Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells6
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory82.4 B

Variable types

Text2
Categorical1
Numeric6

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/a77ecb5a-15c3-438a-b6c2-1d9b254e0ddc

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 이용자활동평가부정평가비율High correlation
이용자활동평가부정평가비율 is highly overall correlated with 이용자활동평가긍정평가비율High correlation
수 is highly overall correlated with 이용자활동평가영상조회수High correlation
이용자활동평가긍정평가비율 has 3 (10.0%) missing valuesMissing
이용자활동평가부정평가비율 has 3 (10.0%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가구독자수 has 1 (3.3%) zerosZeros
이용자활동평가부정평가비율 has 7 (23.3%) zerosZeros
수 has 10 (33.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:15:09.913052
Analysis finished2023-12-10 14:15:17.410583
Duration7.5 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
2023-12-10T23:15:17.808644image/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/UCG66Zd-uypYaf1RLaJcIt3g
2nd rowhttps://www.youtube.com/channel/UCK1sVuXaDvJeNwl9noN5nOA
3rd rowhttps://www.youtube.com/channel/UCk7fKricfVdDcC6qSp9cHtw
4th rowhttps://www.youtube.com/channel/UCj1dw4G9v09OLXIxiL_VUEA
5th rowhttps://www.youtube.com/channel/UCFL1sCAksD6_7JIZwwHcwjQ
ValueCountFrequency (%)
https://www.youtube.com/channel/ucyylilojyqkafklvjzx5img 2
 
6.7%
https://www.youtube.com/channel/ucg66zd-uypyaf1rlajcit3g 1
 
3.3%
https://www.youtube.com/channel/ucqppzb7y4ajz6vv1f3v066g 1
 
3.3%
https://www.youtube.com/channel/ucf-rfadn7dzd-si2t3rkcaq 1
 
3.3%
https://www.youtube.com/channel/ucsu-i-vhliamfv_ceayz5rq 1
 
3.3%
https://www.youtube.com/channel/uccqtri69dsvyhn3exeptz1a 1
 
3.3%
https://www.youtube.com/channel/ucol7j0e4pahjw6eu-5qdboa 1
 
3.3%
https://www.youtube.com/channel/ucoplcjfbp9wgadbbfjydyvg 1
 
3.3%
https://www.youtube.com/channel/uca56qkmvvvq1imn4xbxakea 1
 
3.3%
https://www.youtube.com/channel/uclgp4-40xif4r5xhvzpnkgg 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:15:18.974898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 106
 
6.3%
t 99
 
5.9%
c 73
 
4.3%
e 72
 
4.3%
u 68
 
4.0%
o 67
 
4.0%
h 66
 
3.9%
n 66
 
3.9%
. 60
 
3.6%
Other values (57) 883
52.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1014
60.4%
Uppercase Letter 337
 
20.1%
Other Punctuation 210
 
12.5%
Decimal Number 103
 
6.1%
Dash Punctuation 10
 
0.6%
Connector Punctuation 6
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 106
 
10.5%
t 99
 
9.8%
c 73
 
7.2%
e 72
 
7.1%
u 68
 
6.7%
o 67
 
6.6%
h 66
 
6.5%
n 66
 
6.5%
y 44
 
4.3%
a 43
 
4.2%
Other values (16) 310
30.6%
Uppercase Letter
ValueCountFrequency (%)
C 37
 
11.0%
U 36
 
10.7%
A 18
 
5.3%
J 17
 
5.0%
L 17
 
5.0%
V 17
 
5.0%
I 14
 
4.2%
F 14
 
4.2%
O 13
 
3.9%
Q 13
 
3.9%
Other values (16) 141
41.8%
Decimal Number
ValueCountFrequency (%)
4 16
15.5%
5 15
14.6%
6 13
12.6%
1 12
11.7%
3 11
10.7%
9 11
10.7%
0 8
7.8%
7 6
 
5.8%
2 6
 
5.8%
8 5
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1351
80.4%
Common 329
 
19.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 106
 
7.8%
t 99
 
7.3%
c 73
 
5.4%
e 72
 
5.3%
u 68
 
5.0%
o 67
 
5.0%
h 66
 
4.9%
n 66
 
4.9%
y 44
 
3.3%
a 43
 
3.2%
Other values (42) 647
47.9%
Common
ValueCountFrequency (%)
/ 120
36.5%
. 60
18.2%
: 30
 
9.1%
4 16
 
4.9%
5 15
 
4.6%
6 13
 
4.0%
1 12
 
3.6%
3 11
 
3.3%
9 11
 
3.3%
- 10
 
3.0%
Other values (5) 31
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 106
 
6.3%
t 99
 
5.9%
c 73
 
4.3%
e 72
 
4.3%
u 68
 
4.0%
o 67
 
4.0%
h 66
 
3.9%
n 66
 
3.9%
. 60
 
3.6%
Other values (57) 883
52.6%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:19.706504image/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=ZHOjdTdqcHA
2nd rowhttps://www.youtube.com/watch?v=VVKknuMXt-w
3rd rowhttps://www.youtube.com/watch?v=JWkB-wfjEqc
4th rowhttps://www.youtube.com/watch?v=DS50NxwA1Yc
5th rowhttps://www.youtube.com/watch?v=EmzVZN0c0nQ
ValueCountFrequency (%)
https://www.youtube.com/watch?v=zhojdtdqcha 1
 
3.3%
https://www.youtube.com/watch?v=vvkknumxt-w 1
 
3.3%
https://www.youtube.com/watch?v=pkga-_g_qni 1
 
3.3%
https://www.youtube.com/watch?v=0vbpath-qf4 1
 
3.3%
https://www.youtube.com/watch?v=k6n6v37odei 1
 
3.3%
https://www.youtube.com/watch?v=sfkpavrxzwk 1
 
3.3%
https://www.youtube.com/watch?v=fbjonpwyi_o 1
 
3.3%
https://www.youtube.com/watch?v=zlgwf2hzjms 1
 
3.3%
https://www.youtube.com/watch?v=hdblxyt-fre 1
 
3.3%
https://www.youtube.com/watch?v=y7cqazdugxo 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:15:20.510962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 128
 
9.9%
w 125
 
9.7%
/ 90
 
7.0%
o 70
 
5.4%
c 68
 
5.3%
h 65
 
5.0%
u 62
 
4.8%
. 60
 
4.7%
s 40
 
3.1%
e 37
 
2.9%
Other values (59) 545
42.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 862
66.8%
Other Punctuation 210
 
16.3%
Uppercase Letter 138
 
10.7%
Decimal Number 38
 
2.9%
Math Symbol 30
 
2.3%
Dash Punctuation 7
 
0.5%
Connector Punctuation 5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 128
14.8%
w 125
14.5%
o 70
 
8.1%
c 68
 
7.9%
h 65
 
7.5%
u 62
 
7.2%
s 40
 
4.6%
e 37
 
4.3%
v 34
 
3.9%
y 34
 
3.9%
Other values (16) 199
23.1%
Uppercase Letter
ValueCountFrequency (%)
F 10
 
7.2%
I 9
 
6.5%
Y 9
 
6.5%
Z 9
 
6.5%
D 8
 
5.8%
B 8
 
5.8%
E 7
 
5.1%
N 6
 
4.3%
Q 6
 
4.3%
K 6
 
4.3%
Other values (16) 60
43.5%
Decimal Number
ValueCountFrequency (%)
0 8
21.1%
2 5
13.2%
4 4
10.5%
8 4
10.5%
5 4
10.5%
6 3
 
7.9%
1 3
 
7.9%
3 3
 
7.9%
9 2
 
5.3%
7 2
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
: 30
 
14.3%
? 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000
77.5%
Common 290
 
22.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 128
 
12.8%
w 125
 
12.5%
o 70
 
7.0%
c 68
 
6.8%
h 65
 
6.5%
u 62
 
6.2%
s 40
 
4.0%
e 37
 
3.7%
v 34
 
3.4%
y 34
 
3.4%
Other values (42) 337
33.7%
Common
ValueCountFrequency (%)
/ 90
31.0%
. 60
20.7%
: 30
 
10.3%
? 30
 
10.3%
= 30
 
10.3%
0 8
 
2.8%
- 7
 
2.4%
_ 5
 
1.7%
2 5
 
1.7%
4 4
 
1.4%
Other values (7) 21
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 128
 
9.9%
w 125
 
9.7%
/ 90
 
7.0%
o 70
 
5.4%
c 68
 
5.3%
h 65
 
5.0%
u 62
 
4.8%
. 60
 
4.7%
s 40
 
3.1%
e 37
 
2.9%
Other values (59) 545
42.2%

이용자활동평가생성기간
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-12-10
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-10
2nd row2020-12-10
3rd row2020-12-10
4th row2020-12-10
5th row2020-12-10

Common Values

ValueCountFrequency (%)
2020-12-10 30
100.0%

Length

2023-12-10T23:15:20.740822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:20.954133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-10 30
100.0%

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2046771 × 109
Minimum137478
Maximum8.0904144 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:21.148992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum137478
5-th percentile186959.35
Q147576394
median1.7578984 × 108
Q31.3337194 × 109
95-th percentile5.5434731 × 109
Maximum8.0904144 × 109
Range8.0902769 × 109
Interquartile range (IQR)1.286143 × 109

Descriptive statistics

Standard deviation2.019537 × 109
Coefficient of variation (CV)1.6764136
Kurtosis4.5317213
Mean1.2046771 × 109
Median Absolute Deviation (MAD)1.7563754 × 108
Skewness2.2207933
Sum3.6140312 × 1010
Variance4.0785295 × 1018
MonotonicityNot monotonic
2023-12-10T23:15:21.378448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1052857896 2
 
6.7%
70192245 1
 
3.3%
107325003 1
 
3.3%
4347706725 1
 
3.3%
86519124 1
 
3.3%
1713104836 1
 
3.3%
1181980515 1
 
3.3%
4981821 1
 
3.3%
137478 1
 
3.3%
418194381 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
137478 1
3.3%
167131 1
3.3%
211194 1
3.3%
359252 1
3.3%
4981821 1
3.3%
8474934 1
3.3%
32443155 1
3.3%
45664799 1
3.3%
53311179 1
3.3%
56822221 1
3.3%
ValueCountFrequency (%)
8090414361 1
3.3%
5826130303 1
3.3%
5198003296 1
3.3%
4347706725 1
3.3%
1978497581 1
3.3%
1713104836 1
3.3%
1688671245 1
3.3%
1384299062 1
3.3%
1181980515 1
3.3%
1052857896 2
6.7%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1098076.2
Minimum0
Maximum6250000
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:21.601370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1165.85
Q1139000
median421500
Q31140000
95-th percentile4541000
Maximum6250000
Range6250000
Interquartile range (IQR)1001000

Descriptive statistics

Standard deviation1530613.7
Coefficient of variation (CV)1.3939048
Kurtosis4.5071919
Mean1098076.2
Median Absolute Deviation (MAD)420296.5
Skewness2.1582571
Sum32942287
Variance2.3427782 × 1012
MonotonicityNot monotonic
2023-12-10T23:15:21.801453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1140000 2
 
6.7%
391000 1
 
3.3%
337000 1
 
3.3%
2560000 1
 
3.3%
195000 1
 
3.3%
1460000 1
 
3.3%
1050000 1
 
3.3%
11300 1
 
3.3%
0 1
 
3.3%
873000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0 1
3.3%
827 1
3.3%
1580 1
3.3%
1680 1
3.3%
11300 1
3.3%
25900 1
3.3%
106000 1
3.3%
130000 1
3.3%
166000 1
3.3%
195000 1
3.3%
ValueCountFrequency (%)
6250000 1
3.3%
4910000 1
3.3%
4090000 1
3.3%
2560000 1
3.3%
1970000 1
3.3%
1890000 1
3.3%
1460000 1
3.3%
1140000 2
6.7%
1100000 1
3.3%
1050000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113850.2
Minimum10
Maximum1891432
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:22.008489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile68.95
Q1595.5
median4331
Q342307.75
95-th percentile534852.65
Maximum1891432
Range1891422
Interquartile range (IQR)41712.25

Descriptive statistics

Standard deviation368741.26
Coefficient of variation (CV)3.2388284
Kurtosis20.173912
Mean113850.2
Median Absolute Deviation (MAD)3923
Skewness4.3857472
Sum3415506
Variance1.3597012 × 1011
MonotonicityNot monotonic
2023-12-10T23:15:22.306404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
32931 1
 
3.3%
177021 1
 
3.3%
8065 1
 
3.3%
60423 1
 
3.3%
1671 1
 
3.3%
490 1
 
3.3%
426 1
 
3.3%
4417 1
 
3.3%
28 1
 
3.3%
99288 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10 1
3.3%
28 1
3.3%
119 1
3.3%
390 1
3.3%
426 1
3.3%
444 1
3.3%
490 1
3.3%
585 1
3.3%
627 1
3.3%
678 1
3.3%
ValueCountFrequency (%)
1891432 1
3.3%
827624 1
3.3%
177021 1
3.3%
129782 1
3.3%
99288 1
3.3%
60423 1
3.3%
54351 1
3.3%
44491 1
3.3%
35758 1
3.3%
32931 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)74.1%
Missing3
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean95.162963
Minimum75
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:22.513094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile79.35
Q194
median96.7
Q399.8
95-th percentile100
Maximum100
Range25
Interquartile range (IQR)5.8

Descriptive statistics

Standard deviation6.5499353
Coefficient of variation (CV)0.068828619
Kurtosis5.4927398
Mean95.162963
Median Absolute Deviation (MAD)2.9
Skewness-2.30342
Sum2569.4
Variance42.901652
MonotonicityNot monotonic
2023-12-10T23:15:22.715336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
100.0 7
23.3%
75.0 2
 
6.7%
94.6 1
 
3.3%
93.3 1
 
3.3%
98.1 1
 
3.3%
93.9 1
 
3.3%
89.5 1
 
3.3%
95.4 1
 
3.3%
96.7 1
 
3.3%
94.1 1
 
3.3%
Other values (10) 10
33.3%
(Missing) 3
 
10.0%
ValueCountFrequency (%)
75.0 2
6.7%
89.5 1
3.3%
90.8 1
3.3%
93.3 1
3.3%
93.8 1
3.3%
93.9 1
3.3%
94.1 1
3.3%
94.6 1
3.3%
94.7 1
3.3%
94.9 1
3.3%
ValueCountFrequency (%)
100.0 7
23.3%
99.6 1
 
3.3%
99.5 1
 
3.3%
99.3 1
 
3.3%
98.1 1
 
3.3%
97.9 1
 
3.3%
97.0 1
 
3.3%
96.7 1
 
3.3%
96.3 1
 
3.3%
95.4 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct20
Distinct (%)74.1%
Missing3
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean4.8407407
Minimum0
Maximum25
Zeros7
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:22.919990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median3.3
Q36
95-th percentile20.65
Maximum25
Range25
Interquartile range (IQR)5.8

Descriptive statistics

Standard deviation6.5507639
Coefficient of variation (CV)1.3532565
Kurtosis5.4822083
Mean4.8407407
Median Absolute Deviation (MAD)2.9
Skewness2.3008027
Sum130.7
Variance42.912507
MonotonicityNot monotonic
2023-12-10T23:15:23.164240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 7
23.3%
25.0 2
 
6.7%
5.4 1
 
3.3%
6.7 1
 
3.3%
1.9 1
 
3.3%
6.1 1
 
3.3%
10.5 1
 
3.3%
4.6 1
 
3.3%
3.3 1
 
3.3%
5.9 1
 
3.3%
Other values (10) 10
33.3%
(Missing) 3
 
10.0%
ValueCountFrequency (%)
0.0 7
23.3%
0.4 1
 
3.3%
0.5 1
 
3.3%
0.7 1
 
3.3%
1.9 1
 
3.3%
2.1 1
 
3.3%
3.0 1
 
3.3%
3.3 1
 
3.3%
3.7 1
 
3.3%
4.6 1
 
3.3%
ValueCountFrequency (%)
25.0 2
6.7%
10.5 1
3.3%
9.2 1
3.3%
6.7 1
3.3%
6.3 1
3.3%
6.1 1
3.3%
5.9 1
3.3%
5.4 1
3.3%
5.3 1
3.3%
5.1 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.06667
Minimum0
Maximum1165
Zeros10
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:23.396747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q3128
95-th percentile643.1
Maximum1165
Range1165
Interquartile range (IQR)128

Descriptive statistics

Standard deviation265.46094
Coefficient of variation (CV)1.9509623
Kurtosis7.5225065
Mean136.06667
Median Absolute Deviation (MAD)6
Skewness2.6531085
Sum4082
Variance70469.513
MonotonicityNot monotonic
2023-12-10T23:15:23.721571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 10
33.3%
1 3
 
10.0%
92 1
 
3.3%
212 1
 
3.3%
104 1
 
3.3%
9 1
 
3.3%
2 1
 
3.3%
3 1
 
3.3%
217 1
 
3.3%
136 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
0 10
33.3%
1 3
 
10.0%
2 1
 
3.3%
3 1
 
3.3%
9 1
 
3.3%
10 1
 
3.3%
21 1
 
3.3%
28 1
 
3.3%
81 1
 
3.3%
92 1
 
3.3%
ValueCountFrequency (%)
1165 1
3.3%
671 1
3.3%
609 1
3.3%
470 1
3.3%
249 1
3.3%
217 1
3.3%
212 1
3.3%
136 1
3.3%
104 1
3.3%
92 1
3.3%

Interactions

2023-12-10T23:15:16.006032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:10.364152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:11.740642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:12.853716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.170507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.131255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:16.185093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:10.522949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:11.912899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.244400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.355873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.298379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:16.316982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:10.682172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:12.061825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.449768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.496118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.452851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:16.460161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:11.047992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:12.286542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.671561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.665483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.614211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:16.583222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:11.348950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:12.480772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:13.864533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.808029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.769323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:16.715742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:11.570794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:12.666780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:14.017746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.000656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:15.873846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:15:23.989495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0001.0000.9600.9601.000
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0000.9810.0000.0000.0000.000
이용자활동평가구독자수1.0001.0000.9811.0000.4130.0000.0000.000
이용자활동평가영상조회수1.0001.0000.0000.4131.0000.9120.9120.981
이용자활동평가긍정평가비율0.9601.0000.0000.0000.9121.0001.0000.634
이용자활동평가부정평가비율0.9601.0000.0000.0000.9121.0001.0000.634
수1.0001.0000.0000.0000.9810.6340.6341.000
2023-12-10T23:15:24.217630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9860.2830.189-0.1890.024
이용자활동평가구독자수0.9861.0000.2650.178-0.178-0.004
이용자활동평가영상조회수0.2830.2651.000-0.2740.2740.820
이용자활동평가긍정평가비율0.1890.178-0.2741.000-1.000-0.153
이용자활동평가부정평가비율-0.189-0.1780.274-1.0001.0000.153
수0.024-0.0040.820-0.1530.1531.000

Missing values

2023-12-10T23:15:16.895544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:15:17.152905image/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.
2023-12-10T23:15:17.322540image/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/UCG66Zd-uypYaf1RLaJcIt3ghttps://www.youtube.com/watch?v=ZHOjdTdqcHA2020-12-10701922453910003293199.30.792
1https://www.youtube.com/channel/UCK1sVuXaDvJeNwl9noN5nOAhttps://www.youtube.com/watch?v=VVKknuMXt-w2020-12-1058261303034090000424599.50.528
2https://www.youtube.com/channel/UCk7fKricfVdDcC6qSp9cHtwhttps://www.youtube.com/watch?v=JWkB-wfjEqc2020-12-10847493425900302794.95.110
3https://www.youtube.com/channel/UCj1dw4G9v09OLXIxiL_VUEAhttps://www.youtube.com/watch?v=DS50NxwA1Yc2020-12-102442546774520003575896.33.7609
4https://www.youtube.com/channel/UCFL1sCAksD6_7JIZwwHcwjQhttps://www.youtube.com/watch?v=EmzVZN0c0nQ2020-12-10809041436162500007225100.00.00
5https://www.youtube.com/channel/UCEcuyrAqhRVUmRdOd6FGKSwhttps://www.youtube.com/watch?v=8dt3oiqxydg2020-12-108496529619770004449197.03.081
6https://www.youtube.com/channel/UCKNZsAeQXpvI-Mpoc0ZKhsAhttps://www.youtube.com/watch?v=NnssnouGhJY2020-12-106070999828800067893.86.31
7https://www.youtube.com/channel/UCF3UEVPt5zZTlBVJwDG317ghttps://www.youtube.com/watch?v=W35CMDslmnQ2020-12-101978497581197000082762497.92.1671
8https://www.youtube.com/channel/UCYyLIlOJyqkAFKlVjzX5imghttps://www.youtube.com/watch?v=vxrfjIc8FE02020-12-1010528578961140000393694.75.30
9https://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLghttps://www.youtube.com/watch?v=zteTGfrg5qo2020-12-1051980032964910000642499.60.421
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCw5qFHQAmgvsWTHRgI4xlJwhttps://www.youtube.com/watch?v=R04BEfBRoe82020-12-10167131168010<NA><NA>0
21https://www.youtube.com/channel/UClgp4-40Xif4r5xHVzpNkgghttps://www.youtube.com/watch?v=y7cqAZDUgXo2020-12-10359252158039075.025.00
22https://www.youtube.com/channel/UCa56qkMvVvq1IMn4xbXaKEAhttps://www.youtube.com/watch?v=HDBLXYt-FRE2020-12-104181943818730009928895.44.6217
23https://www.youtube.com/channel/UCOPLCJFBP9WgaDBbfJYdyVghttps://www.youtube.com/watch?v=ZlgWf2hZJms2020-12-10137478028<NA><NA>0
24https://www.youtube.com/channel/UCoL7J0e4paHJW6eu-5QDbOAhttps://www.youtube.com/watch?v=FBjONPWYI_o2020-12-10498182111300441789.510.53
25https://www.youtube.com/channel/UCYyLIlOJyqkAFKlVjzX5imghttps://www.youtube.com/watch?v=sFKpAVrXZWk2020-12-1010528578961140000426100.00.00
26https://www.youtube.com/channel/UCcQTRi69dsVYHN3exePtZ1Ahttps://www.youtube.com/watch?v=K6n6v37ODEI2020-12-1011819805151050000490100.00.02
27https://www.youtube.com/channel/UCsU-I-vHLiaMfV_ceaYz5rQhttps://www.youtube.com/watch?v=0vBPAth-qF42020-12-1017131048361460000167193.96.19
28https://www.youtube.com/channel/UCF-rFAdN7dzd-SI2T3rkCaQhttps://www.youtube.com/watch?v=Pkga-_G_QnI2020-12-10865191241950006042398.11.9104
29https://www.youtube.com/channel/UCG5bAssl2H0wjLG4BEv5ScQhttps://www.youtube.com/watch?v=LzFFIPgVdlk2020-12-1043477067252560000806593.36.70