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/3500e611-a7a2-48fe-9033-17403d0af2d9

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 2 (6.7%) missing valuesMissing
이용자활동평가부정평가비율 has 2 (6.7%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가부정평가비율 has 10 (33.3%) zerosZeros
수 has 7 (23.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:12:47.073757
Analysis finished2023-12-10 14:12:54.586415
Duration7.51 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
2023-12-10T23:12:54.953396image/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

Unique27 ?
Unique (%)90.0%

Sample

1st rowhttps://www.youtube.com/channel/UC22go5LdQEw-iDuxFb4C0hw
2nd rowhttps://www.youtube.com/channel/UCiBr0bK06imaMbLc8sAEz0A
3rd rowhttps://www.youtube.com/channel/UC12XQWcIlaavjjbhh6EeMJw
4th rowhttps://www.youtube.com/channel/UCDEOj33PPDR-Hw9RxdKfjpw
5th rowhttps://www.youtube.com/channel/UC4DgFN9dvM0DPXXvsS3FO-w
ValueCountFrequency (%)
https://www.youtube.com/channel/uc5hsw5oy2vfvfsihpib-avq 3
 
10.0%
https://www.youtube.com/channel/uc22go5ldqew-iduxfb4c0hw 1
 
3.3%
https://www.youtube.com/channel/ucibr0bk06imamblc8saez0a 1
 
3.3%
https://www.youtube.com/channel/ucy7h0ug0btro-x9rx8opdgg 1
 
3.3%
https://www.youtube.com/channel/ucxnstq6suzpafsmb-5nybxa 1
 
3.3%
https://www.youtube.com/channel/uc3m0s5xaqydctblhc8j1uog 1
 
3.3%
https://www.youtube.com/channel/uchlsejxrixzwmarc2omwmcq 1
 
3.3%
https://www.youtube.com/channel/ucmip5tn3nhknykkgvfbhteg 1
 
3.3%
https://www.youtube.com/channel/ucmjnkt6kitwaztqvwuasplg 1
 
3.3%
https://www.youtube.com/channel/ucvg7coejm6ud_ronuddiofw 1
 
3.3%
Other values (18) 18
60.0%
2023-12-10T23:12:55.618517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 111
 
6.6%
t 100
 
6.0%
h 78
 
4.6%
c 71
 
4.2%
o 70
 
4.2%
n 69
 
4.1%
e 69
 
4.1%
u 68
 
4.0%
. 60
 
3.6%
Other values (57) 864
51.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1043
62.1%
Uppercase Letter 329
 
19.6%
Other Punctuation 210
 
12.5%
Decimal Number 86
 
5.1%
Dash Punctuation 9
 
0.5%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 111
 
10.6%
t 100
 
9.6%
h 78
 
7.5%
c 71
 
6.8%
o 70
 
6.7%
n 69
 
6.6%
e 69
 
6.6%
u 68
 
6.5%
m 44
 
4.2%
b 41
 
3.9%
Other values (16) 322
30.9%
Uppercase Letter
ValueCountFrequency (%)
C 40
 
12.2%
U 37
 
11.2%
A 24
 
7.3%
S 17
 
5.2%
H 13
 
4.0%
Q 13
 
4.0%
M 13
 
4.0%
I 13
 
4.0%
D 13
 
4.0%
X 13
 
4.0%
Other values (16) 133
40.4%
Decimal Number
ValueCountFrequency (%)
5 12
14.0%
2 11
12.8%
9 10
11.6%
0 10
11.6%
4 10
11.6%
3 9
10.5%
8 8
9.3%
6 7
8.1%
7 5
5.8%
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 1372
81.7%
Common 308
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 111
 
8.1%
t 100
 
7.3%
h 78
 
5.7%
c 71
 
5.2%
o 70
 
5.1%
n 69
 
5.0%
e 69
 
5.0%
u 68
 
5.0%
m 44
 
3.2%
b 41
 
3.0%
Other values (42) 651
47.4%
Common
ValueCountFrequency (%)
/ 120
39.0%
. 60
19.5%
: 30
 
9.7%
5 12
 
3.9%
2 11
 
3.6%
9 10
 
3.2%
0 10
 
3.2%
4 10
 
3.2%
- 9
 
2.9%
3 9
 
2.9%
Other values (5) 27
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 111
 
6.6%
t 100
 
6.0%
h 78
 
4.6%
c 71
 
4.2%
o 70
 
4.2%
n 69
 
4.1%
e 69
 
4.1%
u 68
 
4.0%
. 60
 
3.6%
Other values (57) 864
51.4%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:12:56.008426image/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=7s5h_CFpFsU
2nd rowhttps://www.youtube.com/watch?v=P9OomFksKR0
3rd rowhttps://www.youtube.com/watch?v=AvW7Mbh_wjA
4th rowhttps://www.youtube.com/watch?v=RuafJp4j2Gk
5th rowhttps://www.youtube.com/watch?v=wJB7cFCm3Sc
ValueCountFrequency (%)
https://www.youtube.com/watch?v=7s5h_cfpfsu 1
 
3.3%
https://www.youtube.com/watch?v=p9oomfkskr0 1
 
3.3%
https://www.youtube.com/watch?v=eulmgcbd6-q 1
 
3.3%
https://www.youtube.com/watch?v=nysa_bwggbu 1
 
3.3%
https://www.youtube.com/watch?v=d0bwqlcahky 1
 
3.3%
https://www.youtube.com/watch?v=lxvofydxwum 1
 
3.3%
https://www.youtube.com/watch?v=fey_czjep-g 1
 
3.3%
https://www.youtube.com/watch?v=bre7owb2mva 1
 
3.3%
https://www.youtube.com/watch?v=3grr1382dds 1
 
3.3%
https://www.youtube.com/watch?v=ipuade2fhku 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:12:56.625230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 129
 
10.0%
t 120
 
9.3%
/ 90
 
7.0%
h 68
 
5.3%
o 67
 
5.2%
c 67
 
5.2%
u 65
 
5.0%
. 60
 
4.7%
s 38
 
2.9%
b 37
 
2.9%
Other values (59) 549
42.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 856
66.4%
Other Punctuation 210
 
16.3%
Uppercase Letter 135
 
10.5%
Decimal Number 49
 
3.8%
Math Symbol 30
 
2.3%
Connector Punctuation 6
 
0.5%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 129
15.1%
t 120
14.0%
h 68
 
7.9%
o 67
 
7.8%
c 67
 
7.8%
u 65
 
7.6%
s 38
 
4.4%
b 37
 
4.3%
v 37
 
4.3%
m 36
 
4.2%
Other values (16) 192
22.4%
Uppercase Letter
ValueCountFrequency (%)
F 13
 
9.6%
A 12
 
8.9%
U 11
 
8.1%
E 9
 
6.7%
R 8
 
5.9%
P 7
 
5.2%
C 6
 
4.4%
W 6
 
4.4%
I 6
 
4.4%
X 5
 
3.7%
Other values (16) 52
38.5%
Decimal Number
ValueCountFrequency (%)
7 10
20.4%
6 6
12.2%
3 6
12.2%
2 6
12.2%
5 5
10.2%
8 4
 
8.2%
9 4
 
8.2%
0 4
 
8.2%
4 3
 
6.1%
1 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
: 30
 
14.3%
? 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 991
76.8%
Common 299
 
23.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 129
 
13.0%
t 120
 
12.1%
h 68
 
6.9%
o 67
 
6.8%
c 67
 
6.8%
u 65
 
6.6%
s 38
 
3.8%
b 37
 
3.7%
v 37
 
3.7%
m 36
 
3.6%
Other values (42) 327
33.0%
Common
ValueCountFrequency (%)
/ 90
30.1%
. 60
20.1%
: 30
 
10.0%
= 30
 
10.0%
? 30
 
10.0%
7 10
 
3.3%
6 6
 
2.0%
_ 6
 
2.0%
3 6
 
2.0%
2 6
 
2.0%
Other values (7) 25
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 129
 
10.0%
t 120
 
9.3%
/ 90
 
7.0%
h 68
 
5.3%
o 67
 
5.2%
c 67
 
5.2%
u 65
 
5.0%
. 60
 
4.7%
s 38
 
2.9%
b 37
 
2.9%
Other values (59) 549
42.6%

이용자활동평가생성기간
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-07-01 00:00:00
Maximum2021-07-01 00:00:00
2023-12-10T23:12:56.812856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:56.960809image/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%
Mean1.6621679 × 109
Minimum21731
Maximum1.4036322 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:12:57.127302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21731
5-th percentile377449.35
Q152246145
median2.8322786 × 108
Q38.1236292 × 108
95-th percentile9.5615042 × 109
Maximum1.4036322 × 1010
Range1.40363 × 1010
Interquartile range (IQR)7.6011678 × 108

Descriptive statistics

Standard deviation3.4452586 × 109
Coefficient of variation (CV)2.0727501
Kurtosis7.5077128
Mean1.6621679 × 109
Median Absolute Deviation (MAD)2.7913282 × 108
Skewness2.7957421
Sum4.9865036 × 1010
Variance1.1869807 × 1019
MonotonicityNot monotonic
2023-12-10T23:12:57.371956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
812362925 3
 
10.0%
3660936170 1
 
3.3%
220775449 1
 
3.3%
265013392 1
 
3.3%
560957902 1
 
3.3%
50703 1
 
3.3%
1381061078 1
 
3.3%
535398043 1
 
3.3%
35600339 1
 
3.3%
6457021171 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
21731 1
3.3%
50703 1
3.3%
776806 1
3.3%
912523 1
3.3%
2692259 1
3.3%
6123016 1
3.3%
35600339 1
3.3%
51750951 1
3.3%
53731727 1
3.3%
63042170 1
3.3%
ValueCountFrequency (%)
14036321665 1
 
3.3%
12101535821 1
 
3.3%
6457021171 1
 
3.3%
4196972304 1
 
3.3%
3660936170 1
 
3.3%
2418804462 1
 
3.3%
1381061078 1
 
3.3%
812362925 3
10.0%
560957902 1
 
3.3%
535398043 1
 
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1650762.6
Minimum167
Maximum16400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:12:57.592129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum167
5-th percentile1055
Q1162750
median426500
Q31070000
95-th percentile7110500
Maximum16400000
Range16399833
Interquartile range (IQR)907250

Descriptive statistics

Standard deviation3359481.9
Coefficient of variation (CV)2.0351091
Kurtosis13.211263
Mean1650762.6
Median Absolute Deviation (MAD)423755
Skewness3.4398554
Sum49522877
Variance1.1286119 × 1013
MonotonicityNot monotonic
2023-12-10T23:12:57.804052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1070000 3
 
10.0%
4040000 1
 
3.3%
529000 1
 
3.3%
405000 1
 
3.3%
715000 1
 
3.3%
1010 1
 
3.3%
1480000 1
 
3.3%
694000 1
 
3.3%
226000 1
 
3.3%
5620000 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
167 1
3.3%
1010 1
3.3%
1110 1
3.3%
1210 1
3.3%
4280 1
3.3%
25100 1
3.3%
108000 1
3.3%
151000 1
3.3%
198000 1
3.3%
202000 1
3.3%
ValueCountFrequency (%)
16400000 1
 
3.3%
8330000 1
 
3.3%
5620000 1
 
3.3%
4040000 1
 
3.3%
3450000 1
 
3.3%
1550000 1
 
3.3%
1480000 1
 
3.3%
1070000 3
10.0%
913000 1
 
3.3%
715000 1
 
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66602.3
Minimum125
Maximum994237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:12:58.183797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125
5-th percentile275.45
Q1734.5
median6809.5
Q330571.5
95-th percentile263210.5
Maximum994237
Range994112
Interquartile range (IQR)29837

Descriptive statistics

Standard deviation187817.02
Coefficient of variation (CV)2.8199781
Kurtosis22.032372
Mean66602.3
Median Absolute Deviation (MAD)6463
Skewness4.5126944
Sum1998069
Variance3.5275235 × 1010
MonotonicityNot monotonic
2023-12-10T23:12:58.403650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
23891 1
 
3.3%
373 1
 
3.3%
13091 1
 
3.3%
24153 1
 
3.3%
648 1
 
3.3%
17763 1
 
3.3%
125 1
 
3.3%
4243 1
 
3.3%
994 1
 
3.3%
60051 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
125 1
3.3%
239 1
3.3%
320 1
3.3%
373 1
3.3%
528 1
3.3%
589 1
3.3%
609 1
3.3%
648 1
3.3%
994 1
3.3%
1582 1
3.3%
ValueCountFrequency (%)
994237 1
3.3%
297280 1
3.3%
221570 1
3.3%
113526 1
3.3%
83786 1
3.3%
60051 1
3.3%
57841 1
3.3%
32711 1
3.3%
24153 1
3.3%
23891 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)64.3%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean96.339286
Minimum68.2
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:12:58.587525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68.2
5-th percentile88.045
Q195.3
median98.75
Q3100
95-th percentile100
Maximum100
Range31.8
Interquartile range (IQR)4.7

Descriptive statistics

Standard deviation6.4444831
Coefficient of variation (CV)0.066893615
Kurtosis13.756578
Mean96.339286
Median Absolute Deviation (MAD)1.25
Skewness-3.3994798
Sum2697.5
Variance41.531362
MonotonicityNot monotonic
2023-12-10T23:12:58.763137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
100.0 10
33.3%
98.8 2
 
6.7%
98.2 1
 
3.3%
94.2 1
 
3.3%
68.2 1
 
3.3%
99.4 1
 
3.3%
88.5 1
 
3.3%
99.7 1
 
3.3%
96.4 1
 
3.3%
96.9 1
 
3.3%
Other values (8) 8
26.7%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
68.2 1
3.3%
87.8 1
3.3%
88.5 1
3.3%
94.0 1
3.3%
94.2 1
3.3%
94.3 1
3.3%
95.0 1
3.3%
95.4 1
3.3%
95.6 1
3.3%
96.4 1
3.3%
ValueCountFrequency (%)
100.0 10
33.3%
99.7 1
 
3.3%
99.4 1
 
3.3%
98.8 2
 
6.7%
98.7 1
 
3.3%
98.2 1
 
3.3%
97.6 1
 
3.3%
96.9 1
 
3.3%
96.4 1
 
3.3%
95.6 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct18
Distinct (%)64.3%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean3.6642857
Minimum0
Maximum31.8
Zeros10
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:12:58.948624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.3
Q34.7
95-th percentile11.955
Maximum31.8
Range31.8
Interquartile range (IQR)4.7

Descriptive statistics

Standard deviation6.4430965
Coefficient of variation (CV)1.7583499
Kurtosis13.762423
Mean3.6642857
Median Absolute Deviation (MAD)1.3
Skewness3.4001443
Sum102.6
Variance41.513492
MonotonicityNot monotonic
2023-12-10T23:12:59.148521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 10
33.3%
1.3 2
 
6.7%
3.6 1
 
3.3%
5.8 1
 
3.3%
31.8 1
 
3.3%
0.6 1
 
3.3%
1.2 1
 
3.3%
11.5 1
 
3.3%
0.3 1
 
3.3%
3.1 1
 
3.3%
Other values (8) 8
26.7%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
0.0 10
33.3%
0.3 1
 
3.3%
0.6 1
 
3.3%
1.2 1
 
3.3%
1.3 2
 
6.7%
1.8 1
 
3.3%
2.4 1
 
3.3%
3.1 1
 
3.3%
3.6 1
 
3.3%
4.4 1
 
3.3%
ValueCountFrequency (%)
31.8 1
3.3%
12.2 1
3.3%
11.5 1
3.3%
6.0 1
3.3%
5.8 1
3.3%
5.7 1
3.3%
5.0 1
3.3%
4.6 1
3.3%
4.4 1
3.3%
3.6 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.33333
Minimum0
Maximum1373
Zeros7
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:12:59.365625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median12.5
Q378.75
95-th percentile395.85
Maximum1373
Range1373
Interquartile range (IQR)77.75

Descriptive statistics

Standard deviation262.49234
Coefficient of variation (CV)2.515901
Kurtosis19.98335
Mean104.33333
Median Absolute Deviation (MAD)12.5
Skewness4.2455839
Sum3130
Variance68902.23
MonotonicityNot monotonic
2023-12-10T23:12:59.593379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 7
23.3%
1 4
13.3%
13 2
 
6.7%
3 2
 
6.7%
69 1
 
3.3%
12 1
 
3.3%
16 1
 
3.3%
75 1
 
3.3%
24 1
 
3.3%
149 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
0 7
23.3%
1 4
13.3%
2 1
 
3.3%
3 2
 
6.7%
12 1
 
3.3%
13 2
 
6.7%
16 1
 
3.3%
24 1
 
3.3%
35 1
 
3.3%
69 1
 
3.3%
ValueCountFrequency (%)
1373 1
3.3%
453 1
3.3%
326 1
3.3%
240 1
3.3%
149 1
3.3%
129 1
3.3%
111 1
3.3%
80 1
3.3%
75 1
3.3%
69 1
3.3%

Interactions

2023-12-10T23:12:52.254834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:47.477598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:48.307851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:49.301590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:50.269707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:51.158901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:52.815317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:47.648996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:48.472348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:49.448328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:50.423142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:51.308644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:52.965944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:47.804457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:48.628127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:49.593498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:50.563851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:51.442503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:53.111779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:47.933795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:48.798547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:49.769932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:50.717680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:51.763501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:53.364077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:48.046985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:48.947600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:49.953130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:50.869845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:51.924073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:53.543747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:48.175405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:49.104535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:50.103830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:51.015016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:12:52.080209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:12:59.767364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0001.0000.0000.0000.000
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0001.0000.0000.2400.2400.000
이용자활동평가구독자수1.0001.0001.0001.0000.2210.0000.0000.000
이용자활동평가영상조회수1.0001.0000.0000.2211.0000.2970.2970.812
이용자활동평가긍정평가비율0.0001.0000.2400.0000.2971.0001.0000.000
이용자활동평가부정평가비율0.0001.0000.2400.0000.2971.0001.0000.000
수0.0001.0000.0000.0000.8120.0000.0001.000
2023-12-10T23:12:59.969344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9810.325-0.4710.4690.210
이용자활동평가구독자수0.9811.0000.353-0.4560.4540.267
이용자활동평가영상조회수0.3250.3531.000-0.5820.5880.777
이용자활동평가긍정평가비율-0.471-0.456-0.5821.000-1.000-0.469
이용자활동평가부정평가비율0.4690.4540.588-1.0001.0000.475
수0.2100.2670.777-0.4690.4751.000

Missing values

2023-12-10T23:12:53.814868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:12:54.154381image/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.
2023-12-10T23:12:54.467412image/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/UC22go5LdQEw-iDuxFb4C0hwhttps://www.youtube.com/watch?v=7s5h_CFpFsU2021-07-01366093617040400002389196.93.169
1https://www.youtube.com/channel/UCiBr0bK06imaMbLc8sAEz0Ahttps://www.youtube.com/watch?v=P9OomFksKR02021-07-011403632166583300001699798.71.33
2https://www.youtube.com/channel/UC12XQWcIlaavjjbhh6EeMJwhttps://www.youtube.com/watch?v=AvW7Mbh_wjA2021-07-01103017894198000597197.62.41
3https://www.youtube.com/channel/UCDEOj33PPDR-Hw9RxdKfjpwhttps://www.youtube.com/watch?v=RuafJp4j2Gk2021-07-017755491120200099423794.35.71373
4https://www.youtube.com/channel/UC4DgFN9dvM0DPXXvsS3FO-whttps://www.youtube.com/watch?v=wJB7cFCm3Sc2021-07-01612301625100589100.00.00
5https://www.youtube.com/channel/UCUMI7D_spGZO2wCgtXiarAghttps://www.youtube.com/watch?v=QFAwZPAFnIo2021-07-019125231210239100.00.00
6https://www.youtube.com/channel/UCqMixH4Cc7CdySihHG4kkIAhttps://www.youtube.com/watch?v=7f_K53vxpjI2021-07-013379640302950003271195.05.080
7https://www.youtube.com/channel/UChWrFUrthv30VN9GJrGjv3whttps://www.youtube.com/watch?v=hnTpAGfUKSs2021-07-015373172727700011352695.44.6240
8https://www.youtube.com/channel/UC9iYGheHksAaocXVcPtcdWghttps://www.youtube.com/watch?v=NiqvukPwquU2021-07-017768061110609100.00.01
9https://www.youtube.com/channel/UCfWZnsdfiKvOyHDGfzMT3Cghttps://www.youtube.com/watch?v=4Wx7MylXxvA2021-07-013014423244480007648100.00.03
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLghttps://www.youtube.com/watch?v=vdUIRDLEbX82021-07-01645702117156200001920100.00.01
21https://www.youtube.com/channel/UC5HSw5OY2vfVFSihpiB-AVQhttps://www.youtube.com/watch?v=ipuadE2FHkU2021-07-0181236292510700008378698.81.3326
22https://www.youtube.com/channel/UCmip5Tn3nHkNykkGvfbhteghttps://www.youtube.com/watch?v=3gRr1382dds2021-07-01356003392260006005199.70.3149
23https://www.youtube.com/channel/UC5HSw5OY2vfVFSihpiB-AVQhttps://www.youtube.com/watch?v=BrE7owb2mvA2021-07-01812362925107000099488.511.524
24https://www.youtube.com/channel/UC5HSw5OY2vfVFSihpiB-AVQhttps://www.youtube.com/watch?v=Fey_CzjeP-g2021-07-018123629251070000424398.81.213
25https://www.youtube.com/channel/UCHlSeJxRIXZWMARC2oMwmcQhttps://www.youtube.com/watch?v=lXVOfYdxWuM2021-07-01535398043694000125100.00.00
26https://www.youtube.com/channel/UC3m0s5XAQydCtbLHc8j1Uoghttps://www.youtube.com/watch?v=D0bWqlcAhkY2021-07-01138106107814800001776399.40.675
27https://www.youtube.com/channel/UCxnsTq6SUzpAFSMB-5nybXAhttps://www.youtube.com/watch?v=NYSa_BwGGbU2021-07-01507031010648100.00.00
28https://www.youtube.com/channel/UCy7h0uG0btRO-X9rx8oPdgghttps://www.youtube.com/watch?v=EUlmGcbd6-Q2021-07-015609579027150002415368.231.80
29https://www.youtube.com/channel/UCR5cyf8hncN_AaQPfmvmlgAhttps://www.youtube.com/watch?v=X0A92ohiaPA2021-07-012650133924050001309194.25.816