Overview

Dataset statistics

Number of variables15
Number of observations28
Missing cells52
Missing cells (%)12.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory134.7 B

Variable types

Text3
DateTime2
Numeric8
Categorical2

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/f2dd7c8b-e193-4d9a-82ca-a342fcb686fd

Alerts

개선도지수수집일자 has constant value ""Constant
최근개선도지수 is highly overall correlated with 개선도최근표준점수High correlation
개선도최근표준점수 is highly overall correlated with 최근개선도지수High correlation
최초6개월개선도 is highly overall correlated with 최초12개월개선도High correlation
최초12개월개선도 is highly overall correlated with 최초6개월개선도High correlation
개선도지수채널설명 has 6 (21.4%) missing valuesMissing
개선도채널생성일자 has 1 (3.6%) missing valuesMissing
최근6개월개선도 has 18 (64.3%) missing valuesMissing
최근12개월개선도 has 15 (53.6%) missing valuesMissing
최근개선도지수 has 10 (35.7%) missing valuesMissing
최근6개월표준점수 has 2 (7.1%) missing valuesMissing
개선도지수채널ID has unique valuesUnique
개선도지수채널명 has unique valuesUnique
최근6개월개선도 has 1 (3.6%) zerosZeros
최근12개월개선도 has 2 (7.1%) zerosZeros
최근개선도지수 has 7 (25.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:21:36.693556
Analysis finished2023-12-10 14:21:44.812028
Duration8.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개선도지수채널ID
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T23:21:44.977642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters672
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

Unique28 ?
Unique (%)100.0%

Sample

1st rowUC0bm8kKuMp8chJuxzlLnlnA
2nd rowUC-JZtfVAgIjmNfhapEV3zgg
3rd rowUC2tGWq3BCZUDAgNh965yM-A
4th rowUC1dK7oMUSR9Rnk1BSpOKZng
5th rowUC3m0s5XAQydCtbLHc8j1Uog
ValueCountFrequency (%)
uc0bm8kkump8chjuxzllnlna 1
 
3.6%
uc-jztfvagijmnfhapev3zgg 1
 
3.6%
uccflwtdjf1fqxkilmvauw2w 1
 
3.6%
uccir1qib7r1mr77byzj0miq 1
 
3.6%
ucaj-meoch1trpz7la3upprw 1
 
3.6%
uccd5onp_ljxqu0us89wm-ww 1
 
3.6%
uc9dpfivlnpbohm81mfghhsq 1
 
3.6%
uc9egnou8y9ty3zkrxfk0t_w 1
 
3.6%
uc99oela9yvqgkq9ffbvm9iq 1
 
3.6%
uc9153vuiks_neltqwdqx-6a 1
 
3.6%
Other values (18) 18
64.3%
2023-12-10T23:21:45.318861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 39
 
5.8%
U 37
 
5.5%
9 20
 
3.0%
g 17
 
2.5%
A 17
 
2.5%
l 16
 
2.4%
w 16
 
2.4%
t 15
 
2.2%
1 15
 
2.2%
d 14
 
2.1%
Other values (54) 466
69.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 287
42.7%
Lowercase Letter 257
38.2%
Decimal Number 109
 
16.2%
Connector Punctuation 10
 
1.5%
Dash Punctuation 9
 
1.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 39
 
13.6%
U 37
 
12.9%
A 17
 
5.9%
Q 14
 
4.9%
Y 13
 
4.5%
M 12
 
4.2%
E 11
 
3.8%
B 10
 
3.5%
K 10
 
3.5%
F 10
 
3.5%
Other values (16) 114
39.7%
Lowercase Letter
ValueCountFrequency (%)
g 17
 
6.6%
l 16
 
6.2%
w 16
 
6.2%
t 15
 
5.8%
d 14
 
5.4%
m 13
 
5.1%
q 12
 
4.7%
f 11
 
4.3%
x 11
 
4.3%
z 10
 
3.9%
Other values (16) 122
47.5%
Decimal Number
ValueCountFrequency (%)
9 20
18.3%
1 15
13.8%
7 14
12.8%
3 13
11.9%
8 12
11.0%
6 9
8.3%
0 9
8.3%
4 6
 
5.5%
2 6
 
5.5%
5 5
 
4.6%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 544
81.0%
Common 128
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 39
 
7.2%
U 37
 
6.8%
g 17
 
3.1%
A 17
 
3.1%
l 16
 
2.9%
w 16
 
2.9%
t 15
 
2.8%
d 14
 
2.6%
Q 14
 
2.6%
m 13
 
2.4%
Other values (42) 346
63.6%
Common
ValueCountFrequency (%)
9 20
15.6%
1 15
11.7%
7 14
10.9%
3 13
10.2%
8 12
9.4%
_ 10
7.8%
6 9
7.0%
- 9
7.0%
0 9
7.0%
4 6
 
4.7%
Other values (2) 11
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 39
 
5.8%
U 37
 
5.5%
9 20
 
3.0%
g 17
 
2.5%
A 17
 
2.5%
l 16
 
2.4%
w 16
 
2.4%
t 15
 
2.2%
1 15
 
2.2%
d 14
 
2.1%
Other values (54) 466
69.3%

개선도지수채널명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T23:21:45.570817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length8.3571429
Min length2

Characters and Unicode

Total characters234
Distinct characters129
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 (%)100.0%

Sample

1st row주예지 JOOYEJI
2nd row차차튜브 Chacha Tube
3rd row파쇄축
4th row정선호
5th rowKBS 한국방송
ValueCountFrequency (%)
주예지 1
 
2.4%
자유분방travellog 1
 
2.4%
daedue 1
 
2.4%
tv 1
 
2.4%
재외동포재단_okf 1
 
2.4%
0zoo 1
 
2.4%
영주 1
 
2.4%
황꿀 1
 
2.4%
gguul's 1
 
2.4%
boundary 1
 
2.4%
Other values (32) 32
76.2%
2023-12-10T23:21:46.018283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
6.0%
a 8
 
3.4%
u 7
 
3.0%
o 6
 
2.6%
e 6
 
2.6%
T 6
 
2.6%
g 5
 
2.1%
O 4
 
1.7%
b 4
 
1.7%
V 4
 
1.7%
Other values (119) 170
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
50.4%
Lowercase Letter 60
25.6%
Uppercase Letter 36
 
15.4%
Space Separator 14
 
6.0%
Other Punctuation 1
 
0.4%
Decimal Number 1
 
0.4%
Connector Punctuation 1
 
0.4%
Dash Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 3
 
2.5%
방 3
 
2.5%
도 3
 
2.5%
주 3
 
2.5%
의 3
 
2.5%
경 3
 
2.5%
라 3
 
2.5%
재 3
 
2.5%
한 3
 
2.5%
리 3
 
2.5%
Other values (76) 88
74.6%
Lowercase Letter
ValueCountFrequency (%)
a 8
13.3%
u 7
11.7%
o 6
10.0%
e 6
10.0%
g 5
 
8.3%
b 4
 
6.7%
n 3
 
5.0%
r 3
 
5.0%
s 3
 
5.0%
l 2
 
3.3%
Other values (10) 13
21.7%
Uppercase Letter
ValueCountFrequency (%)
T 6
16.7%
O 4
11.1%
V 4
11.1%
K 3
8.3%
D 3
8.3%
I 3
8.3%
J 3
8.3%
S 2
 
5.6%
L 1
 
2.8%
F 1
 
2.8%
Other values (6) 6
16.7%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
50.4%
Latin 96
41.0%
Common 20
 
8.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 3
 
2.5%
방 3
 
2.5%
도 3
 
2.5%
주 3
 
2.5%
의 3
 
2.5%
경 3
 
2.5%
라 3
 
2.5%
재 3
 
2.5%
한 3
 
2.5%
리 3
 
2.5%
Other values (76) 88
74.6%
Latin
ValueCountFrequency (%)
a 8
 
8.3%
u 7
 
7.3%
o 6
 
6.2%
e 6
 
6.2%
T 6
 
6.2%
g 5
 
5.2%
O 4
 
4.2%
b 4
 
4.2%
V 4
 
4.2%
n 3
 
3.1%
Other values (26) 43
44.8%
Common
ValueCountFrequency (%)
14
70.0%
' 1
 
5.0%
0 1
 
5.0%
_ 1
 
5.0%
- 1
 
5.0%
) 1
 
5.0%
( 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
50.4%
ASCII 116
49.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
 
12.1%
a 8
 
6.9%
u 7
 
6.0%
o 6
 
5.2%
e 6
 
5.2%
T 6
 
5.2%
g 5
 
4.3%
O 4
 
3.4%
b 4
 
3.4%
V 4
 
3.4%
Other values (33) 52
44.8%
Hangul
ValueCountFrequency (%)
국 3
 
2.5%
방 3
 
2.5%
도 3
 
2.5%
주 3
 
2.5%
의 3
 
2.5%
경 3
 
2.5%
라 3
 
2.5%
재 3
 
2.5%
한 3
 
2.5%
리 3
 
2.5%
Other values (76) 88
74.6%

개선도지수수집일자
Date

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2021-03-31 00:00:00
Maximum2021-03-31 00:00:00
2023-12-10T23:21:46.144362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:46.253712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

개선도지수채널설명
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing6
Missing (%)21.4%
Memory size356.0 B
2023-12-10T23:21:46.544303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length456
Median length89.5
Mean length142.22727
Min length7

Characters and Unicode

Total characters3129
Distinct characters396
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

Unique22 ?
Unique (%)100.0%

Sample

1st rowEmailchadahye@gmail.com Insta cha.dahye
2nd row철권 관련 영상 채널입니다.
3rd row대한민국 대표 공영방송 KBS(Korean Broadcasting System) 의 공식 유튜브 채널 입니다. 재미있고 유익한 소식을 전하겠습니다.
4th row평화와 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.krgwportal
5th row사진과 캠핑을 즐기고 있는 3교대 직장인의 공간 입니다
ValueCountFrequency (%)
30
 
5.5%
미라지 5
 
0.9%
◐ 4
 
0.7%
함께 4
 
0.7%
제 4
 
0.7%
유튜브 4
 
0.7%
공식 4
 
0.7%
많이 4
 
0.7%
채널입니다 4
 
0.7%
영상 4
 
0.7%
Other values (403) 475
87.6%
2023-12-10T23:21:47.050075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
610
 
19.5%
a 77
 
2.5%
t 74
 
2.4%
o 73
 
2.3%
. 66
 
2.1%
n 48
 
1.5%
e 47
 
1.5%
r 43
 
1.4%
: 40
 
1.3%
g 38
 
1.2%
Other values (386) 2013
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1405
44.9%
Lowercase Letter 757
24.2%
Space Separator 610
19.5%
Other Punctuation 180
 
5.8%
Decimal Number 70
 
2.2%
Uppercase Letter 52
 
1.7%
Close Punctuation 13
 
0.4%
Open Punctuation 11
 
0.4%
Other Symbol 9
 
0.3%
Math Symbol 7
 
0.2%
Other values (3) 15
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
니 37
 
2.6%
이 37
 
2.6%
다 37
 
2.6%
하 27
 
1.9%
는 25
 
1.8%
상 23
 
1.6%
ㅡ 22
 
1.6%
요 21
 
1.5%
을 21
 
1.5%
에 20
 
1.4%
Other values (307) 1135
80.8%
Lowercase Letter
ValueCountFrequency (%)
a 77
 
10.2%
t 74
 
9.8%
o 73
 
9.6%
n 48
 
6.3%
e 47
 
6.2%
r 43
 
5.7%
g 38
 
5.0%
m 38
 
5.0%
w 37
 
4.9%
i 37
 
4.9%
Other values (16) 245
32.4%
Uppercase Letter
ValueCountFrequency (%)
T 9
17.3%
V 6
11.5%
S 5
9.6%
P 4
 
7.7%
I 3
 
5.8%
G 3
 
5.8%
Y 3
 
5.8%
K 3
 
5.8%
D 2
 
3.8%
F 2
 
3.8%
Other values (10) 12
23.1%
Other Punctuation
ValueCountFrequency (%)
. 66
36.7%
: 40
22.2%
! 18
 
10.0%
' 17
 
9.4%
; 16
 
8.9%
# 12
 
6.7%
@ 6
 
3.3%
? 2
 
1.1%
* 2
 
1.1%
& 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 14
20.0%
3 12
17.1%
2 12
17.1%
1 11
15.7%
7 7
10.0%
4 3
 
4.3%
6 3
 
4.3%
8 3
 
4.3%
5 3
 
4.3%
9 2
 
2.9%
Math Symbol
ValueCountFrequency (%)
⊙ 4
57.1%
~ 2
28.6%
+ 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 10
76.9%
] 3
 
23.1%
Open Punctuation
ValueCountFrequency (%)
( 8
72.7%
[ 3
 
27.3%
Other Symbol
ValueCountFrequency (%)
♥ 5
55.6%
◐ 4
44.4%
Space Separator
ValueCountFrequency (%)
610
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1405
44.9%
Common 915
29.2%
Latin 809
25.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
니 37
 
2.6%
이 37
 
2.6%
다 37
 
2.6%
하 27
 
1.9%
는 25
 
1.8%
상 23
 
1.6%
ㅡ 22
 
1.6%
요 21
 
1.5%
을 21
 
1.5%
에 20
 
1.4%
Other values (307) 1135
80.8%
Latin
ValueCountFrequency (%)
a 77
 
9.5%
t 74
 
9.1%
o 73
 
9.0%
n 48
 
5.9%
e 47
 
5.8%
r 43
 
5.3%
g 38
 
4.7%
m 38
 
4.7%
w 37
 
4.6%
i 37
 
4.6%
Other values (36) 297
36.7%
Common
ValueCountFrequency (%)
610
66.7%
. 66
 
7.2%
: 40
 
4.4%
! 18
 
2.0%
' 17
 
1.9%
; 16
 
1.7%
0 14
 
1.5%
3 12
 
1.3%
# 12
 
1.3%
2 12
 
1.3%
Other values (23) 98
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1711
54.7%
Hangul 1381
44.1%
Compat Jamo 24
 
0.8%
Misc Symbols 5
 
0.2%
Math Operators 4
 
0.1%
Geometric Shapes 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
610
35.7%
a 77
 
4.5%
t 74
 
4.3%
o 73
 
4.3%
. 66
 
3.9%
n 48
 
2.8%
e 47
 
2.7%
r 43
 
2.5%
: 40
 
2.3%
g 38
 
2.2%
Other values (66) 595
34.8%
Hangul
ValueCountFrequency (%)
니 37
 
2.7%
이 37
 
2.7%
다 37
 
2.7%
하 27
 
2.0%
는 25
 
1.8%
상 23
 
1.7%
요 21
 
1.5%
을 21
 
1.5%
에 20
 
1.4%
영 19
 
1.4%
Other values (305) 1114
80.7%
Compat Jamo
ValueCountFrequency (%)
ㅡ 22
91.7%
ㅠ 2
 
8.3%
Misc Symbols
ValueCountFrequency (%)
♥ 5
100.0%
Math Operators
ValueCountFrequency (%)
⊙ 4
100.0%
Geometric Shapes
ValueCountFrequency (%)
◐ 4
100.0%

개선도채널생성일자
Date

MISSING 

Distinct27
Distinct (%)100.0%
Missing1
Missing (%)3.6%
Memory size356.0 B
Minimum2011-01-10 00:00:00
Maximum2019-07-23 00:00:00
2023-12-10T23:21:47.260834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:47.446400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

최근6개월개선도
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)100.0%
Missing18
Missing (%)64.3%
Infinite0
Infinite (%)0.0%
Mean-12
Minimum-54
Maximum13
Zeros1
Zeros (%)3.6%
Negative7
Negative (%)25.0%
Memory size384.0 B
2023-12-10T23:21:47.576036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-54
5-th percentile-51.75
Q1-10.5
median-6
Q3-0.5
95-th percentile8.95
Maximum13
Range67
Interquartile range (IQR)10

Descriptive statistics

Standard deviation21.964618
Coefficient of variation (CV)-1.8303848
Kurtosis0.7954728
Mean-12
Median Absolute Deviation (MAD)5.5
Skewness-1.3342194
Sum-120
Variance482.44444
MonotonicityNot monotonic
2023-12-10T23:21:47.714545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
-54 1
 
3.6%
-5 1
 
3.6%
13 1
 
3.6%
-7 1
 
3.6%
-11 1
 
3.6%
4 1
 
3.6%
-49 1
 
3.6%
-2 1
 
3.6%
-9 1
 
3.6%
0 1
 
3.6%
(Missing) 18
64.3%
ValueCountFrequency (%)
-54 1
3.6%
-49 1
3.6%
-11 1
3.6%
-9 1
3.6%
-7 1
3.6%
-5 1
3.6%
-2 1
3.6%
0 1
3.6%
4 1
3.6%
13 1
3.6%
ValueCountFrequency (%)
13 1
3.6%
4 1
3.6%
0 1
3.6%
-2 1
3.6%
-5 1
3.6%
-7 1
3.6%
-9 1
3.6%
-11 1
3.6%
-49 1
3.6%
-54 1
3.6%

최근12개월개선도
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)53.8%
Missing15
Missing (%)53.6%
Infinite0
Infinite (%)0.0%
Mean1.6153846
Minimum-7
Maximum43
Zeros2
Zeros (%)7.1%
Negative9
Negative (%)32.1%
Memory size384.0 B
2023-12-10T23:21:47.848183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7
5-th percentile-7
Q1-2
median-1
Q30
95-th percentile18.4
Maximum43
Range50
Interquartile range (IQR)2

Descriptive statistics

Standard deviation12.698678
Coefficient of variation (CV)7.8610861
Kurtosis11.688955
Mean1.6153846
Median Absolute Deviation (MAD)1
Skewness3.3356559
Sum21
Variance161.25641
MonotonicityNot monotonic
2023-12-10T23:21:47.943491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
-1 5
 
17.9%
0 2
 
7.1%
-7 2
 
7.1%
-2 1
 
3.6%
43 1
 
3.6%
2 1
 
3.6%
-3 1
 
3.6%
(Missing) 15
53.6%
ValueCountFrequency (%)
-7 2
 
7.1%
-3 1
 
3.6%
-2 1
 
3.6%
-1 5
17.9%
0 2
 
7.1%
2 1
 
3.6%
43 1
 
3.6%
ValueCountFrequency (%)
43 1
 
3.6%
2 1
 
3.6%
0 2
 
7.1%
-1 5
17.9%
-2 1
 
3.6%
-3 1
 
3.6%
-7 2
 
7.1%

최초6개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
13 
0
11 
1
4 

Length

Max length4
Median length1
Mean length2.3928571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 13
46.4%
0 11
39.3%
1 4
 
14.3%

Length

2023-12-10T23:21:48.048984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:21:48.141449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
46.4%
0 11
39.3%
1 4
 
14.3%

최초12개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
13 
0
12 
1
3 

Length

Max length4
Median length1
Mean length2.3928571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 13
46.4%
0 12
42.9%
1 3
 
10.7%

Length

2023-12-10T23:21:48.235653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:21:48.329427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
46.4%
0 12
42.9%
1 3
 
10.7%

최근개선도지수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct12
Distinct (%)66.7%
Missing10
Missing (%)35.7%
Infinite0
Infinite (%)0.0%
Mean35.091111
Minimum0
Maximum196.83
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T23:21:48.408392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15.22
Q339.8
95-th percentile113.326
Maximum196.83
Range196.83
Interquartile range (IQR)39.8

Descriptive statistics

Standard deviation51.601037
Coefficient of variation (CV)1.4704874
Kurtosis4.9641781
Mean35.091111
Median Absolute Deviation (MAD)15.22
Skewness2.1227306
Sum631.64
Variance2662.6671
MonotonicityNot monotonic
2023-12-10T23:21:48.537865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 7
25.0%
19.33 1
 
3.6%
13.82 1
 
3.6%
27.96 1
 
3.6%
196.83 1
 
3.6%
98.59 1
 
3.6%
16.62 1
 
3.6%
13.3 1
 
3.6%
93.3 1
 
3.6%
73.31 1
 
3.6%
Other values (2) 2
 
7.1%
(Missing) 10
35.7%
ValueCountFrequency (%)
0.0 7
25.0%
13.3 1
 
3.6%
13.82 1
 
3.6%
16.62 1
 
3.6%
19.33 1
 
3.6%
27.96 1
 
3.6%
38.27 1
 
3.6%
40.31 1
 
3.6%
73.31 1
 
3.6%
93.3 1
 
3.6%
ValueCountFrequency (%)
196.83 1
3.6%
98.59 1
3.6%
93.3 1
3.6%
73.31 1
3.6%
40.31 1
3.6%
38.27 1
3.6%
27.96 1
3.6%
19.33 1
3.6%
16.62 1
3.6%
13.82 1
3.6%

최근6개월표준점수
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)73.1%
Missing2
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean-7.1584615
Minimum-25.31
Maximum11.77
Zeros0
Zeros (%)0.0%
Negative20
Negative (%)71.4%
Memory size384.0 B
2023-12-10T23:21:48.646492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-25.31
5-th percentile-15.1725
Q1-11.93
median-10.79
Q3-2.71
95-th percentile8.825
Maximum11.77
Range37.08
Interquartile range (IQR)9.22

Descriptive statistics

Standard deviation8.2872551
Coefficient of variation (CV)-1.1576866
Kurtosis0.71413025
Mean-7.1584615
Median Absolute Deviation (MAD)2.795
Skewness0.57436074
Sum-186.12
Variance68.678598
MonotonicityNot monotonic
2023-12-10T23:21:48.746756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
-11.93 7
25.0%
-11.32 2
 
7.1%
-2.36 1
 
3.6%
-25.31 1
 
3.6%
-13.41 1
 
3.6%
-4.35 1
 
3.6%
-8.24 1
 
3.6%
11.77 1
 
3.6%
-12.96 1
 
3.6%
-4.17 1
 
3.6%
Other values (9) 9
32.1%
(Missing) 2
 
7.1%
ValueCountFrequency (%)
-25.31 1
 
3.6%
-15.76 1
 
3.6%
-13.41 1
 
3.6%
-12.96 1
 
3.6%
-11.93 7
25.0%
-11.32 2
 
7.1%
-10.26 1
 
3.6%
-8.24 1
 
3.6%
-7.82 1
 
3.6%
-4.35 1
 
3.6%
ValueCountFrequency (%)
11.77 1
3.6%
10.98 1
3.6%
2.36 1
3.6%
1.88 1
3.6%
1.17 1
3.6%
0.27 1
3.6%
-2.36 1
3.6%
-3.76 1
3.6%
-4.17 1
3.6%
-4.35 1
3.6%

최근12개월표준점수
Real number (ℝ)

Distinct23
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.3960714
Minimum-10.26
Maximum7.76
Zeros0
Zeros (%)0.0%
Negative21
Negative (%)75.0%
Memory size384.0 B
2023-12-10T23:21:48.844365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10.26
5-th percentile-6.27
Q1-2.8325
median-2.19
Q30.09
95-th percentile3.723
Maximum7.76
Range18.02
Interquartile range (IQR)2.9225

Descriptive statistics

Standard deviation3.444571
Coefficient of variation (CV)-2.4673315
Kurtosis1.9375726
Mean-1.3960714
Median Absolute Deviation (MAD)1.22
Skewness0.20172996
Sum-39.09
Variance11.865069
MonotonicityNot monotonic
2023-12-10T23:21:48.942285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
-2.38 5
 
17.9%
1.35 2
 
7.1%
1.6 1
 
3.6%
-0.66 1
 
3.6%
7.76 1
 
3.6%
-2.87 1
 
3.6%
-2.88 1
 
3.6%
-4.97 1
 
3.6%
-1.76 1
 
3.6%
-0.8 1
 
3.6%
Other values (13) 13
46.4%
ValueCountFrequency (%)
-10.26 1
 
3.6%
-6.97 1
 
3.6%
-4.97 1
 
3.6%
-3.71 1
 
3.6%
-3.24 1
 
3.6%
-2.88 1
 
3.6%
-2.87 1
 
3.6%
-2.82 1
 
3.6%
-2.38 5
17.9%
-2.22 1
 
3.6%
ValueCountFrequency (%)
7.76 1
3.6%
3.94 1
3.6%
3.32 1
3.6%
2.55 1
3.6%
1.6 1
3.6%
1.35 2
7.1%
-0.33 1
3.6%
-0.66 1
3.6%
-0.8 1
3.6%
-1.43 1
3.6%

최초6개월표준점수
Real number (ℝ)

Distinct17
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.043571429
Minimum-1.48
Maximum0.92
Zeros0
Zeros (%)0.0%
Negative8
Negative (%)28.6%
Memory size384.0 B
2023-12-10T23:21:49.037157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.48
5-th percentile-1.1055
Q1-0.22
median0.17
Q30.17
95-th percentile0.435
Maximum0.92
Range2.4
Interquartile range (IQR)0.39

Descriptive statistics

Standard deviation0.51411351
Coefficient of variation (CV)-11.799326
Kurtosis2.2738399
Mean-0.043571429
Median Absolute Deviation (MAD)0.035
Skewness-1.3479096
Sum-1.22
Variance0.2643127
MonotonicityNot monotonic
2023-12-10T23:21:49.138985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.17 12
42.9%
0.92 1
 
3.6%
-0.41 1
 
3.6%
-0.67 1
 
3.6%
0.18 1
 
3.6%
0.1 1
 
3.6%
0.54 1
 
3.6%
-0.66 1
 
3.6%
-1.48 1
 
3.6%
0.21 1
 
3.6%
Other values (7) 7
25.0%
ValueCountFrequency (%)
-1.48 1
3.6%
-1.34 1
3.6%
-0.67 1
3.6%
-0.66 1
3.6%
-0.59 1
3.6%
-0.41 1
3.6%
-0.34 1
3.6%
-0.18 1
3.6%
0.08 1
3.6%
0.1 1
3.6%
ValueCountFrequency (%)
0.92 1
 
3.6%
0.54 1
 
3.6%
0.24 1
 
3.6%
0.21 1
 
3.6%
0.18 1
 
3.6%
0.17 12
42.9%
0.14 1
 
3.6%
0.1 1
 
3.6%
0.08 1
 
3.6%
-0.18 1
 
3.6%

최초12개월표준점수
Real number (ℝ)

Distinct17
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.35714286
Minimum-0.23
Maximum1.21
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)3.6%
Memory size384.0 B
2023-12-10T23:21:49.228038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.23
5-th percentile0.0935
Q10.25
median0.25
Q30.3425
95-th percentile0.923
Maximum1.21
Range1.44
Interquartile range (IQR)0.0925

Descriptive statistics

Standard deviation0.29041295
Coefficient of variation (CV)0.81315626
Kurtosis2.4654847
Mean0.35714286
Median Absolute Deviation (MAD)0.065
Skewness1.2914368
Sum10
Variance0.084339683
MonotonicityNot monotonic
2023-12-10T23:21:49.333573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.25 11
39.3%
0.32 2
 
7.1%
0.78 1
 
3.6%
0.75 1
 
3.6%
0.24 1
 
3.6%
0.31 1
 
3.6%
0.35 1
 
3.6%
0.58 1
 
3.6%
1.21 1
 
3.6%
-0.23 1
 
3.6%
Other values (7) 7
25.0%
ValueCountFrequency (%)
-0.23 1
 
3.6%
0.09 1
 
3.6%
0.1 1
 
3.6%
0.15 1
 
3.6%
0.24 1
 
3.6%
0.25 11
39.3%
0.3 1
 
3.6%
0.31 1
 
3.6%
0.32 2
 
7.1%
0.34 1
 
3.6%
ValueCountFrequency (%)
1.21 1
3.6%
1.0 1
3.6%
0.78 1
3.6%
0.75 1
3.6%
0.64 1
3.6%
0.58 1
3.6%
0.35 1
3.6%
0.34 1
3.6%
0.32 2
7.1%
0.31 1
3.6%

개선도최근표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.223571
Minimum-30.34
Maximum249.84
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)7.1%
Memory size384.0 B
2023-12-10T23:21:49.441268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-30.34
5-th percentile-1.4795
Q115.7025
median18.55
Q318.8975
95-th percentile63.825
Maximum249.84
Range280.18
Interquartile range (IQR)3.195

Descriptive statistics

Standard deviation47.05656
Coefficient of variation (CV)1.8655788
Kurtosis20.843024
Mean25.223571
Median Absolute Deviation (MAD)1.29
Skewness4.313751
Sum706.26
Variance2214.3198
MonotonicityNot monotonic
2023-12-10T23:21:49.540211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
18.55 3
 
10.7%
18.98 1
 
3.6%
249.84 1
 
3.6%
22.1 1
 
3.6%
18.07 1
 
3.6%
18.11 1
 
3.6%
80.17 1
 
3.6%
18.68 1
 
3.6%
18.85 1
 
3.6%
17.49 1
 
3.6%
Other values (16) 16
57.1%
ValueCountFrequency (%)
-30.34 1
3.6%
-3.52 1
3.6%
2.31 1
3.6%
6.44 1
3.6%
7.3 1
3.6%
10.52 1
3.6%
14.84 1
3.6%
15.99 1
3.6%
17.03 1
3.6%
17.49 1
3.6%
ValueCountFrequency (%)
249.84 1
3.6%
80.17 1
3.6%
33.47 1
3.6%
22.1 1
3.6%
20.09 1
3.6%
19.33 1
3.6%
18.98 1
3.6%
18.87 1
3.6%
18.85 1
3.6%
18.78 1
3.6%

Interactions

2023-12-10T23:21:43.285097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:37.409097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.079473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.037705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.771224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.623755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.454519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.428294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.374535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:37.492209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.158520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.123639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.861690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.707779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.555859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.534670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.458422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:37.564978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.258822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.203484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.938187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.792964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.681845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.639949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.573492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:37.650791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.362051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.294461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.040815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.935673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.844177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.737642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.676281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:37.746609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.448209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.392626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.219620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.053616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.994684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.861576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.785283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:37.834026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.537248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.502641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.331257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.186525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.114766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.986147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.889817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:37.922580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.879634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.590407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.425942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.273850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.220637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.089046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.978218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.000020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:38.959289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:39.676009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:40.528677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:41.369443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:42.324159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:21:43.188431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:21:49.625910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개선도지수채널ID개선도지수채널명개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
개선도지수채널ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도지수채널명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도지수채널설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도채널생성일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
최근6개월개선도1.0001.0001.0001.0001.0000.1760.7040.0000.6910.8200.7810.0000.6850.000
최근12개월개선도1.0001.0001.0001.0000.1761.0000.0000.0000.9810.0000.0000.7971.0000.000
최초6개월개선도1.0001.0001.0001.0000.7040.0001.0000.8150.0000.1980.4840.0000.0000.444
최초12개월개선도1.0001.0001.0001.0000.0000.0000.8151.0000.0000.0000.6500.0000.3960.561
최근개선도지수1.0001.0001.0001.0000.6910.9810.0000.0001.0000.0000.4880.8290.9110.000
최근6개월표준점수1.0001.0001.0001.0000.8200.0000.1980.0000.0001.0000.0000.5900.8020.000
최근12개월표준점수1.0001.0001.0001.0000.7810.0000.4840.6500.4880.0001.0000.0000.0000.503
최초6개월표준점수1.0001.0001.0001.0000.0000.7970.0000.0000.8290.5900.0001.0000.8330.155
최초12개월표준점수1.0001.0001.0001.0000.6851.0000.0000.3960.9110.8020.0000.8331.0000.570
개선도최근표준점수1.0001.0001.0001.0000.0000.0000.4440.5610.0000.0000.5030.1550.5701.000
2023-12-10T23:21:49.752399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초6개월개선도최초12개월개선도
최초6개월개선도1.0000.604
최초12개월개선도0.6041.000
2023-12-10T23:21:49.849637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최근6개월개선도최근12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수최초6개월개선도최초12개월개선도
최근6개월개선도1.000-0.304-0.091-0.417-0.2550.1660.3500.3940.1770.000
최근12개월개선도-0.3041.000-0.1080.1460.0140.070-0.424-0.3030.0000.000
최근개선도지수-0.091-0.1081.0000.300-0.237-0.2250.164-0.5110.0000.000
최근6개월표준점수-0.4170.1460.3001.000-0.032-0.002-0.034-0.3420.0000.000
최근12개월표준점수-0.2550.014-0.237-0.0321.000-0.100-0.0800.0860.2770.403
최초6개월표준점수0.1660.070-0.225-0.002-0.1001.000-0.3580.1830.0000.000
최초12개월표준점수0.350-0.4240.164-0.034-0.080-0.3581.000-0.3340.0000.122
개선도최근표준점수0.394-0.303-0.511-0.3420.0860.183-0.3341.0000.2490.334
최초6개월개선도0.1770.0000.0000.0000.2770.0000.0000.2491.0000.604
최초12개월개선도0.0000.0000.0000.0000.4030.0000.1220.3340.6041.000

Missing values

2023-12-10T23:21:44.096114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:21:44.273228image/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.
2023-12-10T23:21:44.686667image/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
0UC0bm8kKuMp8chJuxzlLnlnA주예지 JOOYEJI2021-03-31<NA><NA><NA>0000.0-10.261.60.920.3218.98
1UC-JZtfVAgIjmNfhapEV3zgg차차튜브 Chacha Tube2021-03-31Emailchadahye@gmail.com Insta cha.dahye2015-10-23<NA><NA><NA><NA>0.0-11.93-1.980.170.2518.78
2UC2tGWq3BCZUDAgNh965yM-A파쇄축2021-03-31철권 관련 영상 채널입니다.2013-08-19<NA><NA>000.0-11.32-2.160.080.1533.47
3UC1dK7oMUSR9Rnk1BSpOKZng정선호2021-03-31<NA>2011-01-10-54-1<NA><NA>19.331.17-3.240.170.252.31
4UC3m0s5XAQydCtbLHc8j1UogKBS 한국방송2021-03-31대한민국 대표 공영방송 KBS(Korean Broadcasting System) 의 공식 유튜브 채널 입니다. 재미있고 유익한 소식을 전하겠습니다.2011-08-24-5-2<NA><NA>13.820.271.350.170.257.3
5UC499dzcb2Fx9RD39Vqpz-lg강원도 - Gangwon2021-03-31평화와 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.krgwportal2014-05-1513-1<NA><NA>27.96-7.82-10.26-0.591.014.84
6UC4KEOaKK3hYA8sAHogi1bAg리얼베어TV2021-03-31사진과 캠핑을 즐기고 있는 3교대 직장인의 공간 입니다2012-02-12<NA><NA><NA><NA><NA>-11.93-2.380.170.2518.57
7UC69l_rtlCQ7M4Mz2RCS80BA미야옹철의 냥냥펀치2021-03-31반려묘 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_babyc2018-11-23-7-100196.831.882.55-0.340.36.44
8UC6Jl3MrfGBvRYxXgdDxXzVADOJIN도진이2021-03-31<NA>2019-07-23-11430098.59-3.761.35-0.180.110.52
9UC6yL_G-xY4kxYWdgYqHEmRA잘먹겠습니다2021-03-31안녕하세요 잘먹겠습니다에 강형식입니다. 제 채널은 여러 맛집을 다니며 음식을 리뷰하는 푸드 컨텐츠 채널을 구독자 분들과 함께 만들어 가려고 합니다. 앞으로 많은 댓글과 구독; 좋아요 부탁드립니다. 전세계 모든음식을 리뷰하는 그날까지... 잘먹겠습니다! anilok.hw@gmail.com2018-05-28<NA><NA><NA><NA><NA>-11.93-2.380.170.2518.55
개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
18UC8gCJEe6FFHdhZyul6zLeMQ생방송심야토론2021-03-31<NA>2018-06-07<NA>-70073.31-12.96-0.330.540.3517.03
19UC9153vUIKS_nEltqwdQX-6A세경2021-03-31안녕하세요 구독자여러분들! 다양한 요리 영상과 먹방 영상; 일상영상등을 업로드 중 이에요♥ 구독하기& 좋아요 많이 부탁드려요♥ Instagram _ 33wannabe332015-06-25<NA><NA><NA><NA><NA>-11.93-2.380.170.2518.64
20UC99OELa9yvqgkq9ffBvm9iQ갑수목장gabsupasture2021-03-31갑수목장에 오신 것을 환영합니다. 좋아요와 구독 진심으로 감사드립니다. pgs3620@naver.com2019-01-15<NA><NA><NA><NA><NA>11.77-3.710.170.2518.55
21UC9EgNOu8Y9tY3zkrXFk0T_w경기신용보증재단2021-03-31'중소기업과 소상공인의 희망을 함께하는 신용파트너'; 경기신용보증재단은 사업성과 기술력은 있지만; 담보력이 부족해 금융기관으로부터 자금조달이 어려운 중소기업과 소상공인에게 실질적인 자금을 지원하는 비영리 공공법인입니다. 앞으로 유튜브를 통해 재단의 소식과 보증상품들을 소개하며 경기도 기업인들에게 더욱 가까이 다가겠습니다. 많은 관심 부탁드립니다.2019-02-12<NA><NA>00<NA><NA>-0.80.10.3217.49
22UC9dpfiVlNpBoHm81mfghhSQ주랄라2021-03-31'주랄라와 룰루랄라 놀아보자' 라는 의미의 채널입니다.2017-10-01<NA><NA>000.0-11.93-2.380.180.3118.85
23UCCD5onP_ljXqu0Us89Wm-WwKIDS한국의약품안전관리원2021-03-31<NA>2017-01-18<NA><NA><NA><NA><NA>-8.24-1.760.170.2418.68
24UCAJ-meoCh1TrPZ7La3UpPrw빅헤드2021-03-31취미 방송인입니다. 주로 FPS나 밀리터리류 게임을 선호하며 대충 방송하는 것을 좋아합니다.2014-02-060-1<NA><NA>38.27-4.35-4.970.170.2580.17
25UCCIR1qib7R1mR77byZJ0MiQ블루베리TV2021-03-31블루베리TV에 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><NA>1140.31-13.41-2.88-0.670.7518.11
26UCCflwTdJf1fQxKilMVAuW2wbexco2021-03-31<NA>2019-04-08<NA><NA>00<NA>-25.31-2.87-0.410.7818.07
27UCE1N1MU4TwiEVrqJY6UW7Hw솔라시도2021-03-31솔라와 앙금이의 평범한 하루하루를 기록합니다. 이름 : 솔라 성별 : 여아 생일 : 2018.6.30 견종 : 보더콜리 색상 : 블루화이트 특징 : 1분도 쉬지 않는 에너자이저; 털 옷 안에 사람 있음. 이름 : 앙금 성별 : 남아 생일 : 2019.3.1. 추정 견종 : 보더코기 + 반달곰 조금(?) 색상 : 블랙에 화이트 한스푼 특징 : 유기견 엄마와 함께 길거리에서 발견된 꼬물이 오줌싸개 비즈니스 문의: sollasido@sandboxnetwork.net2017-07-23<NA>0<NA><NA>0.0-11.937.760.170.2522.1