Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory82.4 B

Variable types

Text2
DateTime1
Numeric6

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/c9285c56-7193-4ac6-a80c-3861a743ce44

Alerts

이용자활동평가생성기간 has constant value ""Constant
이용자활동평가채널조회수 is highly overall correlated with 이용자활동평가구독자수High correlation
이용자활동평가구독자수 is highly overall correlated with 이용자활동평가채널조회수High correlation
이용자활동평가영상조회수 is highly overall correlated with 수High correlation
이용자활동평가긍정평가비율 is highly overall correlated with 이용자활동평가부정평가비율High correlation
이용자활동평가부정평가비율 is highly overall correlated with 이용자활동평가긍정평가비율High correlation
수 is highly overall correlated with 이용자활동평가영상조회수High correlation
이용자활동평가긍정평가비율 has 1 (3.3%) missing valuesMissing
이용자활동평가부정평가비율 has 1 (3.3%) missing valuesMissing
이용자활동평가채널ID has unique valuesUnique
이용자활동평가영상ID has unique valuesUnique
이용자활동평가채널조회수 has unique valuesUnique
이용자활동평가구독자수 has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가구독자수 has 1 (3.3%) zerosZeros
이용자활동평가긍정평가비율 has 1 (3.3%) zerosZeros
이용자활동평가부정평가비율 has 6 (20.0%) zerosZeros
수 has 6 (20.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:48:46.129118
Analysis finished2023-12-10 13:48:53.683893
Duration7.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

이용자활동평가채널ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:53.994862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length56
Mean length56
Min length56

Characters and Unicode

Total characters1680
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowhttps://www.youtube.com/channel/UCbdeHam35cqnRNdVT3Y0ldg
2nd rowhttps://www.youtube.com/channel/UCbqaq8v32GGyaz9AGyW3ryA
3rd rowhttps://www.youtube.com/channel/UCcL8PoeJCC6DwAcKyzw_eQg
4th rowhttps://www.youtube.com/channel/UCFL1sCAksD6_7JIZwwHcwjQ
5th rowhttps://www.youtube.com/channel/UCNjQBiTSdoj2tCQLBGXFksw
ValueCountFrequency (%)
https://www.youtube.com/channel/ucbdeham35cqnrndvt3y0ldg 1
 
3.3%
https://www.youtube.com/channel/ucbqaq8v32ggyaz9agyw3rya 1
 
3.3%
https://www.youtube.com/channel/ucggrekytx4zhdx3uyfnxpjq 1
 
3.3%
https://www.youtube.com/channel/ucpvkqycqk2huumcjseuiy5g 1
 
3.3%
https://www.youtube.com/channel/uc3m0s5xaqydctblhc8j1uog 1
 
3.3%
https://www.youtube.com/channel/ucibr0bk06imamblc8saez0a 1
 
3.3%
https://www.youtube.com/channel/ucichcolwlbmd87quhlnuxjq 1
 
3.3%
https://www.youtube.com/channel/ucifyup4_ti70yckkvjalxoa 1
 
3.3%
https://www.youtube.com/channel/ucirw9xgyl2b6lyfwr1asiaa 1
 
3.3%
https://www.youtube.com/channel/ucs2yujwlg2tsotuedszf3_g 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:48:54.600800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 106
 
6.3%
t 98
 
5.8%
c 75
 
4.5%
u 73
 
4.3%
o 69
 
4.1%
n 69
 
4.1%
e 68
 
4.0%
h 67
 
4.0%
. 60
 
3.6%
Other values (57) 875
52.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1021
60.8%
Uppercase Letter 337
 
20.1%
Other Punctuation 210
 
12.5%
Decimal Number 96
 
5.7%
Connector Punctuation 9
 
0.5%
Dash Punctuation 7
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 106
 
10.4%
t 98
 
9.6%
c 75
 
7.3%
u 73
 
7.1%
o 69
 
6.8%
n 69
 
6.8%
e 68
 
6.7%
h 67
 
6.6%
y 44
 
4.3%
a 41
 
4.0%
Other values (16) 311
30.5%
Uppercase Letter
ValueCountFrequency (%)
C 50
 
14.8%
U 35
 
10.4%
A 18
 
5.3%
Y 17
 
5.0%
Q 17
 
5.0%
X 16
 
4.7%
I 15
 
4.5%
H 14
 
4.2%
B 13
 
3.9%
D 13
 
3.9%
Other values (16) 129
38.3%
Decimal Number
ValueCountFrequency (%)
3 15
15.6%
2 12
12.5%
8 12
12.5%
1 12
12.5%
0 10
10.4%
4 8
8.3%
7 7
7.3%
5 7
7.3%
6 7
7.3%
9 6
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1358
80.8%
Common 322
 
19.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 106
 
7.8%
t 98
 
7.2%
c 75
 
5.5%
u 73
 
5.4%
o 69
 
5.1%
n 69
 
5.1%
e 68
 
5.0%
h 67
 
4.9%
C 50
 
3.7%
y 44
 
3.2%
Other values (42) 639
47.1%
Common
ValueCountFrequency (%)
/ 120
37.3%
. 60
18.6%
: 30
 
9.3%
3 15
 
4.7%
2 12
 
3.7%
8 12
 
3.7%
1 12
 
3.7%
0 10
 
3.1%
_ 9
 
2.8%
4 8
 
2.5%
Other values (5) 34
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 106
 
6.3%
t 98
 
5.8%
c 75
 
4.5%
u 73
 
4.3%
o 69
 
4.1%
n 69
 
4.1%
e 68
 
4.0%
h 67
 
4.0%
. 60
 
3.6%
Other values (57) 875
52.1%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:54.986072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters1290
Distinct characters69
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowhttps://www.youtube.com/watch?v=oXz5hQyMpB4
2nd rowhttps://www.youtube.com/watch?v=n7D1GKyaMAQ
3rd rowhttps://www.youtube.com/watch?v=2H-qAYc7Ywk
4th rowhttps://www.youtube.com/watch?v=tKUJBpctf_c
5th rowhttps://www.youtube.com/watch?v=VOKD8WkBcEk
ValueCountFrequency (%)
https://www.youtube.com/watch?v=oxz5hqympb4 1
 
3.3%
https://www.youtube.com/watch?v=n7d1gkyamaq 1
 
3.3%
https://www.youtube.com/watch?v=tffy5sfplsi 1
 
3.3%
https://www.youtube.com/watch?v=ltngkpbmomw 1
 
3.3%
https://www.youtube.com/watch?v=oglzofmvawu 1
 
3.3%
https://www.youtube.com/watch?v=zsfw4nilmfi 1
 
3.3%
https://www.youtube.com/watch?v=m395uqo1pru 1
 
3.3%
https://www.youtube.com/watch?v=-hac47ewbsu 1
 
3.3%
https://www.youtube.com/watch?v=-ntl02z6x1g 1
 
3.3%
https://www.youtube.com/watch?v=varx36knzua 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:48:55.592478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 130
 
10.1%
t 127
 
9.8%
/ 90
 
7.0%
c 66
 
5.1%
o 65
 
5.0%
h 62
 
4.8%
. 60
 
4.7%
u 60
 
4.7%
p 38
 
2.9%
s 37
 
2.9%
Other values (59) 555
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 847
65.7%
Other Punctuation 210
 
16.3%
Uppercase Letter 141
 
10.9%
Decimal Number 55
 
4.3%
Math Symbol 30
 
2.3%
Dash Punctuation 5
 
0.4%
Connector Punctuation 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 130
15.3%
t 127
15.0%
c 66
 
7.8%
o 65
 
7.7%
h 62
 
7.3%
u 60
 
7.1%
p 38
 
4.5%
s 37
 
4.4%
a 37
 
4.4%
v 35
 
4.1%
Other values (16) 190
22.4%
Uppercase Letter
ValueCountFrequency (%)
M 12
 
8.5%
U 11
 
7.8%
E 9
 
6.4%
Q 8
 
5.7%
I 7
 
5.0%
F 7
 
5.0%
Y 6
 
4.3%
W 6
 
4.3%
V 6
 
4.3%
J 6
 
4.3%
Other values (16) 63
44.7%
Decimal Number
ValueCountFrequency (%)
9 7
12.7%
0 6
10.9%
8 6
10.9%
7 6
10.9%
4 6
10.9%
1 6
10.9%
5 5
9.1%
6 5
9.1%
2 5
9.1%
3 3
5.5%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
? 30
 
14.3%
: 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 988
76.6%
Common 302
 
23.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 130
 
13.2%
t 127
 
12.9%
c 66
 
6.7%
o 65
 
6.6%
h 62
 
6.3%
u 60
 
6.1%
p 38
 
3.8%
s 37
 
3.7%
a 37
 
3.7%
v 35
 
3.5%
Other values (42) 331
33.5%
Common
ValueCountFrequency (%)
/ 90
29.8%
. 60
19.9%
= 30
 
9.9%
? 30
 
9.9%
: 30
 
9.9%
9 7
 
2.3%
0 6
 
2.0%
8 6
 
2.0%
7 6
 
2.0%
4 6
 
2.0%
Other values (7) 31
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 130
 
10.1%
t 127
 
9.8%
/ 90
 
7.0%
c 66
 
5.1%
o 65
 
5.0%
h 62
 
4.8%
. 60
 
4.7%
u 60
 
4.7%
p 38
 
2.9%
s 37
 
2.9%
Other values (59) 555
43.0%

이용자활동평가생성기간
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2020-11-01 00:00:00
Maximum2020-11-01 00:00:00
2023-12-10T22:48:55.767689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:55.957980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0511282 × 109
Minimum1710490
Maximum1.1801985 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:56.145341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1710490
5-th percentile5037540.5
Q131120606
median98896814
Q36.0004766 × 108
95-th percentile5.7920465 × 109
Maximum1.1801985 × 1010
Range1.1800274 × 1010
Interquartile range (IQR)5.6892706 × 108

Descriptive statistics

Standard deviation2.5444843 × 109
Coefficient of variation (CV)2.4207175
Kurtosis12.285022
Mean1.0511282 × 109
Median Absolute Deviation (MAD)80291620
Skewness3.449075
Sum3.1533845 × 1010
Variance6.4744006 × 1018
MonotonicityNot monotonic
2023-12-10T22:48:56.347858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
8522896 1
 
3.3%
87859394 1
 
3.3%
575471370 1
 
3.3%
2185886 1
 
3.3%
52511270 1
 
3.3%
1181508021 1
 
3.3%
11801984887 1
 
3.3%
608239763 1
 
3.3%
71810228 1
 
3.3%
1332784881 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1710490 1
3.3%
2185886 1
3.3%
8522896 1
3.3%
9352012 1
3.3%
13739574 1
3.3%
26256228 1
3.3%
28815345 1
3.3%
30189596 1
3.3%
33913638 1
3.3%
37631729 1
3.3%
ValueCountFrequency (%)
11801984887 1
3.3%
7762390116 1
3.3%
3383848728 1
3.3%
1789503301 1
3.3%
1629198444 1
3.3%
1332784881 1
3.3%
1181508021 1
3.3%
608239763 1
3.3%
575471370 1
3.3%
217098795 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1114606.3
Minimum0
Maximum7750000
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:56.560725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11879.5
Q1124000
median297500
Q3854250
95-th percentile6028000
Maximum7750000
Range7750000
Interquartile range (IQR)730250

Descriptive statistics

Standard deviation2002457.4
Coefficient of variation (CV)1.7965602
Kurtosis4.9396873
Mean1114606.3
Median Absolute Deviation (MAD)240200
Skewness2.3958947
Sum33438190
Variance4.0098357 × 1012
MonotonicityNot monotonic
2023-12-10T22:48:56.838116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 1
 
3.3%
492000 1
 
3.3%
795000 1
 
3.3%
44000 1
 
3.3%
61800 1
 
3.3%
1260000 1
 
3.3%
7750000 1
 
3.3%
874000 1
 
3.3%
153000 1
 
3.3%
3250000 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0 1
3.3%
4090 1
3.3%
21400 1
3.3%
23100 1
3.3%
44000 1
3.3%
52800 1
3.3%
61800 1
3.3%
115000 1
3.3%
151000 1
3.3%
153000 1
3.3%
ValueCountFrequency (%)
7750000 1
3.3%
6100000 1
3.3%
5940000 1
3.3%
3250000 1
3.3%
1820000 1
3.3%
1720000 1
3.3%
1260000 1
3.3%
874000 1
3.3%
795000 1
3.3%
492000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95076.033
Minimum102
Maximum1325617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:57.097435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile185.45
Q11561.5
median7545.5
Q364191.5
95-th percentile414934.5
Maximum1325617
Range1325515
Interquartile range (IQR)62630

Descriptive statistics

Standard deviation255163.83
Coefficient of variation (CV)2.6837871
Kurtosis19.894126
Mean95076.033
Median Absolute Deviation (MAD)7358
Skewness4.2758561
Sum2852281
Variance6.5108579 × 1010
MonotonicityNot monotonic
2023-12-10T22:48:57.391153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
167 1
 
3.3%
2199 1
 
3.3%
2945 1
 
3.3%
4531 1
 
3.3%
491871 1
 
3.3%
864 1
 
3.3%
4261 1
 
3.3%
320901 1
 
3.3%
102 1
 
3.3%
1325617 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
102 1
3.3%
167 1
3.3%
208 1
3.3%
296 1
3.3%
437 1
3.3%
839 1
3.3%
864 1
3.3%
1349 1
3.3%
2199 1
3.3%
2831 1
3.3%
ValueCountFrequency (%)
1325617 1
3.3%
491871 1
3.3%
320901 1
3.3%
125448 1
3.3%
112479 1
3.3%
98986 1
3.3%
78620 1
3.3%
66308 1
3.3%
57842 1
3.3%
54453 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)65.5%
Missing1
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean92.168966
Minimum0
Maximum100
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:57.599943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile77.96
Q195.5
median97.6
Q398.8
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation18.739323
Coefficient of variation (CV)0.20331489
Kurtosis22.606452
Mean92.168966
Median Absolute Deviation (MAD)1.8
Skewness-4.5745873
Sum2672.9
Variance351.16222
MonotonicityNot monotonic
2023-12-10T22:48:57.964196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
100.0 6
20.0%
96.5 2
 
6.7%
97.9 2
 
6.7%
97.6 2
 
6.7%
97.5 2
 
6.7%
83.3 2
 
6.7%
96.4 1
 
3.3%
97.7 1
 
3.3%
94.1 1
 
3.3%
74.4 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
0.0 1
3.3%
74.4 1
3.3%
83.3 2
6.7%
86.2 1
3.3%
92.9 1
3.3%
94.1 1
3.3%
95.5 1
3.3%
95.8 1
3.3%
96.4 1
3.3%
96.5 2
6.7%
ValueCountFrequency (%)
100.0 6
20.0%
99.0 1
 
3.3%
98.8 1
 
3.3%
98.5 1
 
3.3%
98.0 1
 
3.3%
97.9 2
 
6.7%
97.7 1
 
3.3%
97.6 2
 
6.7%
97.5 2
 
6.7%
96.5 2
 
6.7%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)65.5%
Missing1
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean7.8310345
Minimum0
Maximum100
Zeros6
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:58.209998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.2
median2.4
Q34.5
95-th percentile22.04
Maximum100
Range100
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation18.739323
Coefficient of variation (CV)2.3929562
Kurtosis22.606452
Mean7.8310345
Median Absolute Deviation (MAD)1.8
Skewness4.5745873
Sum227.1
Variance351.16222
MonotonicityNot monotonic
2023-12-10T22:48:58.441910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 6
20.0%
3.5 2
 
6.7%
2.1 2
 
6.7%
2.4 2
 
6.7%
2.5 2
 
6.7%
16.7 2
 
6.7%
3.6 1
 
3.3%
2.3 1
 
3.3%
5.9 1
 
3.3%
25.6 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
0.0 6
20.0%
1.0 1
 
3.3%
1.2 1
 
3.3%
1.5 1
 
3.3%
2.0 1
 
3.3%
2.1 2
 
6.7%
2.3 1
 
3.3%
2.4 2
 
6.7%
2.5 2
 
6.7%
3.5 2
 
6.7%
ValueCountFrequency (%)
100.0 1
3.3%
25.6 1
3.3%
16.7 2
6.7%
13.8 1
3.3%
7.1 1
3.3%
5.9 1
3.3%
4.5 1
3.3%
4.2 1
3.3%
3.6 1
3.3%
3.5 2
6.7%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.93333
Minimum0
Maximum1300
Zeros6
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:58.657688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q3118.25
95-th percentile566.65
Maximum1300
Range1300
Interquartile range (IQR)117.25

Descriptive statistics

Standard deviation271.88803
Coefficient of variation (CV)2.1938248
Kurtosis12.580173
Mean123.93333
Median Absolute Deviation (MAD)10
Skewness3.3719554
Sum3718
Variance73923.099
MonotonicityNot monotonic
2023-12-10T22:48:58.863945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 6
20.0%
2 3
 
10.0%
1 3
 
10.0%
4 1
 
3.3%
7 1
 
3.3%
22 1
 
3.3%
378 1
 
3.3%
1300 1
 
3.3%
18 1
 
3.3%
342 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
0 6
20.0%
1 3
10.0%
2 3
10.0%
4 1
 
3.3%
6 1
 
3.3%
7 1
 
3.3%
13 1
 
3.3%
18 1
 
3.3%
21 1
 
3.3%
22 1
 
3.3%
ValueCountFrequency (%)
1300 1
3.3%
721 1
3.3%
378 1
3.3%
342 1
3.3%
213 1
3.3%
187 1
3.3%
148 1
3.3%
128 1
3.3%
89 1
3.3%
72 1
3.3%

Interactions

2023-12-10T22:48:51.856637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:46.800116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:47.816032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:48.725275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:49.676045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:50.542899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:52.042948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:46.947313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:47.976978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:48.873063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:49.825457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:50.699550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:52.245773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:47.216000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:48.138960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:49.030577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:49.982841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:50.946410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:52.388030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:47.356281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:48.287422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:49.240933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:50.134404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:51.243303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:52.541567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:47.503115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:48.446820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:49.373992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:50.272288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:51.535063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:53.023155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:47.644739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:48.577409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:49.520764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:50.405366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:51.705917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:48:59.003484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0000.8960.0000.3370.3370.000
이용자활동평가구독자수1.0001.0000.8961.0000.7370.6780.6780.000
이용자활동평가영상조회수1.0001.0000.0000.7371.0000.8540.8540.710
이용자활동평가긍정평가비율1.0001.0000.3370.6780.8541.0001.0000.000
이용자활동평가부정평가비율1.0001.0000.3370.6780.8541.0001.0000.000
수1.0001.0000.0000.0000.7100.0000.0001.000
2023-12-10T22:48:59.199524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.8870.234-0.1760.1760.021
이용자활동평가구독자수0.8871.0000.346-0.0930.0930.141
이용자활동평가영상조회수0.2340.3461.000-0.1270.1270.843
이용자활동평가긍정평가비율-0.176-0.093-0.1271.000-1.0000.097
이용자활동평가부정평가비율0.1760.0930.127-1.0001.000-0.097
수0.0210.1410.8430.097-0.0971.000

Missing values

2023-12-10T22:48:53.208127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:48:53.423394image/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.
2023-12-10T22:48:53.592562image/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

이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
0https://www.youtube.com/channel/UCbdeHam35cqnRNdVT3Y0ldghttps://www.youtube.com/watch?v=oXz5hQyMpB42020-11-0185228960167100.00.00
1https://www.youtube.com/channel/UCbqaq8v32GGyaz9AGyW3ryAhttps://www.youtube.com/watch?v=n7D1GKyaMAQ2020-11-012625622834400012544899.01.089
2https://www.youtube.com/channel/UCcL8PoeJCC6DwAcKyzw_eQghttps://www.youtube.com/watch?v=2H-qAYc7Ywk2020-11-011509155431730003189096.53.5213
3https://www.youtube.com/channel/UCFL1sCAksD6_7JIZwwHcwjQhttps://www.youtube.com/watch?v=tKUJBpctf_c2020-11-01776239011661000007862097.92.1128
4https://www.youtube.com/channel/UCNjQBiTSdoj2tCQLBGXFkswhttps://www.youtube.com/watch?v=VOKD8WkBcEk2020-11-011710490231002363697.62.440
5https://www.youtube.com/channel/UC2MgNh831KCMuYkK7u8C2dghttps://www.youtube.com/watch?v=D8ct7dFNpDY2020-11-011743228153860006630897.52.5148
6https://www.youtube.com/channel/UC-PHIZjV-oX8H7zD1cCN2NQhttps://www.youtube.com/watch?v=Vx0SIeFjm282020-11-0169026823414000437100.00.02
7https://www.youtube.com/channel/UCFCtZJTuJhE18k8IXwmXTYQhttps://www.youtube.com/watch?v=wF66s9JDgW42020-11-0116291984441820000638895.54.52
8https://www.youtube.com/channel/UCOHYlves6oxhyIQBRIIpPTQhttps://www.youtube.com/watch?v=-n4y2sSYwUs2020-11-0128815345151000936495.84.221
9https://www.youtube.com/channel/UCHwOQ9wD0XJLnCEYiHQM1jQhttps://www.youtube.com/watch?v=tUnUJEEb1Xw2020-11-01935201221400134983.316.71
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UC141BuVRzSSXJX33Am9yxEAhttps://www.youtube.com/watch?v=MQ1WPCUQAME2020-11-0160503018188000283192.97.16
21https://www.youtube.com/channel/UCs2yuJwlg2TsOtUeDSZF3_ghttps://www.youtube.com/watch?v=vaRx36knzUA2020-11-011435506963020005784298.81.2342
22https://www.youtube.com/channel/UCiRw9xGyL2b6lYfWR1ASIaAhttps://www.youtube.com/watch?v=-NtL02Z6x1g2020-11-0113327848813250000132561774.425.618
23https://www.youtube.com/channel/UCiFYUP4_TI70yCkkVJAlxoAhttps://www.youtube.com/watch?v=-HaC47eWbsU2020-11-0171810228153000102100.00.00
24https://www.youtube.com/channel/UCIchCOLwLBMD87quHlNuXjQhttps://www.youtube.com/watch?v=M395Uqo1pRU2020-11-0160823976387400032090197.92.11300
25https://www.youtube.com/channel/UCiBr0bK06imaMbLc8sAEz0Ahttps://www.youtube.com/watch?v=zsfw4NIlMfI2020-11-01118019848877750000426194.15.91
26https://www.youtube.com/channel/UC3m0s5XAQydCtbLHc8j1Uoghttps://www.youtube.com/watch?v=oglZOFMvAwU2020-11-0111815080211260000864100.00.01
27https://www.youtube.com/channel/UCpvkqYCqk2huuMcJsEuiY5ghttps://www.youtube.com/watch?v=LtNGkpbmOMw2020-11-01525112706180049187196.53.5378
28https://www.youtube.com/channel/UCggrEkYTx4zhDX3UyfnXPjQhttps://www.youtube.com/watch?v=TfFY5sFplSI2020-11-012185886440004531100.00.022
29https://www.youtube.com/channel/UCWlV3Lz_55UaX4JsMj-z__Qhttps://www.youtube.com/watch?v=0bSiwkvjCrc2020-11-01575471370795000294597.72.37