Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells4
Missing cells (%)1.5%
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/514e518f-0622-4472-9214-f3c81ef45ef4

Alerts

이용자활동평가생성기간 has constant value ""Constant
이용자활동평가채널조회수 is highly overall correlated with 이용자활동평가구독자수 and 2 other fieldsHigh correlation
이용자활동평가구독자수 is highly overall correlated with 이용자활동평가채널조회수 and 1 other fieldsHigh correlation
이용자활동평가영상조회수 is highly overall correlated with 이용자활동평가채널조회수 and 4 other fieldsHigh correlation
이용자활동평가긍정평가비율 is highly overall correlated with 이용자활동평가영상조회수 and 1 other fieldsHigh correlation
이용자활동평가부정평가비율 is highly overall correlated with 이용자활동평가영상조회수 and 1 other fieldsHigh correlation
수 is highly overall correlated with 이용자활동평가채널조회수 and 1 other fieldsHigh correlation
이용자활동평가긍정평가비율 has 2 (6.7%) missing valuesMissing
이용자활동평가부정평가비율 has 2 (6.7%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가구독자수 has 1 (3.3%) zerosZeros
이용자활동평가부정평가비율 has 9 (30.0%) zerosZeros
수 has 8 (26.7%) zerosZeros

Reproduction

Analysis started2023-12-10 13:49:40.643103
Analysis finished2023-12-10 13:49:47.449440
Duration6.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

이용자활동평가채널ID
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:49:47.775087image/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

Unique28 ?
Unique (%)93.3%

Sample

1st rowhttps://www.youtube.com/channel/UCw6AmebJ0sUuDdfFNFfa74g
2nd rowhttps://www.youtube.com/channel/UCweOkPb1wVVH0Q0Tlj4a5Pw
3rd rowhttps://www.youtube.com/channel/UCUHzBC3_hS0n1HdnP8JaLkw
4th rowhttps://www.youtube.com/channel/UCn0nlepACCBD6rxj-GUwn5A
5th rowhttps://www.youtube.com/channel/UCOYC5dyftpdpnb5x2PL-9_A
ValueCountFrequency (%)
https://www.youtube.com/channel/ucmjnkt6kitwaztqvwuasplg 2
 
6.7%
https://www.youtube.com/channel/ucw6amebj0suuddffnffa74g 1
 
3.3%
https://www.youtube.com/channel/ucddbeywg8a51191uulfndjq 1
 
3.3%
https://www.youtube.com/channel/uclzb2iz5jpotnz0s-qu6wiw 1
 
3.3%
https://www.youtube.com/channel/uc-9oz6oofrznaouq48-lava 1
 
3.3%
https://www.youtube.com/channel/uch5swfph2irzvhooxwt8eqa 1
 
3.3%
https://www.youtube.com/channel/uccp6_mw3hhctsrnky4sjcfa 1
 
3.3%
https://www.youtube.com/channel/ucb-ogycx9me8np9gegpmjug 1
 
3.3%
https://www.youtube.com/channel/ucyzzwcuxyn6tkaeyqrefj2w 1
 
3.3%
https://www.youtube.com/channel/ucg9afjtz-lmchaio1kjsirg 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T22:49:48.697429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 114
 
6.8%
t 95
 
5.7%
n 71
 
4.2%
e 70
 
4.2%
o 69
 
4.1%
u 67
 
4.0%
h 66
 
3.9%
c 64
 
3.8%
. 60
 
3.6%
Other values (57) 884
52.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1030
61.3%
Uppercase Letter 329
 
19.6%
Other Punctuation 210
 
12.5%
Decimal Number 94
 
5.6%
Dash Punctuation 14
 
0.8%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 114
 
11.1%
t 95
 
9.2%
n 71
 
6.9%
e 70
 
6.8%
o 69
 
6.7%
u 67
 
6.5%
h 66
 
6.4%
c 64
 
6.2%
a 47
 
4.6%
p 43
 
4.2%
Other values (16) 324
31.5%
Uppercase Letter
ValueCountFrequency (%)
C 43
 
13.1%
U 43
 
13.1%
A 17
 
5.2%
Z 15
 
4.6%
P 14
 
4.3%
D 14
 
4.3%
T 13
 
4.0%
O 13
 
4.0%
K 12
 
3.6%
R 12
 
3.6%
Other values (16) 133
40.4%
Decimal Number
ValueCountFrequency (%)
6 14
14.9%
0 14
14.9%
3 10
10.6%
1 9
9.6%
2 9
9.6%
4 9
9.6%
8 8
8.5%
5 8
8.5%
9 8
8.5%
7 5
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1359
80.9%
Common 321
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 114
 
8.4%
t 95
 
7.0%
n 71
 
5.2%
e 70
 
5.2%
o 69
 
5.1%
u 67
 
4.9%
h 66
 
4.9%
c 64
 
4.7%
a 47
 
3.5%
C 43
 
3.2%
Other values (42) 653
48.1%
Common
ValueCountFrequency (%)
/ 120
37.4%
. 60
18.7%
: 30
 
9.3%
- 14
 
4.4%
6 14
 
4.4%
0 14
 
4.4%
3 10
 
3.1%
1 9
 
2.8%
2 9
 
2.8%
4 9
 
2.8%
Other values (5) 32
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 114
 
6.8%
t 95
 
5.7%
n 71
 
4.2%
e 70
 
4.2%
o 69
 
4.1%
u 67
 
4.0%
h 66
 
3.9%
c 64
 
3.8%
. 60
 
3.6%
Other values (57) 884
52.6%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:49:49.713139image/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=X9RGodJoOJU
2nd rowhttps://www.youtube.com/watch?v=g2tDD6vdjC0
3rd rowhttps://www.youtube.com/watch?v=5BruvDRLCUs
4th rowhttps://www.youtube.com/watch?v=5-4VgYGpE3g
5th rowhttps://www.youtube.com/watch?v=DqdM4JXXJv4
ValueCountFrequency (%)
https://www.youtube.com/watch?v=x9rgodjooju 1
 
3.3%
https://www.youtube.com/watch?v=g2tdd6vdjc0 1
 
3.3%
https://www.youtube.com/watch?v=g7ysithfmci 1
 
3.3%
https://www.youtube.com/watch?v=zxdt60mmojq 1
 
3.3%
https://www.youtube.com/watch?v=-znhy4vdrmm 1
 
3.3%
https://www.youtube.com/watch?v=wlnfqbwxscm 1
 
3.3%
https://www.youtube.com/watch?v=d3btbihqx_m 1
 
3.3%
https://www.youtube.com/watch?v=r1lyqoif__q 1
 
3.3%
https://www.youtube.com/watch?v=r_mnmkubxgu 1
 
3.3%
https://www.youtube.com/watch?v=gf-fmlytnt8 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:49:50.341324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 126
 
9.8%
t 124
 
9.6%
/ 90
 
7.0%
o 65
 
5.0%
u 64
 
5.0%
c 62
 
4.8%
h 62
 
4.8%
. 60
 
4.7%
v 38
 
2.9%
s 36
 
2.8%
Other values (59) 563
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 843
65.3%
Other Punctuation 210
 
16.3%
Uppercase Letter 160
 
12.4%
Decimal Number 34
 
2.6%
Math Symbol 30
 
2.3%
Connector Punctuation 7
 
0.5%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 126
14.9%
t 124
14.7%
o 65
 
7.7%
u 64
 
7.6%
c 62
 
7.4%
h 62
 
7.4%
v 38
 
4.5%
s 36
 
4.3%
b 34
 
4.0%
m 34
 
4.0%
Other values (16) 198
23.5%
Uppercase Letter
ValueCountFrequency (%)
M 11
 
6.9%
Y 11
 
6.9%
X 10
 
6.2%
N 8
 
5.0%
R 8
 
5.0%
H 8
 
5.0%
T 8
 
5.0%
D 8
 
5.0%
B 8
 
5.0%
L 7
 
4.4%
Other values (16) 73
45.6%
Decimal Number
ValueCountFrequency (%)
4 7
20.6%
3 4
11.8%
0 4
11.8%
7 3
8.8%
6 3
8.8%
8 3
8.8%
2 3
8.8%
5 3
8.8%
1 2
 
5.9%
9 2
 
5.9%
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 (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1003
77.8%
Common 287
 
22.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 126
 
12.6%
t 124
 
12.4%
o 65
 
6.5%
u 64
 
6.4%
c 62
 
6.2%
h 62
 
6.2%
v 38
 
3.8%
s 36
 
3.6%
b 34
 
3.4%
m 34
 
3.4%
Other values (42) 358
35.7%
Common
ValueCountFrequency (%)
/ 90
31.4%
. 60
20.9%
= 30
 
10.5%
? 30
 
10.5%
: 30
 
10.5%
4 7
 
2.4%
_ 7
 
2.4%
- 6
 
2.1%
3 4
 
1.4%
0 4
 
1.4%
Other values (7) 19
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 126
 
9.8%
t 124
 
9.6%
/ 90
 
7.0%
o 65
 
5.0%
u 64
 
5.0%
c 62
 
4.8%
h 62
 
4.8%
. 60
 
4.7%
v 38
 
2.9%
s 36
 
2.8%
Other values (59) 563
43.6%

이용자활동평가생성기간
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-01-01 00:00:00
Maximum2021-01-01 00:00:00
2023-12-10T22:49:50.554261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:50.735184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5893221 × 109
Minimum234054
Maximum1.8470776 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:49:50.928708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum234054
5-th percentile328920.55
Q115523256
median53803542
Q36.8004285 × 108
95-th percentile9.255806 × 109
Maximum1.8470776 × 1010
Range1.8470542 × 1010
Interquartile range (IQR)6.6451959 × 108

Descriptive statistics

Standard deviation4.077429 × 109
Coefficient of variation (CV)2.5655146
Kurtosis11.318755
Mean1.5893221 × 109
Median Absolute Deviation (MAD)53531734
Skewness3.3326432
Sum4.7679662 × 1010
Variance1.6625428 × 1019
MonotonicityNot monotonic
2023-12-10T22:49:51.139972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
5390560954 2
 
6.7%
9639506 1
 
3.3%
18470775554 1
 
3.3%
234054 1
 
3.3%
756486526 1
 
3.3%
54450413 1
 
3.3%
41843954 1
 
3.3%
352581 1
 
3.3%
435026444 1
 
3.3%
404099 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
234054 1
3.3%
309562 1
3.3%
352581 1
3.3%
404099 1
3.3%
877171 1
3.3%
7123053 1
3.3%
9639506 1
3.3%
11940384 1
3.3%
26271874 1
3.3%
31448729 1
3.3%
ValueCountFrequency (%)
18470775554 1
3.3%
12418279160 1
3.3%
5390560954 2
6.7%
1160623872 1
3.3%
1094751641 1
3.3%
756486526 1
3.3%
686980182 1
3.3%
659230842 1
3.3%
435026444 1
3.3%
272102156 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1640010.7
Minimum0
Maximum21600000
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:49:51.363078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1369.5
Q134350
median252500
Q31117500
95-th percentile6662000
Maximum21600000
Range21600000
Interquartile range (IQR)1083150

Descriptive statistics

Standard deviation4190265.7
Coefficient of variation (CV)2.5550234
Kurtosis18.772878
Mean1640010.7
Median Absolute Deviation (MAD)249680
Skewness4.1250938
Sum49200320
Variance1.7558327 × 1013
MonotonicityNot monotonic
2023-12-10T22:49:51.634732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
5100000 2
 
6.7%
263000 1
 
3.3%
21600000 1
 
3.3%
1940 1
 
3.3%
1120000 1
 
3.3%
242000 1
 
3.3%
311000 1
 
3.3%
1760 1
 
3.3%
354000 1
 
3.3%
3700 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0 1
3.3%
1050 1
3.3%
1760 1
3.3%
1940 1
3.3%
3700 1
3.3%
6370 1
3.3%
21400 1
3.3%
21800 1
3.3%
72000 1
3.3%
76500 1
3.3%
ValueCountFrequency (%)
21600000 1
3.3%
7940000 1
3.3%
5100000 2
6.7%
1300000 1
3.3%
1170000 1
3.3%
1140000 1
3.3%
1120000 1
3.3%
1110000 1
3.3%
665000 1
3.3%
543000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194757.63
Minimum10
Maximum2673332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:49:51.886507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile37.9
Q1645.75
median24358.5
Q393288.5
95-th percentile867547.9
Maximum2673332
Range2673322
Interquartile range (IQR)92642.75

Descriptive statistics

Standard deviation523473.46
Coefficient of variation (CV)2.68782
Kurtosis18.387717
Mean194757.63
Median Absolute Deviation (MAD)24130
Skewness4.1016079
Sum5842729
Variance2.7402447 × 1011
MonotonicityNot monotonic
2023-12-10T22:49:52.116772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
238092 1
 
3.3%
3649 1
 
3.3%
10 1
 
3.3%
104407 1
 
3.3%
96349 1
 
3.3%
61333 1
 
3.3%
48314 1
 
3.3%
50 1
 
3.3%
257 1
 
3.3%
22151 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10 1
3.3%
28 1
3.3%
50 1
3.3%
200 1
3.3%
257 1
3.3%
457 1
3.3%
524 1
3.3%
641 1
3.3%
660 1
3.3%
934 1
3.3%
ValueCountFrequency (%)
2673332 1
3.3%
1094626 1
3.3%
590008 1
3.3%
529563 1
3.3%
238092 1
3.3%
118037 1
3.3%
104407 1
3.3%
96349 1
3.3%
84107 1
3.3%
61333 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)71.4%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean96.889286
Minimum86.3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:49:52.314223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.3
5-th percentile88.32
Q195.85
median98.1
Q3100
95-th percentile100
Maximum100
Range13.7
Interquartile range (IQR)4.15

Descriptive statistics

Standard deviation3.7799019
Coefficient of variation (CV)0.03901259
Kurtosis2.07731
Mean96.889286
Median Absolute Deviation (MAD)1.9
Skewness-1.6001664
Sum2712.9
Variance14.287659
MonotonicityNot monotonic
2023-12-10T22:49:52.503844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
100.0 9
30.0%
96.9 1
 
3.3%
98.2 1
 
3.3%
97.1 1
 
3.3%
96.5 1
 
3.3%
86.3 1
 
3.3%
95.5 1
 
3.3%
95.7 1
 
3.3%
87.9 1
 
3.3%
98.7 1
 
3.3%
Other values (10) 10
33.3%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
86.3 1
3.3%
87.9 1
3.3%
89.1 1
3.3%
92.8 1
3.3%
94.6 1
3.3%
95.5 1
3.3%
95.7 1
3.3%
95.9 1
3.3%
96.4 1
3.3%
96.5 1
3.3%
ValueCountFrequency (%)
100.0 9
30.0%
99.2 1
 
3.3%
99.0 1
 
3.3%
98.7 1
 
3.3%
98.4 1
 
3.3%
98.2 1
 
3.3%
98.0 1
 
3.3%
97.1 1
 
3.3%
96.9 1
 
3.3%
96.7 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct20
Distinct (%)71.4%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean3.1107143
Minimum0
Maximum13.7
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:49:52.682474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.9
Q34.15
95-th percentile11.68
Maximum13.7
Range13.7
Interquartile range (IQR)4.15

Descriptive statistics

Standard deviation3.7799019
Coefficient of variation (CV)1.2151235
Kurtosis2.07731
Mean3.1107143
Median Absolute Deviation (MAD)1.9
Skewness1.6001664
Sum87.1
Variance14.287659
MonotonicityNot monotonic
2023-12-10T22:49:52.890553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 9
30.0%
3.1 1
 
3.3%
1.8 1
 
3.3%
2.9 1
 
3.3%
3.5 1
 
3.3%
13.7 1
 
3.3%
4.5 1
 
3.3%
4.3 1
 
3.3%
12.1 1
 
3.3%
1.3 1
 
3.3%
Other values (10) 10
33.3%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
0.0 9
30.0%
0.8 1
 
3.3%
1.0 1
 
3.3%
1.3 1
 
3.3%
1.6 1
 
3.3%
1.8 1
 
3.3%
2.0 1
 
3.3%
2.9 1
 
3.3%
3.1 1
 
3.3%
3.3 1
 
3.3%
ValueCountFrequency (%)
13.7 1
3.3%
12.1 1
3.3%
10.9 1
3.3%
7.2 1
3.3%
5.4 1
3.3%
4.5 1
3.3%
4.3 1
3.3%
4.1 1
3.3%
3.6 1
3.3%
3.5 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.8
Minimum0
Maximum1080
Zeros8
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:49:53.105059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25
median12
Q3136.5
95-th percentile514.35
Maximum1080
Range1080
Interquartile range (IQR)136.25

Descriptive statistics

Standard deviation233.10297
Coefficient of variation (CV)1.8098056
Kurtosis9.2737435
Mean128.8
Median Absolute Deviation (MAD)12
Skewness2.8225584
Sum3864
Variance54336.993
MonotonicityNot monotonic
2023-12-10T22:49:53.314642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 8
26.7%
1 2
 
6.7%
63 1
 
3.3%
278 1
 
3.3%
120 1
 
3.3%
110 1
 
3.3%
10 1
 
3.3%
5 1
 
3.3%
2 1
 
3.3%
91 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
0 8
26.7%
1 2
 
6.7%
2 1
 
3.3%
3 1
 
3.3%
5 1
 
3.3%
8 1
 
3.3%
10 1
 
3.3%
14 1
 
3.3%
42 1
 
3.3%
62 1
 
3.3%
ValueCountFrequency (%)
1080 1
3.3%
585 1
3.3%
428 1
3.3%
351 1
3.3%
292 1
3.3%
278 1
3.3%
176 1
3.3%
142 1
3.3%
120 1
3.3%
110 1
3.3%

Interactions

2023-12-10T22:49:45.997824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:41.156878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:42.130674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.005035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.824650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:44.906108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:46.170430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:41.364160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:42.272448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.143725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.996529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:45.185477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:46.296568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:41.498938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:42.423942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.271795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:44.204348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:45.334340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:46.431922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:41.641114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:42.576102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.407537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:44.364253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:45.519746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:46.563996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:41.811226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:42.748212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.545707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:44.597995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:45.693274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:46.707945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:41.986884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:42.883626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:43.689504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:44.755589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:49:45.846110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:49:53.540544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0001.0000.0000.0001.000
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0001.0000.5550.6420.6420.637
이용자활동평가구독자수1.0001.0001.0001.0000.5590.6600.6600.641
이용자활동평가영상조회수1.0001.0000.5550.5591.0000.0000.0000.893
이용자활동평가긍정평가비율0.0001.0000.6420.6600.0001.0001.0000.382
이용자활동평가부정평가비율0.0001.0000.6420.6600.0001.0001.0000.382
수1.0001.0000.6370.6410.8930.3820.3821.000
2023-12-10T22:49:53.740339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.8980.608-0.4620.4620.517
이용자활동평가구독자수0.8981.0000.696-0.4990.4990.483
이용자활동평가영상조회수0.6080.6961.000-0.5770.5770.774
이용자활동평가긍정평가비율-0.462-0.499-0.5771.000-1.000-0.486
이용자활동평가부정평가비율0.4620.4990.577-1.0001.0000.486
수0.5170.4830.774-0.4860.4861.000

Missing values

2023-12-10T22:49:46.881325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:49:47.113954image/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.
2023-12-10T22:49:47.327479image/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/UCw6AmebJ0sUuDdfFNFfa74ghttps://www.youtube.com/watch?v=X9RGodJoOJU2021-01-01963950626300023809298.41.60
1https://www.youtube.com/channel/UCweOkPb1wVVH0Q0Tlj4a5Pwhttps://www.youtube.com/watch?v=g2tDD6vdjC02021-01-011847077555421600000267333299.20.81080
2https://www.youtube.com/channel/UCUHzBC3_hS0n1HdnP8JaLkwhttps://www.youtube.com/watch?v=5BruvDRLCUs2021-01-01386686612300003530499.01.0176
3https://www.youtube.com/channel/UCn0nlepACCBD6rxj-GUwn5Ahttps://www.youtube.com/watch?v=5-4VgYGpE3g2021-01-0111606238721300000109462698.02.0428
4https://www.youtube.com/channel/UCOYC5dyftpdpnb5x2PL-9_Ahttps://www.youtube.com/watch?v=DqdM4JXXJv42021-01-014507122693600327995.94.162
5https://www.youtube.com/channel/UCl02ZJk18gXDfs-Gl76PDSwhttps://www.youtube.com/watch?v=Er7zHdsfHrI2021-01-011194038421800660100.00.00
6https://www.youtube.com/channel/UC1Wq-BQZblFGbGgDAoCwrmAhttps://www.youtube.com/watch?v=CdWixjAKJTU2021-01-012110788595430006021192.87.2142
7https://www.youtube.com/channel/UCVZI7eLie2UlZph6aiBRNrwhttps://www.youtube.com/watch?v=hqxrLjrNqWA2021-01-012721021564690008410789.110.9351
8https://www.youtube.com/channel/UC0p33ZnRkC4p0jiPJajQZkwhttps://www.youtube.com/watch?v=RYrR6ALJfEU2021-01-018771716370641<NA><NA>0
9https://www.youtube.com/channel/UCJUv6GUKdsr3kbEADWeKp-Qhttps://www.youtube.com/watch?v=jtOFanb2NYM2021-01-01712305321400457100.00.03
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCG9aFJTZ-lMCHAiO1KJsirghttps://www.youtube.com/watch?v=ZdeELsTiBHg2021-01-01686980182665000200100.00.01
21https://www.youtube.com/channel/UCyzZWCuxYN6TKAEyqReFj2whttps://www.youtube.com/watch?v=GF-fMlyTnT82021-01-014040993700524100.00.02
22https://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLghttps://www.youtube.com/watch?v=R_MNMKubXgU2021-01-01539056095451000002215195.54.55
23https://www.youtube.com/channel/UCB-ogYCX9Me8nP9gEGpMjUghttps://www.youtube.com/watch?v=R1LYQOiF__Q2021-01-01435026444354000257100.00.00
24https://www.youtube.com/channel/UCCP6_mw3hHctSRNKy4SjCfAhttps://www.youtube.com/watch?v=d3BTBIHqx_M2021-01-01352581176050100.00.00
25https://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLghttps://www.youtube.com/watch?v=WLNFqBwxsCM2021-01-01539056095451000004831486.313.710
26https://www.youtube.com/channel/UCh5Swfph2irzVHOoxwT8EQAhttps://www.youtube.com/watch?v=-ZNhY4vDRmM2021-01-01418439543110006133396.53.5110
27https://www.youtube.com/channel/UC-9oz6OofrZnaOUQ48-LavAhttps://www.youtube.com/watch?v=zxDT60mmojQ2021-01-01544504132420009634997.12.9120
28https://www.youtube.com/channel/UClzB2iZ5jPoTNz0S-QU6Wiwhttps://www.youtube.com/watch?v=G7YsitHFMCI2021-01-01756486526112000010440798.21.8278
29https://www.youtube.com/channel/UC9UK-raVMHOPfisiO8pTDSwhttps://www.youtube.com/watch?v=3H3QzxHqX4s2021-01-01234054194010100.00.00