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
DateTime1
Numeric6

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/5ad2f579-9383-4431-acc1-909e382c5a52

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 1 other fieldsHigh correlation
이용자활동평가부정평가비율 is highly overall correlated with 이용자활동평가영상조회수 and 1 other fieldsHigh correlation
수 is highly overall correlated with 이용자활동평가영상조회수High correlation
이용자활동평가긍정평가비율 has 4 (13.3%) missing valuesMissing
이용자활동평가부정평가비율 has 4 (13.3%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가부정평가비율 has 9 (30.0%) zerosZeros
수 has 12 (40.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:56:28.651933
Analysis finished2023-12-10 13:56:36.184619
Duration7.53 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
2023-12-10T22:56:36.498036image/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/UCwC8xqx6nDDBRKV2sB-tNBA
2nd rowhttps://www.youtube.com/channel/UCJUv6GUKdsr3kbEADWeKp-Q
3rd rowhttps://www.youtube.com/channel/UCYyLIlOJyqkAFKlVjzX5img
4th rowhttps://www.youtube.com/channel/UCweOkPb1wVVH0Q0Tlj4a5Pw
5th rowhttps://www.youtube.com/channel/UCPde4guD9yFBRzkxk2PatoA
ValueCountFrequency (%)
https://www.youtube.com/channel/ucwlv3lz_55uax4jsmj-z__q 2
 
6.7%
https://www.youtube.com/channel/ucwc8xqx6nddbrkv2sb-tnba 1
 
3.3%
https://www.youtube.com/channel/uckinyts9ihqoewr1sze2jtw 1
 
3.3%
https://www.youtube.com/channel/uc35sh2izcodayjdm_bknvla 1
 
3.3%
https://www.youtube.com/channel/ucjfmsgohnkfiyhkcblbxrhg 1
 
3.3%
https://www.youtube.com/channel/ucx_dzpi6efsohgtokag43-a 1
 
3.3%
https://www.youtube.com/channel/ucff7sq_kjcepzvr8h8us8ww 1
 
3.3%
https://www.youtube.com/channel/uc70u2e8gk14r7qffs7ehndw 1
 
3.3%
https://www.youtube.com/channel/ucfw4m1bjyydn1yts8szldzg 1
 
3.3%
https://www.youtube.com/channel/ucnfohbybpwtozi8tc8gaugq 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T22:56:37.238617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 113
 
6.7%
t 97
 
5.8%
e 76
 
4.5%
h 71
 
4.2%
o 70
 
4.2%
n 69
 
4.1%
u 67
 
4.0%
c 65
 
3.9%
. 60
 
3.6%
Other values (57) 872
51.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1010
60.1%
Uppercase Letter 340
 
20.2%
Other Punctuation 210
 
12.5%
Decimal Number 92
 
5.5%
Connector Punctuation 18
 
1.1%
Dash Punctuation 10
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 113
 
11.2%
t 97
 
9.6%
e 76
 
7.5%
h 71
 
7.0%
o 70
 
6.9%
n 69
 
6.8%
u 67
 
6.6%
c 65
 
6.4%
s 46
 
4.6%
l 44
 
4.4%
Other values (16) 292
28.9%
Uppercase Letter
ValueCountFrequency (%)
C 41
 
12.1%
U 41
 
12.1%
A 20
 
5.9%
P 17
 
5.0%
B 16
 
4.7%
Q 16
 
4.7%
F 15
 
4.4%
D 14
 
4.1%
M 14
 
4.1%
S 13
 
3.8%
Other values (16) 133
39.1%
Decimal Number
ValueCountFrequency (%)
8 12
13.0%
2 12
13.0%
5 11
12.0%
1 10
10.9%
4 10
10.9%
0 9
9.8%
3 8
8.7%
9 7
7.6%
7 7
7.6%
6 6
6.5%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1350
80.4%
Common 330
 
19.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 113
 
8.4%
t 97
 
7.2%
e 76
 
5.6%
h 71
 
5.3%
o 70
 
5.2%
n 69
 
5.1%
u 67
 
5.0%
c 65
 
4.8%
s 46
 
3.4%
l 44
 
3.3%
Other values (42) 632
46.8%
Common
ValueCountFrequency (%)
/ 120
36.4%
. 60
18.2%
: 30
 
9.1%
_ 18
 
5.5%
8 12
 
3.6%
2 12
 
3.6%
5 11
 
3.3%
1 10
 
3.0%
4 10
 
3.0%
- 10
 
3.0%
Other values (5) 37
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 113
 
6.7%
t 97
 
5.8%
e 76
 
4.5%
h 71
 
4.2%
o 70
 
4.2%
n 69
 
4.1%
u 67
 
4.0%
c 65
 
3.9%
. 60
 
3.6%
Other values (57) 872
51.9%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:56:37.711700image/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=F5PG9IJ0eUc
2nd rowhttps://www.youtube.com/watch?v=PzxxP781Bpo
3rd rowhttps://www.youtube.com/watch?v=4piwvhJgIqI
4th rowhttps://www.youtube.com/watch?v=AR--iSa7JPA
5th rowhttps://www.youtube.com/watch?v=ha-FxjCwCSc
ValueCountFrequency (%)
https://www.youtube.com/watch?v=f5pg9ij0euc 1
 
3.3%
https://www.youtube.com/watch?v=pzxxp781bpo 1
 
3.3%
https://www.youtube.com/watch?v=ul4rn1teljc 1
 
3.3%
https://www.youtube.com/watch?v=ywhqink2ifg 1
 
3.3%
https://www.youtube.com/watch?v=ilbgypbduvi 1
 
3.3%
https://www.youtube.com/watch?v=ukzacwa3a4w 1
 
3.3%
https://www.youtube.com/watch?v=hz5vvzjbu7e 1
 
3.3%
https://www.youtube.com/watch?v=gmlm3krajnq 1
 
3.3%
https://www.youtube.com/watch?v=djo9o65d0q0 1
 
3.3%
https://www.youtube.com/watch?v=4lyrloik_tc 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:56:38.486430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 128
 
9.9%
t 121
 
9.4%
/ 90
 
7.0%
c 68
 
5.3%
o 66
 
5.1%
u 65
 
5.0%
h 64
 
5.0%
. 60
 
4.7%
a 38
 
2.9%
y 37
 
2.9%
Other values (59) 553
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 855
66.3%
Other Punctuation 210
 
16.3%
Uppercase Letter 132
 
10.2%
Decimal Number 57
 
4.4%
Math Symbol 30
 
2.3%
Connector Punctuation 3
 
0.2%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 128
15.0%
t 121
14.2%
c 68
 
8.0%
o 66
 
7.7%
u 65
 
7.6%
h 64
 
7.5%
a 38
 
4.4%
y 37
 
4.3%
p 36
 
4.2%
v 35
 
4.1%
Other values (16) 197
23.0%
Uppercase Letter
ValueCountFrequency (%)
I 12
 
9.1%
P 11
 
8.3%
K 8
 
6.1%
S 8
 
6.1%
A 8
 
6.1%
U 7
 
5.3%
Y 6
 
4.5%
E 6
 
4.5%
D 5
 
3.8%
Q 5
 
3.8%
Other values (16) 56
42.4%
Decimal Number
ValueCountFrequency (%)
0 9
15.8%
2 7
12.3%
6 7
12.3%
4 6
10.5%
9 6
10.5%
7 6
10.5%
8 5
8.8%
1 5
8.8%
5 4
7.0%
3 2
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
: 30
 
14.3%
? 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 987
76.5%
Common 303
 
23.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 128
 
13.0%
t 121
 
12.3%
c 68
 
6.9%
o 66
 
6.7%
u 65
 
6.6%
h 64
 
6.5%
a 38
 
3.9%
y 37
 
3.7%
p 36
 
3.6%
v 35
 
3.5%
Other values (42) 329
33.3%
Common
ValueCountFrequency (%)
/ 90
29.7%
. 60
19.8%
: 30
 
9.9%
? 30
 
9.9%
= 30
 
9.9%
0 9
 
3.0%
2 7
 
2.3%
6 7
 
2.3%
4 6
 
2.0%
9 6
 
2.0%
Other values (7) 28
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 128
 
9.9%
t 121
 
9.4%
/ 90
 
7.0%
c 68
 
5.3%
o 66
 
5.1%
u 65
 
5.0%
h 64
 
5.0%
. 60
 
4.7%
a 38
 
2.9%
y 37
 
2.9%
Other values (59) 553
42.9%

이용자활동평가생성기간
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-04-01 00:00:00
Maximum2021-04-01 00:00:00
2023-12-10T22:56:38.686635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:38.848303image/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%
Mean2.0948824 × 109
Minimum54781
Maximum2.0203885 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:39.067579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54781
5-th percentile300630.95
Q19055299.5
median1.1752957 × 108
Q36.267797 × 108
95-th percentile1.4687287 × 1010
Maximum2.0203885 × 1010
Range2.0203831 × 1010
Interquartile range (IQR)6.177244 × 108

Descriptive statistics

Standard deviation5.1489276 × 109
Coefficient of variation (CV)2.45786
Kurtosis8.7016243
Mean2.0948824 × 109
Median Absolute Deviation (MAD)1.1675619 × 108
Skewness3.0482535
Sum6.2846471 × 1010
Variance2.6511455 × 1019
MonotonicityNot monotonic
2023-12-10T22:56:39.287972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
626779698 2
 
6.7%
1199889 1
 
3.3%
1234789 1
 
3.3%
209472628 1
 
3.3%
14791310 1
 
3.3%
54781 1
 
3.3%
3943885104 1
 
3.3%
15148489 1
 
3.3%
520811924 1
 
3.3%
102718290 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
54781 1
3.3%
262799 1
3.3%
346870 1
3.3%
1199889 1
3.3%
1234789 1
3.3%
1501516 1
3.3%
1844750 1
3.3%
7143296 1
3.3%
14791310 1
3.3%
15148489 1
3.3%
ValueCountFrequency (%)
20203885328 1
3.3%
19384521526 1
3.3%
8946223243 1
3.3%
3943885104 1
3.3%
3682327590 1
3.3%
2084222100 1
3.3%
1254976959 1
3.3%
626779698 2
6.7%
520811924 1
3.3%
476449172 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2422414.8
Minimum524
Maximum26800000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:39.512299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum524
5-th percentile2011.5
Q123150
median192500
Q3858000
95-th percentile15221500
Maximum26800000
Range26799476
Interquartile range (IQR)834850

Descriptive statistics

Standard deviation6264291.6
Coefficient of variation (CV)2.5859698
Kurtosis10.721827
Mean2422414.8
Median Absolute Deviation (MAD)187920
Skewness3.3375098
Sum72672444
Variance3.9241349 × 1013
MonotonicityNot monotonic
2023-12-10T22:56:39.729388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
858000 2
 
6.7%
3880 1
 
3.3%
7770 1
 
3.3%
158000 1
 
3.3%
29300 1
 
3.3%
524 1
 
3.3%
3270000 1
 
3.3%
138000 1
 
3.3%
698000 1
 
3.3%
376000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
524 1
3.3%
1350 1
3.3%
2820 1
3.3%
3880 1
3.3%
5280 1
3.3%
7220 1
3.3%
7770 1
3.3%
21100 1
3.3%
29300 1
3.3%
59800 1
3.3%
ValueCountFrequency (%)
26800000 1
3.3%
22300000 1
3.3%
6570000 1
3.3%
6210000 1
3.3%
3270000 1
3.3%
1330000 1
3.3%
1270000 1
3.3%
858000 2
6.7%
698000 1
3.3%
442000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91996.233
Minimum4
Maximum1328186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:39.919827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile20.05
Q1684.75
median1343
Q382251.5
95-th percentile297191.9
Maximum1328186
Range1328182
Interquartile range (IQR)81566.75

Descriptive statistics

Standard deviation249045.89
Coefficient of variation (CV)2.7071314
Kurtosis22.492617
Mean91996.233
Median Absolute Deviation (MAD)1321.5
Skewness4.539489
Sum2759887
Variance6.2023858 × 1010
MonotonicityNot monotonic
2023-12-10T22:56:40.135344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
7 1
 
3.3%
894 1
 
3.3%
1004 1
 
3.3%
366 1
 
3.3%
220 1
 
3.3%
1264 1
 
3.3%
16653 1
 
3.3%
4018 1
 
3.3%
615 1
 
3.3%
2049 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4 1
3.3%
7 1
3.3%
36 1
3.3%
161 1
3.3%
220 1
3.3%
262 1
3.3%
366 1
3.3%
615 1
3.3%
894 1
3.3%
903 1
3.3%
ValueCountFrequency (%)
1328186 1
3.3%
365132 1
3.3%
214154 1
3.3%
180987 1
3.3%
158694 1
3.3%
155123 1
3.3%
113191 1
3.3%
84941 1
3.3%
74183 1
3.3%
34530 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)61.5%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean95.080769
Minimum61.5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:40.319854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61.5
5-th percentile80.125
Q194.225
median98.2
Q3100
95-th percentile100
Maximum100
Range38.5
Interquartile range (IQR)5.775

Descriptive statistics

Standard deviation8.5471876
Coefficient of variation (CV)0.089893967
Kurtosis9.6805906
Mean95.080769
Median Absolute Deviation (MAD)1.8
Skewness-2.9363848
Sum2472.1
Variance73.054415
MonotonicityNot monotonic
2023-12-10T22:56:40.530308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
100.0 9
30.0%
98.6 2
 
6.7%
95.2 2
 
6.7%
90.0 1
 
3.3%
99.4 1
 
3.3%
87.1 1
 
3.3%
97.8 1
 
3.3%
93.9 1
 
3.3%
99.5 1
 
3.3%
92.8 1
 
3.3%
Other values (6) 6
20.0%
(Missing) 4
13.3%
ValueCountFrequency (%)
61.5 1
3.3%
77.8 1
3.3%
87.1 1
3.3%
90.0 1
3.3%
92.8 1
3.3%
93.4 1
3.3%
93.9 1
3.3%
95.2 2
6.7%
96.4 1
3.3%
97.4 1
3.3%
ValueCountFrequency (%)
100.0 9
30.0%
99.5 1
 
3.3%
99.4 1
 
3.3%
98.6 2
 
6.7%
97.8 1
 
3.3%
97.5 1
 
3.3%
97.4 1
 
3.3%
96.4 1
 
3.3%
95.2 2
 
6.7%
93.9 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct16
Distinct (%)61.5%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean4.9192308
Minimum0
Maximum38.5
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:40.751245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.8
Q35.775
95-th percentile19.875
Maximum38.5
Range38.5
Interquartile range (IQR)5.775

Descriptive statistics

Standard deviation8.5471876
Coefficient of variation (CV)1.7375049
Kurtosis9.6805906
Mean4.9192308
Median Absolute Deviation (MAD)1.8
Skewness2.9363848
Sum127.9
Variance73.054415
MonotonicityNot monotonic
2023-12-10T22:56:40.960650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.0 9
30.0%
1.4 2
 
6.7%
4.8 2
 
6.7%
10.0 1
 
3.3%
0.6 1
 
3.3%
12.9 1
 
3.3%
2.2 1
 
3.3%
6.1 1
 
3.3%
0.5 1
 
3.3%
7.2 1
 
3.3%
Other values (6) 6
20.0%
(Missing) 4
13.3%
ValueCountFrequency (%)
0.0 9
30.0%
0.5 1
 
3.3%
0.6 1
 
3.3%
1.4 2
 
6.7%
2.2 1
 
3.3%
2.5 1
 
3.3%
2.6 1
 
3.3%
3.6 1
 
3.3%
4.8 2
 
6.7%
6.1 1
 
3.3%
ValueCountFrequency (%)
38.5 1
3.3%
22.2 1
3.3%
12.9 1
3.3%
10.0 1
3.3%
7.2 1
3.3%
6.6 1
3.3%
6.1 1
3.3%
4.8 2
6.7%
3.6 1
3.3%
2.6 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean180.9
Minimum0
Maximum1354
Zeros12
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:56:41.149438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q3126.5
95-th percentile1235.8
Maximum1354
Range1354
Interquartile range (IQR)126.5

Descriptive statistics

Standard deviation386.60408
Coefficient of variation (CV)2.1371149
Kurtosis5.110109
Mean180.9
Median Absolute Deviation (MAD)2
Skewness2.4760166
Sum5427
Variance149462.71
MonotonicityNot monotonic
2023-12-10T22:56:41.320052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 12
40.0%
1 2
 
6.7%
2 2
 
6.7%
137 1
 
3.3%
18 1
 
3.3%
36 1
 
3.3%
74 1
 
3.3%
95 1
 
3.3%
265 1
 
3.3%
1333 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0 12
40.0%
1 2
 
6.7%
2 2
 
6.7%
6 1
 
3.3%
9 1
 
3.3%
18 1
 
3.3%
36 1
 
3.3%
74 1
 
3.3%
95 1
 
3.3%
137 1
 
3.3%
ValueCountFrequency (%)
1354 1
3.3%
1333 1
3.3%
1117 1
3.3%
421 1
3.3%
381 1
3.3%
265 1
3.3%
175 1
3.3%
137 1
3.3%
95 1
3.3%
74 1
3.3%

Interactions

2023-12-10T22:56:34.689441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:29.166298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:30.343080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:31.235372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:32.159606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:33.624779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:34.880318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:29.448850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:30.493841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:31.396980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:32.351999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:33.783555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:35.069456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:29.645039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:30.624535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:31.528069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:32.519148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:33.946244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:35.220795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:29.815959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:30.755677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:31.686055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:32.680773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:34.130723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:35.373770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:29.995858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:30.888811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:31.844992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:32.842865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:34.375420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:35.529121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:30.184968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:31.059263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:32.012296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:33.042972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:56:34.525187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:56:41.499205image/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
이용자활동평가채널조회수1.0001.0001.0000.8120.7560.0000.0000.667
이용자활동평가구독자수1.0001.0000.8121.0000.5860.0000.0000.667
이용자활동평가영상조회수1.0001.0000.7560.5861.0000.0000.0000.856
이용자활동평가긍정평가비율0.0001.0000.0000.0000.0001.0001.0000.000
이용자활동평가부정평가비율0.0001.0000.0000.0000.0001.0001.0000.000
수1.0001.0000.6670.6670.8560.0000.0001.000
2023-12-10T22:56:41.653788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9840.467-0.0410.0410.455
이용자활동평가구독자수0.9841.0000.452-0.0330.0330.467
이용자활동평가영상조회수0.4670.4521.000-0.5030.5030.813
이용자활동평가긍정평가비율-0.041-0.033-0.5031.000-1.000-0.229
이용자활동평가부정평가비율0.0410.0330.503-1.0001.0000.229
수0.4550.4670.813-0.2290.2291.000

Missing values

2023-12-10T22:56:35.696853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:56:35.932505image/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.
2023-12-10T22:56:36.104073image/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/UCwC8xqx6nDDBRKV2sB-tNBAhttps://www.youtube.com/watch?v=F5PG9IJ0eUc2021-04-01119988938807<NA><NA>0
1https://www.youtube.com/channel/UCJUv6GUKdsr3kbEADWeKp-Qhttps://www.youtube.com/watch?v=PzxxP781Bpo2021-04-017143296211001288100.00.09
2https://www.youtube.com/channel/UCYyLIlOJyqkAFKlVjzX5imghttps://www.youtube.com/watch?v=4piwvhJgIqI2021-04-0112549769591270000161100.00.01
3https://www.youtube.com/channel/UCweOkPb1wVVH0Q0Tlj4a5Pwhttps://www.youtube.com/watch?v=AR--iSa7JPA2021-04-01193845215262230000011319199.50.5421
4https://www.youtube.com/channel/UCPde4guD9yFBRzkxk2PatoAhttps://www.youtube.com/watch?v=ha-FxjCwCSc2021-04-013682327590621000090390.010.02
5https://www.youtube.com/channel/UCEf_Bc-KVd7onSeifS3py9ghttps://www.youtube.com/watch?v=yO1sSyDE6XE2021-04-01202038853282680000036513299.40.61354
6https://www.youtube.com/channel/UCWlV3Lz_55UaX4JsMj-z__Qhttps://www.youtube.com/watch?v=MjoZnJ676s02021-04-01626779698858000133487.112.96
7https://www.youtube.com/channel/UCNeHPUKNUBmBMZy_rzHPzSwhttps://www.youtube.com/watch?v=y_v1yp71FY42021-04-0110176446922700015512398.61.4381
8https://www.youtube.com/channel/UCrsWhKQLfeUel3hoWV7qjtwhttps://www.youtube.com/watch?v=XrBpAPcDrXQ2021-04-01230228216650018098797.82.21117
9https://www.youtube.com/channel/UCDIB1DOwPPe58M2fHPyVVDAhttps://www.youtube.com/watch?v=qiPVOfA4iq82021-04-0118507997812700015869493.96.1175
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCuwlFZQgh8FJ42wm06PbtDQhttps://www.youtube.com/watch?v=QSogEj_IsNg2021-04-0134687013504<NA><NA>0
21https://www.youtube.com/channel/UC5fN2gdOeABC3LF_-cxb_0Ahttps://www.youtube.com/watch?v=4lYRloiK_Tc2021-04-0120650393598007418397.42.674
22https://www.youtube.com/channel/UCNFohBYBPwTOZi8TC8GauGQhttps://www.youtube.com/watch?v=djO9o65d0q02021-04-013005544580900204977.822.20
23https://www.youtube.com/channel/UCFw4M1BJYYdN1YtS8SzlDzghttps://www.youtube.com/watch?v=GMlm3KrajnQ2021-04-01102718290376000615100.00.00
24https://www.youtube.com/channel/UC70u2e8gK14R7QfFs7ehNDwhttps://www.youtube.com/watch?v=hZ5vVzJBU7E2021-04-01520811924698000401898.61.42
25https://www.youtube.com/channel/UCff7sQ_kjCEPZvr8h8US8wwhttps://www.youtube.com/watch?v=uKZAcwa3A4w2021-04-011514848913800016653<NA><NA>36
26https://www.youtube.com/channel/UCx_dzPI6efSohgtOkAG43-Ahttps://www.youtube.com/watch?v=IlBGyPbDuvI2021-04-01394388510432700001264100.00.00
27https://www.youtube.com/channel/UCjFMsGohnkFiyHKCBlbxRhghttps://www.youtube.com/watch?v=YwHQINK2ifg2021-04-0154781524220100.00.00
28https://www.youtube.com/channel/UC35SH2IZCoDAyjdM_BKNVlAhttps://www.youtube.com/watch?v=uL4Rn1teLjc2021-04-011479131029300366100.00.018
29https://www.youtube.com/channel/UC41Vyqs1wSY0FTMqDsLsELAhttps://www.youtube.com/watch?v=fO6IxlrCpaM2021-04-012094726281580001004100.00.00