Overview

Dataset statistics

Number of variables20
Number of observations27
Missing cells19
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory179.9 B

Variable types

Text3
DateTime2
Numeric8
Categorical7

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/6188c704-6182-4cea-8df9-924d1b1252e7

Alerts

상호작용지수수집일자 has constant value ""Constant
상호작용지수전체표준점수 is highly overall correlated with 지수전체 and 13 other fieldsHigh correlation
3개월표준점수 is highly overall correlated with 상호작용지수전체 and 2 other fieldsHigh correlation
상호작용지수주당덧글수 is highly overall correlated with 지수전체 and 13 other fieldsHigh correlation
상호작용지수3개월 is highly overall correlated with 상호작용지수전체 and 2 other fieldsHigh correlation
1개월표준점수 is highly overall correlated with 상호작용지수전체 and 2 other fieldsHigh correlation
상호작용지수1개월 is highly overall correlated with 상호작용지수전체 and 2 other fieldsHigh correlation
상호작용지수전체 is highly overall correlated with 지수전체 and 13 other fieldsHigh correlation
지수전체 is highly overall correlated with 지수1개월 and 9 other fieldsHigh correlation
지수1개월 is highly overall correlated with 지수전체 and 8 other fieldsHigh correlation
지수3개월 is highly overall correlated with 지수전체 and 6 other fieldsHigh correlation
평균덧글수 is highly overall correlated with 지수전체 and 8 other fieldsHigh correlation
주당덧글수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
상호작용지수평균덧글수 is highly overall correlated with 지수전체 and 8 other fieldsHigh correlation
평균수표준점수 is highly overall correlated with 지수전체 and 7 other fieldsHigh correlation
주당수표준점수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
상호작용지수전체 is highly imbalanced (61.2%)Imbalance
상호작용지수1개월 is highly imbalanced (77.1%)Imbalance
상호작용지수3개월 is highly imbalanced (77.1%)Imbalance
상호작용지수주당덧글수 is highly imbalanced (61.8%)Imbalance
상호작용지수전체표준점수 is highly imbalanced (71.3%)Imbalance
1개월표준점수 is highly imbalanced (77.1%)Imbalance
3개월표준점수 is highly imbalanced (77.1%)Imbalance
상호작용지수채널설명 has 5 (18.5%) missing valuesMissing
상호작용지수채널생성일자 has 8 (29.6%) missing valuesMissing
평균덧글수 has 2 (7.4%) missing valuesMissing
상호작용지수평균덧글수 has 2 (7.4%) missing valuesMissing
평균수표준점수 has 2 (7.4%) missing valuesMissing
상호작용지수채널ID has unique valuesUnique
상호작용지수채널명 has unique valuesUnique
지수전체 has 3 (11.1%) zerosZeros
지수1개월 has 12 (44.4%) zerosZeros
지수3개월 has 8 (29.6%) zerosZeros
평균덧글수 has 1 (3.7%) zerosZeros
주당덧글수 has 4 (14.8%) zerosZeros
상호작용지수평균덧글수 has 1 (3.7%) zerosZeros

Reproduction

Analysis started2023-12-10 13:57:46.989321
Analysis finished2023-12-10 13:58:01.627227
Duration14.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호작용지수채널ID
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-10T22:58:01.912311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

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

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st rowUC-gWrEGYpG2jYfl8A_KIGnQ
2nd rowUC-JZtfVAgIjmNfhapEV3zgg
3rd rowUC0ZqpSq-OIpOITZ7U16-Xeg
4th rowUC0ru5w57PyGpbsEKwN4LuwA
5th rowUC12BY9i1Lurqcvt-IZOpVvw
ValueCountFrequency (%)
uc-gwregypg2jyfl8a_kignq 1
 
3.7%
uc3izksevpdzpsbawxbxunda 1
 
3.7%
uc60z87qoafcpzme6mpgpifq 1
 
3.7%
uc5xk2xdrud3-kgjks1igumg 1
 
3.7%
uc5r3whrx4z7pesypdlgktgw 1
 
3.7%
uc1aattgksf9qtkcwkhtms6a 1
 
3.7%
uc5ce1xgat0jjoxcfwzl1jcg 1
 
3.7%
uc5fl8a5kyrw51zhm4ydsaag 1
 
3.7%
uc4vd5jpdxzrpy1bpradjhsa 1
 
3.7%
uc4sxrraltvpl0zogq5ikvxw 1
 
3.7%
Other values (17) 17
63.0%
2023-12-10T22:58:02.700827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 31
 
4.8%
C 31
 
4.8%
g 21
 
3.2%
p 19
 
2.9%
A 18
 
2.8%
1 15
 
2.3%
5 14
 
2.2%
2 14
 
2.2%
I 14
 
2.2%
4 13
 
2.0%
Other values (54) 458
70.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 281
43.4%
Lowercase Letter 259
40.0%
Decimal Number 96
 
14.8%
Dash Punctuation 8
 
1.2%
Connector Punctuation 4
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 31
 
11.0%
C 31
 
11.0%
A 18
 
6.4%
I 14
 
5.0%
G 13
 
4.6%
Z 13
 
4.6%
K 12
 
4.3%
Y 11
 
3.9%
B 11
 
3.9%
Q 11
 
3.9%
Other values (16) 116
41.3%
Lowercase Letter
ValueCountFrequency (%)
g 21
 
8.1%
p 19
 
7.3%
w 12
 
4.6%
t 12
 
4.6%
q 12
 
4.6%
r 12
 
4.6%
d 11
 
4.2%
f 11
 
4.2%
m 11
 
4.2%
o 10
 
3.9%
Other values (16) 128
49.4%
Decimal Number
ValueCountFrequency (%)
1 15
15.6%
5 14
14.6%
2 14
14.6%
4 13
13.5%
0 8
8.3%
7 8
8.3%
3 8
8.3%
6 7
7.3%
9 5
 
5.2%
8 4
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 540
83.3%
Common 108
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 31
 
5.7%
C 31
 
5.7%
g 21
 
3.9%
p 19
 
3.5%
A 18
 
3.3%
I 14
 
2.6%
G 13
 
2.4%
Z 13
 
2.4%
w 12
 
2.2%
t 12
 
2.2%
Other values (42) 356
65.9%
Common
ValueCountFrequency (%)
1 15
13.9%
5 14
13.0%
2 14
13.0%
4 13
12.0%
0 8
7.4%
- 8
7.4%
7 8
7.4%
3 8
7.4%
6 7
6.5%
9 5
 
4.6%
Other values (2) 8
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 31
 
4.8%
C 31
 
4.8%
g 21
 
3.2%
p 19
 
2.9%
A 18
 
2.8%
1 15
 
2.3%
5 14
 
2.2%
2 14
 
2.2%
I 14
 
2.2%
4 13
 
2.0%
Other values (54) 458
70.7%

상호작용지수채널명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-10T22:58:03.139424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length10.407407
Min length3

Characters and Unicode

Total characters281
Distinct characters139
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row[KERI]한국전기연구원
2nd row차차튜브 Chacha Tube
3rd row유디티TV
4th row재민정
5th rowyoloria욜로리아
ValueCountFrequency (%)
in 2
 
3.7%
keri]한국전기연구원 1
 
1.9%
darlim&hamabal 1
 
1.9%
50대 1
 
1.9%
컴쟁이 1
 
1.9%
baseyou21 1
 
1.9%
flower 1
 
1.9%
pig]꽃돼지 1
 
1.9%
로젠젠_세계여행일지 1
 
1.9%
조랭몬 1
 
1.9%
Other values (43) 43
79.6%
2023-12-10T22:58:03.899369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
 
9.6%
a 16
 
5.7%
o 11
 
3.9%
e 11
 
3.9%
r 7
 
2.5%
n 7
 
2.5%
l 6
 
2.1%
T 6
 
2.1%
i 5
 
1.8%
u 5
 
1.8%
Other values (129) 180
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112
39.9%
Lowercase Letter 94
33.5%
Uppercase Letter 35
 
12.5%
Space Separator 27
 
9.6%
Decimal Number 4
 
1.4%
Open Punctuation 3
 
1.1%
Close Punctuation 3
 
1.1%
Connector Punctuation 1
 
0.4%
Other Punctuation 1
 
0.4%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 3
 
2.7%
일 3
 
2.7%
로 3
 
2.7%
기 3
 
2.7%
주 2
 
1.8%
다 2
 
1.8%
인 2
 
1.8%
젠 2
 
1.8%
라 2
 
1.8%
지 2
 
1.8%
Other values (82) 88
78.6%
Lowercase Letter
ValueCountFrequency (%)
a 16
17.0%
o 11
11.7%
e 11
11.7%
r 7
 
7.4%
n 7
 
7.4%
l 6
 
6.4%
i 5
 
5.3%
u 5
 
5.3%
p 4
 
4.3%
b 4
 
4.3%
Other values (9) 18
19.1%
Uppercase Letter
ValueCountFrequency (%)
T 6
17.1%
H 3
 
8.6%
E 3
 
8.6%
I 3
 
8.6%
Y 2
 
5.7%
K 2
 
5.7%
L 2
 
5.7%
B 2
 
5.7%
V 2
 
5.7%
C 2
 
5.7%
Other values (8) 8
22.9%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
2 1
25.0%
5 1
25.0%
0 1
25.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
] 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Math Symbol
ValueCountFrequency (%)
∨ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 129
45.9%
Hangul 112
39.9%
Common 40
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 3
 
2.7%
일 3
 
2.7%
로 3
 
2.7%
기 3
 
2.7%
주 2
 
1.8%
다 2
 
1.8%
인 2
 
1.8%
젠 2
 
1.8%
라 2
 
1.8%
지 2
 
1.8%
Other values (82) 88
78.6%
Latin
ValueCountFrequency (%)
a 16
 
12.4%
o 11
 
8.5%
e 11
 
8.5%
r 7
 
5.4%
n 7
 
5.4%
l 6
 
4.7%
T 6
 
4.7%
i 5
 
3.9%
u 5
 
3.9%
p 4
 
3.1%
Other values (27) 51
39.5%
Common
ValueCountFrequency (%)
27
67.5%
[ 3
 
7.5%
] 3
 
7.5%
_ 1
 
2.5%
1 1
 
2.5%
2 1
 
2.5%
& 1
 
2.5%
5 1
 
2.5%
∨ 1
 
2.5%
0 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168
59.8%
Hangul 112
39.9%
Math Operators 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27
16.1%
a 16
 
9.5%
o 11
 
6.5%
e 11
 
6.5%
r 7
 
4.2%
n 7
 
4.2%
l 6
 
3.6%
T 6
 
3.6%
i 5
 
3.0%
u 5
 
3.0%
Other values (36) 67
39.9%
Hangul
ValueCountFrequency (%)
정 3
 
2.7%
일 3
 
2.7%
로 3
 
2.7%
기 3
 
2.7%
주 2
 
1.8%
다 2
 
1.8%
인 2
 
1.8%
젠 2
 
1.8%
라 2
 
1.8%
지 2
 
1.8%
Other values (82) 88
78.6%
Math Operators
ValueCountFrequency (%)
∨ 1
100.0%

상호작용지수수집일자
Date

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2021-10-31 00:00:00
Maximum2021-10-31 00:00:00
2023-12-10T22:58:04.115883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:04.271556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

상호작용지수채널설명
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing5
Missing (%)18.5%
Memory size348.0 B
2023-12-10T22:58:04.542943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length651
Median length117
Mean length159.22727
Min length30

Characters and Unicode

Total characters3503
Distinct characters360
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

Unique22 ?
Unique (%)100.0%

Sample

1st 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
2nd rowEmailchadahye@gmail.com Insta cha.dahye
3rd row만원으로일주일반찬만들기; 간단요리; 맛있는다이어트레시피
4th row#경기관광공사 공식 유튜브 채널입니다 Gyeonggi Tourism Organization's official youtube channel 어제의 기억과 내일의 희망이 함께 공존하는 곳; 사랑도 여행도 #경기도 소중해진 하루엔 경기도 #경기관광 #ㄱㄱㄱㄱ #ㄲㄲ #ㅋㅋ
5th row캡틴피터 Captain Peter vashtebah@gmail.com
ValueCountFrequency (%)
35
 
6.8%
유튜브 6
 
1.2%
영상 4
 
0.8%
도그캐슬 4
 
0.8%
하오 4
 
0.8%
함께 4
 
0.8%
and 4
 
0.8%
are 3
 
0.6%
하오와 3
 
0.6%
있습니다 3
 
0.6%
Other values (403) 448
86.5%
2023-12-10T22:58:05.096279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
566
 
16.2%
e 135
 
3.9%
o 126
 
3.6%
a 120
 
3.4%
t 101
 
2.9%
n 87
 
2.5%
r 79
 
2.3%
. 72
 
2.1%
c 67
 
1.9%
m 67
 
1.9%
Other values (350) 2083
59.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1295
37.0%
Other Letter 1069
30.5%
Space Separator 566
16.2%
Other Punctuation 213
 
6.1%
Uppercase Letter 202
 
5.8%
Decimal Number 75
 
2.1%
Math Symbol 40
 
1.1%
Dash Punctuation 13
 
0.4%
Connector Punctuation 10
 
0.3%
Modifier Symbol 6
 
0.2%
Other values (3) 14
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 40
 
3.7%
하 29
 
2.7%
다 29
 
2.7%
니 22
 
2.1%
의 22
 
2.1%
오 19
 
1.8%
로 16
 
1.5%
기 16
 
1.5%
버 15
 
1.4%
리 15
 
1.4%
Other values (270) 846
79.1%
Lowercase Letter
ValueCountFrequency (%)
e 135
 
10.4%
o 126
 
9.7%
a 120
 
9.3%
t 101
 
7.8%
n 87
 
6.7%
r 79
 
6.1%
c 67
 
5.2%
m 67
 
5.2%
i 60
 
4.6%
s 60
 
4.6%
Other values (16) 393
30.3%
Uppercase Letter
ValueCountFrequency (%)
T 19
 
9.4%
E 17
 
8.4%
I 17
 
8.4%
S 14
 
6.9%
H 12
 
5.9%
B 11
 
5.4%
A 10
 
5.0%
N 10
 
5.0%
W 9
 
4.5%
O 9
 
4.5%
Other values (14) 74
36.6%
Other Punctuation
ValueCountFrequency (%)
. 72
33.8%
: 49
23.0%
; 30
14.1%
! 24
 
11.3%
# 13
 
6.1%
@ 11
 
5.2%
* 8
 
3.8%
& 4
 
1.9%
? 1
 
0.5%
' 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 16
21.3%
0 14
18.7%
2 13
17.3%
5 7
9.3%
9 7
9.3%
4 5
 
6.7%
8 4
 
5.3%
3 4
 
5.3%
6 3
 
4.0%
7 2
 
2.7%
Math Symbol
ValueCountFrequency (%)
= 28
70.0%
~ 12
30.0%
Other Symbol
ValueCountFrequency (%)
♥ 3
75.0%
▶ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
566
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1497
42.7%
Hangul 1069
30.5%
Common 937
26.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 40
 
3.7%
하 29
 
2.7%
다 29
 
2.7%
니 22
 
2.1%
의 22
 
2.1%
오 19
 
1.8%
로 16
 
1.5%
기 16
 
1.5%
버 15
 
1.4%
리 15
 
1.4%
Other values (270) 846
79.1%
Latin
ValueCountFrequency (%)
e 135
 
9.0%
o 126
 
8.4%
a 120
 
8.0%
t 101
 
6.7%
n 87
 
5.8%
r 79
 
5.3%
c 67
 
4.5%
m 67
 
4.5%
i 60
 
4.0%
s 60
 
4.0%
Other values (40) 595
39.7%
Common
ValueCountFrequency (%)
566
60.4%
. 72
 
7.7%
: 49
 
5.2%
; 30
 
3.2%
= 28
 
3.0%
! 24
 
2.6%
1 16
 
1.7%
0 14
 
1.5%
- 13
 
1.4%
# 13
 
1.4%
Other values (20) 112
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2430
69.4%
Hangul 1061
30.3%
Compat Jamo 8
 
0.2%
Misc Symbols 3
 
0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
566
23.3%
e 135
 
5.6%
o 126
 
5.2%
a 120
 
4.9%
t 101
 
4.2%
n 87
 
3.6%
r 79
 
3.3%
. 72
 
3.0%
c 67
 
2.8%
m 67
 
2.8%
Other values (68) 1010
41.6%
Hangul
ValueCountFrequency (%)
이 40
 
3.8%
하 29
 
2.7%
다 29
 
2.7%
니 22
 
2.1%
의 22
 
2.1%
오 19
 
1.8%
로 16
 
1.5%
기 16
 
1.5%
버 15
 
1.4%
리 15
 
1.4%
Other values (267) 838
79.0%
Compat Jamo
ValueCountFrequency (%)
ㄱ 4
50.0%
ㅋ 2
25.0%
ㄲ 2
25.0%
Misc Symbols
ValueCountFrequency (%)
♥ 3
100.0%
Geometric Shapes
ValueCountFrequency (%)
▶ 1
100.0%

상호작용지수채널생성일자
Date

MISSING 

Distinct19
Distinct (%)100.0%
Missing8
Missing (%)29.6%
Memory size348.0 B
Minimum2008-06-04 00:00:00
Maximum2019-02-03 00:00:00
2023-12-10T22:58:05.341063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:58:05.579628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

지수전체
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9045115 × 1015
Minimum0
Maximum7.8413227 × 1016
Zeros3
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-10T22:58:05.841895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14519222
median3.233303 × 109
Q37.6581612 × 1010
95-th percentile4.0808686 × 1012
Maximum7.8413227 × 1016
Range7.8413227 × 1016
Interquartile range (IQR)7.6577092 × 1010

Descriptive statistics

Standard deviation1.5090569 × 1016
Coefficient of variation (CV)5.1955618
Kurtosis27
Mean2.9045115 × 1015
Median Absolute Deviation (MAD)3.233303 × 109
Skewness5.1961524
Sum7.8421811 × 1016
Variance2.2772527 × 1032
MonotonicityNot monotonic
2023-12-10T22:58:06.119306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 3
 
11.1%
7057589 1
 
3.7%
28665 1
 
3.7%
739900 1
 
3.7%
2472264070000 1
 
3.7%
531458458000 1
 
3.7%
408297440 1
 
3.7%
242913952000 1
 
3.7%
225291696 1
 
3.7%
27824740400 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
0 3
11.1%
28665 1
 
3.7%
739900 1
 
3.7%
1355516 1
 
3.7%
1980855 1
 
3.7%
7057589 1
 
3.7%
20099382 1
 
3.7%
25512972 1
 
3.7%
225291696 1
 
3.7%
237818880 1
 
3.7%
ValueCountFrequency (%)
78413227000000000 1
3.7%
4770270500000 1
3.7%
2472264070000 1
3.7%
531458458000 1
3.7%
249613156000 1
3.7%
242913952000 1
3.7%
85977817000 1
3.7%
67185406000 1
3.7%
60974686000 1
3.7%
50712785000 1
3.7%

지수1개월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9929278 × 1011
Minimum0
Maximum8.0806045 × 1012
Zeros12
Zeros (%)44.4%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-10T22:58:06.369938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median44
Q3966783
95-th percentile1.2458433 × 108
Maximum8.0806045 × 1012
Range8.0806045 × 1012
Interquartile range (IQR)966783

Descriptive statistics

Standard deviation1.5551108 × 1012
Coefficient of variation (CV)5.1959517
Kurtosis27
Mean2.9929278 × 1011
Median Absolute Deviation (MAD)44
Skewness5.1961524
Sum8.0809052 × 1012
Variance2.4183697 × 1024
MonotonicityNot monotonic
2023-12-10T22:58:06.635114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 12
44.4%
28665 1
 
3.7%
6439297 1
 
3.7%
137350160 1
 
3.7%
5537 1
 
3.7%
1837935 1
 
3.7%
560 1
 
3.7%
44 1
 
3.7%
8080604500000 1
 
3.7%
94797408 1
 
3.7%
Other values (6) 6
22.2%
ValueCountFrequency (%)
0 12
44.4%
18 1
 
3.7%
44 1
 
3.7%
560 1
 
3.7%
5537 1
 
3.7%
28665 1
 
3.7%
59640 1
 
3.7%
60444 1
 
3.7%
95631 1
 
3.7%
1837935 1
 
3.7%
ValueCountFrequency (%)
8080604500000 1
3.7%
137350160 1
3.7%
94797408 1
3.7%
37711592 1
3.7%
22284604 1
3.7%
6439297 1
3.7%
1837935 1
3.7%
95631 1
3.7%
60444 1
3.7%
59640 1
3.7%

지수3개월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1931988 × 1012
Minimum0
Maximum5.92139 × 1013
Zeros8
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-10T22:58:06.838778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3182
Q331012450
95-th percentile1.0007402 × 109
Maximum5.92139 × 1013
Range5.92139 × 1013
Interquartile range (IQR)31012450

Descriptive statistics

Standard deviation1.1395702 × 1013
Coefficient of variation (CV)5.1959276
Kurtosis27
Mean2.1931988 × 1012
Median Absolute Deviation (MAD)3182
Skewness5.1961524
Sum5.9216367 × 1013
Variance1.2986203 × 1026
MonotonicityNot monotonic
2023-12-10T22:58:07.117314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 8
29.6%
228 2
 
7.4%
305721 1
 
3.7%
59213900000000 1
 
3.7%
139603872 1
 
3.7%
531868032 1
 
3.7%
83415 1
 
3.7%
35612612 1
 
3.7%
3182 1
 
3.7%
2997 1
 
3.7%
Other values (9) 9
33.3%
ValueCountFrequency (%)
0 8
29.6%
21 1
 
3.7%
228 2
 
7.4%
532 1
 
3.7%
2997 1
 
3.7%
3182 1
 
3.7%
28665 1
 
3.7%
83415 1
 
3.7%
189888 1
 
3.7%
305721 1
 
3.7%
ValueCountFrequency (%)
59213900000000 1
3.7%
1201685380 1
3.7%
531868032 1
3.7%
313991648 1
3.7%
215257296 1
3.7%
139603872 1
3.7%
35612612 1
3.7%
26412288 1
3.7%
2306865 1
3.7%
305721 1
3.7%

평균덧글수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct25
Distinct (%)100.0%
Missing2
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean6203.0245
Minimum0
Maximum149519.48
Zeros1
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-10T22:58:07.334421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.7128
Q126.672
median111.269
Q3205.794
95-th percentile1156.8618
Maximum149519.48
Range149519.48
Interquartile range (IQR)179.122

Descriptive statistics

Standard deviation29859.409
Coefficient of variation (CV)4.8136855
Kurtosis24.993131
Mean6203.0245
Median Absolute Deviation (MAD)94.525
Skewness4.999012
Sum155075.61
Variance8.915843 × 108
MonotonicityNot monotonic
2023-12-10T22:58:07.552803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
140.813 1
 
3.7%
5.808 1
 
3.7%
773.345 1
 
3.7%
111.564 1
 
3.7%
45.846 1
 
3.7%
769.543 1
 
3.7%
59.682 1
 
3.7%
59.959 1
 
3.7%
9.065 1
 
3.7%
131.726 1
 
3.7%
Other values (15) 15
55.6%
(Missing) 2
 
7.4%
ValueCountFrequency (%)
0.0 1
3.7%
4.439 1
3.7%
5.808 1
3.7%
9.065 1
3.7%
12.443 1
3.7%
14.964 1
3.7%
26.672 1
3.7%
31.5 1
3.7%
45.846 1
3.7%
54.963 1
3.7%
ValueCountFrequency (%)
149519.48 1
3.7%
1240.5 1
3.7%
822.309 1
3.7%
773.345 1
3.7%
769.543 1
3.7%
535.061 1
3.7%
205.794 1
3.7%
200.274 1
3.7%
188.593 1
3.7%
140.813 1
3.7%

주당덧글수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5868.037
Minimum0
Maximum152176
Zeros4
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-10T22:58:07.779023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median77
Q3428
95-th percentile1317.7
Maximum152176
Range152176
Interquartile range (IQR)423

Descriptive statistics

Standard deviation29242.1
Coefficient of variation (CV)4.9832848
Kurtosis26.99107
Mean5868.037
Median Absolute Deviation (MAD)77
Skewness5.194914
Sum158437
Variance8.5510039 × 108
MonotonicityNot monotonic
2023-12-10T22:58:08.001230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 4
 
14.8%
5 2
 
7.4%
3 1
 
3.7%
152176 1
 
3.7%
2 1
 
3.7%
771 1
 
3.7%
298 1
 
3.7%
57 1
 
3.7%
615 1
 
3.7%
13 1
 
3.7%
Other values (13) 13
48.1%
ValueCountFrequency (%)
0 4
14.8%
2 1
 
3.7%
3 1
 
3.7%
5 2
7.4%
8 1
 
3.7%
13 1
 
3.7%
14 1
 
3.7%
20 1
 
3.7%
57 1
 
3.7%
77 1
 
3.7%
ValueCountFrequency (%)
152176 1
3.7%
1552 1
3.7%
771 1
3.7%
690 1
3.7%
615 1
3.7%
552 1
3.7%
434 1
3.7%
422 1
3.7%
311 1
3.7%
298 1
3.7%

상호작용지수전체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size348.0 B
0.0
23 
0.006
 
1
100.0
 
1
0.001
 
1
0.003
 
1

Length

Max length5
Median length3
Mean length3.2962963
Min length3

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st row0.0
2nd row0.0
3rd row0.006
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 23
85.2%
0.006 1
 
3.7%
100.0 1
 
3.7%
0.001 1
 
3.7%
0.003 1
 
3.7%

Length

2023-12-10T22:58:08.271754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:58:08.563153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 23
85.2%
0.006 1
 
3.7%
100.0 1
 
3.7%
0.001 1
 
3.7%
0.003 1
 
3.7%

상호작용지수1개월
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
0
26 
100
 
1

Length

Max length3
Median length1
Mean length1.0740741
Min length1

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26
96.3%
100 1
 
3.7%

Length

2023-12-10T22:58:08.779784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:58:08.957404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 26
96.3%
100 1
 
3.7%

상호작용지수3개월
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
0
26 
27
 
1

Length

Max length2
Median length1
Mean length1.037037
Min length1

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26
96.3%
27 1
 
3.7%

Length

2023-12-10T22:58:09.121537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:58:09.277930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 26
96.3%
27 1
 
3.7%

상호작용지수평균덧글수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct24
Distinct (%)96.0%
Missing2
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean4.14868
Minimum0
Maximum100
Zeros1
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-10T22:58:09.435071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0032
Q10.018
median0.074
Q30.138
95-th percentile0.774
Maximum100
Range100
Interquartile range (IQR)0.12

Descriptive statistics

Standard deviation19.970239
Coefficient of variation (CV)4.8136368
Kurtosis24.993127
Mean4.14868
Median Absolute Deviation (MAD)0.064
Skewness4.9990116
Sum103.717
Variance398.81044
MonotonicityNot monotonic
2023-12-10T22:58:09.626986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.04 2
 
7.4%
100.0 1
 
3.7%
0.004 1
 
3.7%
0.517 1
 
3.7%
0.075 1
 
3.7%
0.031 1
 
3.7%
0.515 1
 
3.7%
0.006 1
 
3.7%
0.088 1
 
3.7%
0.003 1
 
3.7%
Other values (14) 14
51.9%
(Missing) 2
 
7.4%
ValueCountFrequency (%)
0.0 1
3.7%
0.003 1
3.7%
0.004 1
3.7%
0.006 1
3.7%
0.008 1
3.7%
0.01 1
3.7%
0.018 1
3.7%
0.021 1
3.7%
0.031 1
3.7%
0.037 1
3.7%
ValueCountFrequency (%)
100.0 1
3.7%
0.83 1
3.7%
0.55 1
3.7%
0.517 1
3.7%
0.515 1
3.7%
0.358 1
3.7%
0.138 1
3.7%
0.134 1
3.7%
0.126 1
3.7%
0.094 1
3.7%

상호작용지수주당덧글수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
0
24 
1
 
2
100
 
1

Length

Max length3
Median length1
Mean length1.0740741
Min length1

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24
88.9%
1 2
 
7.4%
100 1
 
3.7%

Length

2023-12-10T22:58:09.794734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:58:09.945289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24
88.9%
1 2
 
7.4%
100 1
 
3.7%

상호작용지수전체표준점수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
-0.03
25 
-0.02
 
1
50.45
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row-0.03
2nd row-0.03
3rd row-0.02
4th row-0.03
5th row-0.03

Common Values

ValueCountFrequency (%)
-0.03 25
92.6%
-0.02 1
 
3.7%
50.45 1
 
3.7%

Length

2023-12-10T22:58:10.095883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:58:10.241458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.03 25
92.6%
0.02 1
 
3.7%
50.45 1
 
3.7%

1개월표준점수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
-0.04
26 
47.51
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row-0.04
2nd row-0.04
3rd row-0.04
4th row-0.04
5th row-0.04

Common Values

ValueCountFrequency (%)
-0.04 26
96.3%
47.51 1
 
3.7%

Length

2023-12-10T22:58:10.439393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:58:10.569596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.04 26
96.3%
47.51 1
 
3.7%

3개월표준점수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
-0.03
26 
13.18
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row-0.03
2nd row-0.03
3rd row-0.03
4th row-0.03
5th row-0.03

Common Values

ValueCountFrequency (%)
-0.03 26
96.3%
13.18 1
 
3.7%

Length

2023-12-10T22:58:10.741403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:58:10.884480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.03 26
96.3%
13.18 1
 
3.7%

평균수표준점수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)44.0%
Missing2
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean1.6332
Minimum-0.1
Maximum41.61
Zeros0
Zeros (%)0.0%
Negative19
Negative (%)70.4%
Memory size375.0 B
2023-12-10T22:58:11.026748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.1
5-th percentile-0.1
Q1-0.09
median-0.07
Q3-0.04
95-th percentile0.226
Maximum41.61
Range41.71
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation8.3290084
Coefficient of variation (CV)5.0998092
Kurtosis24.993098
Mean1.6332
Median Absolute Deviation (MAD)0.02
Skewness4.9990074
Sum40.83
Variance69.372381
MonotonicityNot monotonic
2023-12-10T22:58:11.178588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
-0.09 5
18.5%
-0.08 4
14.8%
-0.1 3
11.1%
-0.04 3
11.1%
-0.06 2
 
7.4%
-0.07 2
 
7.4%
0.12 2
 
7.4%
0.05 1
 
3.7%
0.13 1
 
3.7%
0.25 1
 
3.7%
(Missing) 2
 
7.4%
ValueCountFrequency (%)
-0.1 3
11.1%
-0.09 5
18.5%
-0.08 4
14.8%
-0.07 2
 
7.4%
-0.06 2
 
7.4%
-0.04 3
11.1%
0.05 1
 
3.7%
0.12 2
 
7.4%
0.13 1
 
3.7%
0.25 1
 
3.7%
ValueCountFrequency (%)
41.61 1
 
3.7%
0.25 1
 
3.7%
0.13 1
 
3.7%
0.12 2
 
7.4%
0.05 1
 
3.7%
-0.04 3
11.1%
-0.06 2
 
7.4%
-0.07 2
 
7.4%
-0.08 4
14.8%
-0.09 5
18.5%

주당수표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2174074
Minimum-0.14
Maximum35.02
Zeros0
Zeros (%)0.0%
Negative22
Negative (%)81.5%
Memory size375.0 B
2023-12-10T22:58:11.347514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.14
5-th percentile-0.14
Q1-0.14
median-0.12
Q3-0.04
95-th percentile0.166
Maximum35.02
Range35.16
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation6.7560182
Coefficient of variation (CV)5.5495129
Kurtosis26.991012
Mean1.2174074
Median Absolute Deviation (MAD)0.02
Skewness5.1949059
Sum32.87
Variance45.643781
MonotonicityNot monotonic
2023-12-10T22:58:11.508782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
-0.14 9
33.3%
-0.13 3
 
11.1%
-0.12 3
 
11.1%
-0.04 2
 
7.4%
-0.07 2
 
7.4%
0.22 1
 
3.7%
-0.11 1
 
3.7%
-0.01 1
 
3.7%
35.02 1
 
3.7%
0.02 1
 
3.7%
Other values (3) 3
 
11.1%
ValueCountFrequency (%)
-0.14 9
33.3%
-0.13 3
 
11.1%
-0.12 3
 
11.1%
-0.11 1
 
3.7%
-0.09 1
 
3.7%
-0.07 2
 
7.4%
-0.04 2
 
7.4%
-0.01 1
 
3.7%
0.01 1
 
3.7%
0.02 1
 
3.7%
ValueCountFrequency (%)
35.02 1
3.7%
0.22 1
3.7%
0.04 1
3.7%
0.02 1
3.7%
0.01 1
3.7%
-0.01 1
3.7%
-0.04 2
7.4%
-0.07 2
7.4%
-0.09 1
3.7%
-0.11 1
3.7%

Interactions

2023-12-10T22:57:58.758429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:49.272260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:50.636480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:51.858394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:53.716331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:55.072348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:56.338146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:57.644789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:58.928361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:49.482843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:50.787559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:52.032190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:53.868246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:55.256054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:56.611276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:57.795566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:59.087015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:49.636616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:50.944922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:52.212220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:54.028661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:55.430628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:56.755265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:57.936379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:59.280468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:49.801110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:51.104432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:52.430134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:54.186611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:55.569937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:56.915160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:58.077355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:59.419709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:50.025997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:51.253267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:52.695220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:54.364573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:55.741564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:57.070395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:58.229539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:59.657274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:50.174979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:51.403284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:53.252871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:54.563290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:55.910752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:57.224137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:58.372038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:59.844058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:50.324932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:51.539911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:53.389198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:54.745356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:56.045255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:57.353542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:58.502715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:59.973944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:50.476552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:51.689652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:53.526497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:54.899865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:56.182667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:57.488300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:58.613254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:58:11.687854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호작용지수채널ID상호작용지수채널명상호작용지수채널설명상호작용지수채널생성일자지수전체지수1개월지수3개월평균덧글수주당덧글수상호작용지수전체상호작용지수1개월상호작용지수3개월상호작용지수평균덧글수상호작용지수주당덧글수상호작용지수전체표준점수1개월표준점수3개월표준점수평균수표준점수주당수표준점수
상호작용지수채널ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상호작용지수채널명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상호작용지수채널설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상호작용지수채널생성일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지수전체1.0001.0001.0001.0001.0000.6480.6480.6430.6481.0000.6480.6480.6431.0001.0000.6480.6480.6430.648
지수1개월1.0001.0001.0001.0000.6481.0000.6480.6430.6481.0000.6480.6480.6431.0001.0000.6480.6480.6430.648
지수3개월1.0001.0001.0001.0000.6480.6481.0000.6430.6481.0000.6480.6480.6431.0001.0000.6480.6480.6430.648
평균덧글수1.0001.0001.0001.0000.6430.6430.6431.0000.6431.0000.6430.6430.6431.0001.0000.6430.6430.6430.643
주당덧글수1.0001.0001.0001.0000.6480.6480.6480.6431.0001.0000.6480.6480.6431.0001.0000.6480.6480.6430.648
상호작용지수전체1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상호작용지수1개월1.0001.0001.0001.0000.6480.6480.6480.6430.6481.0001.0000.6480.6431.0001.0000.6480.6480.6430.648
상호작용지수3개월1.0001.0001.0001.0000.6480.6480.6480.6430.6481.0000.6481.0000.6431.0001.0000.6480.6480.6430.648
상호작용지수평균덧글수1.0001.0001.0001.0000.6430.6430.6430.6430.6431.0000.6430.6431.0001.0001.0000.6430.6430.6430.643
상호작용지수주당덧글수1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9851.0001.0001.0001.000
상호작용지수전체표준점수1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9851.0001.0001.0001.0001.000
1개월표준점수1.0001.0001.0001.0000.6480.6480.6480.6430.6481.0000.6480.6480.6431.0001.0001.0000.6480.6430.648
3개월표준점수1.0001.0001.0001.0000.6480.6480.6480.6430.6481.0000.6480.6480.6431.0001.0000.6481.0000.6430.648
평균수표준점수1.0001.0001.0001.0000.6430.6430.6430.6430.6431.0000.6430.6430.6431.0001.0000.6430.6431.0000.643
주당수표준점수1.0001.0001.0001.0000.6480.6480.6480.6430.6481.0000.6480.6480.6431.0001.0000.6480.6480.6431.000
2023-12-10T22:58:11.979146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호작용지수전체표준점수3개월표준점수상호작용지수주당덧글수상호작용지수3개월1개월표준점수상호작용지수1개월상호작용지수전체
상호작용지수전체표준점수1.0000.9800.8480.9800.9800.9800.957
3개월표준점수0.9801.0000.9800.4480.4480.4480.938
상호작용지수주당덧글수0.8480.9801.0000.9800.9800.9800.957
상호작용지수3개월0.9800.4480.9801.0000.4480.4480.938
1개월표준점수0.9800.4480.9800.4481.0000.4480.938
상호작용지수1개월0.9800.4480.9800.4480.4481.0000.938
상호작용지수전체0.9570.9380.9570.9380.9380.9381.000
2023-12-10T22:58:12.192877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지수전체지수1개월지수3개월평균덧글수주당덧글수상호작용지수평균덧글수평균수표준점수주당수표준점수상호작용지수전체상호작용지수1개월상호작용지수3개월상호작용지수주당덧글수상호작용지수전체표준점수1개월표준점수3개월표준점수
지수전체1.0000.6260.6150.8600.9770.8580.8590.9650.9380.4480.4480.9800.9800.4480.448
지수1개월0.6261.0000.9240.5040.5830.5070.4780.5820.9380.4480.4480.9800.9800.4480.448
지수3개월0.6150.9241.0000.4820.5700.4850.4720.5480.9380.4480.4480.9800.9800.4480.448
평균덧글수0.8600.5040.4821.0000.8871.0000.9920.9000.9330.4430.4430.9780.9780.4430.443
주당덧글수0.9770.5830.5700.8871.0000.8840.8940.9820.9380.4480.4480.9800.9800.4480.448
상호작용지수평균덧글수0.8580.5070.4851.0000.8841.0000.9920.8980.9330.4430.4430.9780.9780.4430.443
평균수표준점수0.8590.4780.4720.9920.8940.9921.0000.9010.9330.4430.4430.9780.9780.4430.443
주당수표준점수0.9650.5820.5480.9000.9820.8980.9011.0000.9380.4480.4480.9800.9800.4480.448
상호작용지수전체0.9380.9380.9380.9330.9380.9330.9330.9381.0000.9380.9380.9570.9570.9380.938
상호작용지수1개월0.4480.4480.4480.4430.4480.4430.4430.4480.9381.0000.4480.9800.9800.4480.448
상호작용지수3개월0.4480.4480.4480.4430.4480.4430.4430.4480.9380.4481.0000.9800.9800.4480.448
상호작용지수주당덧글수0.9800.9800.9800.9780.9800.9780.9780.9800.9570.9800.9801.0000.8480.9800.980
상호작용지수전체표준점수0.9800.9800.9800.9780.9800.9780.9780.9800.9570.9800.9800.8481.0000.9800.980
1개월표준점수0.4480.4480.4480.4430.4480.4430.4430.4480.9380.4480.4480.9800.9801.0000.448
3개월표준점수0.4480.4480.4480.4430.4480.4430.4430.4480.9380.4480.4480.9800.9800.4481.000

Missing values

2023-12-10T22:58:00.220241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:58:00.771757image/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.
2023-12-10T22:58:01.469311image/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

상호작용지수채널ID상호작용지수채널명상호작용지수수집일자상호작용지수채널설명상호작용지수채널생성일자지수전체지수1개월지수3개월평균덧글수주당덧글수상호작용지수전체상호작용지수1개월상호작용지수3개월상호작용지수평균덧글수상호작용지수주당덧글수상호작용지수전체표준점수1개월표준점수3개월표준점수평균수표준점수주당수표준점수
0UC-gWrEGYpG2jYfl8A_KIGnQ[KERI]한국전기연구원2021-10-31전기전문 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_keri2012-03-077057589030572114.96430.0000.010-0.03-0.04-0.03-0.09-0.14
1UC-JZtfVAgIjmNfhapEV3zgg차차튜브 Chacha Tube2021-10-31Emailchadahye@gmail.com Insta cha.dahye2015-10-232551297200140.813140.0000.0940-0.03-0.04-0.03-0.06-0.13
2UC0ZqpSq-OIpOITZ7U16-Xeg유디티TV2021-10-31<NA><NA>4770270500000947974081201685380535.06115520.006000.3581-0.02-0.04-0.030.050.22
3UC0ru5w57PyGpbsEKwN4LuwA재민정2021-10-31<NA>2013-05-130000.000.0000.00-0.03-0.04-0.03-0.1-0.14
4UC12BY9i1Lurqcvt-IZOpVvwyoloria욜로리아2021-10-31만원으로일주일반찬만들기; 간단요리; 맛있는다이어트레시피2013-01-0516490277900596402306865111.269770.0000.0740-0.03-0.04-0.03-0.07-0.12
5UC1AlGbEktTiXzBdLx9vkBoQ경기관광2021-10-31#경기관광공사 공식 유튜브 채널입니다 Gyeonggi Tourism Organization's official youtube channel 어제의 기억과 내일의 희망이 함께 공존하는 곳; 사랑도 여행도 #경기도 소중해진 하루엔 경기도 #경기관광 #ㄱㄱㄱㄱ #ㄲㄲ #ㅋㅋ<NA>2378188806044418988826.672200.0000.0180-0.03-0.04-0.03-0.09-0.13
6UC1UtimqTCgBv2to4togsqAACaptain Peter ∨ 캡틴피터2021-10-31캡틴피터 Captain Peter vashtebah@gmail.com2015-08-1332333030400532188.5931130.0000.1260-0.03-0.04-0.03-0.04-0.11
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8UC0LJ-IvV4jNxbXm_KO9bDvQ광주맛집2021-10-31요리할 줄 아는 놈이 맛을 안다~ 광주 토박이가 리뷰 해주는 리얼 광주맛집!!2019-02-0319808551822812.44380.0000.0080-0.03-0.04-0.03-0.09-0.14
9UC270ueFEsQ21S26TYI_9yVA야신야덕2021-10-31야구 유튜브 채널! 야구 유튜버 빡코가 야구와 다양한 스포츠를 함께 다루고 있습니다:) 여러분 기상천외한 아이디어와 창의력으로 스포츠를 즐겨봅시다! 구독부탁드려요~~:) #스포츠 #운동 #야구2018-06-276097468600022284604215257296200.2745520.0000.1340-0.03-0.04-0.03-0.04-0.01
상호작용지수채널ID상호작용지수채널명상호작용지수수집일자상호작용지수채널설명상호작용지수채널생성일자지수전체지수1개월지수3개월평균덧글수주당덧글수상호작용지수전체상호작용지수1개월상호작용지수3개월상호작용지수평균덧글수상호작용지수주당덧글수상호작용지수전체표준점수1개월표준점수3개월표준점수평균수표준점수주당수표준점수
17UC4VljnooZZkRhhb5s5rv1Mw[Flower pig]꽃돼지2021-10-31스폰문의 fbrur1234@naver.com 카카오톡:8992tt 꽃님들 항상 감사합니다2017-03-2624961315600000131.7266900.0000.0880-0.03-0.04-0.03-0.060.02
18UC4sxrralTvPl0ZogQ5iKVxw로젠젠_세계여행일지2021-10-31안녕하세요~! 여행의 모든 순간을 기록해서 저만의 감성으로 보여주고싶은 로젠젠이라고 합니다. 아이슬란드;페루;볼리비아; 남미여행 호주여행 등등! 제 여행을 함께 즐겨주세요!2018-11-11135551602289.06550.0000.0060-0.03-0.04-0.03-0.09-0.14
19UC4vD5JpdxZRPy1bpRAdjhSA조랭몬 YouTube2021-10-31유튜버&스트리머 조랭몬의 공식 유튜브채널이지롱 이메일 raengmon@naver.com 트위치TV https:www.twitch.tvraengmon 유튜브 https:goo.gler9JGv 트위터 http:goo.gly4Huqo 네이버블로그 goo.glkHZNCb 네이버팬카페 랭떡방♥ http:cafe.naver.comraengmon2015-01-10278247404000059.9592110.0000.040-0.03-0.04-0.03-0.08-0.09
20UC5FL8a5KYrW51zhm4YdSAAg인간적인생활2021-10-31주로 합성 소스들로 MAD를 만들거나 게임 애니메이션 등을 업로드하는 인간적인생활이라고 합니다*^^*2012-06-28225291696560318259.682130.0000.040-0.03-0.04-0.03-0.08-0.13
21UC5Ce1XGat0JJOXcFWZl1jcg달마발 Darlim&Hamabal2021-10-31Welcome; We are Darlim Kim & Hamabal Fan Email : kdl_hmb@naver.com Business Email :kdl_hmb@sandboxnetwork.net<NA>242913952000183793535612612769.5436150.0000.5150-0.03-0.04-0.030.120.01
22UC1aaTtgKSF9QtkcwKhTmS6A루코 ruko2021-10-31<NA><NA>40829744055378341545.846570.0000.0310-0.03-0.04-0.03-0.08-0.12
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24UC5xK2Xdrud3-KGjkS1Igumgssin 씬님2021-10-31안녕하세요 뷰티크리에이터 씬님입니다. 새로운 메이크업 영상이 보고싶다면 구독버튼 눌러주세요! Hi guys this is SSIN. Subscribe to my channel and watch more funny makeup tutorials!<NA>24722640700006439297139603872773.3457710.003000.5171-0.03-0.04-0.030.120.04
25UC60Z87qoAFcpZME6mPGpIFQ다정다감2021-10-31안녕하세요! 다정다감이에요 영상은 매주 일요일에 업로드 됩니다! . . Instagram(인스타그램) : dajeong_423_ E-mail(이메일) : dajeong8205@naver.com2018-12-18000<NA>00.000<NA>0-0.03-0.04-0.03<NA>-0.14
26UC6EQCTpOEFF5Hh6DmkBzRUg선택을 쉽게 해주는 라똘2021-10-31먹방; 여행 ; 음악 ; 리뷰 ; 상담 여러가지 종합적으로 하는 말그대로 라이브 똘아이 방송<NA>739900005.80820.0000.0040-0.03-0.04-0.03-0.1-0.14