Overview

Dataset statistics

Number of variables12
Number of observations29
Missing cells15
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory95.6 B

Variable types

Text6
Categorical3
DateTime1
Numeric1
Boolean1

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/4028f541-3529-4d06-a67b-33d514ec79c7

Alerts

채널수집일자 has constant value ""Constant
구독자수비공개정보 is highly imbalanced (63.8%)Imbalance
채널국가 is highly imbalanced (50.3%)Imbalance
채널채널설명 has 1 (3.4%) missing valuesMissing
채널채널키워드명 has 7 (24.1%) missing valuesMissing
영상 has 7 (24.1%) missing valuesMissing
채널채널경로명 has unique valuesUnique
채널채널생성일자 has unique valuesUnique
채널아이콘 has unique valuesUnique
채널채널명 has unique valuesUnique
채널구독자수 has 2 (6.9%) zerosZeros

Reproduction

Analysis started2023-12-10 13:42:54.139176
Analysis finished2023-12-10 13:42:56.422435
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

채널채널경로명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T22:42:56.723252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length56
Mean length56
Min length56

Characters and Unicode

Total characters1624
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

Unique29 ?
Unique (%)100.0%

Sample

1st rowhttps://www.youtube.com/channel/UCRHqySX7C4-xj6BI2LHGr6w
2nd rowhttps://www.youtube.com/channel/UCc7eenRzcuNtJ2v4Ej9Ihfw
3rd rowhttps://www.youtube.com/channel/UC1Wq-BQZblFGbGgDAoCwrmA
4th rowhttps://www.youtube.com/channel/UCrBI3umiAJ6GcwD7jmD3AmQ
5th rowhttps://www.youtube.com/channel/UC2fsxQr6Hcx1enORxXgKpxQ
ValueCountFrequency (%)
https://www.youtube.com/channel/ucrhqysx7c4-xj6bi2lhgr6w 1
 
3.4%
https://www.youtube.com/channel/ucyifsblfslhhv4zhhqkorng 1
 
3.4%
https://www.youtube.com/channel/ucuw1hxbo5mdvuhgmzrdk3aw 1
 
3.4%
https://www.youtube.com/channel/ucqeezzuvbs9ojgbecgduvcg 1
 
3.4%
https://www.youtube.com/channel/ucwkkbajrxzojvoex6aiaedq 1
 
3.4%
https://www.youtube.com/channel/uc_6a_0vdy5jbf0n2h17975q 1
 
3.4%
https://www.youtube.com/channel/ucylyotaiks8k-vdpqbj9xlq 1
 
3.4%
https://www.youtube.com/channel/ucy7ctqzxofgemlvks4m92zq 1
 
3.4%
https://www.youtube.com/channel/uctlxbnvlkyqlmdtqmlrdefa 1
 
3.4%
https://www.youtube.com/channel/ucowesydgk8eh1u5spvgggxw 1
 
3.4%
Other values (19) 19
65.5%
2023-12-10T22:42:57.412713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 116
 
7.1%
w 107
 
6.6%
t 91
 
5.6%
h 70
 
4.3%
e 70
 
4.3%
c 68
 
4.2%
o 66
 
4.1%
u 66
 
4.1%
n 65
 
4.0%
. 58
 
3.6%
Other values (57) 847
52.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1014
62.4%
Uppercase Letter 308
 
19.0%
Other Punctuation 203
 
12.5%
Decimal Number 83
 
5.1%
Connector Punctuation 9
 
0.6%
Dash Punctuation 7
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 107
 
10.6%
t 91
 
9.0%
h 70
 
6.9%
e 70
 
6.9%
c 68
 
6.7%
o 66
 
6.5%
u 66
 
6.5%
n 65
 
6.4%
l 45
 
4.4%
s 41
 
4.0%
Other values (16) 325
32.1%
Uppercase Letter
ValueCountFrequency (%)
U 40
 
13.0%
C 34
 
11.0%
Q 16
 
5.2%
A 16
 
5.2%
Z 15
 
4.9%
D 14
 
4.5%
V 13
 
4.2%
R 13
 
4.2%
B 12
 
3.9%
H 12
 
3.9%
Other values (16) 123
39.9%
Decimal Number
ValueCountFrequency (%)
7 12
14.5%
1 12
14.5%
6 10
12.0%
9 9
10.8%
5 9
10.8%
3 8
9.6%
2 8
9.6%
8 7
8.4%
4 6
7.2%
0 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/ 116
57.1%
. 58
28.6%
: 29
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1322
81.4%
Common 302
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 107
 
8.1%
t 91
 
6.9%
h 70
 
5.3%
e 70
 
5.3%
c 68
 
5.1%
o 66
 
5.0%
u 66
 
5.0%
n 65
 
4.9%
l 45
 
3.4%
s 41
 
3.1%
Other values (42) 633
47.9%
Common
ValueCountFrequency (%)
/ 116
38.4%
. 58
19.2%
: 29
 
9.6%
7 12
 
4.0%
1 12
 
4.0%
6 10
 
3.3%
9 9
 
3.0%
_ 9
 
3.0%
5 9
 
3.0%
3 8
 
2.6%
Other values (5) 30
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 116
 
7.1%
w 107
 
6.6%
t 91
 
5.6%
h 70
 
4.3%
e 70
 
4.3%
c 68
 
4.2%
o 66
 
4.1%
u 66
 
4.1%
n 65
 
4.0%
. 58
 
3.6%
Other values (57) 847
52.2%

채널수집일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2021-07-01
29 

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 29
100.0%

Length

2023-12-10T22:42:57.718623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:42:57.873803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-07-01 29
100.0%

채널채널생성일자
Date

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2011-08-22 00:00:00
Maximum2019-10-31 00:00:00
2023-12-10T22:42:58.016360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:42:58.273414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

채널아이콘
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T22:42:58.915128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length123
Median length98
Mean length100.31034
Min length96

Characters and Unicode

Total characters2909
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

Unique29 ?
Unique (%)100.0%

Sample

1st rowhttps://yt3.ggpht.com/ytc/AKedOLR_-xEv3rxw43-KeBUXUROfdMZTPLoStOxrWfTEAg=s88-c-k-c0x00ffffff-no-rj
2nd rowhttps://yt3.ggpht.com/ytc/AKedOLQjw2Ux4dByVUz1ye1hqquy3ayrDWFn2o7cydsJxv4=s88-c-k-c0x00ffffff-no-rj
3rd rowhttps://yt3.ggpht.com/ytc/AKedOLRX9NS2_GBpFNq81H_bVqX0Z792HKcp7mYk9zHFRA=s88-c-k-c0x00ffffff-no-rj
4th rowhttps://yt3.ggpht.com/_1ztkE-MNMgBjll0K96aKN7kcCSpZgBoEvArvUgxk4rQvFAQh2s8DEWAiUQvVykjQDV2jGw0sq0=s88-c-k-c0x00ffffff-no-rj
5th rowhttps://yt3.ggpht.com/ytc/AKedOLRWmbSuZmkR2QWmsw864fQLtz8pLFDxG9lDSF47mg=s88-c-k-c0x00ffffff-no-rj
ValueCountFrequency (%)
https://yt3.ggpht.com/ytc/akedolr_-xev3rxw43-kebuxurofdmztplostoxrwfteag=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedolqnubywknilmiiazbzckk932ck33p4x5cluoanb=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedolryrqq-vmtfifnm1agxxzbe8zr1r6w97ito_cto=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedolq8_czqv3rozh7xwx8zc73rjh5sr-tphwykksqx=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedolrngzrvbybooqjynqao9wcrqkeglidrvof8bc77_a=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedolrfqrvuyhznpaku3clpg-lfpgccfqufcfg3obf6sa=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedoltxext05ywlcdyzeo7emm4jdbymiz-kh46rqd-uqq=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedolrnfemu3qigyyqt1kqo0w8zjpa53x7cmrf9ylwl=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/xphs2eqz3dxfzl-gmz0n5mjuqgm6mtkcixchhznl-hydxkdmrbwppkehbad794hr9bkchq_y1g=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
https://yt3.ggpht.com/ytc/akedolr3tuyj6xts3yjijtkcedxsb-gp1ay2tfvb7bwt=s88-c-k-c0x00ffffff-no-rj 1
 
3.4%
Other values (19) 19
65.5%
2023-12-10T22:42:59.943608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 202
 
6.9%
- 166
 
5.7%
t 163
 
5.6%
c 132
 
4.5%
/ 113
 
3.9%
0 102
 
3.5%
g 84
 
2.9%
y 84
 
2.9%
h 79
 
2.7%
s 76
 
2.6%
Other values (58) 1708
58.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1513
52.0%
Uppercase Letter 623
21.4%
Decimal Number 361
 
12.4%
Other Punctuation 200
 
6.9%
Dash Punctuation 166
 
5.7%
Math Symbol 29
 
1.0%
Connector Punctuation 17
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
f 202
13.4%
t 163
 
10.8%
c 132
 
8.7%
g 84
 
5.6%
y 84
 
5.6%
h 79
 
5.2%
s 76
 
5.0%
o 75
 
5.0%
p 75
 
5.0%
r 54
 
3.6%
Other values (16) 489
32.3%
Uppercase Letter
ValueCountFrequency (%)
K 48
 
7.7%
A 44
 
7.1%
O 42
 
6.7%
L 41
 
6.6%
R 35
 
5.6%
Q 31
 
5.0%
C 27
 
4.3%
U 25
 
4.0%
G 24
 
3.9%
B 24
 
3.9%
Other values (16) 282
45.3%
Decimal Number
ValueCountFrequency (%)
0 102
28.3%
8 72
19.9%
3 50
13.9%
7 27
 
7.5%
9 23
 
6.4%
1 21
 
5.8%
4 20
 
5.5%
2 18
 
5.0%
6 15
 
4.2%
5 13
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 113
56.5%
. 58
29.0%
: 29
 
14.5%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%
Math Symbol
ValueCountFrequency (%)
= 29
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2136
73.4%
Common 773
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
f 202
 
9.5%
t 163
 
7.6%
c 132
 
6.2%
g 84
 
3.9%
y 84
 
3.9%
h 79
 
3.7%
s 76
 
3.6%
o 75
 
3.5%
p 75
 
3.5%
r 54
 
2.5%
Other values (42) 1112
52.1%
Common
ValueCountFrequency (%)
- 166
21.5%
/ 113
14.6%
0 102
13.2%
8 72
9.3%
. 58
 
7.5%
3 50
 
6.5%
: 29
 
3.8%
= 29
 
3.8%
7 27
 
3.5%
9 23
 
3.0%
Other values (6) 104
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2909
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 202
 
6.9%
- 166
 
5.7%
t 163
 
5.6%
c 132
 
4.5%
/ 113
 
3.9%
0 102
 
3.5%
g 84
 
2.9%
y 84
 
2.9%
h 79
 
2.7%
s 76
 
2.6%
Other values (58) 1708
58.7%

채널채널설명
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing1
Missing (%)3.4%
Memory size364.0 B
2023-12-10T22:43:00.508411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length606
Median length69
Mean length119
Min length13

Characters and Unicode

Total characters3332
Distinct characters384
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks6 ?
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 row종로여성인력개발센터는 여성의 작은 가능성이 분명한 꿈으로; 분명한 꿈이 확실한 능력으로 키워지는 곳입니다. '꿈은 이루어진다'라는 바람이 현실이 되도록; 변화를 두려워하지 않고; 미래를 향하여 오늘을 뛰어넘는 도약을 약속합니다. 여성발전기본법에 근거하여 설립된 종로여성인력개발센터는 서울시가 지정하고 (사)여성중앙회가 운영하는 공공성을 기반으로 한 전문직업교육 훈련기관입니다. 종로여성인력개발센터에서는 직업훈련 - 고용서비스 - 복지서비스까지 ONE-STOP 종합지원서비스를 제공합니다.
2nd row70대어머니와 떠나는 먹방여행 맛집리뷰.몰카.브이로그 컨텐츠로 찾아뵐게요 ^^ 광고문의 donghoman2@gmail.com
3rd row한국 음식을 즐겨 먹는 한식 요리먹방 입니다. 매일매일 맛있는 영상이 업로드 됩니다.
4th row한국영상자료원 채널입니다.
5th rowASMR 리얼사운드 먹방 채널입니다. 영상은 매일 업로드 합니다. Welcome to Jane's ASMR eating sounds channel. Daily uploads
ValueCountFrequency (%)
12
 
2.2%
채널입니다 8
 
1.5%
유튜브 6
 
1.1%
먹방 5
 
0.9%
공식 5
 
0.9%
de 4
 
0.7%
mi 4
 
0.7%
a 4
 
0.7%
con 3
 
0.5%
jtbc 3
 
0.5%
Other values (447) 494
90.1%
2023-12-10T22:43:01.227327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
571
 
17.1%
a 106
 
3.2%
o 93
 
2.8%
e 88
 
2.6%
n 75
 
2.3%
. 59
 
1.8%
i 58
 
1.7%
s 57
 
1.7%
t 55
 
1.7%
c 52
 
1.6%
Other values (374) 2118
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1347
40.4%
Lowercase Letter 979
29.4%
Space Separator 571
17.1%
Uppercase Letter 158
 
4.7%
Other Punctuation 128
 
3.8%
Decimal Number 57
 
1.7%
Math Symbol 46
 
1.4%
Close Punctuation 12
 
0.4%
Open Punctuation 11
 
0.3%
Dash Punctuation 9
 
0.3%
Other values (3) 14
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 37
 
2.7%
니 33
 
2.4%
이 31
 
2.3%
사 30
 
2.2%
로 28
 
2.1%
인 26
 
1.9%
의 21
 
1.6%
는 18
 
1.3%
여 17
 
1.3%
을 17
 
1.3%
Other values (292) 1089
80.8%
Lowercase Letter
ValueCountFrequency (%)
a 106
 
10.8%
o 93
 
9.5%
e 88
 
9.0%
n 75
 
7.7%
i 58
 
5.9%
s 57
 
5.8%
t 55
 
5.6%
c 52
 
5.3%
m 52
 
5.3%
r 48
 
4.9%
Other values (16) 295
30.1%
Uppercase Letter
ValueCountFrequency (%)
T 18
 
11.4%
C 12
 
7.6%
R 9
 
5.7%
E 9
 
5.7%
S 9
 
5.7%
J 8
 
5.1%
V 8
 
5.1%
A 7
 
4.4%
I 7
 
4.4%
B 7
 
4.4%
Other values (14) 64
40.5%
Other Punctuation
ValueCountFrequency (%)
. 59
46.1%
; 17
 
13.3%
! 14
 
10.9%
: 13
 
10.2%
@ 6
 
4.7%
' 6
 
4.7%
# 6
 
4.7%
※ 4
 
3.1%
& 2
 
1.6%
· 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 12
21.1%
1 12
21.1%
2 8
14.0%
9 7
12.3%
4 4
 
7.0%
3 4
 
7.0%
7 3
 
5.3%
5 3
 
5.3%
6 2
 
3.5%
8 2
 
3.5%
Math Symbol
ValueCountFrequency (%)
= 44
95.7%
~ 2
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 10
83.3%
] 2
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 9
81.8%
[ 2
 
18.2%
Other Symbol
ValueCountFrequency (%)
♥ 3
60.0%
▶ 2
40.0%
Space Separator
ValueCountFrequency (%)
571
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1347
40.4%
Latin 1137
34.1%
Common 848
25.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 37
 
2.7%
니 33
 
2.4%
이 31
 
2.3%
사 30
 
2.2%
로 28
 
2.1%
인 26
 
1.9%
의 21
 
1.6%
는 18
 
1.3%
여 17
 
1.3%
을 17
 
1.3%
Other values (292) 1089
80.8%
Latin
ValueCountFrequency (%)
a 106
 
9.3%
o 93
 
8.2%
e 88
 
7.7%
n 75
 
6.6%
i 58
 
5.1%
s 57
 
5.0%
t 55
 
4.8%
c 52
 
4.6%
m 52
 
4.6%
r 48
 
4.2%
Other values (40) 453
39.8%
Common
ValueCountFrequency (%)
571
67.3%
. 59
 
7.0%
= 44
 
5.2%
; 17
 
2.0%
! 14
 
1.7%
: 13
 
1.5%
0 12
 
1.4%
1 12
 
1.4%
) 10
 
1.2%
( 9
 
1.1%
Other values (22) 87
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1975
59.3%
Hangul 1347
40.4%
Punctuation 4
 
0.1%
Misc Symbols 3
 
0.1%
Geometric Shapes 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
571
28.9%
a 106
 
5.4%
o 93
 
4.7%
e 88
 
4.5%
n 75
 
3.8%
. 59
 
3.0%
i 58
 
2.9%
s 57
 
2.9%
t 55
 
2.8%
c 52
 
2.6%
Other values (68) 761
38.5%
Hangul
ValueCountFrequency (%)
다 37
 
2.7%
니 33
 
2.4%
이 31
 
2.3%
사 30
 
2.2%
로 28
 
2.1%
인 26
 
1.9%
의 21
 
1.6%
는 18
 
1.3%
여 17
 
1.3%
을 17
 
1.3%
Other values (292) 1089
80.8%
Punctuation
ValueCountFrequency (%)
※ 4
100.0%
Misc Symbols
ValueCountFrequency (%)
♥ 3
100.0%
Geometric Shapes
ValueCountFrequency (%)
▶ 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

채널채널범주명
Categorical

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
MCN
17 
공공기관
10 
TV
2 

Length

Max length4
Median length3
Mean length3.2758621
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공기관
2nd rowMCN
3rd rowMCN
4th row공공기관
5th rowMCN

Common Values

ValueCountFrequency (%)
MCN 17
58.6%
공공기관 10
34.5%
TV 2
 
6.9%

Length

2023-12-10T22:43:01.586443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:43:01.796196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mcn 17
58.6%
공공기관 10
34.5%
tv 2
 
6.9%

채널채널명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T22:43:02.238227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length11.137931
Min length3

Characters and Unicode

Total characters323
Distinct characters150
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row종로여성인력개발센터
2nd row70대 어머니와떠나는먹방여행
3rd row한식푸우 Korean food
4th row한국영상자료원
5th rowJane ASMR 제인
ValueCountFrequency (%)
2
 
3.8%
종로여성인력개발센터 1
 
1.9%
70대 1
 
1.9%
한국장기조직기증원[koda 1
 
1.9%
왕쥬 1
 
1.9%
wangju 1
 
1.9%
검은곰의 1
 
1.9%
풍경 1
 
1.9%
인사처tv 1
 
1.9%
동래tv 1
 
1.9%
Other values (42) 42
79.2%
2023-12-10T22:43:02.830085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
7.4%
a 14
 
4.3%
n 10
 
3.1%
o 9
 
2.8%
T 9
 
2.8%
S 7
 
2.2%
e 7
 
2.2%
V 6
 
1.9%
u 6
 
1.9%
A 5
 
1.5%
Other values (140) 226
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
42.4%
Lowercase Letter 85
26.3%
Uppercase Letter 64
19.8%
Space Separator 24
 
7.4%
Close Punctuation 4
 
1.2%
Open Punctuation 4
 
1.2%
Dash Punctuation 3
 
0.9%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 3
 
2.2%
한 3
 
2.2%
식 3
 
2.2%
조 3
 
2.2%
의 3
 
2.2%
인 3
 
2.2%
사 2
 
1.5%
프 2
 
1.5%
리 2
 
1.5%
기 2
 
1.5%
Other values (90) 111
81.0%
Lowercase Letter
ValueCountFrequency (%)
a 14
16.5%
n 10
11.8%
o 9
10.6%
e 7
8.2%
u 6
 
7.1%
g 5
 
5.9%
r 5
 
5.9%
s 4
 
4.7%
i 4
 
4.7%
y 4
 
4.7%
Other values (11) 17
20.0%
Uppercase Letter
ValueCountFrequency (%)
T 9
14.1%
S 7
10.9%
V 6
 
9.4%
A 5
 
7.8%
O 4
 
6.2%
H 4
 
6.2%
J 4
 
6.2%
Y 3
 
4.7%
I 3
 
4.7%
K 3
 
4.7%
Other values (11) 16
25.0%
Close Punctuation
ValueCountFrequency (%)
) 3
75.0%
] 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 3
75.0%
[ 1
 
25.0%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
7 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 149
46.1%
Hangul 137
42.4%
Common 37
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 3
 
2.2%
한 3
 
2.2%
식 3
 
2.2%
조 3
 
2.2%
의 3
 
2.2%
인 3
 
2.2%
사 2
 
1.5%
프 2
 
1.5%
리 2
 
1.5%
기 2
 
1.5%
Other values (90) 111
81.0%
Latin
ValueCountFrequency (%)
a 14
 
9.4%
n 10
 
6.7%
o 9
 
6.0%
T 9
 
6.0%
S 7
 
4.7%
e 7
 
4.7%
V 6
 
4.0%
u 6
 
4.0%
A 5
 
3.4%
g 5
 
3.4%
Other values (32) 71
47.7%
Common
ValueCountFrequency (%)
24
64.9%
- 3
 
8.1%
) 3
 
8.1%
( 3
 
8.1%
[ 1
 
2.7%
] 1
 
2.7%
0 1
 
2.7%
7 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186
57.6%
Hangul 137
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
 
12.9%
a 14
 
7.5%
n 10
 
5.4%
o 9
 
4.8%
T 9
 
4.8%
S 7
 
3.8%
e 7
 
3.8%
V 6
 
3.2%
u 6
 
3.2%
A 5
 
2.7%
Other values (40) 89
47.8%
Hangul
ValueCountFrequency (%)
서 3
 
2.2%
한 3
 
2.2%
식 3
 
2.2%
조 3
 
2.2%
의 3
 
2.2%
인 3
 
2.2%
사 2
 
1.5%
프 2
 
1.5%
리 2
 
1.5%
기 2
 
1.5%
Other values (90) 111
81.0%

채널구독자수
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1393534.5
Minimum0
Maximum17200000
Zeros2
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T22:43:03.044026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q12520
median43900
Q3445000
95-th percentile9164000
Maximum17200000
Range17200000
Interquartile range (IQR)442480

Descriptive statistics

Standard deviation3960801.8
Coefficient of variation (CV)2.8422703
Kurtosis11.880773
Mean1393534.5
Median Absolute Deviation (MAD)43900
Skewness3.530778
Sum40412501
Variance1.5687951 × 1013
MonotonicityNot monotonic
2023-12-10T22:43:03.247263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
20 2
 
6.9%
0 2
 
6.9%
31400 1
 
3.4%
2510000 1
 
3.4%
62 1
 
3.4%
317000 1
 
3.4%
3240 1
 
3.4%
994 1
 
3.4%
12100 1
 
3.4%
445000 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
0 2
6.9%
20 2
6.9%
62 1
3.4%
465 1
3.4%
994 1
3.4%
2520 1
3.4%
3240 1
3.4%
5280 1
3.4%
12100 1
3.4%
12600 1
3.4%
ValueCountFrequency (%)
17200000 1
3.4%
13600000 1
3.4%
2510000 1
3.4%
2240000 1
3.4%
1190000 1
3.4%
1030000 1
3.4%
605000 1
3.4%
445000 1
3.4%
342000 1
3.4%
320000 1
3.4%

구독자수비공개정보
Boolean

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size190.0 B
False
27 
True
 
2
ValueCountFrequency (%)
False 27
93.1%
True 2
 
6.9%
2023-12-10T22:43:03.443606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

채널국가
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
KR
24 
<NA>
4 
PE
 
1

Length

Max length4
Median length2
Mean length2.2758621
Min length2

Unique

Unique1 ?
Unique (%)3.4%

Sample

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

Common Values

ValueCountFrequency (%)
KR 24
82.8%
<NA> 4
 
13.8%
PE 1
 
3.4%

Length

2023-12-10T22:43:03.652037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:43:03.929181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kr 24
82.8%
na 4
 
13.8%
pe 1
 
3.4%

채널채널키워드명
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing7
Missing (%)24.1%
Memory size364.0 B
2023-12-10T22:43:04.368116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length150
Median length34.5
Mean length45.681818
Min length2

Characters and Unicode

Total characters1005
Distinct characters238
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row취업 국비교육 취업알선 고용노동부 여성인력개발센터 청년취업
2nd row한식푸우 푸우먹방 한식요리 한식먹방 요리먹방 먹방푸우 푸우먹방
3rd row영자원 고전영화 한국영화 고전 영화 한국 영화 시네마테크 KOFA 시네마테크KOFA 영상자료원 영상 자료원 koreanfilmarchive KoreanFilmArchive kofa
4th rowasmr eating eating asmr asmr eating show 먹방 먹방 asmr asmr 먹방
5th row신비아파트;장난감놀이;어린이놀이;키즈크리에이터;
ValueCountFrequency (%)
asmr 5
 
2.5%
먹방 5
 
2.5%
eating 3
 
1.5%
교양 2
 
1.0%
미스터트롯 2
 
1.0%
트로트 2
 
1.0%
kofa 2
 
1.0%
임영웅 2
 
1.0%
영화 2
 
1.0%
makeup 2
 
1.0%
Other values (170) 175
86.6%
2023-12-10T22:43:05.139541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
 
17.9%
a 25
 
2.5%
r 24
 
2.4%
e 21
 
2.1%
o 20
 
2.0%
n 20
 
2.0%
이 18
 
1.8%
i 15
 
1.5%
m 14
 
1.4%
트 14
 
1.4%
Other values (228) 654
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 549
54.6%
Lowercase Letter 238
23.7%
Space Separator 180
 
17.9%
Uppercase Letter 32
 
3.2%
Other Punctuation 4
 
0.4%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 18
 
3.3%
트 14
 
2.6%
방 14
 
2.6%
영 13
 
2.4%
먹 12
 
2.2%
시 12
 
2.2%
스 11
 
2.0%
조 8
 
1.5%
원 8
 
1.5%
식 8
 
1.5%
Other values (190) 431
78.5%
Lowercase Letter
ValueCountFrequency (%)
a 25
10.5%
r 24
 
10.1%
e 21
 
8.8%
o 20
 
8.4%
n 20
 
8.4%
i 15
 
6.3%
m 14
 
5.9%
t 13
 
5.5%
g 13
 
5.5%
s 12
 
5.0%
Other values (12) 61
25.6%
Uppercase Letter
ValueCountFrequency (%)
T 4
12.5%
A 4
12.5%
K 4
12.5%
O 3
9.4%
F 3
9.4%
V 3
9.4%
B 3
9.4%
J 3
9.4%
D 2
6.2%
P 1
 
3.1%
Other values (2) 2
6.2%
Decimal Number
ValueCountFrequency (%)
9 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
180
100.0%
Other Punctuation
ValueCountFrequency (%)
; 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 549
54.6%
Latin 270
26.9%
Common 186
 
18.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 18
 
3.3%
트 14
 
2.6%
방 14
 
2.6%
영 13
 
2.4%
먹 12
 
2.2%
시 12
 
2.2%
스 11
 
2.0%
조 8
 
1.5%
원 8
 
1.5%
식 8
 
1.5%
Other values (190) 431
78.5%
Latin
ValueCountFrequency (%)
a 25
 
9.3%
r 24
 
8.9%
e 21
 
7.8%
o 20
 
7.4%
n 20
 
7.4%
i 15
 
5.6%
m 14
 
5.2%
t 13
 
4.8%
g 13
 
4.8%
s 12
 
4.4%
Other values (24) 93
34.4%
Common
ValueCountFrequency (%)
180
96.8%
; 4
 
2.2%
9 1
 
0.5%
1 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 549
54.6%
ASCII 456
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
39.5%
a 25
 
5.5%
r 24
 
5.3%
e 21
 
4.6%
o 20
 
4.4%
n 20
 
4.4%
i 15
 
3.3%
m 14
 
3.1%
t 13
 
2.9%
g 13
 
2.9%
Other values (28) 111
24.3%
Hangul
ValueCountFrequency (%)
이 18
 
3.3%
트 14
 
2.6%
방 14
 
2.6%
영 13
 
2.4%
먹 12
 
2.2%
시 12
 
2.2%
스 11
 
2.0%
조 8
 
1.5%
원 8
 
1.5%
식 8
 
1.5%
Other values (190) 431
78.5%

영상
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing7
Missing (%)24.1%
Memory size364.0 B
2023-12-10T22:43:05.451121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters242
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

Unique22 ?
Unique (%)100.0%

Sample

1st row2rSQm-KZQYc
2nd rowt5TQwKJhdeU
3rd rowYV09sGeeVjg
4th row2ir8xCSNc84
5th rowZwXE7A-KLjw
ValueCountFrequency (%)
t5tqwkjhdeu 1
 
4.5%
yv09sgeevjg 1
 
4.5%
ecjvcuyrhv4 1
 
4.5%
ibpojfpqvmc 1
 
4.5%
c8urakr8slo 1
 
4.5%
qmvn-lswoay 1
 
4.5%
dqdqn9k99a 1
 
4.5%
k4psomk6zp8 1
 
4.5%
hcvqxq5xgsa 1
 
4.5%
e9lbqt-9cio 1
 
4.5%
Other values (12) 12
54.5%
2023-12-10T22:43:05.943597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 10
 
4.1%
K 9
 
3.7%
V 8
 
3.3%
J 8
 
3.3%
9 7
 
2.9%
q 7
 
2.9%
S 7
 
2.9%
4 7
 
2.9%
Q 7
 
2.9%
- 6
 
2.5%
Other values (53) 166
68.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 115
47.5%
Lowercase Letter 82
33.9%
Decimal Number 37
 
15.3%
Dash Punctuation 6
 
2.5%
Connector Punctuation 2
 
0.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 10
 
8.7%
K 9
 
7.8%
V 8
 
7.0%
J 8
 
7.0%
S 7
 
6.1%
Q 7
 
6.1%
M 6
 
5.2%
Y 6
 
5.2%
C 6
 
5.2%
L 5
 
4.3%
Other values (16) 43
37.4%
Lowercase Letter
ValueCountFrequency (%)
q 7
 
8.5%
l 6
 
7.3%
c 5
 
6.1%
r 5
 
6.1%
i 5
 
6.1%
d 5
 
6.1%
w 5
 
6.1%
v 4
 
4.9%
o 4
 
4.9%
p 4
 
4.9%
Other values (16) 32
39.0%
Decimal Number
ValueCountFrequency (%)
9 7
18.9%
4 7
18.9%
0 6
16.2%
8 6
16.2%
5 4
10.8%
6 2
 
5.4%
7 2
 
5.4%
2 2
 
5.4%
1 1
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 197
81.4%
Common 45
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 10
 
5.1%
K 9
 
4.6%
V 8
 
4.1%
J 8
 
4.1%
q 7
 
3.6%
S 7
 
3.6%
Q 7
 
3.6%
M 6
 
3.0%
Y 6
 
3.0%
l 6
 
3.0%
Other values (42) 123
62.4%
Common
ValueCountFrequency (%)
9 7
15.6%
4 7
15.6%
- 6
13.3%
0 6
13.3%
8 6
13.3%
5 4
8.9%
_ 2
 
4.4%
6 2
 
4.4%
7 2
 
4.4%
2 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 10
 
4.1%
K 9
 
3.7%
V 8
 
3.3%
J 8
 
3.3%
9 7
 
2.9%
q 7
 
2.9%
S 7
 
2.9%
4 7
 
2.9%
Q 7
 
2.9%
- 6
 
2.5%
Other values (53) 166
68.6%

Interactions

2023-12-10T22:42:55.594023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:43:06.126984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채널채널경로명채널채널생성일자채널아이콘채널채널설명채널채널범주명채널채널명채널구독자수구독자수비공개정보채널국가채널채널키워드명영상
채널채널경로명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
채널채널생성일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
채널아이콘1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
채널채널설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
채널채널범주명1.0001.0001.0001.0001.0001.0000.2100.1690.0001.0001.000
채널채널명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
채널구독자수1.0001.0001.0001.0000.2101.0001.0000.0000.0001.0001.000
구독자수비공개정보1.0001.0001.0001.0000.1691.0000.0001.0000.0001.0001.000
채널국가1.0001.0001.0001.0000.0001.0000.0000.0001.000NaN1.000
채널채널키워드명1.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.000
영상1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-10T22:43:06.376179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채널국가채널채널범주명구독자수비공개정보
채널국가1.0000.0000.000
채널채널범주명0.0001.0000.268
구독자수비공개정보0.0000.2681.000
2023-12-10T22:43:06.528134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채널구독자수채널채널범주명구독자수비공개정보채널국가
채널구독자수1.0000.1860.0000.000
채널채널범주명0.1861.0000.2680.000
구독자수비공개정보0.0000.2681.0000.000
채널국가0.0000.0000.0001.000

Missing values

2023-12-10T22:42:55.796587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:42:56.065445image/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.
2023-12-10T22:42:56.319611image/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

채널채널경로명채널수집일자채널채널생성일자채널아이콘채널채널설명채널채널범주명채널채널명채널구독자수구독자수비공개정보채널국가채널채널키워드명영상
0https://www.youtube.com/channel/UCRHqySX7C4-xj6BI2LHGr6w2021-07-012017-01-31https://yt3.ggpht.com/ytc/AKedOLR_-xEv3rxw43-KeBUXUROfdMZTPLoStOxrWfTEAg=s88-c-k-c0x00ffffff-no-rj종로여성인력개발센터는 여성의 작은 가능성이 분명한 꿈으로; 분명한 꿈이 확실한 능력으로 키워지는 곳입니다. '꿈은 이루어진다'라는 바람이 현실이 되도록; 변화를 두려워하지 않고; 미래를 향하여 오늘을 뛰어넘는 도약을 약속합니다. 여성발전기본법에 근거하여 설립된 종로여성인력개발센터는 서울시가 지정하고 (사)여성중앙회가 운영하는 공공성을 기반으로 한 전문직업교육 훈련기관입니다. 종로여성인력개발센터에서는 직업훈련 - 고용서비스 - 복지서비스까지 ONE-STOP 종합지원서비스를 제공합니다.공공기관종로여성인력개발센터20FalseKR취업 국비교육 취업알선 고용노동부 여성인력개발센터 청년취업2rSQm-KZQYc
1https://www.youtube.com/channel/UCc7eenRzcuNtJ2v4Ej9Ihfw2021-07-012013-05-03https://yt3.ggpht.com/ytc/AKedOLQjw2Ux4dByVUz1ye1hqquy3ayrDWFn2o7cydsJxv4=s88-c-k-c0x00ffffff-no-rj70대어머니와 떠나는 먹방여행 맛집리뷰.몰카.브이로그 컨텐츠로 찾아뵐게요 ^^ 광고문의 donghoman2@gmail.comMCN70대 어머니와떠나는먹방여행31400FalseKR<NA>t5TQwKJhdeU
2https://www.youtube.com/channel/UC1Wq-BQZblFGbGgDAoCwrmA2021-07-012014-02-14https://yt3.ggpht.com/ytc/AKedOLRX9NS2_GBpFNq81H_bVqX0Z792HKcp7mYk9zHFRA=s88-c-k-c0x00ffffff-no-rj한국 음식을 즐겨 먹는 한식 요리먹방 입니다. 매일매일 맛있는 영상이 업로드 됩니다.MCN한식푸우 Korean food605000FalseKR한식푸우 푸우먹방 한식요리 한식먹방 요리먹방 먹방푸우 푸우먹방YV09sGeeVjg
3https://www.youtube.com/channel/UCrBI3umiAJ6GcwD7jmD3AmQ2021-07-012012-02-01https://yt3.ggpht.com/_1ztkE-MNMgBjll0K96aKN7kcCSpZgBoEvArvUgxk4rQvFAQh2s8DEWAiUQvVykjQDV2jGw0sq0=s88-c-k-c0x00ffffff-no-rj한국영상자료원 채널입니다.공공기관한국영상자료원12600FalseKR영자원 고전영화 한국영화 고전 영화 한국 영화 시네마테크 KOFA 시네마테크KOFA 영상자료원 영상 자료원 koreanfilmarchive KoreanFilmArchive kofa2ir8xCSNc84
4https://www.youtube.com/channel/UC2fsxQr6Hcx1enORxXgKpxQ2021-07-012012-11-17https://yt3.ggpht.com/ytc/AKedOLRWmbSuZmkR2QWmsw864fQLtz8pLFDxG9lDSF47mg=s88-c-k-c0x00ffffff-no-rjASMR 리얼사운드 먹방 채널입니다. 영상은 매일 업로드 합니다. Welcome to Jane's ASMR eating sounds channel. Daily uploadsMCNJane ASMR 제인13600000FalseKRasmr eating eating asmr asmr eating show 먹방 먹방 asmr asmr 먹방ZwXE7A-KLjw
5https://www.youtube.com/channel/UCfYBSrfvB-ArSvsQGljQ-7w2021-07-012018-01-18https://yt3.ggpht.com/ytc/AKedOLQOnDm4yk20NbiyrCQH49rSY9_rqbSM-irP9DGU0w=s88-c-k-c0x00ffffff-no-rj즐거움이 가득한 해피토이에 오신것을 환영합니다 ^0^ 도야와 엄마 아빠의 재미난 이야기 많이 기대해주세요! 구독 좋아요 꾸욱~ 눌러주세요 ~! ============================================ Welcome to Happy Toy full of fun.♥ The new images are updated daily at 5pm. Please; subscribed to it much!! lieben01@naver.comMCN해피토이(HappyToy)1030000FalseKR신비아파트;장난감놀이;어린이놀이;키즈크리에이터;AL0QLjLvwY0
6https://www.youtube.com/channel/UChRFfOYgUHoo1Oeugk8pJfg2021-07-012015-01-01https://yt3.ggpht.com/ytc/AKedOLSinfEodKCr9zQ-7VDZuUCBLoC5E1Dkfw-iAnrswg=s88-c-k-c0x00ffffff-no-rj사진으로는 이해하기 어려웠던 메이크업을 영상으로 쉽게 보여드리려고 시작한 하코냥의 유튜브 채널 앞으로 다양한 영상으로 쉽고 재미있고 결과물이 좋은 메이크업 보여드릴께요 [작업실 이사했어요] 주소 : 서울특별시 강남구 삼성로116길 5 3층 E-mail : weinnie@naver.comMCN하코냥 Hakonyang320000FalseKRmakeupH0qdRf4VW4A
7https://www.youtube.com/channel/UC9kmlDcqksaOnCkC_qzGacA2021-07-012015-07-14https://yt3.ggpht.com/ytc/AKedOLRgI5sw16chfOqHXSKUl2CI5n7RaG64LC6U-zU6Pg=s88-c-k-c0x00ffffff-no-rjrisabaeofficial@gmail.com https:instagram.comrisabae_artMCNRISABAE2240000FalseKRmakeup tutorialBcTKyJKJECM
8https://www.youtube.com/channel/UCfkVXdwu_UpWmmhSUNH1D4w2021-07-012012-08-29https://yt3.ggpht.com/ytc/AKedOLSH21RV98j6B4QdqV_zWI_GKaLHu1flodTj2zeC0g=s88-c-k-c0x00ffffff-no-rjYOUTUBER - INFLUENCER - KPOPER.MCNKISSYS43900FalsePE<NA>JlspU5H7SKU
9https://www.youtube.com/channel/UC4vD5JpdxZRPy1bpRAdjhSA2021-07-012015-01-10https://yt3.ggpht.com/ytc/AKedOLSBApdm2tOy13jvfb9ddF4tXCK_j-P5ygFduVEmNA=s88-c-k-c0x00ffffff-no-rj유튜버&스트리머 조랭몬의 공식 유튜브채널이지롱 이메일 raengmon@naver.com 트위치TV https:www.twitch.tvraengmon 유튜브 https:goo.gler9JGv 트위터 http:goo.gly4Huqo 네이버블로그 goo.glkHZNCb 네이버팬카페 랭떡방♥ http:cafe.naver.comraengmonMCN조랭몬 YouTube61700FalseKR조랭몬 랭몬 joraengmon raengmon twitchv-MaX5I_ib0
채널채널경로명채널수집일자채널채널생성일자채널아이콘채널채널설명채널채널범주명채널채널명채널구독자수구독자수비공개정보채널국가채널채널키워드명영상
19https://www.youtube.com/channel/UCNzYaPkki55QOp5u2UPJvzA2021-07-012013-11-06https://yt3.ggpht.com/ytc/AKedOLQX_tElyxe3bKjwID2htWrNFxhwsnMQyGyyzG90=s88-c-k-c0x00ffffff-no-rj먹방 BJ WANGJU Wangju mukbang 아프리카TV 먹방 & 보이는라디오 여캠 BJ 왕쥬의 유튜브 채널입니다. Mukbang Dance cover Eat Cook Funny video Makeup Beauty Radio Vlog 먹방 Korean Eating Show ※왕쥬 관련 주소※ Afreeca TV ▶ http:afreeca.comdjsrhkwl Instagram ▶ https:instagram.comdjsrhkwl1MCN왕쥬 Wangju445000FalseKR왕쥬 먹방 vlog 브이로그-Dqdqn9K99A
20https://www.youtube.com/channel/UCOwesydgK8eH1u5SPVggGXw2021-07-012019-05-18https://yt3.ggpht.com/ytc/AKedOLR3Tuyj6xts3yjijtKCedxSB-gp1AY2tFVb7BWT=s88-c-k-c0x00ffffff-no-rj여행 혹은 산책 기록에 대한 영상이 업로드되는 채널입니다. Panasonic DC-G9Lumix 12-32mmRonin SC를 사용합니다. :)MCN검은곰의 풍경20FalseKR검은곰 여행 풍경<NA>
21https://www.youtube.com/channel/UCTlXbNVlKyqLmDTqmlrdEFA2021-07-012014-12-18https://yt3.ggpht.com/XPhs2EQZ3dxFZL-gmz0n5MJUqGM6MtkCIXChhzNl-hYDXkdMRBWPpKehBaD794HR9bKcHQ_y1g=s88-c-k-c0x00ffffff-no-rj정부 수립 이후 약 70년간 대한민국의 중앙인사관장기관(Central Personnel Agency)은 국가 인적자원관리의 효율성과 정부인사의 공정성을 높이기 위해 변화 발전되어 왔습니다. 지난 1948년 정부 수립 이후 고시위원회와 총무처(인사국) 체제로 출발하여 국무원 사무국; 국무원 사무처; 내각 사무처; 행정자치부를 거쳐 1999년에 중앙인사위원회가 설치 되어 내각의 각 부로부터 독립된 인사행정 전담부서로 운영되었습니다. 그 후 중앙인사위원회(인사정책); 행정자치부(인사집행)로 이원화되어 있던 인사행정 기능을 2004년에 중앙인사위원회로 통합 일원화 하였습니다. 이후 2008년에 중앙인사위원회가 다른 기능과 통폐합되어 행정안전부(인사실)· 안전행정부(인사실) 체제로 유지되다가; 2014년 11월 19일 공직 인사혁신을 전담하는 인사혁신처가 신설 되어 공무원 연금개혁; 경력개방형제도; 중앙선발위원회; 전문직공무원 제도 도입 등 공직의 개방성과 전문성을 높이기 위해 노력하여 왔습니다. 새정부 출범을 맞아 인사혁신처는 '국민의 나라; 정의로운 대한민국' 실현을 위하여 정부혁신과 연계한 통합적인 인사혁신; 사람존중 인사혁신을 지속적으로 추진하겠습니다.공공기관인사처TV12100FalseKR공무원 인사혁신처 인사처 인혁처 국가직공무원 공무원시험 psatqMVn-lSWoAY
22https://www.youtube.com/channel/UCY7cTqZxoFgeMlVKS4m92ZQ2021-07-012017-06-07https://yt3.ggpht.com/ytc/AKedOLRnFeMU3QIGyYQT1kQo0w8ZjPA53X7cMRf9yLWl=s88-c-k-c0x00ffffff-no-rj동래구 공식 유튜브 채널입니다. 동래구의 아름다움과 구정 소식을 전해드리겠습니다. #동래 #동래구 #살기좋은동래 #동래구청 #dongnae #동래TV공공기관동래TV - 동래구 공식 유튜브994False<NA><NA>C8uRakr8Slo
23https://www.youtube.com/channel/UCyLYotaiks8k-vdPqBJ9xlQ2021-07-012014-03-05https://yt3.ggpht.com/ytc/AKedOLTXeXt05ywlCdyZeo7EmM4JdBYMiz-KH46RqD-uqQ=s88-c-k-c0x00ffffff-no-rj청정임실을 보여드립니다!!! 임실엔TV에서 임실군청 공무원들의 활약을 기대해주세요.공공기관임실엔TV3240FalseKR임실군 임실엔TV 임실N치즈 임실치즈테마파크ibPOJFpqvMc
24https://www.youtube.com/channel/UC_6a_0VDy5JbF0n2H17975Q2021-07-012014-08-22https://yt3.ggpht.com/ytc/AKedOLRfqRVUYhZnpaKU3cLpG-lfpgcCFQUFCfG3obf6sA=s88-c-k-c0x00ffffff-no-rjHola a todos bienvenidos a mi canal soy Mell una paraguaya casada con un coreano; actualmente viviendo en corea del sur. Si quieres conocer como es mi vida aqui conocer mas de la cultura coreana te invito a que te suscribas a mi canal. Tambien hablaremos de moda; cosmeticos rutinas de belleza y un poco de kpop con mi amigo Mikel Moran suscribanse por favor y compartan nuestros videos con sus amigos..estaremos muy muy agradecidos GRACIASMCNParaguaya en corea del sur317000False<NA><NA><NA>
25https://www.youtube.com/channel/UCWkkBajrXZoJVOEX6aIAEdQ2021-07-012013-09-11https://yt3.ggpht.com/ytc/AKedOLRNGzrVbyBOOqJYnqAo9WcRqkegliDRVoF8BC77_A=s88-c-k-c0x00ffffff-no-rj서울시농수산식품공사 공식 유튜브 채널입니다. 서울시농수산식품공사와 함께하는 농산물 유통 효율화! 안전 먹거리 공급! 건강한 식문화 창조!공공기관서울시농수산식품공사0TrueKR가락시장 송파구 가락몰 시설현대화 청과직판 수산식판 직판상인 쿠킹스튜디오 서울식생활시민학교 요리교실<NA>
26https://www.youtube.com/channel/UCqeeZzUVbS9OjGBecGDUVcg2021-07-012014-01-09https://yt3.ggpht.com/ytc/AKedOLQ8_CzQV3Rozh7xwx8zc73rJh5sR-tphWykKsQx=s88-c-k-c0x00ffffff-no-rj<NA>공공기관용산소방서(Yongsan Fire Station)62False<NA><NA><NA>
27https://www.youtube.com/channel/UCuw1hxBo5mDVUhgMzRDk3aw2021-07-012011-10-13https://yt3.ggpht.com/ytc/AKedOLRyRqq-vmTfIFnM1aGXXzbE8ZR1r6w97itO_CTO=s88-c-k-c0x00ffffff-no-rjTV조선(TVCHOSUN) 방송 공식 YouTube 입니다.TVTVCHOSUN - TV조선2510000FalseKRTV조선 TV 조선 티비 티비조선 티브이조선 티조 조선일보 방송 뉴스 종합편성 종편 트로트 트롯 미스터트롯 아내의맛 미스트롯 임영웅 영탁 이찬원 예능 드라마 미스 미스터 아내 맛 종합 편성 교양 시사 프로그램 채널 19 번 보도 기자 피디 PD 프로 제작 콘텐츠 라이브<NA>
28https://www.youtube.com/channel/UCyzZWCuxYN6TKAEyqReFj2w2021-07-012019-10-31https://yt3.ggpht.com/ytc/AKedOLSlP3fqPFfB9379WrtYlKTErvkzj47X9VAQwOKf=s88-c-k-c0x00ffffff-no-rj김천시 공식 유튜브채널 김천의 모든것을 담아 전하겠습니다 구독과 좋아요 꼭 눌러주세요 ^^공공기관김천시0TrueKR<NA>YKSvHWF6_M4