Overview

Dataset statistics

Number of variables15
Number of observations24
Missing cells41
Missing cells (%)11.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory135.5 B

Variable types

Text3
DateTime2
Numeric7
Categorical3

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/45a6dc95-79ce-44c9-8cbd-6c6498a58e4a

Alerts

최초12개월개선도 is highly overall correlated with 최근6개월개선도 and 6 other fieldsHigh correlation
최초6개월개선도 is highly overall correlated with 최근6개월개선도 and 6 other fieldsHigh correlation
최근12개월개선도 is highly overall correlated with 최근6개월개선도 and 2 other fieldsHigh correlation
최근6개월개선도 is highly overall correlated with 최근개선도지수 and 5 other fieldsHigh correlation
최근개선도지수 is highly overall correlated with 최근6개월개선도 and 3 other fieldsHigh correlation
최근6개월표준점수 is highly overall correlated with 최초6개월개선도 and 1 other fieldsHigh correlation
최근12개월표준점수 is highly overall correlated with 최근6개월개선도 and 3 other fieldsHigh correlation
최초6개월표준점수 is highly overall correlated with 최근6개월개선도 and 2 other fieldsHigh correlation
최초12개월표준점수 is highly overall correlated with 최초12개월개선도High correlation
개선도최근표준점수 is highly overall correlated with 최근개선도지수 and 2 other fieldsHigh correlation
개선도지수채널설명 has 6 (25.0%) missing valuesMissing
개선도채널생성일자 has 5 (20.8%) missing valuesMissing
최근6개월개선도 has 16 (66.7%) missing valuesMissing
최근개선도지수 has 12 (50.0%) missing valuesMissing
최근6개월표준점수 has 2 (8.3%) missing valuesMissing
개선도지수채널ID has unique valuesUnique
개선도지수채널명 has unique valuesUnique
최근6개월개선도 has 2 (8.3%) zerosZeros
최근개선도지수 has 4 (16.7%) zerosZeros

Reproduction

Analysis started2023-12-10 13:56:49.028752
Analysis finished2023-12-10 13:56:59.197977
Duration10.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개선도지수채널ID
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-10T22:56:59.409569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters576
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

Unique24 ?
Unique (%)100.0%

Sample

1st rowUCOnQvpKoRz7FnPYNJUOda-A
2nd rowUCW99_pwOr9JvzjZ81bMMjSg
3rd rowUC0hk2D145ogyBYMKjylWkkw
4th rowUC1dMe0fYTM4r9mNQc9v1ziA
5th rowUC2BoyzFAwgfRFc5aJrYsGZg
ValueCountFrequency (%)
uconqvpkorz7fnpynjuoda-a 1
 
4.2%
ucw99_pwor9jvzjz81bmmjsg 1
 
4.2%
uc8jolz-ya34ylqtz2tqslgw 1
 
4.2%
uc85mxewraycnlfmrhbdaalg 1
 
4.2%
uc7bqxkhltafctwwwhuzoouq 1
 
4.2%
uc0sfszeosuewxys7okktelq 1
 
4.2%
uc2d79s4t-z8gty2ceicwhmg 1
 
4.2%
uc6dtags0tiobtojlnlwzdqw 1
 
4.2%
uc69dhld0fumlgp9bsxitbdw 1
 
4.2%
uc5oft5dvf43m2cfmhpjlvgq 1
 
4.2%
Other values (14) 14
58.3%
2023-12-10T22:56:59.899288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 33
 
5.7%
C 31
 
5.4%
Q 19
 
3.3%
w 17
 
3.0%
g 14
 
2.4%
A 13
 
2.3%
Z 13
 
2.3%
9 12
 
2.1%
W 12
 
2.1%
o 12
 
2.1%
Other values (54) 400
69.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 263
45.7%
Lowercase Letter 212
36.8%
Decimal Number 88
 
15.3%
Dash Punctuation 8
 
1.4%
Connector Punctuation 5
 
0.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 33
 
12.5%
C 31
 
11.8%
Q 19
 
7.2%
A 13
 
4.9%
Z 13
 
4.9%
W 12
 
4.6%
O 10
 
3.8%
Y 10
 
3.8%
G 10
 
3.8%
L 9
 
3.4%
Other values (16) 103
39.2%
Lowercase Letter
ValueCountFrequency (%)
w 17
 
8.0%
g 14
 
6.6%
o 12
 
5.7%
d 11
 
5.2%
l 11
 
5.2%
f 10
 
4.7%
k 9
 
4.2%
z 9
 
4.2%
e 9
 
4.2%
h 8
 
3.8%
Other values (16) 102
48.1%
Decimal Number
ValueCountFrequency (%)
9 12
13.6%
4 11
12.5%
5 10
11.4%
0 10
11.4%
2 9
10.2%
7 9
10.2%
8 8
9.1%
3 7
8.0%
6 7
8.0%
1 5
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 475
82.5%
Common 101
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 33
 
6.9%
C 31
 
6.5%
Q 19
 
4.0%
w 17
 
3.6%
g 14
 
2.9%
A 13
 
2.7%
Z 13
 
2.7%
W 12
 
2.5%
o 12
 
2.5%
d 11
 
2.3%
Other values (42) 300
63.2%
Common
ValueCountFrequency (%)
9 12
11.9%
4 11
10.9%
5 10
9.9%
0 10
9.9%
2 9
8.9%
7 9
8.9%
8 8
7.9%
- 8
7.9%
3 7
6.9%
6 7
6.9%
Other values (2) 10
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 576
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 33
 
5.7%
C 31
 
5.4%
Q 19
 
3.3%
w 17
 
3.0%
g 14
 
2.4%
A 13
 
2.3%
Z 13
 
2.3%
9 12
 
2.1%
W 12
 
2.1%
o 12
 
2.1%
Other values (54) 400
69.4%

개선도지수채널명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-10T22:57:00.413142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14.5
Mean length10.333333
Min length3

Characters and Unicode

Total characters248
Distinct characters122
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

Unique24 ?
Unique (%)100.0%

Sample

1st rowvivienvalz
2nd rowEvan Toys
3rd row안녕히_계세요
4th rowSaehyeon세현
5th row후투브
ValueCountFrequency (%)
vivienvalz 1
 
2.4%
발달장애 1
 
2.4%
한국전력 1
 
2.4%
kepco 1
 
2.4%
애주가tv참pd 1
 
2.4%
잡아바 1
 
2.4%
tv 1
 
2.4%
경기도일자리재단 1
 
2.4%
ebs 1
 
2.4%
디딤돌 1
 
2.4%
Other values (32) 32
76.2%
2023-12-10T22:57:01.126484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
7.3%
e 8
 
3.2%
T 8
 
3.2%
a 7
 
2.8%
o 7
 
2.8%
S 6
 
2.4%
E 6
 
2.4%
v 5
 
2.0%
s 5
 
2.0%
V 5
 
2.0%
Other values (112) 173
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
36.7%
Lowercase Letter 66
26.6%
Uppercase Letter 61
24.6%
Space Separator 18
 
7.3%
Close Punctuation 3
 
1.2%
Open Punctuation 3
 
1.2%
Decimal Number 3
 
1.2%
Other Punctuation 1
 
0.4%
Connector Punctuation 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 3
 
3.3%
국 3
 
3.3%
주 2
 
2.2%
자 2
 
2.2%
선 2
 
2.2%
브 2
 
2.2%
히 2
 
2.2%
세 2
 
2.2%
구 2
 
2.2%
기 2
 
2.2%
Other values (63) 69
75.8%
Lowercase Letter
ValueCountFrequency (%)
e 8
12.1%
a 7
10.6%
o 7
10.6%
v 5
 
7.6%
s 5
 
7.6%
i 5
 
7.6%
f 4
 
6.1%
c 3
 
4.5%
r 3
 
4.5%
n 3
 
4.5%
Other values (11) 16
24.2%
Uppercase Letter
ValueCountFrequency (%)
T 8
13.1%
S 6
 
9.8%
E 6
 
9.8%
V 5
 
8.2%
C 4
 
6.6%
D 4
 
6.6%
P 3
 
4.9%
O 3
 
4.9%
H 3
 
4.9%
K 3
 
4.9%
Other values (9) 16
26.2%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
9 1
33.3%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
] 3
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 127
51.2%
Hangul 91
36.7%
Common 30
 
12.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 3
 
3.3%
국 3
 
3.3%
주 2
 
2.2%
자 2
 
2.2%
선 2
 
2.2%
브 2
 
2.2%
히 2
 
2.2%
세 2
 
2.2%
구 2
 
2.2%
기 2
 
2.2%
Other values (63) 69
75.8%
Latin
ValueCountFrequency (%)
e 8
 
6.3%
T 8
 
6.3%
a 7
 
5.5%
o 7
 
5.5%
S 6
 
4.7%
E 6
 
4.7%
v 5
 
3.9%
s 5
 
3.9%
V 5
 
3.9%
i 5
 
3.9%
Other values (30) 65
51.2%
Common
ValueCountFrequency (%)
18
60.0%
] 3
 
10.0%
[ 3
 
10.0%
5 1
 
3.3%
9 1
 
3.3%
. 1
 
3.3%
1 1
 
3.3%
_ 1
 
3.3%
- 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 157
63.3%
Hangul 91
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
 
11.5%
e 8
 
5.1%
T 8
 
5.1%
a 7
 
4.5%
o 7
 
4.5%
S 6
 
3.8%
E 6
 
3.8%
v 5
 
3.2%
s 5
 
3.2%
V 5
 
3.2%
Other values (39) 82
52.2%
Hangul
ValueCountFrequency (%)
한 3
 
3.3%
국 3
 
3.3%
주 2
 
2.2%
자 2
 
2.2%
선 2
 
2.2%
브 2
 
2.2%
히 2
 
2.2%
세 2
 
2.2%
구 2
 
2.2%
기 2
 
2.2%
Other values (63) 69
75.8%

개선도지수수집일자
Date

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2021-09-06 00:00:00
Maximum2021-09-28 00:00:00
2023-12-10T22:57:01.369642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:01.552654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

개선도지수채널설명
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing6
Missing (%)25.0%
Memory size324.0 B
2023-12-10T22:57:01.953013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length893
Median length97
Mean length173.33333
Min length1

Characters and Unicode

Total characters3120
Distinct characters367
Distinct categories15 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st rowEvan Toys Learning Videos for Kids Children Toddlers Educational Fun and Creatives Videos
2nd row.
3rd row뷰티와 일상을 기록하는 유튜버 세현입니다 비즈니스 문의- saehyeon031105@gmail.com 으로 주시면 감사하겠습니다!
4th row인스타 @jj_d_m_pp 고양이를 좋아하는 사람의 소소한채널; [고양이와 소소한생활] 입니다. 16년 3월 25일; 길냥이였던 쫄냥이를 만났고; 출산이 임박해보이는 커다란 배를 보고 멸치라도 줄까 집에 들인 이후 쭉; 집사의 길을 걸어가고 있습니다. 초보 집사로 좌충우돌 해 가며 현재 반려묘 네마리; 쫄냥까망단추뿌꾸를 키우고 있습니다. 고양이로 인해 많이 웃게되는 나날을 함께하고 싶습니다~^^
5th row전기전문 정부출연연구기관 한국전기연구원의 공식 유튜브 채널입니다. - 전기기술관련 연구성과 영상 - 주요 행사관련 영상 - 과학문화확산을 위한 다채로운 영상 등이 여러분께 제공되고 있습니다. 많은 관심과 참여 부탁드립니다. ============================ -홈 페 이 지 : http:www.keri.re.kr -네이버BLOG: http:blog.naver.comkeri_on -네이버POST: http:post.naver.comkeri_on -네이버 T V : http:tv.naver.comkeri -페 이 스 북 : http:www.facebook.comkeristory -인스타그램 : http:www.instagram.comkokoma_keri
ValueCountFrequency (%)
49
 
9.6%
▶ 20
 
3.9%
월~금 8
 
1.6%
공식 5
 
1.0%
있습니다 5
 
1.0%
주말 4
 
0.8%
09:00 4
 
0.8%
유튜브 4
 
0.8%
채널입니다 4
 
0.8%
매일 4
 
0.8%
Other values (357) 405
79.1%
2023-12-10T22:57:02.607435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
550
 
17.6%
- 178
 
5.7%
0 88
 
2.8%
: 73
 
2.3%
o 63
 
2.0%
. 60
 
1.9%
t 55
 
1.8%
a 49
 
1.6%
e 47
 
1.5%
1 39
 
1.2%
Other values (357) 1918
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1119
35.9%
Lowercase Letter 625
20.0%
Space Separator 550
17.6%
Decimal Number 207
 
6.6%
Dash Punctuation 178
 
5.7%
Other Punctuation 175
 
5.6%
Uppercase Letter 106
 
3.4%
Math Symbol 61
 
2.0%
Open Punctuation 31
 
1.0%
Close Punctuation 31
 
1.0%
Other values (5) 37
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 38
 
3.4%
니 34
 
3.0%
이 29
 
2.6%
의 21
 
1.9%
입 20
 
1.8%
일 19
 
1.7%
한 18
 
1.6%
주 17
 
1.5%
하 17
 
1.5%
스 17
 
1.5%
Other values (274) 889
79.4%
Lowercase Letter
ValueCountFrequency (%)
o 63
 
10.1%
t 55
 
8.8%
a 49
 
7.8%
e 47
 
7.5%
i 36
 
5.8%
n 32
 
5.1%
m 32
 
5.1%
r 31
 
5.0%
w 31
 
5.0%
s 31
 
5.0%
Other values (15) 218
34.9%
Uppercase Letter
ValueCountFrequency (%)
T 19
17.9%
D 10
 
9.4%
V 9
 
8.5%
S 8
 
7.5%
E 6
 
5.7%
O 6
 
5.7%
B 5
 
4.7%
C 5
 
4.7%
L 5
 
4.7%
P 4
 
3.8%
Other values (15) 29
27.4%
Decimal Number
ValueCountFrequency (%)
0 88
42.5%
1 39
18.8%
2 19
 
9.2%
6 18
 
8.7%
5 9
 
4.3%
9 9
 
4.3%
7 8
 
3.9%
4 7
 
3.4%
8 7
 
3.4%
3 3
 
1.4%
Other Punctuation
ValueCountFrequency (%)
: 73
41.7%
. 60
34.3%
; 13
 
7.4%
! 12
 
6.9%
# 6
 
3.4%
@ 6
 
3.4%
* 2
 
1.1%
' 2
 
1.1%
? 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 31
50.8%
= 30
49.2%
Open Punctuation
ValueCountFrequency (%)
[ 24
77.4%
( 7
 
22.6%
Close Punctuation
ValueCountFrequency (%)
] 24
77.4%
) 7
 
22.6%
Other Symbol
ValueCountFrequency (%)
▶ 21
84.0%
♥ 4
 
16.0%
Space Separator
ValueCountFrequency (%)
550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1270
40.7%
Hangul 1119
35.9%
Latin 731
23.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 38
 
3.4%
니 34
 
3.0%
이 29
 
2.6%
의 21
 
1.9%
입 20
 
1.8%
일 19
 
1.7%
한 18
 
1.6%
주 17
 
1.5%
하 17
 
1.5%
스 17
 
1.5%
Other values (274) 889
79.4%
Latin
ValueCountFrequency (%)
o 63
 
8.6%
t 55
 
7.5%
a 49
 
6.7%
e 47
 
6.4%
i 36
 
4.9%
n 32
 
4.4%
m 32
 
4.4%
r 31
 
4.2%
w 31
 
4.2%
s 31
 
4.2%
Other values (40) 324
44.3%
Common
ValueCountFrequency (%)
550
43.3%
- 178
 
14.0%
0 88
 
6.9%
: 73
 
5.7%
. 60
 
4.7%
1 39
 
3.1%
~ 31
 
2.4%
= 30
 
2.4%
[ 24
 
1.9%
] 24
 
1.9%
Other values (23) 173
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1974
63.3%
Hangul 1119
35.9%
Geometric Shapes 21
 
0.7%
Misc Symbols 4
 
0.1%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
550
27.9%
- 178
 
9.0%
0 88
 
4.5%
: 73
 
3.7%
o 63
 
3.2%
. 60
 
3.0%
t 55
 
2.8%
a 49
 
2.5%
e 47
 
2.4%
1 39
 
2.0%
Other values (69) 772
39.1%
Hangul
ValueCountFrequency (%)
다 38
 
3.4%
니 34
 
3.0%
이 29
 
2.6%
의 21
 
1.9%
입 20
 
1.8%
일 19
 
1.7%
한 18
 
1.6%
주 17
 
1.5%
하 17
 
1.5%
스 17
 
1.5%
Other values (274) 889
79.4%
Geometric Shapes
ValueCountFrequency (%)
▶ 21
100.0%
Misc Symbols
ValueCountFrequency (%)
♥ 4
100.0%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

개선도채널생성일자
Date

MISSING 

Distinct19
Distinct (%)100.0%
Missing5
Missing (%)20.8%
Memory size324.0 B
Minimum2011-05-18 00:00:00
Maximum2019-01-18 00:00:00
2023-12-10T22:57:02.884793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:03.167570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

최근6개월개선도
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6
Distinct (%)75.0%
Missing16
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean-0.875
Minimum-12
Maximum12
Zeros2
Zeros (%)8.3%
Negative4
Negative (%)16.7%
Memory size348.0 B
2023-12-10T22:57:03.377826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-12
5-th percentile-9.2
Q1-2.5
median-1
Q30.25
95-th percentile8.15
Maximum12
Range24
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation6.6211242
Coefficient of variation (CV)-7.5669991
Kurtosis2.754685
Mean-0.875
Median Absolute Deviation (MAD)1.5
Skewness0.48028713
Sum-7
Variance43.839286
MonotonicityNot monotonic
2023-12-10T22:57:03.584622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
-2 2
 
8.3%
0 2
 
8.3%
-12 1
 
4.2%
12 1
 
4.2%
-4 1
 
4.2%
1 1
 
4.2%
(Missing) 16
66.7%
ValueCountFrequency (%)
-12 1
4.2%
-4 1
4.2%
-2 2
8.3%
0 2
8.3%
1 1
4.2%
12 1
4.2%
ValueCountFrequency (%)
12 1
4.2%
1 1
4.2%
0 2
8.3%
-2 2
8.3%
-4 1
4.2%
-12 1
4.2%

최근12개월개선도
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
16 
0
3 
2
2 
-27
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.0833333
Min length1

Unique

Unique3 ?
Unique (%)12.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 16
66.7%
0 3
 
12.5%
2 2
 
8.3%
-27 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%

Length

2023-12-10T22:57:03.801666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:03.993949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
66.7%
0 3
 
12.5%
2 2
 
8.3%
27 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%

최초6개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
18 
0
4 
1
2 

Length

Max length4
Median length4
Mean length3.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
75.0%
0 4
 
16.7%
1 2
 
8.3%

Length

2023-12-10T22:57:04.550658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:04.732821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
75.0%
0 4
 
16.7%
1 2
 
8.3%

최초12개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
18 
0
5 
-1
 
1

Length

Max length4
Median length4
Mean length3.2916667
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
75.0%
0 5
 
20.8%
-1 1
 
4.2%

Length

2023-12-10T22:57:04.934689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:05.154998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
75.0%
0 5
 
20.8%
1 1
 
4.2%

최근개선도지수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct9
Distinct (%)75.0%
Missing12
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean11.285
Minimum0
Maximum53.62
Zeros4
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-10T22:57:05.300634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.655
Q314.7525
95-th percentile35.4755
Maximum53.62
Range53.62
Interquartile range (IQR)14.7525

Descriptive statistics

Standard deviation15.228408
Coefficient of variation (CV)1.349438
Kurtosis5.6119739
Mean11.285
Median Absolute Deviation (MAD)6.655
Skewness2.1752837
Sum135.42
Variance231.90441
MonotonicityNot monotonic
2023-12-10T22:57:05.566529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 4
 
16.7%
13.67 1
 
4.2%
6.65 1
 
4.2%
20.63 1
 
4.2%
17.37 1
 
4.2%
6.66 1
 
4.2%
2.94 1
 
4.2%
53.62 1
 
4.2%
13.88 1
 
4.2%
(Missing) 12
50.0%
ValueCountFrequency (%)
0.0 4
16.7%
2.94 1
 
4.2%
6.65 1
 
4.2%
6.66 1
 
4.2%
13.67 1
 
4.2%
13.88 1
 
4.2%
17.37 1
 
4.2%
20.63 1
 
4.2%
53.62 1
 
4.2%
ValueCountFrequency (%)
53.62 1
 
4.2%
20.63 1
 
4.2%
17.37 1
 
4.2%
13.88 1
 
4.2%
13.67 1
 
4.2%
6.66 1
 
4.2%
6.65 1
 
4.2%
2.94 1
 
4.2%
0.0 4
16.7%

최근6개월표준점수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)72.7%
Missing2
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean-6.7709091
Minimum-49.9
Maximum21.54
Zeros0
Zeros (%)0.0%
Negative11
Negative (%)45.8%
Memory size348.0 B
2023-12-10T22:57:05.741319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-49.9
5-th percentile-48.716
Q1-28.69
median0.645
Q314.3075
95-th percentile19.45
Maximum21.54
Range71.44
Interquartile range (IQR)42.9975

Descriptive statistics

Standard deviation24.219978
Coefficient of variation (CV)-3.5770644
Kurtosis-1.3738491
Mean-6.7709091
Median Absolute Deviation (MAD)18.715
Skewness-0.40963066
Sum-148.96
Variance586.60731
MonotonicityNot monotonic
2023-12-10T22:57:05.938357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
-28.69 7
29.2%
-2.15 1
 
4.2%
14.19 1
 
4.2%
-3.86 1
 
4.2%
14.3 1
 
4.2%
19.46 1
 
4.2%
12.57 1
 
4.2%
19.26 1
 
4.2%
-49.9 1
 
4.2%
-49.77 1
 
4.2%
Other values (6) 6
25.0%
(Missing) 2
 
8.3%
ValueCountFrequency (%)
-49.9 1
 
4.2%
-49.77 1
 
4.2%
-28.69 7
29.2%
-3.86 1
 
4.2%
-2.15 1
 
4.2%
3.44 1
 
4.2%
5.05 1
 
4.2%
12.57 1
 
4.2%
14.19 1
 
4.2%
14.3 1
 
4.2%
ValueCountFrequency (%)
21.54 1
4.2%
19.46 1
4.2%
19.26 1
4.2%
17.26 1
4.2%
16.17 1
4.2%
14.31 1
4.2%
14.3 1
4.2%
14.19 1
4.2%
12.57 1
4.2%
5.05 1
4.2%

최근12개월표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4995833
Minimum-1.64
Maximum39.49
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)8.3%
Memory size348.0 B
2023-12-10T22:57:06.185679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.64
5-th percentile0.085
Q16.0875
median6.88
Q37.705
95-th percentile10.939
Maximum39.49
Range41.13
Interquartile range (IQR)1.6175

Descriptive statistics

Standard deviation7.4242549
Coefficient of variation (CV)0.98995565
Kurtosis16.265563
Mean7.4995833
Median Absolute Deviation (MAD)0.83
Skewness3.6168659
Sum179.99
Variance55.119561
MonotonicityNot monotonic
2023-12-10T22:57:06.414999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
6.88 5
20.8%
6.98 2
 
8.3%
7.16 1
 
4.2%
7.7 1
 
4.2%
3.83 1
 
4.2%
6.11 1
 
4.2%
2.31 1
 
4.2%
7.72 1
 
4.2%
11.05 1
 
4.2%
8.38 1
 
4.2%
Other values (9) 9
37.5%
ValueCountFrequency (%)
-1.64 1
 
4.2%
-0.23 1
 
4.2%
1.87 1
 
4.2%
2.31 1
 
4.2%
3.83 1
 
4.2%
6.02 1
 
4.2%
6.11 1
 
4.2%
6.81 1
 
4.2%
6.88 5
20.8%
6.91 1
 
4.2%
ValueCountFrequency (%)
39.49 1
4.2%
11.05 1
4.2%
10.31 1
4.2%
8.38 1
4.2%
7.83 1
4.2%
7.72 1
4.2%
7.7 1
4.2%
7.16 1
4.2%
6.98 2
8.3%
6.91 1
4.2%

최초6개월표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15166667
Minimum-2.03
Maximum2.04
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)12.5%
Memory size348.0 B
2023-12-10T22:57:06.576635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.03
5-th percentile-1.325
Q10.18
median0.18
Q30.2
95-th percentile1.4035
Maximum2.04
Range4.07
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.76334884
Coefficient of variation (CV)5.0330693
Kurtosis4.5733212
Mean0.15166667
Median Absolute Deviation (MAD)0
Skewness-0.59121986
Sum3.64
Variance0.58270145
MonotonicityNot monotonic
2023-12-10T22:57:06.760900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.18 13
54.2%
0.2 2
 
8.3%
0.29 1
 
4.2%
-2.03 1
 
4.2%
-0.05 1
 
4.2%
0.22 1
 
4.2%
0.21 1
 
4.2%
1.6 1
 
4.2%
-1.55 1
 
4.2%
0.17 1
 
4.2%
ValueCountFrequency (%)
-2.03 1
 
4.2%
-1.55 1
 
4.2%
-0.05 1
 
4.2%
0.17 1
 
4.2%
0.18 13
54.2%
0.2 2
 
8.3%
0.21 1
 
4.2%
0.22 1
 
4.2%
0.29 1
 
4.2%
1.6 1
 
4.2%
ValueCountFrequency (%)
2.04 1
 
4.2%
1.6 1
 
4.2%
0.29 1
 
4.2%
0.22 1
 
4.2%
0.21 1
 
4.2%
0.2 2
 
8.3%
0.18 13
54.2%
0.17 1
 
4.2%
-0.05 1
 
4.2%
-1.55 1
 
4.2%

최초12개월표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3275
Minimum-0.41
Maximum2.38
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)8.3%
Memory size348.0 B
2023-12-10T22:57:06.997610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.41
5-th percentile-0.1495
Q10.25
median0.25
Q30.275
95-th percentile0.6535
Maximum2.38
Range2.79
Interquartile range (IQR)0.025

Descriptive statistics

Standard deviation0.47956729
Coefficient of variation (CV)1.4643276
Kurtosis15.943703
Mean0.3275
Median Absolute Deviation (MAD)0.005
Skewness3.4948581
Sum7.86
Variance0.22998478
MonotonicityNot monotonic
2023-12-10T22:57:07.218948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.25 12
50.0%
0.26 2
 
8.3%
0.27 2
 
8.3%
0.31 1
 
4.2%
2.38 1
 
4.2%
-0.22 1
 
4.2%
0.29 1
 
4.2%
0.39 1
 
4.2%
0.7 1
 
4.2%
0.36 1
 
4.2%
ValueCountFrequency (%)
-0.41 1
 
4.2%
-0.22 1
 
4.2%
0.25 12
50.0%
0.26 2
 
8.3%
0.27 2
 
8.3%
0.29 1
 
4.2%
0.31 1
 
4.2%
0.36 1
 
4.2%
0.39 1
 
4.2%
0.7 1
 
4.2%
ValueCountFrequency (%)
2.38 1
 
4.2%
0.7 1
 
4.2%
0.39 1
 
4.2%
0.36 1
 
4.2%
0.31 1
 
4.2%
0.29 1
 
4.2%
0.27 2
 
8.3%
0.26 2
 
8.3%
0.25 12
50.0%
-0.22 1
 
4.2%

개선도최근표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7354167
Minimum-182.33
Maximum20.25
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)12.5%
Memory size348.0 B
2023-12-10T22:57:07.479491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-182.33
5-th percentile-6.3595
Q113.6025
median15.005
Q315.365
95-th percentile19.2275
Maximum20.25
Range202.58
Interquartile range (IQR)1.7625

Descriptive statistics

Standard deviation40.364517
Coefficient of variation (CV)8.5239631
Kurtosis22.618933
Mean4.7354167
Median Absolute Deviation (MAD)0.87
Skewness-4.7035974
Sum113.65
Variance1629.2942
MonotonicityNot monotonic
2023-12-10T22:57:07.733784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
14.93 2
 
8.3%
15.2 2
 
8.3%
19.73 1
 
4.2%
1.05 1
 
4.2%
15.86 1
 
4.2%
15.19 1
 
4.2%
16.38 1
 
4.2%
12.38 1
 
4.2%
-182.33 1
 
4.2%
15.06 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
-182.33 1
4.2%
-7.48 1
4.2%
-0.01 1
4.2%
1.05 1
4.2%
6.32 1
4.2%
12.38 1
4.2%
14.01 1
4.2%
14.9 1
4.2%
14.91 1
4.2%
14.93 2
8.3%
ValueCountFrequency (%)
20.25 1
4.2%
19.73 1
4.2%
16.38 1
4.2%
16.16 1
4.2%
15.89 1
4.2%
15.86 1
4.2%
15.2 2
8.3%
15.19 1
4.2%
15.11 1
4.2%
15.06 1
4.2%

Interactions

2023-12-10T22:56:57.368282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:50.113603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:51.123422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:52.371404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:53.949093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:55.186115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:56.317371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:57.522859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:50.242231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:51.254532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:52.545126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:54.083682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:55.329701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:56.439552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:57.713008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:50.381329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:51.395727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:52.690619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:54.326554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:55.469096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:56.566547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:57.867032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:50.542461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:51.565431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:52.831930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:54.543900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:55.632548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:56.723180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:57.991898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:50.691124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:51.706232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:53.389992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:54.658974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:55.807366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:56.845955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:58.138791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:50.838521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:51.865664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:53.618550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:54.795933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:55.981778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:57.074975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:58.288783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:50.982913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:52.063730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:53.796036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:54.991435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:56.141904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:57.220498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:57:07.969571image/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
개선도지수수집일자1.0001.0001.0001.0001.000NaNNaNNaNNaN0.0000.8840.0000.0000.0000.000
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
최근6개월개선도1.0001.000NaN1.0001.0001.0000.6470.000NaN0.0000.3960.0000.000NaN0.000
최근12개월개선도1.0001.000NaN1.0001.0000.6471.0001.0001.0000.8590.5760.5440.1820.0001.000
최초6개월개선도1.0001.000NaN1.0001.0000.0001.0001.0000.0001.0001.0001.0001.0000.000NaN
최초12개월개선도1.0001.000NaN1.0001.000NaN1.0000.0001.0000.0001.0001.0001.0001.000NaN
최근개선도지수1.0001.0000.0001.0001.0000.0000.8591.0000.0001.0000.0000.1370.0000.0000.581
최근6개월표준점수1.0001.0000.8841.0001.0000.3960.5761.0001.0000.0001.0000.2340.0000.0000.711
최근12개월표준점수1.0001.0000.0001.0001.0000.0000.5441.0001.0000.1370.2341.0000.8480.8330.621
최초6개월표준점수1.0001.0000.0001.0001.0000.0000.1821.0001.0000.0000.0000.8481.0000.9690.000
최초12개월표준점수1.0001.0000.0001.0001.000NaN0.0000.0001.0000.0000.0000.8330.9691.0000.000
개선도최근표준점수1.0001.0000.0001.0001.0000.0001.000NaNNaN0.5810.7110.6210.0000.0001.000
2023-12-10T22:57:08.235065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초12개월개선도최초6개월개선도최근12개월개선도
최초12개월개선도1.0000.0001.000
최초6개월개선도0.0001.0001.000
최근12개월개선도1.0001.0001.000
2023-12-10T22:57:08.432814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최근6개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수최근12개월개선도최초6개월개선도최초12개월개선도
최근6개월개선도1.0000.506-0.400-0.7470.5250.259-0.0840.8661.0001.000
최근개선도지수0.5061.0000.102-0.7050.3760.028-0.6410.3540.7070.000
최근6개월표준점수-0.4000.1021.0000.051-0.1320.179-0.2180.4330.5770.577
최근12개월표준점수-0.747-0.7050.0511.000-0.2010.2480.4830.2640.7070.707
최초6개월표준점수0.5250.376-0.132-0.2011.0000.258-0.0090.0000.7070.707
최초12개월표준점수0.2590.0280.1790.2480.2581.0000.1770.0000.0000.866
개선도최근표준점수-0.084-0.641-0.2180.483-0.0090.1771.0000.2001.0001.000
최근12개월개선도0.8660.3540.4330.2640.0000.0000.2001.0001.0001.000
최초6개월개선도1.0000.7070.5770.7070.7070.0001.0001.0001.0000.000
최초12개월개선도1.0000.0000.5770.7070.7070.8661.0001.0000.0001.000

Missing values

2023-12-10T22:56:58.539097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:56:58.842522image/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.
2023-12-10T22:56:59.070299image/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
0UCOnQvpKoRz7FnPYNJUOda-Avivienvalz2021-09-06<NA>2011-10-02<NA><NA><NA><NA>0.0-49.96.980.180.2519.73
1UCW99_pwOr9JvzjZ81bMMjSgEvan Toys2021-09-07Evan Toys Learning Videos for Kids Children Toddlers Educational Fun and Creatives Videos2017-06-07<NA><NA><NA><NA><NA>-49.776.980.180.2620.25
2UC0hk2D145ogyBYMKjylWkkw안녕히_계세요2021-09-28.2013-03-16<NA><NA><NA><NA><NA>-28.696.880.180.2514.9
3UC1dMe0fYTM4r9mNQc9v1ziASaehyeon세현2021-09-28뷰티와 일상을 기록하는 유튜버 세현입니다 비즈니스 문의- saehyeon031105@gmail.com 으로 주시면 감사하겠습니다!<NA><NA><NA>00<NA>-28.696.880.290.3114.93
4UC2BoyzFAwgfRFc5aJrYsGZg후투브2021-09-28<NA>2012-09-09<NA><NA><NA><NA><NA>-28.696.880.180.2515.03
5UC28lbdOHnj-leok6tHIx7ew고양이와 소소한생활2021-09-28인스타 @jj_d_m_pp 고양이를 좋아하는 사람의 소소한채널; [고양이와 소소한생활] 입니다. 16년 3월 25일; 길냥이였던 쫄냥이를 만났고; 출산이 임박해보이는 커다란 배를 보고 멸치라도 줄까 집에 들인 이후 쭉; 집사의 길을 걸어가고 있습니다. 초보 집사로 좌충우돌 해 가며 현재 반려묘 네마리; 쫄냥까망단추뿌꾸를 키우고 있습니다. 고양이로 인해 많이 웃게되는 나날을 함께하고 싶습니다~^^2013-09-30<NA><NA><NA><NA><NA>-28.696.880.180.2514.98
6UC0ru5w57PyGpbsEKwN4LuwA재민정2021-09-28<NA>2013-05-13<NA><NA><NA><NA><NA>-28.696.880.180.2514.91
7UC-gWrEGYpG2jYfl8A_KIGnQ[KERI]한국전기연구원2021-09-28전기전문 정부출연연구기관 한국전기연구원의 공식 유튜브 채널입니다. - 전기기술관련 연구성과 영상 - 주요 행사관련 영상 - 과학문화확산을 위한 다채로운 영상 등이 여러분께 제공되고 있습니다. 많은 관심과 참여 부탁드립니다. ============================ -홈 페 이 지 : http:www.keri.re.kr -네이버BLOG: http:blog.naver.comkeri_on -네이버POST: http:post.naver.comkeri_on -네이버 T V : http:tv.naver.comkeri -페 이 스 북 : http:www.facebook.comkeristory -인스타그램 : http:www.instagram.comkokoma_keri2012-03-07-2<NA><NA><NA>0.017.266.910.180.2715.11
8UC2Zi06YjNBM37g8d0IkHPMATVCHOSUN PLUS - TV조선 플러스2021-09-28TV조선 방송 채널에; 더한 클립과; 더한 영상들을 모아둔 더한 채널 TV조선 플러스2019-01-18<NA>00-10.021.5439.49-2.032.3815.89
9UC3WJ-rb5w_ShKQw06rNZfuwDiscovery Music Records2021-09-28<NA>2013-09-14<NA><NA>10<NA>14.316.02-0.05-0.2216.16
개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
14UC5UYeBQdzHjOh_vBoDQDkDQ한국전력 KEPCO2021-09-28한국전력공사 공식 유튜브 채널입니다. 안전하고 깨끗한 에너지 세상을 만들기 위한 한국전력의 노력; 한전 직무 소개; 채용 정보; 메세나 활동 등 다양하고 재미있는 콘텐츠를 만나실 수 있습니다.2012-07-05-4<NA><NA><NA>17.375.056.810.210.2914.01
15UC5oft5dVf43M2cFmhpJLVGQ애주가TV참PD2021-09-28세상 모든 안주를 리뷰하는 애주가TV 참PD입니다. 각종문의 이메일주소 : ilovechampd@gmail.com 인스타그램 : ilovechampd2011-05-1802<NA><NA>6.66-2.15-0.230.180.25-0.01
16UC69DhLD0FUmLgP9BsxitbDw잡아바 TV [경기도일자리재단]2021-09-28안녕하세요; 경기도일자리재단 공식 유튜브입니다. 자주 방문 및 구독신청하셔서 유용한 정보 얻어가세요! 일자리플랫폼 잡아바(www.jobaba.net) 페이스북(https:www.facebook.comjobabanet) 인스타그램(https:www.instagram.comjobabanet) 네이버포스트(http:post.naver.comgjf_job) 유튜브(https:www.youtube.comchannelUC69DhLD0FUmLgP9BsxitbDw) 잡아바 앱 다운로드 : 구글플레이스토어나 앱스토어 등에서 ‘경기도일자리재단’ 검색 * 안드로이드 : https:goo.glNLD4CX * IOS : https:goo.glJ5Q1ZP2016-10-17<NA>0<NA><NA>2.9419.268.381.60.3915.2
17UC6DTags0tiObToJLnLWZdQwEBS 디딤돌 발달장애2021-09-28<NA><NA><NA><NA><NA><NA><NA>-28.6911.05-1.550.715.06
18UC2d79S4T-z8gTY2ceICWhMg[지평선TV]김제시공식유튜브2021-09-28김제시 공식 유튜브 채널 '김제지평선TV' 입니다. https:www.youtube.comgimjecity #김제 #지평선TV #김제지평선TV #김제시 #김제시공식유튜브 #지평선2016-03-16<NA><NA><NA><NA><NA>12.577.720.180.2515.2
19UC0sfSZeoSUeWxys7OKkTelQTBS fm 95.1MHz2021-09-28시민의 눈으로 한걸음 더 시민의 방송 TBS FM입니다. [평일] ▶ 김어준의 뉴스공장 [월~금 07:06 ~ 09:00] ▶ 경제발전소 박연미입니다 [월~금 09:00 ~ 09:57] ▶ 이은미와 함께라면 [월~금 10:06 ~ 12:00] ▶ DJ SHOW 9595 [매일 12:11 ~ 14:00] ▶ 최일구의 허리케인라디오 [매일 14:06 ~ 16:00] ▶ 함춘호의 포크송 [월~금 16:06 ~ 17:00] ▶ 김기욱의 라쿠카라차 [월~금 17:00 ~ 18:00] ▶ 신장식의 신장개업 [월~금 18:11 ~ 20:00] ▶ 아닌 밤중에 주진우입니다 [월~금 20:06 ~ 21:00] ▶ 이가희의 러브레터 [월~금 21:00 ~ 21:43] ▶ 달콤한 밤 황진하입니다 [매일 22:06 ~ 24:00] ▶ 라디오를 켜라 정연주입니다 [월~토 05:00 ~ 07:00] [주말] ▶ 뉴스공장 주말특근 [토 07:00 ~ 09:00] ▶ TBS 아고라 [토 09:00 ~ 10:00] ▶ 오늘도 읽음 [일 08:06 ~ 10:00] ▶ 기분좋은 토;일요일 조현아입니다 [주말 10:00 ~ 12:00] ▶ 박성호의 4X6=24 [주말16:06 ~ 18:00] ▶ 웅산의 스윗멜로디 [주말 18:06 ~ 20:00] ▶ 주말이 좋다 나선홍입니다 [주말 20:06 ~ 22:00] ▶ 일요클래식 최영옥입니다 [일 05:00 ~ 08:00] ------------------------------------------------------------------------------------------------------------------------------------------------------------------- ▶TBS 홈페이지 http:tbs.seoul.kr2016-09-1900<NA><NA>53.6219.462.310.180.25-182.33
20UC7bQXKhLtAfCTWWWHUzOoUQ광주동구2021-09-28<NA>2016-12-09<NA><NA><NA><NA><NA>14.36.110.170.2512.38
21UC85mXeWRaycnlFmrhBdaAlg남자커피 Namja Coffee2021-09-28안녕하세요 커피와 음료를 사랑하는 남자커피 입니다!! 집에서 쉽게 만들수있는 음료 레시피 소개와 재미있는 커피상식들을 알려 드리고 싶어 운영하는 채널입니다. 부족할수있지만 재미있게 봐주세요!! 문의 - bakasa0817@gmail.com2018-08-18141013.88-3.863.832.040.3616.38
22UC8JOLZ-YA34ylQTz2tqSlGwKAIST2021-09-28한국과학기술원(KAIST)의 공식 유튜브 채널입니다. This is the official YouTube channel of KAIST.2013-07-28<NA><NA><NA><NA><NA>14.197.70.20.2615.19
23UC8Zv-JxGPLW0oZG4ZQaFQlQ또히DDOHEE2021-09-28또히DDOHEE 채널은 재미있는 일상과 다양한 컨텐츠로 함께 즐기고 나눌 수 있는 공간입니다. ♥ 구독과 좋아요 이쁜 댓글 감사합니다♥ - 첫영상 시작 : 2017.11.11 - 업로드 : 자유 업로딩 ♥함께소통해요♥ - 인스타 만남 : https:www.instagram.comddohee_0126?hl=ko - 비지니스 문의 : mariandk@naver.com [ 해당 영상의 저작권은 또히DDOHEE에게 있습니다. 이 영상을 공유하는 것은 가능하나 허가 없이 변경배포 하는 것은 불가합니다. ]<NA><NA><NA>000.0-28.697.160.2-0.4115.86