Overview

Dataset statistics

Number of variables15
Number of observations24
Missing cells33
Missing cells (%)9.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory135.5 B

Variable types

Text3
DateTime2
Numeric8
Categorical2

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/dd7d6bb7-167d-4896-b6a2-39ed8306b38e

Alerts

최근6개월개선도 is highly overall correlated with 최근6개월표준점수 and 1 other fieldsHigh correlation
최근개선도지수 is highly overall correlated with 최초6개월개선도High correlation
최근6개월표준점수 is highly overall correlated with 최근6개월개선도High correlation
최근12개월표준점수 is highly overall correlated with 최초6개월개선도 and 1 other fieldsHigh correlation
최초6개월개선도 is highly overall correlated with 최근개선도지수 and 1 other fieldsHigh correlation
최초12개월개선도 is highly overall correlated with 최근6개월개선도 and 1 other fieldsHigh correlation
개선도지수채널설명 has 3 (12.5%) missing valuesMissing
최근6개월개선도 has 12 (50.0%) missing valuesMissing
최근12개월개선도 has 10 (41.7%) missing valuesMissing
최근개선도지수 has 7 (29.2%) missing valuesMissing
최근6개월표준점수 has 1 (4.2%) missing valuesMissing
개선도지수채널ID has unique valuesUnique
개선도지수채널명 has unique valuesUnique
개선도채널생성일자 has unique valuesUnique
개선도최근표준점수 has unique valuesUnique
최근12개월개선도 has 1 (4.2%) zerosZeros
최근개선도지수 has 3 (12.5%) zerosZeros

Reproduction

Analysis started2023-12-10 14:13:42.838820
Analysis finished2023-12-10 14:13:57.084715
Duration14.25 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
2023-12-10T23:13:57.353573image/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 rowUCcpAAfKWfnVXViVwfjc2q-A
2nd rowUCw0ZKmxFBc9donV317twWeA
3rd rowUC1EEpE0lA9BaArXhRTHIG6w
4th rowUC-gWrEGYpG2jYfl8A_KIGnQ
5th rowUC4XjKgCtpwpACzUCiUKOd3Q
ValueCountFrequency (%)
uccpaafkwfnvxvivwfjc2q-a 1
 
4.2%
ucw0zkmxfbc9donv317twwea 1
 
4.2%
uceeevbzufze0gmn0ff55h8w 1
 
4.2%
ucecuyraqhrvumrdod6fgksw 1
 
4.2%
uc9t8wl0quwhpcksv73j5dqa 1
 
4.2%
uccxgedotqfr2g2hmev9vsxq 1
 
4.2%
uccwwpm3zkhvckg0tmupkgaa 1
 
4.2%
ucbvdrqetp01juovhaumo08q 1
 
4.2%
ucbdkh3mg6x71y94a2wudetq 1
 
4.2%
ucbioxzdldcnpbm_7uyg0_tg 1
 
4.2%
Other values (14) 14
58.3%
2023-12-10T23:13:57.992269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 32
 
5.6%
C 32
 
5.6%
A 21
 
3.6%
0 15
 
2.6%
G 15
 
2.6%
w 14
 
2.4%
E 13
 
2.3%
p 12
 
2.1%
g 12
 
2.1%
3 11
 
1.9%
Other values (54) 399
69.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 279
48.4%
Lowercase Letter 200
34.7%
Decimal Number 86
 
14.9%
Dash Punctuation 6
 
1.0%
Connector Punctuation 5
 
0.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 32
 
11.5%
C 32
 
11.5%
A 21
 
7.5%
G 15
 
5.4%
E 13
 
4.7%
H 11
 
3.9%
B 11
 
3.9%
Q 11
 
3.9%
V 11
 
3.9%
K 11
 
3.9%
Other values (16) 111
39.8%
Lowercase Letter
ValueCountFrequency (%)
w 14
 
7.0%
p 12
 
6.0%
g 12
 
6.0%
a 11
 
5.5%
d 11
 
5.5%
y 10
 
5.0%
l 9
 
4.5%
c 9
 
4.5%
f 9
 
4.5%
t 8
 
4.0%
Other values (16) 95
47.5%
Decimal Number
ValueCountFrequency (%)
0 15
17.4%
3 11
12.8%
8 9
10.5%
9 9
10.5%
2 9
10.5%
7 8
9.3%
6 8
9.3%
5 7
8.1%
1 6
 
7.0%
4 4
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 479
83.2%
Common 97
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 32
 
6.7%
C 32
 
6.7%
A 21
 
4.4%
G 15
 
3.1%
w 14
 
2.9%
E 13
 
2.7%
p 12
 
2.5%
g 12
 
2.5%
a 11
 
2.3%
H 11
 
2.3%
Other values (42) 306
63.9%
Common
ValueCountFrequency (%)
0 15
15.5%
3 11
11.3%
8 9
9.3%
9 9
9.3%
2 9
9.3%
7 8
8.2%
6 8
8.2%
5 7
7.2%
- 6
 
6.2%
1 6
 
6.2%
Other values (2) 9
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 576
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 32
 
5.6%
C 32
 
5.6%
A 21
 
3.6%
0 15
 
2.6%
G 15
 
2.6%
w 14
 
2.4%
E 13
 
2.3%
p 12
 
2.1%
g 12
 
2.1%
3 11
 
1.9%
Other values (54) 399
69.3%

개선도지수채널명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-10T23:13:58.369860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length14.5
Mean length10.666667
Min length3

Characters and Unicode

Total characters256
Distinct characters122
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row로아TV
2nd row펫파크 feat.스카이티브이
3rd row강과장
4th row[KERI]한국전기연구원
5th row사모장
ValueCountFrequency (%)
로아tv 1
 
2.3%
예술의전당 1
 
2.3%
남구 1
 
2.3%
고래방송국tv 1
 
2.3%
mdromeda 1
 
2.3%
kpop 1
 
2.3%
까꿍이와개세mr리들 1
 
2.3%
hong 1
 
2.3%
sound 1
 
2.3%
부산광역시연제구청 1
 
2.3%
Other values (33) 33
76.7%
2023-12-10T23:13:59.075681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
7.4%
a 10
 
3.9%
e 8
 
3.1%
o 8
 
3.1%
T 6
 
2.3%
S 5
 
2.0%
m 5
 
2.0%
K 5
 
2.0%
D 5
 
2.0%
N 5
 
2.0%
Other values (112) 180
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
41.0%
Uppercase Letter 64
25.0%
Lowercase Letter 63
24.6%
Space Separator 19
 
7.4%
Other Punctuation 2
 
0.8%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 4
 
3.8%
이 4
 
3.8%
국 3
 
2.9%
연 3
 
2.9%
시 3
 
2.9%
장 3
 
2.9%
울 2
 
1.9%
남 2
 
1.9%
디 2
 
1.9%
피 2
 
1.9%
Other values (66) 77
73.3%
Uppercase Letter
ValueCountFrequency (%)
T 6
 
9.4%
S 5
 
7.8%
K 5
 
7.8%
D 5
 
7.8%
N 5
 
7.8%
V 5
 
7.8%
U 4
 
6.2%
O 4
 
6.2%
C 4
 
6.2%
P 4
 
6.2%
Other values (11) 17
26.6%
Lowercase Letter
ValueCountFrequency (%)
a 10
15.9%
e 8
12.7%
o 8
12.7%
m 5
 
7.9%
i 4
 
6.3%
y 3
 
4.8%
r 3
 
4.8%
d 3
 
4.8%
f 3
 
4.8%
l 2
 
3.2%
Other values (10) 14
22.2%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 127
49.6%
Hangul 105
41.0%
Common 24
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 4
 
3.8%
이 4
 
3.8%
국 3
 
2.9%
연 3
 
2.9%
시 3
 
2.9%
장 3
 
2.9%
울 2
 
1.9%
남 2
 
1.9%
디 2
 
1.9%
피 2
 
1.9%
Other values (66) 77
73.3%
Latin
ValueCountFrequency (%)
a 10
 
7.9%
e 8
 
6.3%
o 8
 
6.3%
T 6
 
4.7%
S 5
 
3.9%
m 5
 
3.9%
K 5
 
3.9%
D 5
 
3.9%
N 5
 
3.9%
V 5
 
3.9%
Other values (31) 65
51.2%
Common
ValueCountFrequency (%)
19
79.2%
. 2
 
8.3%
] 1
 
4.2%
[ 1
 
4.2%
- 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151
59.0%
Hangul 105
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
 
12.6%
a 10
 
6.6%
e 8
 
5.3%
o 8
 
5.3%
T 6
 
4.0%
S 5
 
3.3%
m 5
 
3.3%
K 5
 
3.3%
D 5
 
3.3%
N 5
 
3.3%
Other values (36) 75
49.7%
Hangul
ValueCountFrequency (%)
구 4
 
3.8%
이 4
 
3.8%
국 3
 
2.9%
연 3
 
2.9%
시 3
 
2.9%
장 3
 
2.9%
울 2
 
1.9%
남 2
 
1.9%
디 2
 
1.9%
피 2
 
1.9%
Other values (66) 77
73.3%

개선도지수수집일자
Date

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2020-12-14 00:00:00
Maximum2020-12-31 00:00:00
2023-12-10T23:13:59.284123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:59.467085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

개선도지수채널설명
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing3
Missing (%)12.5%
Memory size324.0 B
2023-12-10T23:13:59.796736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length680
Median length95
Mean length158.09524
Min length14

Characters and Unicode

Total characters3320
Distinct characters364
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row안녕하세요 트위치 스트리머 로아___ 입니다 =) https:www.twitch.tvs2kimroa
2nd row그저 하루하루 적당히 열심히 살아가는 직장인의 일상입니다 방문해주셔서 감사합니다 ^^ 비지니스 문의 kangmanagertv@sandboxnetwork.net 인스타그램 kangmang612 개인메일 kang0930yu@gmail.com 주소 : (04387) 서울시 용산구 서빙고로 17 센트럴파크타워; 30층 샌드박스 강과장 (보내주시는 구독자 선물은 샌드박스쪽에서 2주마다 모아서 저에게 택배가 보내지기때문에 변질되는 음식물은 택배로 받기가 어렵습니다)
3rd 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
4th row안녕하세요! 아주 능숙한 게임실력과 파이팅이넘치는 사모장입니다! 동영상 업로드는 매일 1개씩 오후 5시~6시에 올라갑니다!! 문의메일 : mozang11@naver.com
5th row안녕하세요 커피와 음료를 사랑하는 남자커피 입니다!! 집에서 쉽게 만들수있는 음료 레시피 소개와 재미있는 커피상식들을 알려 드리고 싶어 운영하는 채널입니다. 부족할수있지만 재미있게 봐주세요!! 문의 - bakasa0817@gmail.com
ValueCountFrequency (%)
35
 
6.8%
공식 7
 
1.4%
of 5
 
1.0%
문의 4
 
0.8%
있습니다 4
 
0.8%
영상 4
 
0.8%
입니다 4
 
0.8%
채널입니다 4
 
0.8%
채널 4
 
0.8%
인스타그램 4
 
0.8%
Other values (380) 439
85.4%
2023-12-10T23:14:00.529359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
554
 
16.7%
o 100
 
3.0%
t 90
 
2.7%
e 80
 
2.4%
a 75
 
2.3%
n 73
 
2.2%
= 66
 
2.0%
. 64
 
1.9%
i 56
 
1.7%
r 56
 
1.7%
Other values (354) 2106
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1237
37.3%
Lowercase Letter 968
29.2%
Space Separator 554
16.7%
Other Punctuation 173
 
5.2%
Uppercase Letter 171
 
5.2%
Decimal Number 86
 
2.6%
Math Symbol 72
 
2.2%
Connector Punctuation 17
 
0.5%
Close Punctuation 12
 
0.4%
Dash Punctuation 12
 
0.4%
Other values (3) 18
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 31
 
2.5%
니 29
 
2.3%
는 28
 
2.3%
하 25
 
2.0%
이 23
 
1.9%
의 20
 
1.6%
고 18
 
1.5%
한 18
 
1.5%
사 17
 
1.4%
운 17
 
1.4%
Other values (272) 1011
81.7%
Lowercase Letter
ValueCountFrequency (%)
o 100
 
10.3%
t 90
 
9.3%
e 80
 
8.3%
a 75
 
7.7%
n 73
 
7.5%
i 56
 
5.8%
r 56
 
5.8%
m 55
 
5.7%
c 45
 
4.6%
w 42
 
4.3%
Other values (16) 296
30.6%
Uppercase Letter
ValueCountFrequency (%)
S 15
 
8.8%
T 15
 
8.8%
I 13
 
7.6%
P 13
 
7.6%
O 11
 
6.4%
M 11
 
6.4%
A 10
 
5.8%
D 9
 
5.3%
K 9
 
5.3%
B 7
 
4.1%
Other values (16) 58
33.9%
Other Punctuation
ValueCountFrequency (%)
. 64
37.0%
: 41
23.7%
! 30
17.3%
; 19
 
11.0%
@ 11
 
6.4%
* 3
 
1.7%
? 2
 
1.2%
& 1
 
0.6%
· 1
 
0.6%
' 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 18
20.9%
0 15
17.4%
3 12
14.0%
2 10
11.6%
7 10
11.6%
9 5
 
5.8%
5 5
 
5.8%
8 5
 
5.8%
4 3
 
3.5%
6 3
 
3.5%
Math Symbol
ValueCountFrequency (%)
= 66
91.7%
+ 5
 
6.9%
~ 1
 
1.4%
Space Separator
ValueCountFrequency (%)
554
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 6
100.0%
Other Symbol
ValueCountFrequency (%)
★ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1237
37.3%
Latin 1139
34.3%
Common 944
28.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 31
 
2.5%
니 29
 
2.3%
는 28
 
2.3%
하 25
 
2.0%
이 23
 
1.9%
의 20
 
1.6%
고 18
 
1.5%
한 18
 
1.5%
사 17
 
1.4%
운 17
 
1.4%
Other values (272) 1011
81.7%
Latin
ValueCountFrequency (%)
o 100
 
8.8%
t 90
 
7.9%
e 80
 
7.0%
a 75
 
6.6%
n 73
 
6.4%
i 56
 
4.9%
r 56
 
4.9%
m 55
 
4.8%
c 45
 
4.0%
w 42
 
3.7%
Other values (42) 467
41.0%
Common
ValueCountFrequency (%)
554
58.7%
= 66
 
7.0%
. 64
 
6.8%
: 41
 
4.3%
! 30
 
3.2%
; 19
 
2.0%
1 18
 
1.9%
_ 17
 
1.8%
0 15
 
1.6%
) 12
 
1.3%
Other values (20) 108
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2081
62.7%
Hangul 1229
37.0%
Compat Jamo 8
 
0.2%
None 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
554
26.6%
o 100
 
4.8%
t 90
 
4.3%
e 80
 
3.8%
a 75
 
3.6%
n 73
 
3.5%
= 66
 
3.2%
. 64
 
3.1%
i 56
 
2.7%
r 56
 
2.7%
Other values (70) 867
41.7%
Hangul
ValueCountFrequency (%)
다 31
 
2.5%
니 29
 
2.4%
는 28
 
2.3%
하 25
 
2.0%
이 23
 
1.9%
의 20
 
1.6%
고 18
 
1.5%
한 18
 
1.5%
사 17
 
1.4%
운 17
 
1.4%
Other values (271) 1003
81.6%
Compat Jamo
ValueCountFrequency (%)
ㅤ 8
100.0%
None
ValueCountFrequency (%)
· 1
100.0%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%

개선도채널생성일자
Date

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2011-09-20 00:00:00
Maximum2019-06-13 00:00:00
2023-12-10T23:14:00.799445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:01.116235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

최근6개월개선도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)75.0%
Missing12
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean1.3333333
Minimum-5
Maximum19
Zeros0
Zeros (%)0.0%
Negative7
Negative (%)29.2%
Memory size348.0 B
2023-12-10T23:14:01.383585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5
5-th percentile-5
Q1-2.5
median-1.5
Q34.25
95-th percentile11.85
Maximum19
Range24
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation6.7733882
Coefficient of variation (CV)5.0800412
Kurtosis3.6441036
Mean1.3333333
Median Absolute Deviation (MAD)3.5
Skewness1.7218679
Sum16
Variance45.878788
MonotonicityNot monotonic
2023-12-10T23:14:01.622707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
-2 3
 
12.5%
-5 2
 
8.3%
-4 1
 
4.2%
4 1
 
4.2%
6 1
 
4.2%
-1 1
 
4.2%
5 1
 
4.2%
19 1
 
4.2%
3 1
 
4.2%
(Missing) 12
50.0%
ValueCountFrequency (%)
-5 2
8.3%
-4 1
 
4.2%
-2 3
12.5%
-1 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%
5 1
 
4.2%
6 1
 
4.2%
19 1
 
4.2%
ValueCountFrequency (%)
19 1
 
4.2%
6 1
 
4.2%
5 1
 
4.2%
4 1
 
4.2%
3 1
 
4.2%
-1 1
 
4.2%
-2 3
12.5%
-4 1
 
4.2%
-5 2
8.3%

최근12개월개선도
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)50.0%
Missing10
Missing (%)41.7%
Infinite0
Infinite (%)0.0%
Mean0.64285714
Minimum-10
Maximum5
Zeros1
Zeros (%)4.2%
Negative2
Negative (%)8.3%
Memory size348.0 B
2023-12-10T23:14:01.828328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10
5-th percentile-4.8
Q11
median1
Q32
95-th percentile3.7
Maximum5
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.4330328
Coefficient of variation (CV)5.3402733
Kurtosis7.8627521
Mean0.64285714
Median Absolute Deviation (MAD)1
Skewness-2.4802225
Sum9
Variance11.785714
MonotonicityNot monotonic
2023-12-10T23:14:02.013959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 5
20.8%
2 4
 
16.7%
3 1
 
4.2%
-2 1
 
4.2%
0 1
 
4.2%
-10 1
 
4.2%
5 1
 
4.2%
(Missing) 10
41.7%
ValueCountFrequency (%)
-10 1
 
4.2%
-2 1
 
4.2%
0 1
 
4.2%
1 5
20.8%
2 4
16.7%
3 1
 
4.2%
5 1
 
4.2%
ValueCountFrequency (%)
5 1
 
4.2%
3 1
 
4.2%
2 4
16.7%
1 5
20.8%
0 1
 
4.2%
-2 1
 
4.2%
-10 1
 
4.2%

최초6개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
10 
0
10 
1
4 

Length

Max length4
Median length1
Mean length2.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row1
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 10
41.7%
0 10
41.7%
1 4
 
16.7%

Length

2023-12-10T23:14:02.298208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:02.511227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 10
41.7%
0 10
41.7%
1 4
 
16.7%

최초12개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
12 
<NA>
9 
1
3 

Length

Max length4
Median length1
Mean length2.125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 12
50.0%
<NA> 9
37.5%
1 3
 
12.5%

Length

2023-12-10T23:14:02.707086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:02.885841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 12
50.0%
na 9
37.5%
1 3
 
12.5%

최근개선도지수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct15
Distinct (%)88.2%
Missing7
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean22.143529
Minimum0
Maximum61.51
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-10T23:14:03.046362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.33
median15.85
Q338.99
95-th percentile53.83
Maximum61.51
Range61.51
Interquartile range (IQR)29.66

Descriptive statistics

Standard deviation20.193167
Coefficient of variation (CV)0.91192177
Kurtosis-0.78447295
Mean22.143529
Median Absolute Deviation (MAD)13.49
Skewness0.71677486
Sum376.44
Variance407.76397
MonotonicityNot monotonic
2023-12-10T23:14:03.252155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 3
12.5%
10.65 1
 
4.2%
44.48 1
 
4.2%
51.9 1
 
4.2%
38.99 1
 
4.2%
25.23 1
 
4.2%
15.85 1
 
4.2%
51.91 1
 
4.2%
10.07 1
 
4.2%
20.79 1
 
4.2%
Other values (5) 5
20.8%
(Missing) 7
29.2%
ValueCountFrequency (%)
0.0 3
12.5%
2.36 1
 
4.2%
9.33 1
 
4.2%
10.07 1
 
4.2%
10.65 1
 
4.2%
15.06 1
 
4.2%
15.85 1
 
4.2%
18.31 1
 
4.2%
20.79 1
 
4.2%
25.23 1
 
4.2%
ValueCountFrequency (%)
61.51 1
4.2%
51.91 1
4.2%
51.9 1
4.2%
44.48 1
4.2%
38.99 1
4.2%
25.23 1
4.2%
20.79 1
4.2%
18.31 1
4.2%
15.85 1
4.2%
15.06 1
4.2%

최근6개월표준점수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean-4.6421739
Minimum-52.14
Maximum52.16
Zeros0
Zeros (%)0.0%
Negative17
Negative (%)70.8%
Memory size348.0 B
2023-12-10T23:14:03.511930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-52.14
5-th percentile-16.686
Q1-11.895
median-7.58
Q31.425
95-th percentile16.044
Maximum52.16
Range104.3
Interquartile range (IQR)13.32

Descriptive statistics

Standard deviation17.834834
Coefficient of variation (CV)-3.8419142
Kurtosis5.8843692
Mean-4.6421739
Median Absolute Deviation (MAD)5.96
Skewness0.74388664
Sum-106.77
Variance318.0813
MonotonicityNot monotonic
2023-12-10T23:14:03.775831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
-13.54 2
 
8.3%
-8.69 1
 
4.2%
3.04 1
 
4.2%
-0.17 1
 
4.2%
-52.14 1
 
4.2%
4.87 1
 
4.2%
-10.25 1
 
4.2%
-16.87 1
 
4.2%
-7.98 1
 
4.2%
-9.55 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
-52.14 1
4.2%
-16.87 1
4.2%
-15.03 1
4.2%
-14.21 1
4.2%
-13.54 2
8.3%
-10.25 1
4.2%
-9.55 1
4.2%
-8.69 1
4.2%
-8.36 1
4.2%
-7.98 1
4.2%
ValueCountFrequency (%)
52.16 1
4.2%
16.81 1
4.2%
9.15 1
4.2%
4.87 1
4.2%
3.04 1
4.2%
3.02 1
4.2%
-0.17 1
4.2%
-1.8 1
4.2%
-2.3 1
4.2%
-6.88 1
4.2%

최근12개월표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4045833
Minimum-1.18
Maximum27.69
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)8.3%
Memory size348.0 B
2023-12-10T23:14:04.095006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.18
5-th percentile-0.8805
Q15.8175
median7.72
Q39.7
95-th percentile17.7675
Maximum27.69
Range28.87
Interquartile range (IQR)3.8825

Descriptive statistics

Standard deviation6.1930971
Coefficient of variation (CV)0.7368714
Kurtosis3.2685206
Mean8.4045833
Median Absolute Deviation (MAD)2.115
Skewness1.2980717
Sum201.71
Variance38.354452
MonotonicityNot monotonic
2023-12-10T23:14:04.327991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
7.72 2
 
8.3%
7.9 2
 
8.3%
10.9 1
 
4.2%
9.35 1
 
4.2%
8.74 1
 
4.2%
5.08 1
 
4.2%
27.69 1
 
4.2%
7.67 1
 
4.2%
6.76 1
 
4.2%
10.75 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
-1.18 1
4.2%
-1.17 1
4.2%
0.76 1
4.2%
3.78 1
4.2%
5.08 1
4.2%
5.18 1
4.2%
6.03 1
4.2%
6.27 1
4.2%
6.76 1
4.2%
7.01 1
4.2%
ValueCountFrequency (%)
27.69 1
4.2%
17.82 1
4.2%
17.47 1
4.2%
13.4 1
4.2%
10.9 1
4.2%
10.75 1
4.2%
9.35 1
4.2%
8.74 1
4.2%
8.16 1
4.2%
7.9 2
8.3%

최초6개월표준점수
Real number (ℝ)

Distinct18
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.37791667
Minimum-1.64
Maximum4.54
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)12.5%
Memory size348.0 B
2023-12-10T23:14:04.535982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.64
5-th percentile-0.35
Q10.1375
median0.17
Q30.1925
95-th percentile2.269
Maximum4.54
Range6.18
Interquartile range (IQR)0.055

Descriptive statistics

Standard deviation1.0989085
Coefficient of variation (CV)2.9078063
Kurtosis9.675448
Mean0.37791667
Median Absolute Deviation (MAD)0.03
Skewness2.6157276
Sum9.07
Variance1.2075998
MonotonicityNot monotonic
2023-12-10T23:14:04.744435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.17 4
16.7%
0.19 2
 
8.3%
0.18 2
 
8.3%
0.14 2
 
8.3%
0.13 1
 
4.2%
0.1 1
 
4.2%
0.79 1
 
4.2%
0.06 1
 
4.2%
0.16 1
 
4.2%
0.36 1
 
4.2%
Other values (8) 8
33.3%
ValueCountFrequency (%)
-1.64 1
 
4.2%
-0.41 1
 
4.2%
-0.01 1
 
4.2%
0.06 1
 
4.2%
0.1 1
 
4.2%
0.13 1
 
4.2%
0.14 2
8.3%
0.15 1
 
4.2%
0.16 1
 
4.2%
0.17 4
16.7%
ValueCountFrequency (%)
4.54 1
 
4.2%
2.53 1
 
4.2%
0.79 1
 
4.2%
0.41 1
 
4.2%
0.36 1
 
4.2%
0.2 1
 
4.2%
0.19 2
8.3%
0.18 2
8.3%
0.17 4
16.7%
0.16 1
 
4.2%

최초12개월표준점수
Real number (ℝ)

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.52833333
Minimum-16.88
Maximum0.7
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)12.5%
Memory size348.0 B
2023-12-10T23:14:04.962954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-16.88
5-th percentile-1.246
Q10.1375
median0.25
Q30.2925
95-th percentile0.6195
Maximum0.7
Range17.58
Interquartile range (IQR)0.155

Descriptive statistics

Standard deviation3.5050283
Coefficient of variation (CV)-6.6341229
Kurtosis23.315751
Mean-0.52833333
Median Absolute Deviation (MAD)0.09
Skewness-4.8026154
Sum-12.68
Variance12.285223
MonotonicityNot monotonic
2023-12-10T23:14:05.187694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.25 4
16.7%
0.26 3
 
12.5%
0.05 1
 
4.2%
0.12 1
 
4.2%
0.35 1
 
4.2%
0.23 1
 
4.2%
0.21 1
 
4.2%
0.13 1
 
4.2%
-0.43 1
 
4.2%
-1.39 1
 
4.2%
Other values (9) 9
37.5%
ValueCountFrequency (%)
-16.88 1
 
4.2%
-1.39 1
 
4.2%
-0.43 1
 
4.2%
0.05 1
 
4.2%
0.12 1
 
4.2%
0.13 1
 
4.2%
0.14 1
 
4.2%
0.21 1
 
4.2%
0.23 1
 
4.2%
0.25 4
16.7%
ValueCountFrequency (%)
0.7 1
 
4.2%
0.66 1
 
4.2%
0.39 1
 
4.2%
0.38 1
 
4.2%
0.35 1
 
4.2%
0.33 1
 
4.2%
0.28 1
 
4.2%
0.27 1
 
4.2%
0.26 3
12.5%
0.25 4
16.7%

개선도최근표준점수
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.58625
Minimum-12.19
Maximum1347.51
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)4.2%
Memory size348.0 B
2023-12-10T23:14:05.431211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-12.19
5-th percentile1.4615
Q115.11
median18.905
Q320.765
95-th percentile24.489
Maximum1347.51
Range1359.7
Interquartile range (IQR)5.655

Descriptive statistics

Standard deviation271.89585
Coefficient of variation (CV)3.7981574
Kurtosis23.949857
Mean71.58625
Median Absolute Deviation (MAD)3.835
Skewness4.8915393
Sum1718.07
Variance73927.351
MonotonicityNot monotonic
2023-12-10T23:14:05.685060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
24.51 1
 
4.2%
1347.51 1
 
4.2%
11.9 1
 
4.2%
20.01 1
 
4.2%
0.77 1
 
4.2%
18.86 1
 
4.2%
18.98 1
 
4.2%
19.26 1
 
4.2%
23.53 1
 
4.2%
11.2 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
-12.19 1
4.2%
0.77 1
4.2%
5.38 1
4.2%
11.2 1
4.2%
11.9 1
4.2%
14.99 1
4.2%
15.15 1
4.2%
16.39 1
4.2%
17.72 1
4.2%
18.0 1
4.2%
ValueCountFrequency (%)
1347.51 1
4.2%
24.51 1
4.2%
24.37 1
4.2%
23.53 1
4.2%
23.19 1
4.2%
23.03 1
4.2%
20.01 1
4.2%
19.27 1
4.2%
19.26 1
4.2%
19.18 1
4.2%

Interactions

2023-12-10T23:13:53.841076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:44.237437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:45.562530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:47.068549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:48.650243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:50.101847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:51.281427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:52.454850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:53.978642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:44.393669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:45.707285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:47.204827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:48.921260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:50.242831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:51.411241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:52.578467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:54.144467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:44.549202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:46.199512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:47.365740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:49.190260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:50.408429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:51.562801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:52.813822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:54.334403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:44.734687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:46.346278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:47.567789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:49.340353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:50.540416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:51.733138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:52.972559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:54.588720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:44.891244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:46.488977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:47.720338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:49.488258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:50.681190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:51.878484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:53.141619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:54.751855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:45.082465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:46.617883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:47.882019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:49.632599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:50.823130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:52.018687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:53.296965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:54.933845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:45.293950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:46.761837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:48.136088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:49.775177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:50.945836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:52.159109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:53.487932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:55.129567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:45.420844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:46.907234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:48.407622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:49.913503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:51.100015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:52.315213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:13:53.690544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:14:05.874015image/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
개선도지수수집일자1.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
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
최근6개월개선도1.0001.0000.0001.0001.0001.0000.0000.0001.0000.0000.4780.6570.0000.0000.000
최근12개월개선도1.0001.0000.0001.0001.0000.0001.0000.4840.0000.0000.4600.3460.5010.0000.000
최초6개월개선도1.0001.0000.0001.0001.0000.0000.4841.0000.5030.9360.2330.7680.6460.1730.000
최초12개월개선도1.0001.0000.0001.0001.0001.0000.0000.5031.0000.5160.0000.9360.0000.2660.000
최근개선도지수1.0001.0000.0001.0001.0000.0000.0000.9360.5161.0000.2970.8120.7080.9360.000
최근6개월표준점수1.0001.0000.0001.0001.0000.4780.4600.2330.0000.2971.0000.6210.7650.0000.000
최근12개월표준점수1.0001.0000.0001.0001.0000.6570.3460.7680.9360.8120.6211.0000.5250.7920.178
최초6개월표준점수1.0001.0000.0001.0001.0000.0000.5010.6460.0000.7080.7650.5251.0000.0000.000
최초12개월표준점수1.0001.0000.0001.0001.0000.0000.0000.1730.2660.9360.0000.7920.0001.0001.000
개선도최근표준점수1.0001.0000.0001.0001.0000.0000.0000.0000.0000.0000.0000.1780.0001.0001.000
2023-12-10T23:14:06.214245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초12개월개선도최초6개월개선도
최초12개월개선도1.0000.328
최초6개월개선도0.3281.000
2023-12-10T23:14:06.511240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최근6개월개선도최근12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수최초6개월개선도최초12개월개선도
최근6개월개선도1.0000.090-0.2230.533-0.2930.2270.012-0.2540.0000.791
최근12개월개선도0.0901.0000.278-0.1140.1820.204-0.0480.0960.0000.480
최근개선도지수-0.2230.2781.0000.398-0.1300.295-0.195-0.3100.5080.201
최근6개월표준점수0.533-0.1140.3981.000-0.3240.1430.035-0.3650.1980.000
최근12개월표준점수-0.2930.182-0.130-0.3241.0000.1980.144-0.0380.6270.560
최초6개월표준점수0.2270.2040.2950.1430.1981.0000.381-0.4870.3540.000
최초12개월표준점수0.012-0.048-0.1950.0350.1440.3811.000-0.3370.2520.405
개선도최근표준점수-0.2540.096-0.310-0.365-0.038-0.487-0.3371.0000.0000.000
최초6개월개선도0.0000.0000.5080.1980.6270.3540.2520.0001.0000.328
최초12개월개선도0.7910.4800.2010.0000.5600.0000.4050.0000.3281.000

Missing values

2023-12-10T23:13:55.443754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:13:56.459092image/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.
2023-12-10T23:13:56.873136image/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
0UCcpAAfKWfnVXViVwfjc2q-A로아TV2020-12-14안녕하세요 트위치 스트리머 로아___ 입니다 =) https:www.twitch.tvs2kimroa2016-01-26-431110.65-8.697.720.130.0524.51
1UCw0ZKmxFBc9donV317twWeA펫파크 feat.스카이티브이2020-12-29<NA>2014-10-06<NA><NA><NA><NA><NA><NA>17.470.140.145.38
2UC1EEpE0lA9BaArXhRTHIG6w강과장2020-12-31그저 하루하루 적당히 열심히 살아가는 직장인의 일상입니다 방문해주셔서 감사합니다 ^^ 비지니스 문의 kangmanagertv@sandboxnetwork.net 인스타그램 kangmang612 개인메일 kang0930yu@gmail.com 주소 : (04387) 서울시 용산구 서빙고로 17 센트럴파크타워; 30층 샌드박스 강과장 (보내주시는 구독자 선물은 샌드박스쪽에서 2주마다 모아서 저에게 택배가 보내지기때문에 변질되는 음식물은 택배로 받기가 어렵습니다)2018-09-16421044.4816.8113.44.540.3315.15
3UC-gWrEGYpG2jYfl8A_KIGnQ[KERI]한국전기연구원2020-12-31전기전문 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<NA><NA><NA><NA><NA>-15.038.160.190.2819.18
4UC4XjKgCtpwpACzUCiUKOd3Q사모장2020-12-31안녕하세요! 아주 능숙한 게임실력과 파이팅이넘치는 사모장입니다! 동영상 업로드는 매일 1개씩 오후 5시~6시에 올라갑니다!! 문의메일 : mozang11@naver.com2013-12-08620051.952.160.760.20.27-12.19
5UC85mXeWRaycnlFmrhBdaAlg남자커피 Namja Coffee2020-12-31안녕하세요 커피와 음료를 사랑하는 남자커피 입니다!! 집에서 쉽게 만들수있는 음료 레시피 소개와 재미있는 커피상식들을 알려 드리고 싶어 운영하는 채널입니다. 부족할수있지만 재미있게 봐주세요!! 문의 - bakasa0817@gmail.com2018-08-18-221038.99-2.317.822.530.3916.39
6UC8JOLZ-YA34ylQTz2tqSlGwKAIST2020-12-31한국과학기술원(KAIST)의 공식 유튜브 채널입니다! This is the official YouTube channel of KAIST!2013-07-28<NA><NA><NA><NA><NA>-14.217.720.180.2617.72
7UC9G7V6-HU_Cg7-yWLO1rH6wPURE.D퓨어디2020-12-31teenpopk@gmail.com2016-12-21<NA>11125.23-6.883.78-0.01-16.8824.37
8UC2Zi06YjNBM37g8d0IkHPMATVCHOSUN PLUS - TV조선 플러스2020-12-31TV조선 방송 채널에; 더한 클립과; 더한 영상들을 모아둔 더한 채널 TV조선 플러스2019-01-18<NA><NA>0015.85-8.366.27-0.410.718.11
9UC9mVBtjHNwSltQKTyLF2KXw여니네일 YeoniNail2020-12-31간단하고 쉬운 네일아트 방법과 뷰티를 공유하고싶은 Yeoni입니다! 네일아트 뷰티 리뷰 DIY 비지니스 문의 : yeonime0@gmail.com 인스타그램 : https:www.instagram.comyeoni_nailart @yeoni_nailart2014-11-09<NA><NA>000.0-13.547.90.410.3819.27
개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
14UCBHPMXWzZa4RylJ7JbzGsvw까꿍이와개세mr리들2020-12-31반려동물과 함께하는 까꿍이의 일상을 여러분들께 공개합니다!! 까꿍의 공식 반려동물 YOUTUBE 채널 입니다. 타투; 꿍찌;백설!! 반려동물과 언제나 함께하는 까꿍이가 되겠습니다. 까둥이들 사랑합니다 구둑자210;0000명 정말 정말 감사합니다!!! +==================+ ★ 까꿍 새로운이야기 https:www.youtube.comchannelUCL5_pSpcBcT4qySMtB97eMQ 구독하기 https:www.youtube.comchannelUCBHPMXWzZa4RylJ7JbzGsvw?sub_confirmation=1 +==================+2014-12-29-12<NA><NA>10.073.0410.90.170.2523.03
15UCBIoXzDldCnpbM_7uyG0_TgHONG SOUND2020-12-31취미로 유튜브를 시작한 품절남 아재 홍사운드 에요! 지금은 푸드크리에이터로서 그 동안 경험해보지 못한 다양하고 맛있는 음식들을 먹으며 여러분들과 공유하는 채널을 운영하고 있습니다! 감사합니다 ^^ 인스타그램(instargram) : https:www.instagram.comhong_sound 홍사운드(HONG SOUND) 채널은? 취미로 유튜브를 시작한 품절남 아재 홍사운드 에요! 지금은 푸드크리에이터로서 그 동안 경험해보지 못한 다양하고 맛있는 음식들을 먹으며 여러분들과 공유하는 채널을 운영하고 있습니다! 감사합니다 ^^ 1.리얼사운드 먹방 : 실감나는 먹방; 독특한 오프닝송과 맛 설명도 함께 있어요. *No talking ASMR 이팅사운드 : 오직 먹는 소리만 있는 영상 (편안하고 부드러운 화면) *노토킹 ASMR 이팅사운드 영상은 먹는 소리만 듣고 싶어하는 구독자분들을 위해 제작하고 있습니다. 2.미분일기(맛을 나누는 일기) : 그날의 행복한 추억과 음식의 맛을 공유하는 영상일기. 3.긍정부스터(생방송 리얼사운드 먹방) : 매주 수요일 저녁 11시 30분! 홍사운드와 함께 음식도 먹고 즐거운 담소도 나누며 긍정긍정의 힘을 받아가세요! 광고 문의 : 이메일 인스타그램 : https:www.instagram.comhong_sound 이메일 : dkagmr12@naver.com2015-12-11510020.799.15-1.170.36-0.4314.99
16UCBdKH3MG6X71y94A2WUdETQ부산광역시연제구청2020-12-31품격있는 도시; 상생하는 연제. 부산 연제구의 공식 유튜브입니다.2019-06-13<NA><NA><NA><NA><NA>-7.586.030.160.2611.2
17UCBvDRQETp01JUOVHaumO08Q예술의전당 Concert2020-12-31Since 2012.03.28 Seoul Arts Center 예술의전당ㅤㅤㅤㅤ ㅤㅤㅤ Presents_ Seoul Arts Center Exacutive Producer_ Jeon Seongjin VideoAudio Filming & Editing_ Members of the Stage Sound Part ㅤ 제작 : 예술의전당 책임 프로듀서 : 전성진 녹화; 편집 : 예술의전당 무대운영부 음향파트_ 곽동렬; 문성욱; 양승모; 이강진; 전성진; 조민제; 조희명; 주원국; 한국란; 한혜림2012-03-28191000.0-9.5510.750.060.1323.53
18UCCWWpm3ZkHVckG0TMUpkGaAKDI 한국개발연구원2020-12-31KDI(Korea Development Institute; 한국개발연구원) 공식 채널. KDI가 직접 만들고 제공하는 경제·사회이슈 영상보고서를 만나보세요.2013-01-09<NA><NA>002.36-7.986.760.140.2119.26
19UCCXGEDotqfr2g2hMEV9VSxQ인천도시공사2020-12-31<NA>2019-01-29<NA><NA><NA><NA><NA>-16.877.670.180.2518.98
20UC9T8wL0qUwhpcKSv73J5dqA모터피디2020-12-31영상으로 만나는 자동차 매거진 - Auto Magazine www.motorpd.com Facebook: facebook.commotorpd Twitter: twitter.commotorpd1 Instagram: instagrammotorpd1 Google+:plus.google.com113593086973172778755about2015-04-23-50<NA>115.06-10.2527.690.170.2318.86
21UCEcuyrAqhRVUmRdOd6FGKSw기리TV2020-12-31기리TV는 게임 채널입니다2014-01-133-10009.334.875.080.790.350.77
22UCEeEvBzuFze0gMn0FF55h8wDasha Kim2020-12-31<NA>2011-09-20<NA>5<NA><NA>18.31-52.148.740.170.2520.01
23UCEyuopMY0Lx5b5PgCH03FSQCozyDay 코지데이2020-12-31동갑내기 9년차 커플의 포근하고 따뜻한 일상 브이로그 e-mail : cozyday_couple@sandboxnetwork.net2012-08-23-51<NA><NA>61.51-0.179.350.170.2511.9