Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells8
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory82.4 B

Variable types

Text2
Categorical1
Numeric6

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/9597d285-5193-4997-8767-d547b7bbb058

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 이용자활동평가긍정평가비율 and 2 other fieldsHigh correlation
이용자활동평가긍정평가비율 is highly overall correlated with 이용자활동평가영상조회수 and 2 other fieldsHigh correlation
이용자활동평가부정평가비율 is highly overall correlated with 이용자활동평가영상조회수 and 2 other fieldsHigh correlation
수 is highly overall correlated with 이용자활동평가영상조회수 and 2 other fieldsHigh correlation
이용자활동평가긍정평가비율 has 4 (13.3%) missing valuesMissing
이용자활동평가부정평가비율 has 4 (13.3%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가구독자수 has 1 (3.3%) zerosZeros
이용자활동평가부정평가비율 has 14 (46.7%) zerosZeros
수 has 16 (53.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:10:54.168423
Analysis finished2023-12-10 14:11:02.262336
Duration8.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

이용자활동평가채널ID
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:11:02.569465image/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

Unique24 ?
Unique (%)80.0%

Sample

1st rowhttps://www.youtube.com/channel/UCMsjY8EfFZNul-_7DvWe6Aw
2nd rowhttps://www.youtube.com/channel/UCaKod3X1Tn4c7Ci0iUKcvzQ
3rd rowhttps://www.youtube.com/channel/UC6erIDuvbOaAO-OT5rB2Xew
4th rowhttps://www.youtube.com/channel/UCfq4V1DAuaojnr2ryvWNysw
5th rowhttps://www.youtube.com/channel/UCcJSKnYwH-H7PnQh1riE3WA
ValueCountFrequency (%)
https://www.youtube.com/channel/ucamff0euqrf6rwvlbb8plmw 2
 
6.7%
https://www.youtube.com/channel/ucyylilojyqkafklvjzx5img 2
 
6.7%
https://www.youtube.com/channel/ucb-ogycx9me8np9gegpmjug 2
 
6.7%
https://www.youtube.com/channel/uccoyem78cpazqvpe6ltosea 1
 
3.3%
https://www.youtube.com/channel/ucmsjy8effznul-_7dvwe6aw 1
 
3.3%
https://www.youtube.com/channel/uciipmdpvk7nznheushmvkug 1
 
3.3%
https://www.youtube.com/channel/ucwrfj9gc3meixu8fqkjdgxa 1
 
3.3%
https://www.youtube.com/channel/ucyooecrv-fixlpadweiavea 1
 
3.3%
https://www.youtube.com/channel/uckinyts9ihqoewr1sze2jtw 1
 
3.3%
https://www.youtube.com/channel/uctq7fc7eny5mfwa9qd6cqca 1
 
3.3%
Other values (17) 17
56.7%
2023-12-10T23:11:03.164989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 108
 
6.4%
t 96
 
5.7%
n 78
 
4.6%
o 74
 
4.4%
e 74
 
4.4%
c 72
 
4.3%
h 68
 
4.0%
u 68
 
4.0%
. 60
 
3.6%
Other values (57) 862
51.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1035
61.6%
Uppercase Letter 338
 
20.1%
Other Punctuation 210
 
12.5%
Decimal Number 85
 
5.1%
Dash Punctuation 9
 
0.5%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 108
 
10.4%
t 96
 
9.3%
n 78
 
7.5%
o 74
 
7.1%
e 74
 
7.1%
c 72
 
7.0%
h 68
 
6.6%
u 68
 
6.6%
y 43
 
4.2%
l 42
 
4.1%
Other values (16) 312
30.1%
Uppercase Letter
ValueCountFrequency (%)
U 44
 
13.0%
C 39
 
11.5%
A 25
 
7.4%
Y 17
 
5.0%
E 14
 
4.1%
M 14
 
4.1%
O 12
 
3.6%
Q 12
 
3.6%
B 12
 
3.6%
K 11
 
3.3%
Other values (16) 138
40.8%
Decimal Number
ValueCountFrequency (%)
6 16
18.8%
9 12
14.1%
8 11
12.9%
0 10
11.8%
7 9
10.6%
5 8
9.4%
3 6
 
7.1%
2 5
 
5.9%
4 4
 
4.7%
1 4
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1373
81.7%
Common 307
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 108
 
7.9%
t 96
 
7.0%
n 78
 
5.7%
o 74
 
5.4%
e 74
 
5.4%
c 72
 
5.2%
h 68
 
5.0%
u 68
 
5.0%
U 44
 
3.2%
y 43
 
3.1%
Other values (42) 648
47.2%
Common
ValueCountFrequency (%)
/ 120
39.1%
. 60
19.5%
: 30
 
9.8%
6 16
 
5.2%
9 12
 
3.9%
8 11
 
3.6%
0 10
 
3.3%
7 9
 
2.9%
- 9
 
2.9%
5 8
 
2.6%
Other values (5) 22
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 108
 
6.4%
t 96
 
5.7%
n 78
 
4.6%
o 74
 
4.4%
e 74
 
4.4%
c 72
 
4.3%
h 68
 
4.0%
u 68
 
4.0%
. 60
 
3.6%
Other values (57) 862
51.3%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:11:03.581254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters1290
Distinct characters68
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=wVLseHOCwXQ
2nd rowhttps://www.youtube.com/watch?v=FOMboEjk02I
3rd rowhttps://www.youtube.com/watch?v=K0LirpoSI0g
4th rowhttps://www.youtube.com/watch?v=4dTddHbj_tE
5th rowhttps://www.youtube.com/watch?v=4QKOXzyM7dc
ValueCountFrequency (%)
https://www.youtube.com/watch?v=wvlsehocwxq 1
 
3.3%
https://www.youtube.com/watch?v=fomboejk02i 1
 
3.3%
https://www.youtube.com/watch?v=pqffcgimq_y 1
 
3.3%
https://www.youtube.com/watch?v=6cyq39lhlj4 1
 
3.3%
https://www.youtube.com/watch?v=yyt_vqrooyw 1
 
3.3%
https://www.youtube.com/watch?v=k7f82ofgo48 1
 
3.3%
https://www.youtube.com/watch?v=7lluvpgmrmc 1
 
3.3%
https://www.youtube.com/watch?v=rrb0jbfv7rk 1
 
3.3%
https://www.youtube.com/watch?v=yuz-m4n7hkk 1
 
3.3%
https://www.youtube.com/watch?v=buvbsgr3xuo 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:11:04.158138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 130
 
10.1%
t 123
 
9.5%
/ 90
 
7.0%
o 69
 
5.3%
h 66
 
5.1%
u 66
 
5.1%
c 65
 
5.0%
. 60
 
4.7%
y 40
 
3.1%
b 36
 
2.8%
Other values (58) 545
42.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 862
66.8%
Other Punctuation 210
 
16.3%
Uppercase Letter 136
 
10.5%
Decimal Number 41
 
3.2%
Math Symbol 30
 
2.3%
Connector Punctuation 7
 
0.5%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 130
15.1%
t 123
14.3%
o 69
 
8.0%
h 66
 
7.7%
u 66
 
7.7%
c 65
 
7.5%
y 40
 
4.6%
b 36
 
4.2%
p 35
 
4.1%
s 35
 
4.1%
Other values (16) 197
22.9%
Uppercase Letter
ValueCountFrequency (%)
Y 12
 
8.8%
M 11
 
8.1%
I 9
 
6.6%
T 8
 
5.9%
H 7
 
5.1%
B 7
 
5.1%
O 7
 
5.1%
V 7
 
5.1%
E 6
 
4.4%
G 6
 
4.4%
Other values (15) 56
41.2%
Decimal Number
ValueCountFrequency (%)
7 10
24.4%
0 6
14.6%
4 5
12.2%
8 4
 
9.8%
3 4
 
9.8%
9 3
 
7.3%
6 3
 
7.3%
2 3
 
7.3%
1 2
 
4.9%
5 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
? 30
 
14.3%
: 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 998
77.4%
Common 292
 
22.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 130
 
13.0%
t 123
 
12.3%
o 69
 
6.9%
h 66
 
6.6%
u 66
 
6.6%
c 65
 
6.5%
y 40
 
4.0%
b 36
 
3.6%
p 35
 
3.5%
s 35
 
3.5%
Other values (41) 333
33.4%
Common
ValueCountFrequency (%)
/ 90
30.8%
. 60
20.5%
? 30
 
10.3%
= 30
 
10.3%
: 30
 
10.3%
7 10
 
3.4%
_ 7
 
2.4%
0 6
 
2.1%
4 5
 
1.7%
8 4
 
1.4%
Other values (7) 20
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 130
 
10.1%
t 123
 
9.5%
/ 90
 
7.0%
o 69
 
5.3%
h 66
 
5.1%
u 66
 
5.1%
c 65
 
5.0%
. 60
 
4.7%
y 40
 
3.1%
b 36
 
2.8%
Other values (58) 545
42.2%

이용자활동평가생성기간
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-03-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-01
2nd row2021-03-01
3rd row2021-03-01
4th row2021-03-01
5th row2021-03-01

Common Values

ValueCountFrequency (%)
2021-03-01 30
100.0%

Length

2023-12-10T23:11:04.388296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:11:04.544803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 30
100.0%

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8153797 × 109
Minimum217473
Maximum1.3071948 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:04.709454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum217473
5-th percentile844105.45
Q158732514
median5.1793352 × 108
Q31.7625064 × 109
95-th percentile8.4894614 × 109
Maximum1.3071948 × 1010
Range1.3071731 × 1010
Interquartile range (IQR)1.7037739 × 109

Descriptive statistics

Standard deviation3.1204985 × 109
Coefficient of variation (CV)1.7189233
Kurtosis7.556244
Mean1.8153797 × 109
Median Absolute Deviation (MAD)5.1708095 × 108
Skewness2.7447762
Sum5.4461392 × 1010
Variance9.7375109 × 1018
MonotonicityNot monotonic
2023-12-10T23:11:04.963517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
452809411 2
 
6.7%
1212257845 2
 
6.7%
462567806 2
 
6.7%
192563479 1
 
3.3%
539206115 1
 
3.3%
3961976013 1
 
3.3%
50763988 1
 
3.3%
1835541528 1
 
3.3%
1969976651 1
 
3.3%
217473 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
217473 1
3.3%
767974 1
3.3%
937155 1
3.3%
1674456 1
3.3%
2890336 1
3.3%
11207715 1
3.3%
16592132 1
3.3%
50763988 1
3.3%
82638090 1
3.3%
192563479 1
3.3%
ValueCountFrequency (%)
13071948195 1
3.3%
11276037637 1
3.3%
5083645978 1
3.3%
4074554318 1
3.3%
3961976013 1
3.3%
2725475654 1
3.3%
1969976651 1
3.3%
1835541528 1
3.3%
1543400900 1
3.3%
1231155244 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1769119.7
Minimum0
Maximum15600000
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:05.223366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1371.5
Q191600
median859500
Q31322500
95-th percentile6709500
Maximum15600000
Range15600000
Interquartile range (IQR)1230900

Descriptive statistics

Standard deviation3158730.1
Coefficient of variation (CV)1.7854813
Kurtosis13.044085
Mean1769119.7
Median Absolute Deviation (MAD)765800
Skewness3.3861465
Sum53073590
Variance9.9775759 × 1012
MonotonicityNot monotonic
2023-12-10T23:11:05.444082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
848000 2
 
6.7%
1240000 2
 
6.7%
370000 2
 
6.7%
248000 1
 
3.3%
686000 1
 
3.3%
3350000 1
 
3.3%
89500 1
 
3.3%
1710000 1
 
3.3%
1210000 1
 
3.3%
1740 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0 1
3.3%
1070 1
3.3%
1740 1
3.3%
4580 1
3.3%
10400 1
3.3%
12900 1
3.3%
34500 1
3.3%
89500 1
3.3%
97900 1
3.3%
248000 1
3.3%
ValueCountFrequency (%)
15600000 1
3.3%
8100000 1
3.3%
5010000 1
3.3%
4080000 1
3.3%
3350000 1
3.3%
2240000 1
3.3%
1710000 1
3.3%
1350000 1
3.3%
1240000 2
6.7%
1230000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24645.5
Minimum17
Maximum200278
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:05.799123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile98.15
Q1364.25
median1363
Q319669.75
95-th percentile115933.15
Maximum200278
Range200261
Interquartile range (IQR)19305.5

Descriptive statistics

Standard deviation47059.014
Coefficient of variation (CV)1.9094364
Kurtosis6.2946617
Mean24645.5
Median Absolute Deviation (MAD)1307
Skewness2.4721362
Sum739365
Variance2.2145508 × 109
MonotonicityNot monotonic
2023-12-10T23:11:06.204759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
41715 1
 
3.3%
336 1
 
3.3%
55055 1
 
3.3%
845 1
 
3.3%
115816 1
 
3.3%
13634 1
 
3.3%
960 1
 
3.3%
17 1
 
3.3%
21106 1
 
3.3%
95 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
17 1
3.3%
95 1
3.3%
102 1
3.3%
112 1
3.3%
184 1
3.3%
186 1
3.3%
336 1
3.3%
360 1
3.3%
377 1
3.3%
429 1
3.3%
ValueCountFrequency (%)
200278 1
3.3%
116029 1
3.3%
115816 1
3.3%
87919 1
3.3%
55055 1
3.3%
44154 1
3.3%
41715 1
3.3%
21106 1
3.3%
15361 1
3.3%
13634 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)50.0%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean95.346154
Minimum36.8
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:06.487837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.8
5-th percentile85.875
Q195.725
median100
Q3100
95-th percentile100
Maximum100
Range63.2
Interquartile range (IQR)4.275

Descriptive statistics

Standard deviation12.50866
Coefficient of variation (CV)0.13119208
Kurtosis21.073553
Mean95.346154
Median Absolute Deviation (MAD)0
Skewness-4.4489082
Sum2479
Variance156.46658
MonotonicityNot monotonic
2023-12-10T23:11:06.702509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
100.0 14
46.7%
95.8 1
 
3.3%
93.6 1
 
3.3%
96.1 1
 
3.3%
98.6 1
 
3.3%
36.8 1
 
3.3%
95.1 1
 
3.3%
98.8 1
 
3.3%
83.3 1
 
3.3%
95.7 1
 
3.3%
Other values (3) 3
 
10.0%
(Missing) 4
 
13.3%
ValueCountFrequency (%)
36.8 1
3.3%
83.3 1
3.3%
93.6 1
3.3%
93.7 1
3.3%
94.0 1
3.3%
95.1 1
3.3%
95.7 1
3.3%
95.8 1
3.3%
96.1 1
3.3%
97.5 1
3.3%
ValueCountFrequency (%)
100.0 14
46.7%
98.8 1
 
3.3%
98.6 1
 
3.3%
97.5 1
 
3.3%
96.1 1
 
3.3%
95.8 1
 
3.3%
95.7 1
 
3.3%
95.1 1
 
3.3%
94.0 1
 
3.3%
93.7 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)50.0%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean4.6538462
Minimum0
Maximum63.2
Zeros14
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:06.899976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.275
95-th percentile14.125
Maximum63.2
Range63.2
Interquartile range (IQR)4.275

Descriptive statistics

Standard deviation12.50866
Coefficient of variation (CV)2.6878113
Kurtosis21.073553
Mean4.6538462
Median Absolute Deviation (MAD)0
Skewness4.4489082
Sum121
Variance156.46658
MonotonicityNot monotonic
2023-12-10T23:11:07.088860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 14
46.7%
4.2 1
 
3.3%
6.4 1
 
3.3%
3.9 1
 
3.3%
1.4 1
 
3.3%
63.2 1
 
3.3%
4.9 1
 
3.3%
1.2 1
 
3.3%
16.7 1
 
3.3%
4.3 1
 
3.3%
Other values (3) 3
 
10.0%
(Missing) 4
 
13.3%
ValueCountFrequency (%)
0.0 14
46.7%
1.2 1
 
3.3%
1.4 1
 
3.3%
2.5 1
 
3.3%
3.9 1
 
3.3%
4.2 1
 
3.3%
4.3 1
 
3.3%
4.9 1
 
3.3%
6.0 1
 
3.3%
6.3 1
 
3.3%
ValueCountFrequency (%)
63.2 1
3.3%
16.7 1
3.3%
6.4 1
3.3%
6.3 1
3.3%
6.0 1
3.3%
4.9 1
3.3%
4.3 1
3.3%
4.2 1
3.3%
3.9 1
3.3%
2.5 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.5
Minimum0
Maximum413
Zeros16
Zeros (%)53.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:07.251876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q316.75
95-th percentile316.8
Maximum413
Range413
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation108.6839
Coefficient of variation (CV)2.1956343
Kurtosis5.3531216
Mean49.5
Median Absolute Deviation (MAD)0
Skewness2.4769231
Sum1485
Variance11812.19
MonotonicityNot monotonic
2023-12-10T23:11:07.429808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 16
53.3%
413 1
 
3.3%
2 1
 
3.3%
11 1
 
3.3%
12 1
 
3.3%
21 1
 
3.3%
111 1
 
3.3%
88 1
 
3.3%
8 1
 
3.3%
275 1
 
3.3%
Other values (5) 5
 
16.7%
ValueCountFrequency (%)
0 16
53.3%
1 1
 
3.3%
2 1
 
3.3%
8 1
 
3.3%
11 1
 
3.3%
12 1
 
3.3%
16 1
 
3.3%
17 1
 
3.3%
21 1
 
3.3%
88 1
 
3.3%
ValueCountFrequency (%)
413 1
3.3%
351 1
3.3%
275 1
3.3%
159 1
3.3%
111 1
3.3%
88 1
3.3%
21 1
3.3%
17 1
3.3%
16 1
3.3%
12 1
3.3%

Interactions

2023-12-10T23:11:00.719748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:54.839305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:55.982471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:57.692204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:58.698564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:59.626659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:00.916441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:55.034379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:56.554331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:57.862776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:58.870254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:59.774535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:01.118167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:55.188847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:56.788703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:58.037340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:59.032211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:59.949528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:01.275802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:55.368091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:57.018914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:58.220695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:59.171554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:00.123168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:01.432833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:55.556775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:57.300725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:58.371498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:59.308192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:00.309289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:01.577450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:55.832604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:57.532477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:58.539810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:59.480725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:00.560225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:11:07.560790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0000.7651.0001.0000.944
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0000.9860.6690.0000.0000.000
이용자활동평가구독자수1.0001.0000.9861.0000.7450.0000.0000.000
이용자활동평가영상조회수0.7651.0000.6690.7451.0000.0000.0000.884
이용자활동평가긍정평가비율1.0001.0000.0000.0000.0001.0001.0000.594
이용자활동평가부정평가비율1.0001.0000.0000.0000.0001.0001.0000.594
수0.9441.0000.0000.0000.8840.5940.5941.000
2023-12-10T23:11:08.069986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9720.435-0.1920.1920.246
이용자활동평가구독자수0.9721.0000.420-0.0880.0880.210
이용자활동평가영상조회수0.4350.4201.000-0.5800.5800.861
이용자활동평가긍정평가비율-0.192-0.088-0.5801.000-1.000-0.653
이용자활동평가부정평가비율0.1920.0880.580-1.0001.0000.653
수0.2460.2100.861-0.6530.6531.000

Missing values

2023-12-10T23:11:01.754410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:11:01.981269image/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.
2023-12-10T23:11:02.176229image/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/UCMsjY8EfFZNul-_7DvWe6Awhttps://www.youtube.com/watch?v=wVLseHOCwXQ2021-03-011925634792480004171595.84.2413
1https://www.youtube.com/channel/UCaKod3X1Tn4c7Ci0iUKcvzQhttps://www.youtube.com/watch?v=FOMboEjk02I2021-03-0127254756542240000448<NA><NA>0
2https://www.youtube.com/channel/UC6erIDuvbOaAO-OT5rB2Xewhttps://www.youtube.com/watch?v=K0LirpoSI0g2021-03-0150836459785010000958100.00.00
3https://www.youtube.com/channel/UCfq4V1DAuaojnr2ryvWNyswhttps://www.youtube.com/watch?v=4dTddHbj_tE2021-03-0112311552441080000274593.66.42
4https://www.youtube.com/channel/UCcJSKnYwH-H7PnQh1riE3WAhttps://www.youtube.com/watch?v=4QKOXzyM7dc2021-03-0128903364580112100.00.00
5https://www.youtube.com/channel/UCAmff0euQRf6RwVlbB8PLMwhttps://www.youtube.com/watch?v=HIZOuUN_0Yc2021-03-01452809411848000102<NA><NA>0
6https://www.youtube.com/channel/UCn0nlepACCBD6rxj-GUwn5Ahttps://www.youtube.com/watch?v=KOA6VM-xxbI2021-03-01121511442713500001297100.00.00
7https://www.youtube.com/channel/UC9iYGheHksAaocXVcPtcdWghttps://www.youtube.com/watch?v=JNGEZ1cNGyw2021-03-017679741070184<NA><NA>0
8https://www.youtube.com/channel/UC5BMQOsAB8hKUyHu9KI6yighttps://www.youtube.com/watch?v=kyBw_l-qyx82021-03-011127603763715600000953296.13.911
9https://www.youtube.com/channel/UCcJn6oYYnbZZxrWiHGU-Yywhttps://www.youtube.com/watch?v=V7jMSIHZKOE2021-03-011674456129002900100.00.012
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UClzB2iZ5jPoTNz0S-QU6Wiwhttps://www.youtube.com/watch?v=gNvxuGbB_zY2021-03-01821175351114000011602998.81.2275
21https://www.youtube.com/channel/UCl6GW0nhB6UIL05h2oF3vRAhttps://www.youtube.com/watch?v=BuVbSgR3xUo2021-03-01937155042983.316.70
22https://www.youtube.com/channel/UCB-ogYCX9Me8nP9gEGpMjUghttps://www.youtube.com/watch?v=YuZ-m4N7hkk2021-03-0146256780637000095100.00.00
23https://www.youtube.com/channel/UCUj6rrhMTR9pipbAWBAMvUQhttps://www.youtube.com/watch?v=RrB0jBFV7Rk2021-03-0149666091987100021106100.00.016
24https://www.youtube.com/channel/UCnHyx6H7fhKfUoAAaVGYvxQhttps://www.youtube.com/watch?v=7lLuVpgMrMc2021-03-01112077151040017100.00.00
25https://www.youtube.com/channel/UCtQ7Fc7Eny5MfWa9QD6CqcAhttps://www.youtube.com/watch?v=k7f82oFgo482021-03-012174731740960100.00.00
26https://www.youtube.com/channel/UCkinYTS9IHqOEwR1Sze2JTwhttps://www.youtube.com/watch?v=YYt_VQRooyw2021-03-01196997665112100001363495.74.3159
27https://www.youtube.com/channel/UCYooECrv-fIXlPaDwEIaveAhttps://www.youtube.com/watch?v=6cYq39lhlj42021-03-011835541528171000011581693.76.3351
28https://www.youtube.com/channel/UCwRFj9gC3meixU8fqKJdgxAhttps://www.youtube.com/watch?v=PQffCgIMq_Y2021-03-01507639888950084597.52.51
29https://www.youtube.com/channel/UChpjIaEgwtDZtmWEkzFulSAhttps://www.youtube.com/watch?v=grwER-DHTdk2021-03-01396197601333500005505594.06.017