Overview

Dataset statistics

Number of variables20
Number of observations25
Missing cells17
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory180.3 B

Variable types

Text3
Categorical8
DateTime1
Numeric8

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/0614b5f8-81be-4113-a157-77369d9d5e05

Alerts

상호작용지수수집일자 has constant value ""Constant
상호작용지수1개월 has constant value ""Constant
상호작용지수3개월 has constant value ""Constant
1개월표준점수 has constant value ""Constant
3개월표준점수 has constant value ""Constant
상호작용지수전체표준점수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
상호작용지수주당덧글수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
상호작용지수전체 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
지수전체 is highly overall correlated with 지수1개월 and 9 other fieldsHigh correlation
지수1개월 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
지수3개월 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
평균덧글수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
주당덧글수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
상호작용지수평균덧글수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
평균수표준점수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
주당수표준점수 is highly overall correlated with 지수전체 and 9 other fieldsHigh correlation
상호작용지수전체 is highly imbalanced (56.3%)Imbalance
상호작용지수주당덧글수 is highly imbalanced (56.3%)Imbalance
상호작용지수전체표준점수 is highly imbalanced (75.8%)Imbalance
상호작용지수채널설명 has 6 (24.0%) missing valuesMissing
상호작용지수채널생성일자 has 11 (44.0%) missing valuesMissing
상호작용지수채널ID has unique valuesUnique
상호작용지수채널명 has unique valuesUnique
지수전체 has unique valuesUnique
평균덧글수 has unique valuesUnique
지수전체 has 1 (4.0%) zerosZeros
지수1개월 has 7 (28.0%) zerosZeros
지수3개월 has 6 (24.0%) zerosZeros
평균덧글수 has 1 (4.0%) zerosZeros
주당덧글수 has 2 (8.0%) zerosZeros
상호작용지수평균덧글수 has 3 (12.0%) zerosZeros
평균수표준점수 has 1 (4.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:14:05.355196
Analysis finished2023-12-10 14:14:19.469176
Duration14.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호작용지수채널ID
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-10T23:14:19.778671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters600
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

Unique25 ?
Unique (%)100.0%

Sample

1st rowUC-rL1o4m5UamXY7lzGw8P8Q
2nd rowUC0yvvSJLpQLPU6u6-ZaBXvg
3rd rowUC256C9U-lYhr5-Or7vvCrvQ
4th rowUC271vX3c3kYZsgpz7-zPBoA
5th rowUC28lbdOHnj-leok6tHIx7ew
ValueCountFrequency (%)
uc-rl1o4m5uamxy7lzgw8p8q 1
 
4.0%
uc4ykkrchq1i2sspyoq6nt5w 1
 
4.0%
uca_sh8tajjakrdwflkn3fdq 1
 
4.0%
uc9a4spvt4xln98emusd40eg 1
 
4.0%
uc9t8wl0quwhpcksv73j5dqa 1
 
4.0%
uc9sz7d8ytd4c_zwugconm7a 1
 
4.0%
uc91lhnn7zz6gm-br-gzwj0a 1
 
4.0%
uc7bqxkhltafctwwwhuzoouq 1
 
4.0%
uc7ydpatpeb2tuxmupcxirsw 1
 
4.0%
uc7wmb_czx5jf__5kqt4d9ww 1
 
4.0%
Other values (15) 15
60.0%
2023-12-10T23:14:20.436096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 34
 
5.7%
U 32
 
5.3%
A 17
 
2.8%
7 16
 
2.7%
k 15
 
2.5%
8 15
 
2.5%
g 14
 
2.3%
9 14
 
2.3%
4 13
 
2.2%
M 12
 
2.0%
Other values (54) 418
69.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 268
44.7%
Lowercase Letter 204
34.0%
Decimal Number 111
18.5%
Dash Punctuation 9
 
1.5%
Connector Punctuation 8
 
1.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 34
 
12.7%
U 32
 
11.9%
A 17
 
6.3%
M 12
 
4.5%
Q 12
 
4.5%
W 10
 
3.7%
Z 10
 
3.7%
R 10
 
3.7%
D 10
 
3.7%
L 10
 
3.7%
Other values (16) 111
41.4%
Lowercase Letter
ValueCountFrequency (%)
k 15
 
7.4%
g 14
 
6.9%
w 12
 
5.9%
v 12
 
5.9%
t 11
 
5.4%
o 11
 
5.4%
y 10
 
4.9%
j 10
 
4.9%
z 10
 
4.9%
a 9
 
4.4%
Other values (16) 90
44.1%
Decimal Number
ValueCountFrequency (%)
7 16
14.4%
8 15
13.5%
9 14
12.6%
4 13
11.7%
5 11
9.9%
2 10
9.0%
6 9
8.1%
3 9
8.1%
0 8
7.2%
1 6
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 472
78.7%
Common 128
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 34
 
7.2%
U 32
 
6.8%
A 17
 
3.6%
k 15
 
3.2%
g 14
 
3.0%
M 12
 
2.5%
Q 12
 
2.5%
w 12
 
2.5%
v 12
 
2.5%
t 11
 
2.3%
Other values (42) 301
63.8%
Common
ValueCountFrequency (%)
7 16
12.5%
8 15
11.7%
9 14
10.9%
4 13
10.2%
5 11
8.6%
2 10
7.8%
- 9
7.0%
6 9
7.0%
3 9
7.0%
0 8
6.2%
Other values (2) 14
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 34
 
5.7%
U 32
 
5.3%
A 17
 
2.8%
7 16
 
2.7%
k 15
 
2.5%
8 15
 
2.5%
g 14
 
2.3%
9 14
 
2.3%
4 13
 
2.2%
M 12
 
2.0%
Other values (54) 418
69.7%

상호작용지수채널명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-10T23:14:20.826560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length13
Mean length10.84
Min length2

Characters and Unicode

Total characters271
Distinct characters134
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

Unique25 ?
Unique (%)100.0%

Sample

1st row찌워니의 삶
2nd row부산여성가족개발원
3rd rowThat Korean Girl 돌돌콩
4th rowKBS Entertain: 깔깔티비
5th row고양이와 소소한생활
ValueCountFrequency (%)
찌워니의 1
 
2.0%
로하이 1
 
2.0%
청소년방송 1
 
2.0%
권민제 1
 
2.0%
minje 1
 
2.0%
kwon 1
 
2.0%
하모진주_진주시공식유튜브 1
 
2.0%
핫도그tv 1
 
2.0%
한국여행추천tv 1
 
2.0%
대한민국청와대 1
 
2.0%
Other values (39) 39
79.6%
2023-12-10T23:14:21.459486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
8.9%
e 8
 
3.0%
T 8
 
3.0%
o 6
 
2.2%
t 6
 
2.2%
n 6
 
2.2%
E 5
 
1.8%
주 4
 
1.5%
a 4
 
1.5%
i 4
 
1.5%
Other values (124) 196
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
51.3%
Lowercase Letter 56
20.7%
Uppercase Letter 45
 
16.6%
Space Separator 24
 
8.9%
Decimal Number 4
 
1.5%
Connector Punctuation 1
 
0.4%
Other Punctuation 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 4
 
2.9%
구 3
 
2.2%
소 3
 
2.2%
울 3
 
2.2%
국 3
 
2.2%
방 3
 
2.2%
한 3
 
2.2%
청 3
 
2.2%
원 3
 
2.2%
산 3
 
2.2%
Other values (80) 108
77.7%
Uppercase Letter
ValueCountFrequency (%)
T 8
17.8%
E 5
11.1%
V 3
 
6.7%
O 3
 
6.7%
N 3
 
6.7%
K 3
 
6.7%
W 2
 
4.4%
A 2
 
4.4%
M 2
 
4.4%
J 2
 
4.4%
Other values (9) 12
26.7%
Lowercase Letter
ValueCountFrequency (%)
e 8
14.3%
o 6
10.7%
t 6
10.7%
n 6
10.7%
a 4
 
7.1%
i 4
 
7.1%
l 3
 
5.4%
r 3
 
5.4%
h 3
 
5.4%
k 2
 
3.6%
Other values (8) 11
19.6%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
4 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
51.3%
Latin 101
37.3%
Common 31
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 4
 
2.9%
구 3
 
2.2%
소 3
 
2.2%
울 3
 
2.2%
국 3
 
2.2%
방 3
 
2.2%
한 3
 
2.2%
청 3
 
2.2%
원 3
 
2.2%
산 3
 
2.2%
Other values (80) 108
77.7%
Latin
ValueCountFrequency (%)
e 8
 
7.9%
T 8
 
7.9%
o 6
 
5.9%
t 6
 
5.9%
n 6
 
5.9%
E 5
 
5.0%
a 4
 
4.0%
i 4
 
4.0%
l 3
 
3.0%
r 3
 
3.0%
Other values (27) 48
47.5%
Common
ValueCountFrequency (%)
24
77.4%
0 2
 
6.5%
4 1
 
3.2%
1 1
 
3.2%
_ 1
 
3.2%
: 1
 
3.2%
- 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
51.3%
ASCII 132
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
18.2%
e 8
 
6.1%
T 8
 
6.1%
o 6
 
4.5%
t 6
 
4.5%
n 6
 
4.5%
E 5
 
3.8%
a 4
 
3.0%
i 4
 
3.0%
l 3
 
2.3%
Other values (34) 58
43.9%
Hangul
ValueCountFrequency (%)
주 4
 
2.9%
구 3
 
2.2%
소 3
 
2.2%
울 3
 
2.2%
국 3
 
2.2%
방 3
 
2.2%
한 3
 
2.2%
청 3
 
2.2%
원 3
 
2.2%
산 3
 
2.2%
Other values (80) 108
77.7%

상호작용지수수집일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2021-05-31
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-31
2nd row2021-05-31
3rd row2021-05-31
4th row2021-05-31
5th row2021-05-31

Common Values

ValueCountFrequency (%)
2021-05-31 25
100.0%

Length

2023-12-10T23:14:21.642602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:21.772952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-31 25
100.0%

상호작용지수채널설명
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing6
Missing (%)24.0%
Memory size332.0 B
2023-12-10T23:14:22.127959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length578
Median length73
Mean length144.52632
Min length17

Characters and Unicode

Total characters2746
Distinct characters407
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row광고문의 (콜라보문의 가능) jiwonbj@naver.com 페이스북 찌워니 인스타그램 jiwonbj
2nd rowKBS 전설적 레전드 예능프로그램이 모두 여기! 슈퍼스타 리즈시절 대공개 #깔깔티비 #깔깔 #원조 레전드 예능 1박2일 #전설아닌레전드 공포의쿵쿵따 유재석 강호동 #물대포맛집 위험한초대 이효리 하지원 김태희 #대환장시트콤 골든빌리지 금촌댁네사람들 이영자 #코인노래방아니고 쟁반노래방 유재석 이효리 #올드 미스 다이어리 #1박2일 정주행 #1박2일 레전드 #해피투게더 시즌3 #웃지마 사우나 #청춘불패 시즌1; 시즌 2 #스타 히~~스토리 #레전드순삭
3rd 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~^^
4th row종합 게임 영상 채널입니다. Gameplay
5th row매번 재밌는 유머 콘텐츠로 웃음을 드리는 조재원이 되겠습니다! 앞으로 조재원의 신규 콘텐츠 많이 기대해주세요! 광고 및 비즈니스 문의 메일 : jojaewon@sandbox.co.kr 페이스북 : https:www.facebook.comjomansae 인스타그램 : https:m.instagram.comjojaewon0703 틱톡 : https:t.tiktok.comi18nshareuser6537453671877623810 无法阻止的兄妹 시나 웨이보 : https:weibo.com6471416204 도우인 : 无法阻止的兄妹
ValueCountFrequency (%)
14
 
3.0%
채널 5
 
1.1%
유튜브 5
 
1.1%
꼭 4
 
0.8%
공식 4
 
0.8%
1박2일 3
 
0.6%
있습니다 3
 
0.6%
많이 3
 
0.6%
and 3
 
0.6%
the 3
 
0.6%
Other values (389) 427
90.1%
2023-12-10T23:14:22.820714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
502
 
18.3%
o 86
 
3.1%
e 71
 
2.6%
. 59
 
2.1%
t 57
 
2.1%
a 53
 
1.9%
i 49
 
1.8%
n 49
 
1.8%
r 48
 
1.7%
s 36
 
1.3%
Other values (397) 1736
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1193
43.4%
Lowercase Letter 728
26.5%
Space Separator 502
18.3%
Other Punctuation 147
 
5.4%
Decimal Number 101
 
3.7%
Uppercase Letter 53
 
1.9%
Modifier Symbol 4
 
0.1%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Math Symbol 4
 
0.1%
Other values (2) 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 35
 
2.9%
다 33
 
2.8%
니 32
 
2.7%
고 24
 
2.0%
한 23
 
1.9%
는 22
 
1.8%
의 19
 
1.6%
하 18
 
1.5%
로 17
 
1.4%
주 16
 
1.3%
Other values (322) 954
80.0%
Lowercase Letter
ValueCountFrequency (%)
o 86
 
11.8%
e 71
 
9.8%
t 57
 
7.8%
a 53
 
7.3%
i 49
 
6.7%
n 49
 
6.7%
r 48
 
6.6%
s 36
 
4.9%
m 36
 
4.9%
c 27
 
3.7%
Other values (15) 216
29.7%
Uppercase Letter
ValueCountFrequency (%)
T 9
17.0%
I 5
 
9.4%
V 5
 
9.4%
B 3
 
5.7%
C 3
 
5.7%
K 3
 
5.7%
M 2
 
3.8%
D 2
 
3.8%
W 2
 
3.8%
Y 2
 
3.8%
Other values (10) 17
32.1%
Other Punctuation
ValueCountFrequency (%)
. 59
40.1%
; 22
 
15.0%
: 20
 
13.6%
# 15
 
10.2%
' 10
 
6.8%
! 9
 
6.1%
@ 8
 
5.4%
& 2
 
1.4%
* 1
 
0.7%
。 1
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 19
18.8%
7 13
12.9%
3 12
11.9%
2 10
9.9%
8 10
9.9%
0 10
9.9%
5 9
8.9%
6 7
 
6.9%
9 7
 
6.9%
4 4
 
4.0%
Close Punctuation
ValueCountFrequency (%)
) 3
75.0%
] 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 3
75.0%
[ 1
 
25.0%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
502
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1173
42.7%
Latin 781
28.4%
Common 772
28.1%
Han 20
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 35
 
3.0%
다 33
 
2.8%
니 32
 
2.7%
고 24
 
2.0%
한 23
 
2.0%
는 22
 
1.9%
의 19
 
1.6%
하 18
 
1.5%
로 17
 
1.4%
주 16
 
1.4%
Other values (309) 934
79.6%
Latin
ValueCountFrequency (%)
o 86
 
11.0%
e 71
 
9.1%
t 57
 
7.3%
a 53
 
6.8%
i 49
 
6.3%
n 49
 
6.3%
r 48
 
6.1%
s 36
 
4.6%
m 36
 
4.6%
c 27
 
3.5%
Other values (35) 269
34.4%
Common
ValueCountFrequency (%)
502
65.0%
. 59
 
7.6%
; 22
 
2.8%
: 20
 
2.6%
1 19
 
2.5%
# 15
 
1.9%
7 13
 
1.7%
3 12
 
1.6%
2 10
 
1.3%
' 10
 
1.3%
Other values (20) 90
 
11.7%
Han
ValueCountFrequency (%)
妹 2
10.0%
兄 2
10.0%
的 2
10.0%
止 2
10.0%
阻 2
10.0%
法 2
10.0%
无 2
10.0%
國 1
 
5.0%
韓 1
 
5.0%
到 1
 
5.0%
Other values (3) 3
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1552
56.5%
Hangul 1171
42.6%
CJK 20
 
0.7%
Compat Jamo 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
502
32.3%
o 86
 
5.5%
e 71
 
4.6%
. 59
 
3.8%
t 57
 
3.7%
a 53
 
3.4%
i 49
 
3.2%
n 49
 
3.2%
r 48
 
3.1%
s 36
 
2.3%
Other values (64) 542
34.9%
Hangul
ValueCountFrequency (%)
이 35
 
3.0%
다 33
 
2.8%
니 32
 
2.7%
고 24
 
2.0%
한 23
 
2.0%
는 22
 
1.9%
의 19
 
1.6%
하 18
 
1.5%
로 17
 
1.5%
주 16
 
1.4%
Other values (307) 932
79.6%
CJK
ValueCountFrequency (%)
妹 2
10.0%
兄 2
10.0%
的 2
10.0%
止 2
10.0%
阻 2
10.0%
法 2
10.0%
无 2
10.0%
國 1
 
5.0%
韓 1
 
5.0%
到 1
 
5.0%
Other values (3) 3
15.0%
None
ValueCountFrequency (%)
。 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅅ 1
50.0%
ㅏ 1
50.0%

상호작용지수채널생성일자
Date

MISSING 

Distinct14
Distinct (%)100.0%
Missing11
Missing (%)44.0%
Memory size332.0 B
Minimum2011-04-07 00:00:00
Maximum2019-04-04 00:00:00
2023-12-10T23:14:23.030057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:23.239354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

지수전체
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3893842 × 1011
Minimum0
Maximum6.0340395 × 1012
Zeros1
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:14:23.527369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9856
Q13579129
median9.7410515 × 108
Q32.6787017 × 1010
95-th percentile1.9444261 × 1012
Maximum6.0340395 × 1012
Range6.0340395 × 1012
Interquartile range (IQR)2.6783438 × 1010

Descriptive statistics

Standard deviation1.287339 × 1012
Coefficient of variation (CV)2.9328465
Kurtosis15.894053
Mean4.3893842 × 1011
Median Absolute Deviation (MAD)9.7410506 × 108
Skewness3.8267255
Sum1.0973461 × 1013
Variance1.6572418 × 1024
MonotonicityNot monotonic
2023-12-10T23:14:23.770212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
16812059600 1
 
4.0%
0 1
 
4.0%
45201068000 1
 
4.0%
299442 1
 
4.0%
59343544 1
 
4.0%
931334590 1
 
4.0%
88 1
 
4.0%
48928 1
 
4.0%
666105 1
 
4.0%
3579129 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
0 1
4.0%
88 1
4.0%
48928 1
4.0%
299442 1
4.0%
666105 1
4.0%
950820 1
4.0%
3579129 1
4.0%
15025855 1
4.0%
31267264 1
4.0%
44736384 1
4.0%
ValueCountFrequency (%)
6034039500000 1
4.0%
1950264460000 1
4.0%
1921072500000 1
4.0%
816496570000 1
4.0%
128426140000 1
4.0%
45201068000 1
4.0%
26787016700 1
4.0%
23679629300 1
4.0%
16812059600 1
4.0%
3625930750 1
4.0%

지수1개월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.225173 × 108
Minimum0
Maximum1.8679876 × 109
Zeros7
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:14:24.008008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4653
Q3456960
95-th percentile8.5629921 × 108
Maximum1.8679876 × 109
Range1.8679876 × 109
Interquartile range (IQR)456960

Descriptive statistics

Standard deviation4.1984906 × 108
Coefficient of variation (CV)3.4268554
Kurtosis13.876009
Mean1.225173 × 108
Median Absolute Deviation (MAD)4653
Skewness3.7248041
Sum3.0629325 × 109
Variance1.7627324 × 1017
MonotonicityNot monotonic
2023-12-10T23:14:24.244656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 7
28.0%
4475 1
 
4.0%
20 1
 
4.0%
4653 1
 
4.0%
1311 1
 
4.0%
247 1
 
4.0%
1867987580 1
 
4.0%
1053470340 1
 
4.0%
162105 1
 
4.0%
14728 1
 
4.0%
Other values (9) 9
36.0%
ValueCountFrequency (%)
0 7
28.0%
20 1
 
4.0%
247 1
 
4.0%
1311 1
 
4.0%
1870 1
 
4.0%
4475 1
 
4.0%
4653 1
 
4.0%
13150 1
 
4.0%
14728 1
 
4.0%
25970 1
 
4.0%
ValueCountFrequency (%)
1867987580 1
4.0%
1053470340 1
4.0%
67614704 1
4.0%
35112112 1
4.0%
26793030 1
4.0%
10941788 1
4.0%
456960 1
4.0%
327435 1
4.0%
162105 1
4.0%
25970 1
4.0%

지수3개월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1442365 × 108
Minimum0
Maximum9.2599316 × 109
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:14:24.446080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12832
median230384
Q33663240
95-th percentile4.3280747 × 109
Maximum9.2599316 × 109
Range9.2599316 × 109
Interquartile range (IQR)3660408

Descriptive statistics

Standard deviation2.0667891 × 109
Coefficient of variation (CV)2.8929461
Kurtosis13.192539
Mean7.1442365 × 108
Median Absolute Deviation (MAD)230384
Skewness3.5627837
Sum1.7860591 × 1010
Variance4.2716174 × 1018
MonotonicityNot monotonic
2023-12-10T23:14:25.018720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 6
24.0%
56260 1
 
4.0%
605085 1
 
4.0%
2832 1
 
4.0%
230384 1
 
4.0%
34760 1
 
4.0%
11264 1
 
4.0%
9259931600 1
 
4.0%
11256 1
 
4.0%
4951079400 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0 6
24.0%
2832 1
 
4.0%
9262 1
 
4.0%
11256 1
 
4.0%
11264 1
 
4.0%
34760 1
 
4.0%
56260 1
 
4.0%
230384 1
 
4.0%
318364 1
 
4.0%
605085 1
 
4.0%
ValueCountFrequency (%)
9259931600 1
4.0%
4951079400 1
4.0%
1836055810 1
4.0%
1191984770 1
4.0%
448027584 1
4.0%
163229136 1
4.0%
3663240 1
4.0%
2412792 1
4.0%
1500282 1
4.0%
1427226 1
4.0%

평균덧글수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean217.85888
Minimum0
Maximum1493.83
Zeros1
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:14:25.279155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1992
Q15.461
median39.571
Q3170.432
95-th percentile1084.3112
Maximum1493.83
Range1493.83
Interquartile range (IQR)164.971

Descriptive statistics

Standard deviation390.28749
Coefficient of variation (CV)1.7914693
Kurtosis4.8656538
Mean217.85888
Median Absolute Deviation (MAD)39.438
Skewness2.3184493
Sum5446.472
Variance152324.33
MonotonicityNot monotonic
2023-12-10T23:14:25.503978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
97.679 1
 
4.0%
0.0 1
 
4.0%
895.94 1
 
4.0%
0.464 1
 
4.0%
97.674 1
 
4.0%
39.571 1
 
4.0%
0.133 1
 
4.0%
8.688 1
 
4.0%
1.921 1
 
4.0%
6.17 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
0.0 1
4.0%
0.133 1
4.0%
0.464 1
4.0%
1.921 1
4.0%
3.709 1
4.0%
4.209 1
4.0%
5.461 1
4.0%
6.17 1
4.0%
8.688 1
4.0%
9.535 1
4.0%
ValueCountFrequency (%)
1493.83 1
4.0%
1131.404 1
4.0%
895.94 1
4.0%
469.52 1
4.0%
377.835 1
4.0%
276.879 1
4.0%
170.432 1
4.0%
132.682 1
4.0%
127.582 1
4.0%
97.679 1
4.0%

주당덧글수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean548.88
Minimum0
Maximum5086
Zeros2
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:14:25.694363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q15
median38
Q3266
95-th percentile3771.2
Maximum5086
Range5086
Interquartile range (IQR)261

Descriptive statistics

Standard deviation1307.594
Coefficient of variation (CV)2.3822949
Kurtosis8.0565271
Mean548.88
Median Absolute Deviation (MAD)37
Skewness2.9435804
Sum13722
Variance1709802.1
MonotonicityNot monotonic
2023-12-10T23:14:25.935321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 3
 
12.0%
0 2
 
8.0%
113 1
 
4.0%
5 1
 
4.0%
266 1
 
4.0%
10 1
 
4.0%
60 1
 
4.0%
2 1
 
4.0%
12 1
 
4.0%
1616 1
 
4.0%
Other values (12) 12
48.0%
ValueCountFrequency (%)
0 2
8.0%
1 3
12.0%
2 1
 
4.0%
5 1
 
4.0%
7 1
 
4.0%
9 1
 
4.0%
10 1
 
4.0%
12 1
 
4.0%
28 1
 
4.0%
38 1
 
4.0%
ValueCountFrequency (%)
5086 1
4.0%
4310 1
4.0%
1616 1
4.0%
978 1
4.0%
495 1
4.0%
448 1
4.0%
266 1
4.0%
113 1
4.0%
109 1
4.0%
71 1
4.0%

상호작용지수전체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0.0
21 
0.003
 
2
0.01
 
1
0.001
 
1

Length

Max length5
Median length3
Mean length3.28
Min length3

Unique

Unique2 ?
Unique (%)8.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.003
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 21
84.0%
0.003 2
 
8.0%
0.01 1
 
4.0%
0.001 1
 
4.0%

Length

2023-12-10T23:14:26.246818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:26.452379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 21
84.0%
0.003 2
 
8.0%
0.01 1
 
4.0%
0.001 1
 
4.0%

상호작용지수1개월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 25
100.0%

Length

2023-12-10T23:14:26.632785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:26.796188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 25
100.0%

상호작용지수3개월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 25
100.0%

Length

2023-12-10T23:14:26.955925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:27.114468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 25
100.0%

상호작용지수평균덧글수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.14064
Minimum0
Maximum0.964
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:14:27.284119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.004
median0.026
Q30.11
95-th percentile0.6996
Maximum0.964
Range0.964
Interquartile range (IQR)0.106

Descriptive statistics

Standard deviation0.25182283
Coefficient of variation (CV)1.7905492
Kurtosis4.8663031
Mean0.14064
Median Absolute Deviation (MAD)0.026
Skewness2.3183433
Sum3.516
Variance0.06341474
MonotonicityNot monotonic
2023-12-10T23:14:27.541543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 3
 
12.0%
0.063 2
 
8.0%
0.006 2
 
8.0%
0.004 2
 
8.0%
0.303 1
 
4.0%
0.578 1
 
4.0%
0.026 1
 
4.0%
0.001 1
 
4.0%
0.179 1
 
4.0%
0.003 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 3
12.0%
0.001 1
 
4.0%
0.002 1
 
4.0%
0.003 1
 
4.0%
0.004 2
8.0%
0.006 2
8.0%
0.007 1
 
4.0%
0.016 1
 
4.0%
0.026 1
 
4.0%
0.039 1
 
4.0%
ValueCountFrequency (%)
0.964 1
4.0%
0.73 1
4.0%
0.578 1
4.0%
0.303 1
4.0%
0.244 1
4.0%
0.179 1
4.0%
0.11 1
4.0%
0.086 1
4.0%
0.082 1
4.0%
0.063 2
8.0%

상호작용지수주당덧글수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0
21 
1
 
2
4
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)8.0%

Sample

1st row0
2nd row0
3rd row0
4th row4
5th row0

Common Values

ValueCountFrequency (%)
0 21
84.0%
1 2
 
8.0%
4 1
 
4.0%
3 1
 
4.0%

Length

2023-12-10T23:14:27.761468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:28.038928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
84.0%
1 2
 
8.0%
4 1
 
4.0%
3 1
 
4.0%

상호작용지수전체표준점수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
-0.04
24 
-0.03
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)4.0%

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 24
96.0%
-0.03 1
 
4.0%

Length

2023-12-10T23:14:28.222432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:28.379123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.04 24
96.0%
0.03 1
 
4.0%

1개월표준점수
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
-0.02
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
-0.02 25
100.0%

Length

2023-12-10T23:14:28.702832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:28.945622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.02 25
100.0%

3개월표준점수
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
-0.03
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

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 25
100.0%

Length

2023-12-10T23:14:29.096587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:29.270346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.03 25
100.0%

평균수표준점수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0428
Minimum-0.1
Maximum0.31
Zeros1
Zeros (%)4.0%
Negative20
Negative (%)80.0%
Memory size357.0 B
2023-12-10T23:14:29.423635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.1
5-th percentile-0.1
Q1-0.1
median-0.09
Q3-0.06
95-th percentile0.198
Maximum0.31
Range0.41
Interquartile range (IQR)0.04

Descriptive statistics

Standard deviation0.10822507
Coefficient of variation (CV)-2.5286232
Kurtosis4.8302072
Mean-0.0428
Median Absolute Deviation (MAD)0.01
Skewness2.3258251
Sum-1.07
Variance0.011712667
MonotonicityNot monotonic
2023-12-10T23:14:29.633462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
-0.1 12
48.0%
-0.08 2
 
8.0%
-0.09 2
 
8.0%
-0.07 2
 
8.0%
0.31 1
 
4.0%
0.0 1
 
4.0%
-0.06 1
 
4.0%
0.03 1
 
4.0%
0.21 1
 
4.0%
-0.03 1
 
4.0%
ValueCountFrequency (%)
-0.1 12
48.0%
-0.09 2
 
8.0%
-0.08 2
 
8.0%
-0.07 2
 
8.0%
-0.06 1
 
4.0%
-0.03 1
 
4.0%
0.0 1
 
4.0%
0.03 1
 
4.0%
0.15 1
 
4.0%
0.21 1
 
4.0%
ValueCountFrequency (%)
0.31 1
4.0%
0.21 1
4.0%
0.15 1
4.0%
0.03 1
4.0%
0.0 1
4.0%
-0.03 1
4.0%
-0.06 1
4.0%
-0.07 2
8.0%
-0.08 2
8.0%
-0.09 2
8.0%

주당수표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.024
Minimum-0.15
Maximum1.01
Zeros0
Zeros (%)0.0%
Negative21
Negative (%)84.0%
Memory size357.0 B
2023-12-10T23:14:29.826177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.15
5-th percentile-0.15
Q1-0.15
median-0.14
Q3-0.09
95-th percentile0.708
Maximum1.01
Range1.16
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.29744747
Coefficient of variation (CV)-12.393645
Kurtosis8.0877172
Mean-0.024
Median Absolute Deviation (MAD)0.01
Skewness2.9486234
Sum-0.6
Variance0.088475
MonotonicityNot monotonic
2023-12-10T23:14:30.073802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
-0.15 10
40.0%
-0.13 3
 
12.0%
-0.14 3
 
12.0%
-0.12 2
 
8.0%
1.01 1
 
4.0%
0.07 1
 
4.0%
-0.05 1
 
4.0%
-0.04 1
 
4.0%
0.83 1
 
4.0%
0.22 1
 
4.0%
ValueCountFrequency (%)
-0.15 10
40.0%
-0.14 3
 
12.0%
-0.13 3
 
12.0%
-0.12 2
 
8.0%
-0.09 1
 
4.0%
-0.05 1
 
4.0%
-0.04 1
 
4.0%
0.07 1
 
4.0%
0.22 1
 
4.0%
0.83 1
 
4.0%
ValueCountFrequency (%)
1.01 1
 
4.0%
0.83 1
 
4.0%
0.22 1
 
4.0%
0.07 1
 
4.0%
-0.04 1
 
4.0%
-0.05 1
 
4.0%
-0.09 1
 
4.0%
-0.12 2
8.0%
-0.13 3
12.0%
-0.14 3
12.0%

Interactions

2023-12-10T23:14:16.838305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:06.945667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:08.268540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.457273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.637463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.550137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.923597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.394569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:17.032788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:07.148098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:08.426199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.642113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.863525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.682590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.173425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.527315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:17.280290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:07.330600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:08.596013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.853698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.054109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.865860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.457101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.686930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:17.413472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:07.507912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:08.730810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.968297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.209232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.030271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.590626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.809124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:17.536683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:07.650621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:08.893340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.102006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.380095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.191746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.795305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.979162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:17.707174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:07.787534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.031228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.240479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.567937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.327361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.931880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:16.194030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:17.949495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:07.938816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.168949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.371535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.222510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.511671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.083873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:16.483622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:18.117136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:08.105590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.287218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.488366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.380867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.678528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.247087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:16.617901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:14:30.372844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호작용지수채널ID상호작용지수채널명상호작용지수채널설명상호작용지수채널생성일자지수전체지수1개월지수3개월평균덧글수주당덧글수상호작용지수전체상호작용지수평균덧글수상호작용지수주당덧글수상호작용지수전체표준점수평균수표준점수주당수표준점수
상호작용지수채널ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상호작용지수채널명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상호작용지수채널설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상호작용지수채널생성일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.000
지수전체1.0001.0001.0001.0001.0001.0000.9860.8261.0001.0000.8260.9871.0000.9121.000
지수1개월1.0001.0001.0001.0001.0001.0001.0000.8391.0001.0000.8390.7811.0001.0001.000
지수3개월1.0001.0001.0001.0000.9861.0001.0000.8260.8920.9860.8260.9731.0000.9120.892
평균덧글수1.0001.0001.0001.0000.8260.8390.8261.0000.8180.8261.0000.7791.0000.9990.818
주당덧글수1.0001.0001.0001.0001.0001.0000.8920.8181.0001.0000.8181.0001.0000.8861.000
상호작용지수전체1.0001.0001.0001.0001.0001.0000.9860.8261.0001.0000.8260.9871.0000.9121.000
상호작용지수평균덧글수1.0001.0001.0001.0000.8260.8390.8261.0000.8180.8261.0000.7791.0000.9990.818
상호작용지수주당덧글수1.0001.0001.0001.0000.9870.7810.9730.7791.0000.9870.7791.0001.0000.8361.000
상호작용지수전체표준점수1.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
평균수표준점수1.0001.0001.0001.0000.9121.0000.9120.9990.8860.9120.9990.8361.0001.0000.886
주당수표준점수1.0001.0001.0001.0001.0001.0000.8920.8181.0001.0000.8181.0001.0000.8861.000
2023-12-10T23:14:30.680677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호작용지수전체표준점수상호작용지수주당덧글수상호작용지수전체
상호작용지수전체표준점수1.0000.9560.956
상호작용지수주당덧글수0.9561.0000.845
상호작용지수전체0.9560.8451.000
2023-12-10T23:14:30.849820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지수전체지수1개월지수3개월평균덧글수주당덧글수상호작용지수평균덧글수평균수표준점수주당수표준점수상호작용지수전체상호작용지수주당덧글수상호작용지수전체표준점수
지수전체1.0000.7600.7650.9070.9780.9000.8660.9361.0000.8450.956
지수1개월0.7601.0000.9840.6020.7790.5940.5490.7730.9770.8190.978
지수3개월0.7650.9841.0000.5880.7890.5800.5300.7720.8350.7760.956
평균덧글수0.9070.6020.5881.0000.8800.9990.9430.8520.6790.6130.885
주당덧글수0.9780.7790.7890.8801.0000.8710.8390.9670.9760.9760.933
상호작용지수평균덧글수0.9000.5940.5800.9990.8711.0000.9440.8440.6790.6130.885
평균수표준점수0.8660.5490.5300.9430.8390.9441.0000.8330.8120.6920.885
주당수표준점수0.9360.7730.7720.8520.9670.8440.8331.0000.9760.9760.933
상호작용지수전체1.0000.9770.8350.6790.9760.6790.8120.9761.0000.8450.956
상호작용지수주당덧글수0.8450.8190.7760.6130.9760.6130.6920.9760.8451.0000.956
상호작용지수전체표준점수0.9560.9780.9560.8850.9330.8850.8850.9330.9560.9561.000

Missing values

2023-12-10T23:14:18.433024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:14:19.018048image/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.
2023-12-10T23:14:19.340983image/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-rL1o4m5UamXY7lzGw8P8Q찌워니의 삶2021-05-31광고문의 (콜라보문의 가능) jiwonbj@naver.com 페이스북 찌워니 인스타그램 jiwonbj<NA>1681205960044755626097.6791130.0000.0630-0.04-0.02-0.03-0.08-0.12
1UC0yvvSJLpQLPU6u6-ZaBXvg부산여성가족개발원2021-05-31<NA>2016-12-020000.000.0000.00-0.04-0.02-0.03-0.1-0.15
2UC256C9U-lYhr5-Or7vvCrvQThat Korean Girl 돌돌콩2021-05-31<NA><NA>362593075025970142722660.129560.0000.0390-0.04-0.02-0.03-0.09-0.13
3UC271vX3c3kYZsgpz7-zPBoAKBS Entertain: 깔깔티비2021-05-31KBS 전설적 레전드 예능프로그램이 모두 여기! 슈퍼스타 리즈시절 대공개 #깔깔티비 #깔깔 #원조 레전드 예능 1박2일 #전설아닌레전드 공포의쿵쿵따 유재석 강호동 #물대포맛집 위험한초대 이효리 하지원 김태희 #대환장시트콤 골든빌리지 금촌댁네사람들 이영자 #코인노래방아니고 쟁반노래방 유재석 이효리 #올드 미스 다이어리 #1박2일 정주행 #1박2일 레전드 #해피투게더 시즌3 #웃지마 사우나 #청춘불패 시즌1; 시즌 2 #스타 히~~스토리 #레전드순삭2019-04-041950264460000267930301191984770127.58250860.003000.0824-0.04-0.02-0.03-0.071.01
4UC28lbdOHnj-leok6tHIx7ew고양이와 소소한생활2021-05-31인스타 @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~^^2013-09-309508200010.81610.0000.0070-0.04-0.02-0.03-0.1-0.15
5UC2RP9LCRt8AkMZAgujPkRjg예순Games2021-05-31종합 게임 영상 채널입니다. Gameplay<NA>181298598013150318364132.682380.0000.0860-0.04-0.02-0.03-0.07-0.14
6UC2o_y872S6YvaO1K8EYnoxg조재원2021-05-31매번 재밌는 유머 콘텐츠로 웃음을 드리는 조재원이 되겠습니다! 앞으로 조재원의 신규 콘텐츠 많이 기대해주세요! 광고 및 비즈니스 문의 메일 : jojaewon@sandbox.co.kr 페이스북 : https:www.facebook.comjomansae 인스타그램 : https:m.instagram.comjojaewon0703 틱톡 : https:t.tiktok.comi18nshareuser6537453671877623810 无法阻止的兄妹 시나 웨이보 : https:weibo.com6471416204 도우인 : 无法阻止的兄妹<NA>1921072500000351121124480275841493.839780.003000.9641-0.04-0.02-0.030.310.07
7UC35SH2IZCoDAyjdM_BKNVlA붓싼뉴스 - 부산광역시 공식 유튜브 채널2021-05-31안녕하세요. 부산광역시 공식 유튜브 채널 붓싼뉴스 입니다. 여러분에게 꼭 필요한 부산시 정책 콘텐츠를 주기적으로 업데이트해 올리고 있습니다. 붓싼뉴스에서 더 새로운 부산을 만나보세요 :D The official Youtube channel of Busan Metropolitan CIty.2011-04-0797410515032743524127929.535280.0000.0060-0.04-0.02-0.03-0.1-0.14
8UC3GEDF05hzA8xTyN0ZTZWag우피터 WOOPETER2021-05-31스포츠 전문 채널 우피터입니다. for business : peterbenjaminparker00798@gmail.com<NA>23679629300676147041836055810377.8354480.0000.2440-0.04-0.02-0.030.0-0.05
9UC3Md9z1EkkGs8htNkRG3VewCAMAN카맨2021-05-31안녕하세요 카맨입니다 WOW! 문의 : didf2017@gmail.com2014-02-1012842614000010941788163229136170.4324950.0000.110-0.04-0.02-0.03-0.06-0.04
상호작용지수채널ID상호작용지수채널명상호작용지수수집일자상호작용지수채널설명상호작용지수채널생성일자지수전체지수1개월지수3개월평균덧글수주당덧글수상호작용지수전체상호작용지수1개월상호작용지수3개월상호작용지수평균덧글수상호작용지수주당덧글수상호작용지수전체표준점수1개월표준점수3개월표준점수평균수표준점수주당수표준점수
15UC6c5kjucINs9l9WyIcGd4gA한국여행추천TV2021-05-31. 한국의 멋진 풍경을 소개하고 보여주는 TV입니다 여기 오신 모든 분들을 축복하고 ㅅ ㅏ랑합니다. The wonderful scenery of Korea It's an introduction and presentation TV. Everyone who's here. Bless you and I love you. 歡迎來到韓國。 올려진 영상은 저작권 보호를 받습니다 허가없는 편집; 재배포는 금지합니다. 링크공유는 무한 환영합니다. The uploaded video is copyright protected. Unauthorized editing and redistribution are prohibited. Link-sharing is an infinite welcome. 촬영 등에 관한 문의 : kreli1958@gmail.com (촉박한 일정사절; 기타 협의가능) For more information on photography; etc.; please visit kreli1958@gmail.com (A short-term agreement; other consultations are possible) . .2013-02-18447363840112564.20990.0000.0030-0.04-0.02-0.03-0.1-0.15
16UC7WMB_czX5jF__5kqT4d9Ww대한민국청와대2021-05-31청와대 공식 유튜브 채널입니다.2017-05-2681649657000018679875809259931600276.87916160.001000.1791-0.04-0.02-0.03-0.030.22
17UC7YDpATpEB2TuxMuPCxIRsw갑부주방아울렛2021-05-31업소용주방용품 창고형매장 갑부주방아울렛입니다. 에어컨 저온창고 냉동기수리 무엇이든! 식당&카페에 관한 어떠한 것도 한번에 한방에 넉넉하게 해결해보세요. TV서민갑부 출연을 비롯한 30번이상의 방송출연으로 더욱 믿을 수 있는 주방업체입니다.^^ 모두가 갑부되는 넉넉한 주방! 함께성장하는 마음으로 성장하겠습니다.<NA>3579129247112646.17120.0000.0040-0.04-0.02-0.03-0.1-0.14
18UC7bQXKhLtAfCTWWWHUzOoUQ광주동구2021-05-31<NA>2016-12-096661051311347601.92120.0000.0010-0.04-0.02-0.03-0.1-0.15
19UC91LhNN7zZ6gM-BR-gzwj0A서울기술연구원Seoul Institute of Technology2021-05-31<NA>2018-12-1048928008.68810.0000.0060-0.04-0.02-0.03-0.1-0.15
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22UC9a4SPvT4XLn98EMUSD40Eg쪼성환2021-05-31쪼성환이라고 합니다. 영상 한 번만 보세요. 문의:tjdghks3989@naver.com<NA>593435440097.674100.0000.0630-0.04-0.02-0.03-0.08-0.15
23UCA_sH8tAjjakRDWfLKN3FDQ울산 남구 고래방송국TV2021-05-31울산 남구청 공식 유튜브 채널 고래방송국TV 입니다. 직원들이 직접 참여한 콘텐츠 많이 기대해주세요!2019-01-212994422028320.46410.0000.00-0.04-0.02-0.03-0.1-0.15
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