8
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:17.448473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25
median16.5
Q3130.5
95-th percentile565.2
Maximum656
Range656
Interquartile range (IQR)130.25

Descriptive statistics

Standard deviation187.87231
Coefficient of variation (CV)1.6950885
Kurtosis3.1417574
Mean110.83333
Median Absolute Deviation (MAD)16.5
Skewness2.0094349
Sum3325
Variance35296.006
MonotonicityNot monotonic
2023-12-10T23:15:17.758656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 8
26.7%
2 2
 
6.7%
93 1
 
3.3%
277 1
 
3.3%
486 1
 
3.3%
9 1
 
3.3%
630 1
 
3.3%
42 1
 
3.3%
5 1
 
3.3%
656 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
0 8
26.7%
1 1
 
3.3%
2 2
 
6.7%
3 1
 
3.3%
4 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%
24 1
 
3.3%
28 1
 
3.3%
33 1
 
3.3%
ValueCountFrequency (%)
656 1
3.3%
630 1
3.3%
486 1
3.3%
394 1
3.3%
277 1
3.3%
152 1
3.3%
146 1
3.3%
141 1
3.3%
99 1
3.3%
98 1
3.3%

참여영상좋아요수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean736.3
Minimum0
Maximum6924
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:17.975702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q112.25
median130
Q3755.5
95-th percentile2853.8
Maximum6924
Range6924
Interquartile range (IQR)743.25

Descriptive statistics

Standard deviation1410.2286
Coefficient of variation (CV)1.9152908
Kurtosis13.154454
Mean736.3
Median Absolute Deviation (MAD)130
Skewness3.3838862
Sum22089
Variance1988744.8
MonotonicityNot monotonic
2023-12-10T23:15:18.224552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8 2
 
6.7%
0 2
 
6.7%
1007 1
 
3.3%
31 1
 
3.3%
1531 1
 
3.3%
113 1
 
3.3%
3572 1
 
3.3%
699 1
 
3.3%
44 1
 
3.3%
1 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0 2
6.7%
1 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
8 2
6.7%
25 1
3.3%
31 1
3.3%
44 1
3.3%
45 1
3.3%
ValueCountFrequency (%)
6924 1
3.3%
3572 1
3.3%
1976 1
3.3%
1531 1
3.3%
1440 1
3.3%
1229 1
3.3%
1007 1
3.3%
769 1
3.3%
715 1
3.3%
699 1
3.3%

참여영상싫어요수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.9
Minimum0
Maximum91
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:18.446864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q326.75
95-th percentile65.95
Maximum91
Range91
Interquartile range (IQR)26.75

Descriptive statistics

Standard deviation25.155174
Coefficient of variation (CV)1.405317
Kurtosis1.3662211
Mean17.9
Median Absolute Deviation (MAD)6
Skewness1.4870884
Sum537
Variance632.78276
MonotonicityNot monotonic
2023-12-10T23:15:18.645000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 11
36.7%
6 2
 
6.7%
8 2
 
6.7%
2 2
 
6.7%
39 2
 
6.7%
18 1
 
3.3%
54 1
 
3.3%
70 1
 
3.3%
1 1
 
3.3%
91 1
 
3.3%
Other values (6) 6
20.0%
ValueCountFrequency (%)
0 11
36.7%
1 1
 
3.3%
2 2
 
6.7%
6 2
 
6.7%
8 2
 
6.7%
10 1
 
3.3%
16 1
 
3.3%
18 1
 
3.3%
26 1
 
3.3%
27 1
 
3.3%
ValueCountFrequency (%)
91 1
3.3%
70 1
3.3%
61 1
3.3%
54 1
3.3%
53 1
3.3%
39 2
6.7%
27 1
3.3%
26 1
3.3%
18 1
3.3%
16 1
3.3%

참여영상시청수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50568.2
Minimum0
Maximum333622
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:18.837319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile88.4
Q1700.5
median8671.5
Q375522
95-th percentile191218.55
Maximum333622
Range333622
Interquartile range (IQR)74821.5

Descriptive statistics

Standard deviation79127.634
Coefficient of variation (CV)1.5647706
Kurtosis4.6894419
Mean50568.2
Median Absolute Deviation (MAD)8581.5
Skewness2.0721213
Sum1517046
Variance6.2611825 × 109
MonotonicityNot monotonic
2023-12-10T23:15:19.071447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
100901 1
 
3.3%
2282 1
 
3.3%
129914 1
 
3.3%
3197 1
 
3.3%
199607 1
 
3.3%
4787 1
 
3.3%
2847 1
 
3.3%
214 1
 
3.3%
1258 1
 
3.3%
73335 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0 1
3.3%
74 1
3.3%
106 1
3.3%
214 1
3.3%
270 1
3.3%
277 1
3.3%
438 1
3.3%
591 1
3.3%
1029 1
3.3%
1258 1
3.3%
ValueCountFrequency (%)
333622 1
3.3%
199607 1
3.3%
180966 1
3.3%
141545 1
3.3%
129914 1
3.3%
101519 1
3.3%
100901 1
3.3%
76251 1
3.3%
73335 1
3.3%
58148 1
3.3%

영상영상채널명
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:19.782121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length13.5
Mean length8.6666667
Min length2

Characters and Unicode

Total characters260
Distinct characters115
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

Unique28 ?
Unique (%)93.3%

Sample

1st row금똥왁왁
2nd row스팍TV
3rd row포천시청
4th row대한민국 경찰청
5th row흑운장TV [BLACKTUBE]
ValueCountFrequency (%)
대한민국 2
 
3.8%
kbs 2
 
3.8%
sbs 2
 
3.8%
경찰청 2
 
3.8%
ebs 1
 
1.9%
양띵 1
 
1.9%
k-pop 1
 
1.9%
금똥왁왁 1
 
1.9%
지식보관소 1
 
1.9%
아캔streamer 1
 
1.9%
Other values (39) 39
73.6%
2023-12-10T23:15:20.547692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
8.8%
S 12
 
4.6%
B 11
 
4.2%
T 10
 
3.8%
E 7
 
2.7%
a 6
 
2.3%
K 6
 
2.3%
r 6
 
2.3%
e 5
 
1.9%
O 5
 
1.9%
Other values (105) 169
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 88
33.8%
Uppercase Letter 87
33.5%
Lowercase Letter 47
18.1%
Space Separator 23
 
8.8%
Decimal Number 6
 
2.3%
Connector Punctuation 2
 
0.8%
Other Punctuation 2
 
0.8%
Close Punctuation 2
 
0.8%
Open Punctuation 2
 
0.8%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 4
 
4.5%
국 4
 
4.5%
한 3
 
3.4%
지 3
 
3.4%
스 3
 
3.4%
식 2
 
2.3%
회 2
 
2.3%
왁 2
 
2.3%
널 2
 
2.3%
뉴 2
 
2.3%
Other values (55) 61
69.3%
Uppercase Letter
ValueCountFrequency (%)
S 12
13.8%
B 11
12.6%
T 10
11.5%
E 7
 
8.0%
K 6
 
6.9%
O 5
 
5.7%
A 5
 
5.7%
N 4
 
4.6%
L 4
 
4.6%
V 4
 
4.6%
Other values (9) 19
21.8%
Lowercase Letter
ValueCountFrequency (%)
a 6
12.8%
r 6
12.8%
e 5
10.6%
o 4
 
8.5%
m 4
 
8.5%
t 3
 
6.4%
u 3
 
6.4%
s 2
 
4.3%
n 2
 
4.3%
p 2
 
4.3%
Other values (9) 10
21.3%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
5 1
 
16.7%
9 1
 
16.7%
0 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 1
50.0%
] 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 1
50.0%
[ 1
50.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 134
51.5%
Hangul 88
33.8%
Common 38
 
14.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 4
 
4.5%
국 4
 
4.5%
한 3
 
3.4%
지 3
 
3.4%
스 3
 
3.4%
식 2
 
2.3%
회 2
 
2.3%
왁 2
 
2.3%
널 2
 
2.3%
뉴 2
 
2.3%
Other values (55) 61
69.3%
Latin
ValueCountFrequency (%)
S 12
 
9.0%
B 11
 
8.2%
T 10
 
7.5%
E 7
 
5.2%
a 6
 
4.5%
K 6
 
4.5%
r 6
 
4.5%
e 5
 
3.7%
O 5
 
3.7%
A 5
 
3.7%
Other values (28) 61
45.5%
Common
ValueCountFrequency (%)
23
60.5%
1 3
 
7.9%
_ 2
 
5.3%
. 2
 
5.3%
5 1
 
2.6%
9 1
 
2.6%
) 1
 
2.6%
( 1
 
2.6%
[ 1
 
2.6%
0 1
 
2.6%
Other values (2) 2
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
66.2%
Hangul 88
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
 
13.4%
S 12
 
7.0%
B 11
 
6.4%
T 10
 
5.8%
E 7
 
4.1%
a 6
 
3.5%
K 6
 
3.5%
r 6
 
3.5%
e 5
 
2.9%
O 5
 
2.9%
Other values (40) 81
47.1%
Hangul
ValueCountFrequency (%)
청 4
 
4.5%
국 4
 
4.5%
한 3
 
3.4%
지 3
 
3.4%
스 3
 
3.4%
식 2
 
2.3%
회 2
 
2.3%
왁 2
 
2.3%
널 2
 
2.3%
뉴 2
 
2.3%
Other values (55) 61
69.3%

Interactions

2023-12-10T23:15:15.091807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.142914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.806632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.454638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.248222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.327149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.958977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.594777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.405564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.484527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.110153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.744518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.552304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.628433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.266264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.929655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:15:20.720291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
참여영상경로명수참여영상좋아요수참여영상싫어요수참여영상시청수영상영상채널명
참여영상경로명1.0001.0001.0001.0001.0001.000
수1.0001.0000.7810.9230.9121.000
참여영상좋아요수1.0000.7811.0000.8830.8301.000
참여영상싫어요수1.0000.9230.8831.0000.8541.000
참여영상시청수1.0000.9120.8300.8541.0001.000
영상영상채널명1.0001.0001.0001.0001.0001.000
2023-12-10T23:15:20.937253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수참여영상좋아요수참여영상싫어요수참여영상시청수
수1.0000.9560.9400.917
참여영상좋아요수0.9561.0000.9270.954
참여영상싫어요수0.9400.9271.0000.944
참여영상시청수0.9170.9540.9441.000

Missing values

2023-12-10T23:15:15.771031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:15:15.943444image/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=1FyFWWULqmM2021-07-0193100718100901금똥왁왁
1https://www.youtube.com/watch?v=h9hiHdjMogk2021-07-01030106스팍TV
2https://www.youtube.com/watch?v=WZz5svTl76M2021-07-01080277포천시청
3https://www.youtube.com/watch?v=qy6wOHWEApQ2021-07-0144501907대한민국 경찰청
4https://www.youtube.com/watch?v=wxIjiVvJw6A2021-07-011466562776251흑운장TV [BLACKTUBE]
5https://www.youtube.com/watch?v=qXh7Yj8NhSQ2021-07-01983311016100이녕
6https://www.youtube.com/watch?v=G_HXIjpIMVo2021-07-0100074채널A 뉴스TOP10
7https://www.youtube.com/watch?v=0UWqN_QIjgg2021-07-01283251658148KBS Drama
8https://www.youtube.com/watch?v=j6gJZ7dm5rM2021-07-0112501029한국사회복지협의회 나눔채널 공감
9https://www.youtube.com/watch?v=5VR504lZD4M2021-07-01997692634569No.1 DEF DANCE SKOOL
참여영상경로명참여영상수집일자수참여영상좋아요수참여영상싫어요수참여영상시청수영상영상채널명
20https://www.youtube.com/watch?v=szRxmAOPLY02021-07-010000종로티비
21https://www.youtube.com/watch?v=oU-SDXTTzY42021-07-01394144039180966글자네 YouTube
22https://www.youtube.com/watch?v=yO0SCVfYHKQ2021-07-0165612299173335급식커플
23https://www.youtube.com/watch?v=jLqA4PnqXyU2021-07-010801258SBS STORY
24https://www.youtube.com/watch?v=1MLh7RulcXY2021-07-01010214MBN News
25https://www.youtube.com/watch?v=tqHu8JZTG1o2021-07-0154412847Arirang TV
26https://www.youtube.com/watch?v=vH3KhJSxJG02021-07-014269964787KBS Kpop
27https://www.youtube.com/watch?v=q3chWU67gCc2021-07-01630357270199607발__젭
28https://www.youtube.com/watch?v=H3CUd5MUCU02021-07-01911363197SBS Catch
29https://www.youtube.com/watch?v=W7bGdv1fYCU2021-07-01486153139129914양띵 유튜브