Overview

Dataset statistics

Number of variables15
Number of observations27
Missing cells39
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory134.9 B

Variable types

Text3
DateTime2
Numeric7
Categorical3

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/e77ae1f4-ad5a-4e44-82d4-4f180f7265f4

Alerts

최근6개월개선도 is highly overall correlated with 최근6개월표준점수 and 1 other fieldsHigh correlation
최근개선도지수 is highly overall correlated with 개선도최근표준점수High correlation
최근6개월표준점수 is highly overall correlated with 최근6개월개선도High correlation
개선도최근표준점수 is highly overall correlated with 최근개선도지수High correlation
최근12개월개선도 is highly overall correlated with 최근6개월개선도High correlation
최초6개월개선도 is highly overall correlated with 최초12개월개선도High correlation
최초12개월개선도 is highly overall correlated with 최초6개월개선도High correlation
개선도지수채널설명 has 7 (25.9%) missing valuesMissing
개선도채널생성일자 has 1 (3.7%) missing valuesMissing
최근6개월개선도 has 17 (63.0%) missing valuesMissing
최근개선도지수 has 10 (37.0%) missing valuesMissing
최근6개월표준점수 has 1 (3.7%) missing valuesMissing
최근12개월표준점수 has 3 (11.1%) missing valuesMissing
개선도지수채널ID has unique valuesUnique
개선도지수채널명 has unique valuesUnique
최근개선도지수 has 6 (22.2%) zerosZeros

Reproduction

Analysis started2023-12-10 14:19:07.820746
Analysis finished2023-12-10 14:19:15.065622
Duration7.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개선도지수채널ID
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-10T23:19:15.260620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters648
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st rowUCy_OWMB42I6bqaJQjJenKJA
2nd rowUCL-GJ5bmSpexd1-lVbG0xtQ
3rd rowUCw6AmebJ0sUuDdfFNFfa74g
4th rowUCXF_eVsuOWsWX6uIucimUrw
5th rowUC2tGWq3BCZUDAgNh965yM-A
ValueCountFrequency (%)
ucy_owmb42i6bqajqjjenkja 1
 
3.7%
uc7itqntfg_qs1ufcmbgikkw 1
 
3.7%
uccir1qib7r1mr77byzj0miq 1
 
3.7%
uccd5onp_ljxqu0us89wm-ww 1
 
3.7%
uc1dk7omusr9rnk1bspokzng 1
 
3.7%
uc6jl3mrfgbvryxxgddxxzva 1
 
3.7%
uc99oela9yvqgkq9ffbvm9iq 1
 
3.7%
uc9153vuiks_neltqwdqx-6a 1
 
3.7%
uc69l_rtlcq7m4mz2rcs80ba 1
 
3.7%
uc8gcjee6ffhdhzyul6zlemq 1
 
3.7%
Other values (17) 17
63.0%
2023-12-10T23:19:15.853051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 37
 
5.7%
U 35
 
5.4%
A 17
 
2.6%
9 16
 
2.5%
g 16
 
2.5%
t 15
 
2.3%
Q 14
 
2.2%
l 14
 
2.2%
w 13
 
2.0%
b 13
 
2.0%
Other values (54) 458
70.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 277
42.7%
Lowercase Letter 252
38.9%
Decimal Number 99
 
15.3%
Connector Punctuation 11
 
1.7%
Dash Punctuation 9
 
1.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 37
 
13.4%
U 35
 
12.6%
A 17
 
6.1%
Q 14
 
5.1%
J 12
 
4.3%
M 12
 
4.3%
I 11
 
4.0%
F 11
 
4.0%
K 11
 
4.0%
X 9
 
3.2%
Other values (16) 108
39.0%
Lowercase Letter
ValueCountFrequency (%)
g 16
 
6.3%
t 15
 
6.0%
l 14
 
5.6%
w 13
 
5.2%
b 13
 
5.2%
m 13
 
5.2%
x 13
 
5.2%
q 12
 
4.8%
d 12
 
4.8%
u 11
 
4.4%
Other values (16) 120
47.6%
Decimal Number
ValueCountFrequency (%)
9 16
16.2%
7 13
13.1%
1 12
12.1%
3 11
11.1%
0 10
10.1%
6 10
10.1%
8 10
10.1%
4 6
 
6.1%
2 6
 
6.1%
5 5
 
5.1%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 529
81.6%
Common 119
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 37
 
7.0%
U 35
 
6.6%
A 17
 
3.2%
g 16
 
3.0%
t 15
 
2.8%
Q 14
 
2.6%
l 14
 
2.6%
w 13
 
2.5%
b 13
 
2.5%
m 13
 
2.5%
Other values (42) 342
64.7%
Common
ValueCountFrequency (%)
9 16
13.4%
7 13
10.9%
1 12
10.1%
_ 11
9.2%
3 11
9.2%
0 10
8.4%
6 10
8.4%
8 10
8.4%
- 9
7.6%
4 6
 
5.0%
Other values (2) 11
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 37
 
5.7%
U 35
 
5.4%
A 17
 
2.6%
9 16
 
2.5%
g 16
 
2.5%
t 15
 
2.3%
Q 14
 
2.2%
l 14
 
2.2%
w 13
 
2.0%
b 13
 
2.0%
Other values (54) 458
70.7%

개선도지수채널명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-10T23:19:16.224677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length9
Min length2

Characters and Unicode

Total characters243
Distinct characters125
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

Unique27 ?
Unique (%)100.0%

Sample

1st row성우 김혜성의 혜성TV
2nd row토군
3rd rowboomiunni
4th rowEunjung 은정
5th row파쇄축
ValueCountFrequency (%)
성우 1
 
2.3%
자유분방travellog 1
 
2.3%
daedue 1
 
2.3%
tv 1
 
2.3%
재외동포재단_okf 1
 
2.3%
0zoo 1
 
2.3%
영주 1
 
2.3%
황꿀 1
 
2.3%
gguul's 1
 
2.3%
boundary 1
 
2.3%
Other values (33) 33
76.7%
2023-12-10T23:19:16.771627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
6.6%
u 10
 
4.1%
a 8
 
3.3%
o 8
 
3.3%
n 7
 
2.9%
T 7
 
2.9%
g 6
 
2.5%
e 6
 
2.5%
b 5
 
2.1%
V 5
 
2.1%
Other values (115) 165
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107
44.0%
Lowercase Letter 75
30.9%
Uppercase Letter 39
 
16.0%
Space Separator 16
 
6.6%
Other Punctuation 1
 
0.4%
Decimal Number 1
 
0.4%
Dash Punctuation 1
 
0.4%
Connector Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 3
 
2.8%
방 3
 
2.8%
국 3
 
2.8%
한 3
 
2.8%
성 3
 
2.8%
의 3
 
2.8%
재 2
 
1.9%
원 2
 
1.9%
도 2
 
1.9%
냥 2
 
1.9%
Other values (69) 81
75.7%
Lowercase Letter
ValueCountFrequency (%)
u 10
13.3%
a 8
10.7%
o 8
10.7%
n 7
9.3%
g 6
 
8.0%
e 6
 
8.0%
b 5
 
6.7%
s 3
 
4.0%
r 3
 
4.0%
d 2
 
2.7%
Other values (13) 17
22.7%
Uppercase Letter
ValueCountFrequency (%)
T 7
17.9%
V 5
12.8%
O 4
10.3%
K 3
7.7%
J 3
7.7%
D 3
7.7%
I 3
7.7%
E 2
 
5.1%
S 2
 
5.1%
Y 1
 
2.6%
Other values (6) 6
15.4%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 114
46.9%
Hangul 107
44.0%
Common 22
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 3
 
2.8%
방 3
 
2.8%
국 3
 
2.8%
한 3
 
2.8%
성 3
 
2.8%
의 3
 
2.8%
재 2
 
1.9%
원 2
 
1.9%
도 2
 
1.9%
냥 2
 
1.9%
Other values (69) 81
75.7%
Latin
ValueCountFrequency (%)
u 10
 
8.8%
a 8
 
7.0%
o 8
 
7.0%
n 7
 
6.1%
T 7
 
6.1%
g 6
 
5.3%
e 6
 
5.3%
b 5
 
4.4%
V 5
 
4.4%
O 4
 
3.5%
Other values (29) 48
42.1%
Common
ValueCountFrequency (%)
16
72.7%
' 1
 
4.5%
0 1
 
4.5%
- 1
 
4.5%
_ 1
 
4.5%
) 1
 
4.5%
( 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 136
56.0%
Hangul 107
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
 
11.8%
u 10
 
7.4%
a 8
 
5.9%
o 8
 
5.9%
n 7
 
5.1%
T 7
 
5.1%
g 6
 
4.4%
e 6
 
4.4%
b 5
 
3.7%
V 5
 
3.7%
Other values (36) 58
42.6%
Hangul
ValueCountFrequency (%)
리 3
 
2.8%
방 3
 
2.8%
국 3
 
2.8%
한 3
 
2.8%
성 3
 
2.8%
의 3
 
2.8%
재 2
 
1.9%
원 2
 
1.9%
도 2
 
1.9%
냥 2
 
1.9%
Other values (69) 81
75.7%

개선도지수수집일자
Date

Distinct5
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2021-01-11 00:00:00
Maximum2021-01-27 00:00:00
2023-12-10T23:19:16.900741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:17.026544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

개선도지수채널설명
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing7
Missing (%)25.9%
Memory size348.0 B
2023-12-10T23:19:17.302881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length456
Median length83
Mean length139.05
Min length9

Characters and Unicode

Total characters2781
Distinct characters341
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

Unique20 ?
Unique (%)100.0%

Sample

1st row엽기병맛 비글 성우 김혜성과 함께 즐기는 성우 세계!!!! 이제는 대성우시대! 즐겁게 살자라는 신념으로 유튜브 만들고 있습니다 게임도 하고 성우란 직업도 알아보는 성우컨텐츠의 집합소~ 성우 김혜성 홍보홍보 합시다 김혜성 대성 하리라 모두에게 즐거움을 주리라!! https:www.facebook.comgenjicomet 페이스북에서 방송이나 컨텐츠 알림합니다~ 트위치 https:www.twitch.tvgenjicomettv 에서 게임방송합니다 많이 구경 오시구 구독해주세요~^-^ seiyucoute@gmail.com 으로 사연도 좋고 고민도 좋고 질문도 좋고 아무거나 보내주세요~^-^
2nd row재밌게 보셨다면 '좋아요' 구독하기 꼭 부탁드립니다^^
3rd row그냥 나의 기록들
4th row철권 관련 영상 채널입니다.
5th row대한민국 대표 공영방송 KBS(Korean Broadcasting System) 의 공식 유튜브 채널 입니다. 재미있고 유익한 소식을 전하겠습니다.
ValueCountFrequency (%)
16
 
3.6%
유튜브 5
 
1.1%
미라지 5
 
1.1%
많이 5
 
1.1%
구독하기 4
 
0.9%
함께 4
 
0.9%
공식 4
 
0.9%
안녕하세요 4
 
0.9%
좋아요 4
 
0.9%
◐ 4
 
0.9%
Other values (331) 395
87.8%
2023-12-10T23:19:17.751905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
517
 
18.6%
t 83
 
3.0%
a 77
 
2.8%
o 76
 
2.7%
. 57
 
2.0%
e 52
 
1.9%
n 47
 
1.7%
m 43
 
1.5%
w 43
 
1.5%
r 42
 
1.5%
Other values (331) 1744
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1151
41.4%
Lowercase Letter 806
29.0%
Space Separator 517
18.6%
Other Punctuation 153
 
5.5%
Decimal Number 47
 
1.7%
Uppercase Letter 46
 
1.7%
Modifier Symbol 12
 
0.4%
Close Punctuation 11
 
0.4%
Open Punctuation 10
 
0.4%
Other Symbol 9
 
0.3%
Other values (3) 19
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 34
 
3.0%
니 31
 
2.7%
이 29
 
2.5%
ㅡ 22
 
1.9%
하 22
 
1.9%
는 20
 
1.7%
요 19
 
1.7%
고 17
 
1.5%
을 17
 
1.5%
영 16
 
1.4%
Other values (256) 924
80.3%
Lowercase Letter
ValueCountFrequency (%)
t 83
 
10.3%
a 77
 
9.6%
o 76
 
9.4%
e 52
 
6.5%
n 47
 
5.8%
m 43
 
5.3%
w 43
 
5.3%
r 42
 
5.2%
i 41
 
5.1%
g 41
 
5.1%
Other values (15) 261
32.4%
Uppercase Letter
ValueCountFrequency (%)
T 8
17.4%
V 5
10.9%
S 4
 
8.7%
P 3
 
6.5%
K 3
 
6.5%
Y 3
 
6.5%
G 3
 
6.5%
I 3
 
6.5%
C 2
 
4.3%
D 2
 
4.3%
Other values (9) 10
21.7%
Decimal Number
ValueCountFrequency (%)
3 10
21.3%
0 9
19.1%
2 7
14.9%
7 6
12.8%
1 5
10.6%
5 3
 
6.4%
6 2
 
4.3%
4 2
 
4.3%
8 2
 
4.3%
9 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 57
37.3%
: 28
18.3%
! 22
 
14.4%
' 15
 
9.8%
; 13
 
8.5%
# 9
 
5.9%
@ 6
 
3.9%
* 2
 
1.3%
& 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 8
72.7%
] 3
 
27.3%
Open Punctuation
ValueCountFrequency (%)
( 7
70.0%
[ 3
30.0%
Other Symbol
ValueCountFrequency (%)
♥ 5
55.6%
◐ 4
44.4%
Math Symbol
ValueCountFrequency (%)
~ 4
50.0%
⊙ 4
50.0%
Space Separator
ValueCountFrequency (%)
517
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1151
41.4%
Latin 852
30.6%
Common 778
28.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 34
 
3.0%
니 31
 
2.7%
이 29
 
2.5%
ㅡ 22
 
1.9%
하 22
 
1.9%
는 20
 
1.7%
요 19
 
1.7%
고 17
 
1.5%
을 17
 
1.5%
영 16
 
1.4%
Other values (256) 924
80.3%
Latin
ValueCountFrequency (%)
t 83
 
9.7%
a 77
 
9.0%
o 76
 
8.9%
e 52
 
6.1%
n 47
 
5.5%
m 43
 
5.0%
w 43
 
5.0%
r 42
 
4.9%
i 41
 
4.8%
g 41
 
4.8%
Other values (34) 307
36.0%
Common
ValueCountFrequency (%)
517
66.5%
. 57
 
7.3%
: 28
 
3.6%
! 22
 
2.8%
' 15
 
1.9%
; 13
 
1.7%
^ 12
 
1.5%
3 10
 
1.3%
# 9
 
1.2%
0 9
 
1.2%
Other values (21) 86
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1617
58.1%
Hangul 1129
40.6%
Compat Jamo 22
 
0.8%
Misc Symbols 5
 
0.2%
Geometric Shapes 4
 
0.1%
Math Operators 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
517
32.0%
t 83
 
5.1%
a 77
 
4.8%
o 76
 
4.7%
. 57
 
3.5%
e 52
 
3.2%
n 47
 
2.9%
m 43
 
2.7%
w 43
 
2.7%
r 42
 
2.6%
Other values (62) 580
35.9%
Hangul
ValueCountFrequency (%)
다 34
 
3.0%
니 31
 
2.7%
이 29
 
2.6%
하 22
 
1.9%
는 20
 
1.8%
요 19
 
1.7%
고 17
 
1.5%
을 17
 
1.5%
영 16
 
1.4%
리 16
 
1.4%
Other values (255) 908
80.4%
Compat Jamo
ValueCountFrequency (%)
ㅡ 22
100.0%
Misc Symbols
ValueCountFrequency (%)
♥ 5
100.0%
Geometric Shapes
ValueCountFrequency (%)
◐ 4
100.0%
Math Operators
ValueCountFrequency (%)
⊙ 4
100.0%

개선도채널생성일자
Date

MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Memory size348.0 B
Minimum2010-10-29 00:00:00
Maximum2019-07-23 00:00:00
2023-12-10T23:19:17.871194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:18.015156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

최근6개월개선도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)90.0%
Missing17
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean-12.8
Minimum-49
Maximum-1
Zeros0
Zeros (%)0.0%
Negative10
Negative (%)37.0%
Memory size375.0 B
2023-12-10T23:19:18.125312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-49
5-th percentile-48.55
Q1-7.5
median-4.5
Q3-2.25
95-th percentile-1.45
Maximum-1
Range48
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation18.931455
Coefficient of variation (CV)-1.4790199
Kurtosis1.3029444
Mean-12.8
Median Absolute Deviation (MAD)2.5
Skewness-1.7269922
Sum-128
Variance358.4
MonotonicityNot monotonic
2023-12-10T23:19:18.239774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
-2 2
 
7.4%
-48 1
 
3.7%
-4 1
 
3.7%
-8 1
 
3.7%
-5 1
 
3.7%
-1 1
 
3.7%
-6 1
 
3.7%
-3 1
 
3.7%
-49 1
 
3.7%
(Missing) 17
63.0%
ValueCountFrequency (%)
-49 1
3.7%
-48 1
3.7%
-8 1
3.7%
-6 1
3.7%
-5 1
3.7%
-4 1
3.7%
-3 1
3.7%
-2 2
7.4%
-1 1
3.7%
ValueCountFrequency (%)
-1 1
3.7%
-2 2
7.4%
-3 1
3.7%
-4 1
3.7%
-5 1
3.7%
-6 1
3.7%
-8 1
3.7%
-48 1
3.7%
-49 1
3.7%

최근12개월개선도
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size348.0 B
<NA>
14 
1
6 
2
3 
3
2 
4
 
1

Length

Max length4
Median length4
Mean length2.5555556
Min length1

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 14
51.9%
1 6
22.2%
2 3
 
11.1%
3 2
 
7.4%
4 1
 
3.7%
0 1
 
3.7%

Length

2023-12-10T23:19:18.385896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:18.580113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
51.9%
1 6
22.2%
2 3
 
11.1%
3 2
 
7.4%
4 1
 
3.7%
0 1
 
3.7%

최초6개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
<NA>
13 
0
10 
1
4 

Length

Max length4
Median length1
Mean length2.4444444
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 13
48.1%
0 10
37.0%
1 4
 
14.8%

Length

2023-12-10T23:19:18.793819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:18.947090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
48.1%
0 10
37.0%
1 4
 
14.8%

최초12개월개선도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
<NA>
13 
0
9 
1
4 
-1
 
1

Length

Max length4
Median length2
Mean length2.4814815
Min length1

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row-1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 13
48.1%
0 9
33.3%
1 4
 
14.8%
-1 1
 
3.7%

Length

2023-12-10T23:19:19.128278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:19.312328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
48.1%
0 9
33.3%
1 5
 
18.5%

최근개선도지수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct12
Distinct (%)70.6%
Missing10
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean33.573529
Minimum0
Maximum183.34
Zeros6
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-10T23:19:19.468822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12.05
Q334.17
95-th percentile146.676
Maximum183.34
Range183.34
Interquartile range (IQR)34.17

Descriptive statistics

Standard deviation52.074033
Coefficient of variation (CV)1.5510443
Kurtosis4.1481878
Mean33.573529
Median Absolute Deviation (MAD)12.05
Skewness2.1315066
Sum570.75
Variance2711.7049
MonotonicityNot monotonic
2023-12-10T23:19:19.724237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 6
22.2%
30.84 1
 
3.7%
68.72 1
 
3.7%
9.82 1
 
3.7%
42.44 1
 
3.7%
4.57 1
 
3.7%
12.05 1
 
3.7%
22.26 1
 
3.7%
183.34 1
 
3.7%
137.51 1
 
3.7%
Other values (2) 2
 
7.4%
(Missing) 10
37.0%
ValueCountFrequency (%)
0.0 6
22.2%
4.57 1
 
3.7%
9.82 1
 
3.7%
12.05 1
 
3.7%
22.26 1
 
3.7%
25.03 1
 
3.7%
30.84 1
 
3.7%
34.17 1
 
3.7%
42.44 1
 
3.7%
68.72 1
 
3.7%
ValueCountFrequency (%)
183.34 1
3.7%
137.51 1
3.7%
68.72 1
3.7%
42.44 1
3.7%
34.17 1
3.7%
30.84 1
3.7%
25.03 1
3.7%
22.26 1
3.7%
12.05 1
3.7%
9.82 1
3.7%

최근6개월표준점수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)84.6%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean-2.0096154
Minimum-34.95
Maximum21.04
Zeros0
Zeros (%)0.0%
Negative16
Negative (%)59.3%
Memory size375.0 B
2023-12-10T23:19:19.903712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-34.95
5-th percentile-25.58
Q1-8.32
median-2.28
Q37.7
95-th percentile15.5025
Maximum21.04
Range55.99
Interquartile range (IQR)16.02

Descriptive statistics

Standard deviation12.936504
Coefficient of variation (CV)-6.4373032
Kurtosis0.79564524
Mean-2.0096154
Median Absolute Deviation (MAD)8.335
Skewness-0.71813707
Sum-52.25
Variance167.35312
MonotonicityNot monotonic
2023-12-10T23:19:20.084184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
-2.28 5
18.5%
-10.64 1
 
3.7%
8.28 1
 
3.7%
16.81 1
 
3.7%
-2.31 1
 
3.7%
21.04 1
 
3.7%
-4.56 1
 
3.7%
-9.69 1
 
3.7%
6.45 1
 
3.7%
-25.69 1
 
3.7%
Other values (12) 12
44.4%
ValueCountFrequency (%)
-34.95 1
3.7%
-25.69 1
3.7%
-25.25 1
3.7%
-10.64 1
3.7%
-10.59 1
3.7%
-9.69 1
3.7%
-9.05 1
3.7%
-6.13 1
3.7%
-4.56 1
3.7%
-3.51 1
3.7%
ValueCountFrequency (%)
21.04 1
3.7%
16.81 1
3.7%
11.58 1
3.7%
9.73 1
3.7%
8.51 1
3.7%
8.28 1
3.7%
7.88 1
3.7%
7.16 1
3.7%
6.45 1
3.7%
4.08 1
3.7%

최근12개월표준점수
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)91.7%
Missing3
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean5.3045833
Minimum-25.2
Maximum13.25
Zeros0
Zeros (%)0.0%
Negative4
Negative (%)14.8%
Memory size375.0 B
2023-12-10T23:19:20.226636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-25.2
5-th percentile-4.86
Q11.9925
median8.78
Q39.1625
95-th percentile10.68
Maximum13.25
Range38.45
Interquartile range (IQR)7.17

Descriptive statistics

Standard deviation7.9569953
Coefficient of variation (CV)1.5000227
Kurtosis9.1196682
Mean5.3045833
Median Absolute Deviation (MAD)0.78
Skewness-2.7259751
Sum127.31
Variance63.313774
MonotonicityNot monotonic
2023-12-10T23:19:20.402255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
8.89 3
 
11.1%
-1.46 1
 
3.7%
8.49 1
 
3.7%
10.0 1
 
3.7%
8.04 1
 
3.7%
-5.46 1
 
3.7%
1.36 1
 
3.7%
5.66 1
 
3.7%
9.6 1
 
3.7%
-25.2 1
 
3.7%
Other values (12) 12
44.4%
(Missing) 3
 
11.1%
ValueCountFrequency (%)
-25.2 1
3.7%
-5.46 1
3.7%
-1.46 1
3.7%
-1.13 1
3.7%
1.36 1
3.7%
1.88 1
3.7%
2.03 1
3.7%
5.66 1
3.7%
8.04 1
3.7%
8.49 1
3.7%
ValueCountFrequency (%)
13.25 1
 
3.7%
10.8 1
 
3.7%
10.0 1
 
3.7%
9.6 1
 
3.7%
9.37 1
 
3.7%
9.2 1
 
3.7%
9.15 1
 
3.7%
8.96 1
 
3.7%
8.89 3
11.1%
8.86 1
 
3.7%

최초6개월표준점수
Real number (ℝ)

Distinct17
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.072962963
Minimum-1.95
Maximum0.96
Zeros0
Zeros (%)0.0%
Negative9
Negative (%)33.3%
Memory size375.0 B
2023-12-10T23:19:20.568043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.95
5-th percentile-1.047
Q1-0.35
median0.17
Q30.17
95-th percentile0.437
Maximum0.96
Range2.91
Interquartile range (IQR)0.52

Descriptive statistics

Standard deviation0.5645612
Coefficient of variation (CV)-7.7376408
Kurtosis4.1394953
Mean-0.072962963
Median Absolute Deviation (MAD)0.04
Skewness-1.6335608
Sum-1.97
Variance0.31872934
MonotonicityNot monotonic
2023-12-10T23:19:20.734711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.17 11
40.7%
-0.39 1
 
3.7%
-0.47 1
 
3.7%
-0.62 1
 
3.7%
0.18 1
 
3.7%
-0.17 1
 
3.7%
-0.31 1
 
3.7%
0.53 1
 
3.7%
-0.43 1
 
3.7%
-1.95 1
 
3.7%
Other values (7) 7
25.9%
ValueCountFrequency (%)
-1.95 1
3.7%
-1.23 1
3.7%
-0.62 1
3.7%
-0.61 1
3.7%
-0.47 1
3.7%
-0.43 1
3.7%
-0.39 1
3.7%
-0.31 1
3.7%
-0.17 1
3.7%
0.09 1
3.7%
ValueCountFrequency (%)
0.96 1
 
3.7%
0.53 1
 
3.7%
0.22 1
 
3.7%
0.21 1
 
3.7%
0.18 1
 
3.7%
0.17 11
40.7%
0.15 1
 
3.7%
0.09 1
 
3.7%
-0.17 1
 
3.7%
-0.31 1
 
3.7%

최초12개월표준점수
Real number (ℝ)

Distinct16
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.37037037
Minimum-0.24
Maximum1.22
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)3.7%
Memory size375.0 B
2023-12-10T23:19:20.896079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.24
5-th percentile0.083
Q10.25
median0.25
Q30.475
95-th percentile0.906
Maximum1.22
Range1.46
Interquartile range (IQR)0.225

Descriptive statistics

Standard deviation0.30030089
Coefficient of variation (CV)0.81081241
Kurtosis1.744912
Mean0.37037037
Median Absolute Deviation (MAD)0.09
Skewness1.0502425
Sum10
Variance0.090180627
MonotonicityNot monotonic
2023-12-10T23:19:21.031636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.25 11
40.7%
0.35 2
 
7.4%
0.65 1
 
3.7%
0.6 1
 
3.7%
0.74 1
 
3.7%
0.78 1
 
3.7%
0.24 1
 
3.7%
0.08 1
 
3.7%
0.3 1
 
3.7%
-0.24 1
 
3.7%
Other values (6) 6
22.2%
ValueCountFrequency (%)
-0.24 1
 
3.7%
0.08 1
 
3.7%
0.09 1
 
3.7%
0.15 1
 
3.7%
0.24 1
 
3.7%
0.25 11
40.7%
0.3 1
 
3.7%
0.34 1
 
3.7%
0.35 2
 
7.4%
0.6 1
 
3.7%
ValueCountFrequency (%)
1.22 1
3.7%
0.96 1
3.7%
0.78 1
3.7%
0.74 1
3.7%
0.65 1
3.7%
0.64 1
3.7%
0.6 1
3.7%
0.35 2
7.4%
0.34 1
3.7%
0.3 1
3.7%

개선도최근표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.069259
Minimum-31.17
Maximum36.61
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)7.4%
Memory size375.0 B
2023-12-10T23:19:21.165142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-31.17
5-th percentile-19.143
Q115.02
median18.29
Q319.59
95-th percentile26.173
Maximum36.61
Range67.78
Interquartile range (IQR)4.57

Descriptive statistics

Standard deviation14.37893
Coefficient of variation (CV)0.95418959
Kurtosis6.0359116
Mean15.069259
Median Absolute Deviation (MAD)1.6
Skewness-2.3144417
Sum406.87
Variance206.75364
MonotonicityNot monotonic
2023-12-10T23:19:21.307527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
18.26 3
 
11.1%
18.29 2
 
7.4%
18.39 2
 
7.4%
26.62 1
 
3.7%
-27.96 1
 
3.7%
17.81 1
 
3.7%
17.23 1
 
3.7%
12.81 1
 
3.7%
10.38 1
 
3.7%
1.43 1
 
3.7%
Other values (13) 13
48.1%
ValueCountFrequency (%)
-31.17 1
 
3.7%
-27.96 1
 
3.7%
1.43 1
 
3.7%
10.38 1
 
3.7%
10.5 1
 
3.7%
10.69 1
 
3.7%
12.81 1
 
3.7%
17.23 1
 
3.7%
17.81 1
 
3.7%
18.26 3
11.1%
ValueCountFrequency (%)
36.61 1
3.7%
26.62 1
3.7%
25.13 1
3.7%
25.07 1
3.7%
24.96 1
3.7%
23.53 1
3.7%
19.89 1
3.7%
19.29 1
3.7%
18.67 1
3.7%
18.66 1
3.7%

Interactions

2023-12-10T23:19:13.714780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:08.733711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.465200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.280823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.196873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.994522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.735625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:13.813408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:08.835300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.581454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.402744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.310949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.093566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.826700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:13.944090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:08.935702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.677478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.535871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.429525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.196751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.930485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:14.050862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.026755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.782595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.669367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.566200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.286014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:13.033149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:14.157489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.129993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.907579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.794154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.689557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.396704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:13.372288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:14.257031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.243810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.041346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.924003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.802741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.491864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:13.474159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:14.361010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:09.357575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:10.169379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.054362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:11.888041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:12.630041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:13.587183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:19:21.781244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
개선도지수채널ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도지수채널명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도지수수집일자1.0001.0001.0001.0001.000NaN0.0000.0001.0000.0000.0000.0000.0000.0000.128
개선도지수채널설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도채널생성일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
최근6개월개선도1.0001.000NaN1.0001.0001.0000.7460.0000.0000.0000.9780.7180.0000.8730.000
최근12개월개선도1.0001.0000.0001.0001.0000.7461.0000.3100.0000.0000.6110.6460.0000.0000.000
최초6개월개선도1.0001.0000.0001.0001.0000.0000.3101.0000.3610.0000.6390.4270.7160.0000.646
최초12개월개선도1.0001.0001.0001.0001.0000.0000.0000.3611.0000.0000.5850.0000.0000.0000.000
최근개선도지수1.0001.0000.0001.0001.0000.0000.0000.0000.0001.0000.0000.0000.7930.2490.823
최근6개월표준점수1.0001.0000.0001.0001.0000.9780.6110.6390.5850.0001.0000.6530.0000.3440.342
최근12개월표준점수1.0001.0000.0001.0001.0000.7180.6460.4270.0000.0000.6531.0000.2940.8280.578
최초6개월표준점수1.0001.0000.0001.0001.0000.0000.0000.7160.0000.7930.0000.2941.0000.8870.586
최초12개월표준점수1.0001.0000.0001.0001.0000.8730.0000.0000.0000.2490.3440.8280.8871.0000.559
개선도최근표준점수1.0001.0000.1281.0001.0000.0000.0000.6460.0000.8230.3420.5780.5860.5591.000
2023-12-10T23:19:22.004927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초12개월개선도최근12개월개선도최초6개월개선도
최초12개월개선도1.0000.0000.543
최근12개월개선도0.0001.0000.436
최초6개월개선도0.5430.4361.000
2023-12-10T23:19:22.139407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최근6개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수최근12개월개선도최초6개월개선도최초12개월개선도
최근6개월개선도1.0000.0550.5960.359-0.3600.287-0.0790.6090.0000.000
최근개선도지수0.0551.000-0.071-0.247-0.3520.116-0.5990.0000.0000.000
최근6개월표준점수0.596-0.0711.000-0.269-0.024-0.051-0.2210.3950.3330.158
최근12개월표준점수0.359-0.247-0.2691.0000.2090.1440.4460.3970.4190.000
최초6개월표준점수-0.360-0.352-0.0240.2091.000-0.4790.1000.0000.3480.000
최초12개월표준점수0.2870.116-0.0510.144-0.4791.000-0.1570.0000.0000.000
개선도최근표준점수-0.079-0.599-0.2210.4460.100-0.1571.0000.0000.3540.000
최근12개월개선도0.6090.0000.3950.3970.0000.0000.0001.0000.4360.000
최초6개월개선도0.0000.0000.3330.4190.3480.0000.3540.4361.0000.543
최초12개월개선도0.0000.0000.1580.0000.0000.0000.0000.0000.5431.000

Missing values

2023-12-10T23:19:14.519607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:19:14.722460image/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.
2023-12-10T23:19:14.923698image/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

개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
0UCy_OWMB42I6bqaJQjJenKJA성우 김혜성의 혜성TV2021-01-11엽기병맛 비글 성우 김혜성과 함께 즐기는 성우 세계!!!! 이제는 대성우시대! 즐겁게 살자라는 신념으로 유튜브 만들고 있습니다 게임도 하고 성우란 직업도 알아보는 성우컨텐츠의 집합소~ 성우 김혜성 홍보홍보 합시다 김혜성 대성 하리라 모두에게 즐거움을 주리라!! https:www.facebook.comgenjicomet 페이스북에서 방송이나 컨텐츠 알림합니다~ 트위치 https:www.twitch.tvgenjicomettv 에서 게임방송합니다 많이 구경 오시구 구독해주세요~^-^ seiyucoute@gmail.com 으로 사연도 좋고 고민도 좋고 질문도 좋고 아무거나 보내주세요~^-^2018-08-30<NA><NA>0-10.0-10.649.37-0.390.6526.62
1UCL-GJ5bmSpexd1-lVbG0xtQ토군2021-01-14재밌게 보셨다면 '좋아요' 구독하기 꼭 부탁드립니다^^2017-06-02<NA><NA><NA><NA><NA>-6.139.20.170.2524.96
2UCw6AmebJ0sUuDdfFNFfa74gboomiunni2021-01-15그냥 나의 기록들2011-10-07<NA><NA><NA><NA><NA>-9.0513.250.170.2525.13
3UCXF_eVsuOWsWX6uIucimUrwEunjung 은정2021-01-22<NA>2010-10-29<NA>1<NA><NA>0.0-10.5910.80.170.2525.07
4UC2tGWq3BCZUDAgNh965yM-A파쇄축2021-01-27철권 관련 영상 채널입니다.2013-08-19<NA><NA>000.07.888.70.090.1536.61
5UC3m0s5XAQydCtbLHc8j1UogKBS 한국방송2021-01-27대한민국 대표 공영방송 KBS(Korean Broadcasting System) 의 공식 유튜브 채널 입니다. 재미있고 유익한 소식을 전하겠습니다.2011-08-24-484<NA><NA>30.84-34.951.880.170.2518.29
6UC0bm8kKuMp8chJuxzlLnlnA주예지 JOOYEJI2021-01-27<NA><NA>-21000.09.738.860.960.3418.66
7UC499dzcb2Fx9RD39Vqpz-lg강원도 - Gangwon2021-01-27평화와 번영; 강원시대! 강원도의 모든 것을 전세계인과 함께 나눕니다! [강원도청 공식 유튜브] Peace and prosperity; Gangwon time! Share all the information in Gangwon Province with people from all over the world! [official YouTube channel of Gangwon Province] 페이스북 https:www.facebook.comgwdoraeyo 네이버블로그 https:blog.naver.comgwdoraeyo 인스타그램 https:www.instagram.comgangwon_official 트위터 https:twitter.comhappygangwon 카카오스토리 https:story.kakao.comchbanbiraeyo 홈페이지 http:www.provin.gangwon.krgwportal2014-05-15-41<NA><NA>68.72-3.51<NA>-0.610.9610.69
8UC4KEOaKK3hYA8sAHogi1bAg리얼베어TV2021-01-27사진과 캠핑을 즐기고 있는 3교대 직장인의 공간 입니다2012-02-12<NA><NA><NA><NA><NA>-2.288.960.170.2518.29
9UC-JZtfVAgIjmNfhapEV3zgg차차튜브 Chacha Tube2021-01-27Emailchadahye@gmail.com Insta cha.dahye2015-10-23<NA><NA><NA><NA>0.0-2.289.150.170.2518.67
개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
17UC8YB7__KHYn1IfqMMl00XUw자유분방TravelLog2021-01-27http:blog.naver.combk32167 여행영상; 타임랩스 영상 등2011-10-26<NA><NA><NA><NA><NA>11.58<NA>0.170.2519.89
18UC8gCJEe6FFHdhZyul6zLeMQ생방송심야토론2021-01-27<NA>2018-06-07-610022.26-25.699.60.530.3518.39
19UC69l_rtlCQ7M4Mz2RCS80BA미야옹철의 냥냥펀치2021-01-27반려묘 행동 전문 수의사 김명철이 들려주는 현실 집사 이야기 Cat president's Cat talk ♥ 업로드 : 화금 오후 7시 ♥ Upload : TueFri at 7pm ♥ Instagram : http:instagram.comgrrvet http:instagram.comcat_samonim http:instagram.comcat_babyc2018-11-23-3300183.346.455.66-0.310.310.5
20UC9153vUIKS_nEltqwdQX-6A세경2021-01-27안녕하세요 구독자여러분들! 다양한 요리 영상과 먹방 영상; 일상영상등을 업로드 중 이에요♥ 구독하기& 좋아요 많이 부탁드려요♥ Instagram _ 33wannabe332015-06-25<NA><NA><NA><NA><NA>-2.288.890.170.2518.39
21UC99OELa9yvqgkq9ffBvm9iQ갑수목장gabsupasture2021-01-27갑수목장에 오신 것을 환영합니다. 좋아요와 구독 진심으로 감사드립니다. pgs3620@naver.com2019-01-15<NA><NA><NA><NA><NA>-2.288.890.170.2518.26
22UC6Jl3MrfGBvRYxXgdDxXzVADOJIN도진이2021-01-27<NA>2019-07-23-2100137.51-9.691.36-0.170.081.43
23UC1dK7oMUSR9Rnk1BSpOKZng정선호2021-01-27<NA>2011-01-10-490<NA><NA>25.03-4.56-5.460.170.2510.38
24UCCD5onP_ljXqu0Us89Wm-WwKIDS한국의약품안전관리원2021-01-27<NA>2017-01-18<NA><NA><NA><NA><NA>21.048.040.180.2412.81
25UCCIR1qib7R1mR77byZJ0MiQ블루베리TV2021-01-27블루베리TV에 방문해 주셔서 감사합니다^^^ 저는 전남 고흥에서 베리드림이라는 상호로 블루베리농장을 10년이상 운영하고 있습니다. 저는 이 채널을 통하여 첫째 블루베리재배에 방법에 관한 이론과 현장 실습; 그리고 저희 농장에 여러분들을 직접 모셔서 현장감 있는 정보공유; 둘째 농업에 관한 기본적인 이론; 세째 그리고 저희 농장일상과 저의 취미생활 등을 공유하여 여러분과 소통하고자 합니다. 구독과 좋아요 그리고 알람 설정까지 여러분들의 많은 응원 ; 부탁드립니다^^^2018-12-13<NA>21134.17-2.3110.0-0.620.7817.23
26UCCflwTdJf1fQxKilMVAuW2wbexco2021-01-27<NA>2019-04-08<NA><NA>00<NA>16.818.49-0.470.7417.81