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/d2245937-c2a7-4e43-80e4-f55b7d70da82

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 이용자활동평가부정평가비율 and 1 other fieldsHigh correlation
이용자활동평가부정평가비율 is highly overall correlated with 이용자활동평가긍정평가비율 and 1 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
이용자활동평가부정평가비율 has 10 (33.3%) zerosZeros
수 has 11 (36.7%) zerosZeros

Reproduction

Analysis started2023-12-10 14:00:29.090984
Analysis finished2023-12-10 14:00:36.069495
Duration6.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

이용자활동평가채널ID
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:00:36.382439image/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

Unique26 ?
Unique (%)86.7%

Sample

1st rowhttps://www.youtube.com/channel/UChpjIaEgwtDZtmWEkzFulSA
2nd rowhttps://www.youtube.com/channel/UCFL1sCAksD6_7JIZwwHcwjQ
3rd rowhttps://www.youtube.com/channel/UCv7HX-7ctqTH4cXxT1nfrIg
4th rowhttps://www.youtube.com/channel/UCjrwkxVOpN133r1Yp07583Q
5th rowhttps://www.youtube.com/channel/UCTdZyOFVzontd9MZOJDg8Qw
ValueCountFrequency (%)
https://www.youtube.com/channel/ucv7hx-7ctqth4cxxt1nfrig 2
 
6.7%
https://www.youtube.com/channel/ucfw4m1bjyydn1yts8szldzg 2
 
6.7%
https://www.youtube.com/channel/uchpjiaegwtdztmwekzfulsa 1
 
3.3%
https://www.youtube.com/channel/ucsu-i-vhliamfv_ceayz5rq 1
 
3.3%
https://www.youtube.com/channel/ucyzv9v_bwfmgc64glre34oa 1
 
3.3%
https://www.youtube.com/channel/ucf4wxdo3inmxp-y59wxdsfw 1
 
3.3%
https://www.youtube.com/channel/ucljs55bzwmscbpekt3vssoq 1
 
3.3%
https://www.youtube.com/channel/uc75np7iz7xavglamvo9uanw 1
 
3.3%
https://www.youtube.com/channel/ucuwlfzqgh8fj42wm06pbtdq 1
 
3.3%
https://www.youtube.com/channel/ucyu5jq8kvrd9je4e_xlshxw 1
 
3.3%
Other values (18) 18
60.0%
2023-12-10T23:00:37.010758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 118
 
7.0%
t 101
 
6.0%
c 76
 
4.5%
n 73
 
4.3%
o 71
 
4.2%
h 66
 
3.9%
e 64
 
3.8%
u 63
 
3.8%
. 60
 
3.6%
Other values (57) 868
51.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1036
61.7%
Uppercase Letter 307
 
18.3%
Other Punctuation 210
 
12.5%
Decimal Number 110
 
6.5%
Connector Punctuation 10
 
0.6%
Dash Punctuation 7
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 118
 
11.4%
t 101
 
9.7%
c 76
 
7.3%
n 73
 
7.0%
o 71
 
6.9%
h 66
 
6.4%
e 64
 
6.2%
u 63
 
6.1%
s 47
 
4.5%
l 44
 
4.2%
Other values (16) 313
30.2%
Uppercase Letter
ValueCountFrequency (%)
C 36
 
11.7%
U 35
 
11.4%
Z 17
 
5.5%
F 13
 
4.2%
L 13
 
4.2%
Y 12
 
3.9%
D 12
 
3.9%
J 12
 
3.9%
Q 12
 
3.9%
A 11
 
3.6%
Other values (16) 134
43.6%
Decimal Number
ValueCountFrequency (%)
4 20
18.2%
1 20
18.2%
3 13
11.8%
5 13
11.8%
7 12
10.9%
8 9
8.2%
9 8
 
7.3%
6 7
 
6.4%
0 4
 
3.6%
2 4
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1343
79.9%
Common 337
 
20.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 118
 
8.8%
t 101
 
7.5%
c 76
 
5.7%
n 73
 
5.4%
o 71
 
5.3%
h 66
 
4.9%
e 64
 
4.8%
u 63
 
4.7%
s 47
 
3.5%
l 44
 
3.3%
Other values (42) 620
46.2%
Common
ValueCountFrequency (%)
/ 120
35.6%
. 60
17.8%
: 30
 
8.9%
4 20
 
5.9%
1 20
 
5.9%
3 13
 
3.9%
5 13
 
3.9%
7 12
 
3.6%
_ 10
 
3.0%
8 9
 
2.7%
Other values (5) 30
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 118
 
7.0%
t 101
 
6.0%
c 76
 
4.5%
n 73
 
4.3%
o 71
 
4.2%
h 66
 
3.9%
e 64
 
3.8%
u 63
 
3.8%
. 60
 
3.6%
Other values (57) 868
51.7%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:00:37.550345image/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=L-SAWibvwaM
2nd rowhttps://www.youtube.com/watch?v=Lz770wfucMY
3rd rowhttps://www.youtube.com/watch?v=sL3SiaMx6kc
4th rowhttps://www.youtube.com/watch?v=8VWA4CmoVKY
5th rowhttps://www.youtube.com/watch?v=uPV89vg7Ba4
ValueCountFrequency (%)
https://www.youtube.com/watch?v=l-sawibvwam 1
 
3.3%
https://www.youtube.com/watch?v=lz770wfucmy 1
 
3.3%
https://www.youtube.com/watch?v=injm9i1yopa 1
 
3.3%
https://www.youtube.com/watch?v=gvfdhbwuvwa 1
 
3.3%
https://www.youtube.com/watch?v=lq1xeizsdbs 1
 
3.3%
https://www.youtube.com/watch?v=wpluyxz_iuy 1
 
3.3%
https://www.youtube.com/watch?v=iwbtxks_vlg 1
 
3.3%
https://www.youtube.com/watch?v=3j65-jikgto 1
 
3.3%
https://www.youtube.com/watch?v=pfqdwev_vqo 1
 
3.3%
https://www.youtube.com/watch?v=_-zhgndfneg 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:00:38.113269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 129
 
10.0%
t 123
 
9.5%
/ 90
 
7.0%
o 68
 
5.3%
u 68
 
5.3%
h 63
 
4.9%
c 63
 
4.9%
. 60
 
4.7%
s 38
 
2.9%
a 36
 
2.8%
Other values (59) 552
42.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 855
66.3%
Other Punctuation 210
 
16.3%
Uppercase Letter 139
 
10.8%
Decimal Number 45
 
3.5%
Math Symbol 30
 
2.3%
Dash Punctuation 6
 
0.5%
Connector Punctuation 5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 129
15.1%
t 123
14.4%
o 68
 
8.0%
u 68
 
8.0%
h 63
 
7.4%
c 63
 
7.4%
s 38
 
4.4%
a 36
 
4.2%
v 35
 
4.1%
y 35
 
4.1%
Other values (16) 197
23.0%
Uppercase Letter
ValueCountFrequency (%)
W 10
 
7.2%
M 10
 
7.2%
Y 10
 
7.2%
K 8
 
5.8%
V 8
 
5.8%
A 8
 
5.8%
I 7
 
5.0%
E 7
 
5.0%
D 7
 
5.0%
T 6
 
4.3%
Other values (16) 58
41.7%
Decimal Number
ValueCountFrequency (%)
1 8
17.8%
8 7
15.6%
9 6
13.3%
6 5
11.1%
3 5
11.1%
7 4
8.9%
0 3
 
6.7%
4 3
 
6.7%
2 2
 
4.4%
5 2
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
? 30
 
14.3%
: 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 994
77.1%
Common 296
 
22.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 129
 
13.0%
t 123
 
12.4%
o 68
 
6.8%
u 68
 
6.8%
h 63
 
6.3%
c 63
 
6.3%
s 38
 
3.8%
a 36
 
3.6%
v 35
 
3.5%
y 35
 
3.5%
Other values (42) 336
33.8%
Common
ValueCountFrequency (%)
/ 90
30.4%
. 60
20.3%
? 30
 
10.1%
: 30
 
10.1%
= 30
 
10.1%
1 8
 
2.7%
8 7
 
2.4%
- 6
 
2.0%
9 6
 
2.0%
_ 5
 
1.7%
Other values (7) 24
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 129
 
10.0%
t 123
 
9.5%
/ 90
 
7.0%
o 68
 
5.3%
u 68
 
5.3%
h 63
 
4.9%
c 63
 
4.9%
. 60
 
4.7%
s 38
 
2.9%
a 36
 
2.8%
Other values (59) 552
42.8%

이용자활동평가생성기간
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-09-01 00:00:00
Maximum2021-09-01 00:00:00
2023-12-10T23:00:38.305156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:38.471985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0677903 × 109
Minimum378276
Maximum9.7826716 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:38.673211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum378276
5-th percentile3149923.5
Q190504052
median2.2577341 × 108
Q38.3253692 × 108
95-th percentile3.9353537 × 109
Maximum9.7826716 × 109
Range9.7822933 × 109
Interquartile range (IQR)7.4203287 × 108

Descriptive statistics

Standard deviation2.0110956 × 109
Coefficient of variation (CV)1.8834181
Kurtosis12.107637
Mean1.0677903 × 109
Median Absolute Deviation (MAD)2.1764693 × 108
Skewness3.2152147
Sum3.203371 × 1010
Variance4.0445057 × 1018
MonotonicityNot monotonic
2023-12-10T23:00:38.862634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
130387596 2
 
6.7%
149793677 2
 
6.7%
4285622419 1
 
3.3%
29981837 1
 
3.3%
254618034 1
 
3.3%
1723770894 1
 
3.3%
3507247537 1
 
3.3%
434989414 1
 
3.3%
12944797 1
 
3.3%
378276 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
378276 1
3.3%
3020445 1
3.3%
3308175 1
3.3%
12944797 1
3.3%
26995859 1
3.3%
29981837 1
3.3%
54364920 1
3.3%
79002775 1
3.3%
125007882 1
3.3%
130387596 2
6.7%
ValueCountFrequency (%)
9782671568 1
3.3%
4285622419 1
3.3%
3507247537 1
3.3%
3312794109 1
3.3%
2456753876 1
3.3%
1723770894 1
3.3%
1607542594 1
3.3%
880629525 1
3.3%
688259095 1
3.3%
571833647 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean944671
Minimum1420
Maximum6870000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:39.055481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1420
5-th percentile17035.5
Q1163000
median512000
Q3966750
95-th percentile3066000
Maximum6870000
Range6868580
Interquartile range (IQR)803750

Descriptive statistics

Standard deviation1390139.9
Coefficient of variation (CV)1.4715598
Kurtosis11.306709
Mean944671
Median Absolute Deviation (MAD)409500
Skewness3.0747621
Sum28340130
Variance1.9324888 × 1012
MonotonicityNot monotonic
2023-12-10T23:00:39.244566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
163000 2
 
6.7%
490000 2
 
6.7%
3480000 1
 
3.3%
74400 1
 
3.3%
654000 1
 
3.3%
1360000 1
 
3.3%
1530000 1
 
3.3%
601000 1
 
3.3%
59900 1
 
3.3%
1420 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
1420 1
3.3%
7410 1
3.3%
28800 1
3.3%
59900 1
3.3%
74400 1
3.3%
89200 1
3.3%
111000 1
3.3%
163000 2
6.7%
217000 1
3.3%
329000 1
3.3%
ValueCountFrequency (%)
6870000 1
3.3%
3480000 1
3.3%
2560000 1
3.3%
2120000 1
3.3%
1720000 1
3.3%
1530000 1
3.3%
1360000 1
3.3%
979000 1
3.3%
930000 1
3.3%
865000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134827.9
Minimum39
Maximum3330109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:39.445664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile53.2
Q1806.5
median2824.5
Q323335.75
95-th percentile214320.75
Maximum3330109
Range3330070
Interquartile range (IQR)22529.25

Descriptive statistics

Standard deviation606519.4
Coefficient of variation (CV)4.498471
Kurtosis29.340657
Mean134827.9
Median Absolute Deviation (MAD)2677
Skewness5.3941453
Sum4044837
Variance3.6786578 × 1011
MonotonicityNot monotonic
2023-12-10T23:00:39.974507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2478 1
 
3.3%
4085 1
 
3.3%
2969 1
 
3.3%
880 1
 
3.3%
2680 1
 
3.3%
67886 1
 
3.3%
41237 1
 
3.3%
39 1
 
3.3%
233 1
 
3.3%
19528 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
39 1
3.3%
46 1
3.3%
62 1
3.3%
233 1
3.3%
242 1
3.3%
324 1
3.3%
553 1
3.3%
802 1
3.3%
820 1
3.3%
855 1
3.3%
ValueCountFrequency (%)
3330109 1
3.3%
321135 1
3.3%
83770 1
3.3%
67886 1
3.3%
65316 1
3.3%
43280 1
3.3%
41237 1
3.3%
24605 1
3.3%
19528 1
3.3%
10212 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)61.5%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean95.603846
Minimum67.1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:40.202435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67.1
5-th percentile84.475
Q194.775
median97.95
Q3100
95-th percentile100
Maximum100
Range32.9
Interquartile range (IQR)5.225

Descriptive statistics

Standard deviation7.1611441
Coefficient of variation (CV)0.074904351
Kurtosis9.9704234
Mean95.603846
Median Absolute Deviation (MAD)2.05
Skewness-2.909324
Sum2485.7
Variance51.281985
MonotonicityNot monotonic
2023-12-10T23:00:40.381431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
100.0 10
33.3%
94.7 2
 
6.7%
97.1 1
 
3.3%
83.3 1
 
3.3%
95.4 1
 
3.3%
93.9 1
 
3.3%
88.0 1
 
3.3%
98.1 1
 
3.3%
98.4 1
 
3.3%
95.0 1
 
3.3%
Other values (6) 6
20.0%
(Missing) 4
 
13.3%
ValueCountFrequency (%)
67.1 1
3.3%
83.3 1
3.3%
88.0 1
3.3%
90.5 1
3.3%
93.9 1
3.3%
94.7 2
6.7%
95.0 1
3.3%
95.2 1
3.3%
95.4 1
3.3%
97.1 1
3.3%
ValueCountFrequency (%)
100.0 10
33.3%
98.9 1
 
3.3%
98.4 1
 
3.3%
98.1 1
 
3.3%
97.8 1
 
3.3%
97.6 1
 
3.3%
97.1 1
 
3.3%
95.4 1
 
3.3%
95.2 1
 
3.3%
95.0 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct16
Distinct (%)61.5%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean4.3961538
Minimum0
Maximum32.9
Zeros10
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:40.569540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.05
Q35.225
95-th percentile15.525
Maximum32.9
Range32.9
Interquartile range (IQR)5.225

Descriptive statistics

Standard deviation7.1611441
Coefficient of variation (CV)1.6289567
Kurtosis9.9704234
Mean4.3961538
Median Absolute Deviation (MAD)2.05
Skewness2.909324
Sum114.3
Variance51.281985
MonotonicityNot monotonic
2023-12-10T23:00:40.822067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.0 10
33.3%
5.3 2
 
6.7%
2.9 1
 
3.3%
16.7 1
 
3.3%
4.6 1
 
3.3%
6.1 1
 
3.3%
12.0 1
 
3.3%
1.9 1
 
3.3%
1.6 1
 
3.3%
5.0 1
 
3.3%
Other values (6) 6
20.0%
(Missing) 4
 
13.3%
ValueCountFrequency (%)
0.0 10
33.3%
1.1 1
 
3.3%
1.6 1
 
3.3%
1.9 1
 
3.3%
2.2 1
 
3.3%
2.4 1
 
3.3%
2.9 1
 
3.3%
4.6 1
 
3.3%
4.8 1
 
3.3%
5.0 1
 
3.3%
ValueCountFrequency (%)
32.9 1
3.3%
16.7 1
3.3%
12.0 1
3.3%
9.5 1
3.3%
6.1 1
3.3%
5.3 2
6.7%
5.0 1
3.3%
4.8 1
3.3%
4.6 1
3.3%
2.9 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.633333
Minimum0
Maximum967
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:41.127356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q319.25
95-th percentile557.95
Maximum967
Range967
Interquartile range (IQR)19.25

Descriptive statistics

Standard deviation235.42251
Coefficient of variation (CV)2.781676
Kurtosis11.27165
Mean84.633333
Median Absolute Deviation (MAD)4
Skewness3.4692814
Sum2539
Variance55423.757
MonotonicityNot monotonic
2023-12-10T23:00:41.431432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 11
36.7%
1 3
 
10.0%
11 2
 
6.7%
13 1
 
3.3%
125 1
 
3.3%
133 1
 
3.3%
135 1
 
3.3%
2 1
 
3.3%
21 1
 
3.3%
113 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0 11
36.7%
1 3
 
10.0%
2 1
 
3.3%
6 1
 
3.3%
7 1
 
3.3%
8 1
 
3.3%
11 2
 
6.7%
13 1
 
3.3%
14 1
 
3.3%
21 1
 
3.3%
ValueCountFrequency (%)
967 1
3.3%
904 1
3.3%
135 1
3.3%
133 1
3.3%
125 1
3.3%
113 1
3.3%
66 1
3.3%
21 1
3.3%
14 1
3.3%
13 1
3.3%

Interactions

2023-12-10T23:00:34.227225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:29.500376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:30.584896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:31.562024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:32.430346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:33.314601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:34.413723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:29.680033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:30.747650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:31.698632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:32.596591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:33.449089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:34.602587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:29.899299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:30.892066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:31.858791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:32.772723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:33.617357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:34.759403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:30.047138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:31.044308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:31.993696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:32.924968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:33.786590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:34.917449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:30.192865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:31.250000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:32.139714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:33.060545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:33.926095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:35.061669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:30.332351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:31.417384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:32.282311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:33.199216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:34.077597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:00:41.586037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0001.0000.9620.9621.000
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0000.9770.8070.0000.0000.000
이용자활동평가구독자수1.0001.0000.9771.0000.8070.0000.0000.000
이용자활동평가영상조회수1.0001.0000.8070.8071.0000.0000.0000.427
이용자활동평가긍정평가비율0.9621.0000.0000.0000.0001.0001.0000.706
이용자활동평가부정평가비율0.9621.0000.0000.0000.0001.0001.0000.706
수1.0001.0000.0000.0000.4270.7060.7061.000
2023-12-10T23:00:41.799648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9630.291-0.0490.0490.124
이용자활동평가구독자수0.9631.0000.311-0.0580.0580.078
이용자활동평가영상조회수0.2910.3111.000-0.4900.4900.731
이용자활동평가긍정평가비율-0.049-0.058-0.4901.000-1.000-0.635
이용자활동평가부정평가비율0.0490.0580.490-1.0001.0000.635
수0.1240.0780.731-0.6350.6351.000

Missing values

2023-12-10T23:00:35.249405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:00:35.647499image/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.
2023-12-10T23:00:35.893210image/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/UChpjIaEgwtDZtmWEkzFulSAhttps://www.youtube.com/watch?v=L-SAWibvwaM2021-09-01428562241934800002478100.00.00
1https://www.youtube.com/channel/UCFL1sCAksD6_7JIZwwHcwjQhttps://www.youtube.com/watch?v=Lz770wfucMY2021-09-0197826715686870000802100.00.00
2https://www.youtube.com/channel/UCv7HX-7ctqTH4cXxT1nfrIghttps://www.youtube.com/watch?v=sL3SiaMx6kc2021-09-0113038759616300062100.00.00
3https://www.youtube.com/channel/UCjrwkxVOpN133r1Yp07583Qhttps://www.youtube.com/watch?v=8VWA4CmoVKY2021-09-012089452725340002460598.11.98
4https://www.youtube.com/channel/UCTdZyOFVzontd9MZOJDg8Qwhttps://www.youtube.com/watch?v=uPV89vg7Ba42021-09-0126995859111000661197.12.97
5https://www.youtube.com/channel/UC4LW3sOslC14Vn5bcoNUBkghttps://www.youtube.com/watch?v=Ql6KDPWD92k2021-09-015718336479790007028100.00.00
6https://www.youtube.com/channel/UCnx4Fi4cmkLGDiFfZ311wWwhttps://www.youtube.com/watch?v=onEJnHGT1Oc2021-09-0116075425942120000333010994.75.3904
7https://www.youtube.com/channel/UCWlV3Lz_55UaX4JsMj-z__Qhttps://www.youtube.com/watch?v=MZP9xez3vms2021-09-0168825909593000082083.316.76
8https://www.youtube.com/channel/UCG9aFJTZ-lMCHAiO1KJsirghttps://www.youtube.com/watch?v=4duxu-f-f1Q2021-09-01880629525865000324100.00.00
9https://www.youtube.com/channel/UCHsNxA14lzqnrm0mW7GQIXAhttps://www.youtube.com/watch?v=-adysaCh8VI2021-09-0150913758954500032113595.44.6967
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCqgRbodod44OjLp9tqpgkPwhttps://www.youtube.com/watch?v=HKKK98AmD8g2021-09-015436492089200173795.05.013
21https://www.youtube.com/channel/UCilYpdgaNbW8x8_E83vomNwhttps://www.youtube.com/watch?v=_-zhGndFNEg2021-09-012426015563290008377095.24.8113
22https://www.youtube.com/channel/UCyHvSKT_bLDYpkv1JjjsLAghttps://www.youtube.com/watch?v=pfqdwEV_vQo2021-09-014760804764540001952897.62.421
23https://www.youtube.com/channel/UCyU5JQ8KVRD9jE4E_xLsHxwhttps://www.youtube.com/watch?v=3j65-JIkgto2021-09-0130204457410233<NA><NA>2
24https://www.youtube.com/channel/UCuwlFZQgh8FJ42wm06PbtDQhttps://www.youtube.com/watch?v=iwBTxKs_Vlg2021-09-01378276142039<NA><NA>0
25https://www.youtube.com/channel/UC75nP7IZ7xavGlAmVo9uAnwhttps://www.youtube.com/watch?v=WPLuYXZ_iuY2021-09-0112944797599004123798.91.1135
26https://www.youtube.com/channel/UCLJs55bZWMsCBPekt3vssoQhttps://www.youtube.com/watch?v=lq1xEIZSdBs2021-09-0143498941460100067886<NA><NA>133
27https://www.youtube.com/channel/UCF4Wxdo3inmxP-Y59wXDsFwhttps://www.youtube.com/watch?v=GvfDHBWuVWA2021-09-0135072475371530000268067.132.9125
28https://www.youtube.com/channel/UCYZv9v_bwfMGc64gLRe34OAhttps://www.youtube.com/watch?v=injM9I1YopA2021-09-0117237708941360000880100.00.00
29https://www.youtube.com/channel/UC1CBlwiPRgnrXTcODGRxbZwhttps://www.youtube.com/watch?v=OweyJVTQ7CE2021-09-01254618034654000296990.59.50