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
Categorical1
Numeric6

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/38f74fc6-91bf-4182-8f2c-e197e5ddd4b2

Alerts

이용자활동평가생성기간 has constant value ""Constant
이용자활동평가채널조회수 is highly overall correlated with 이용자활동평가구독자수 and 1 other fieldsHigh correlation
이용자활동평가구독자수 is highly overall correlated with 이용자활동평가채널조회수 and 1 other fieldsHigh correlation
이용자활동평가영상조회수 is highly overall correlated with 이용자활동평가채널조회수 and 2 other fieldsHigh 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 4 (13.3%) missing valuesMissing
이용자활동평가부정평가비율 has 4 (13.3%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가긍정평가비율 has 1 (3.3%) zerosZeros
이용자활동평가부정평가비율 has 7 (23.3%) zerosZeros
수 has 13 (43.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:25:13.959051
Analysis finished2023-12-10 14:25:18.129516
Duration4.17 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
2023-12-10T23:25:18.371307image/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/UC35SH2IZCoDAyjdM_BKNVlA
2nd rowhttps://www.youtube.com/channel/UCUj6rrhMTR9pipbAWBAMvUQ
3rd rowhttps://www.youtube.com/channel/UCZFTAP8J_0xEjjhreKMHa4A
4th rowhttps://www.youtube.com/channel/UCTNAz5nQtucQBo7wDd_mIUA
5th rowhttps://www.youtube.com/channel/UCgdZeqgyKQL1durJSAsFAnw
ValueCountFrequency (%)
https://www.youtube.com/channel/uc5bmqosab8hkuyhu9ki6yig 2
 
6.7%
https://www.youtube.com/channel/uc0sfszeosuewxys7okktelq 2
 
6.7%
https://www.youtube.com/channel/uc35sh2izcodayjdm_bknvla 1
 
3.3%
https://www.youtube.com/channel/ucuj6rrhmtr9pipbawbamvuq 1
 
3.3%
https://www.youtube.com/channel/ucelpm9yh_a_qh8n6445g-ow 1
 
3.3%
https://www.youtube.com/channel/uczdzvl6_f1ltlypjej3hihw 1
 
3.3%
https://www.youtube.com/channel/ucjrwkxvopn133r1yp07583q 1
 
3.3%
https://www.youtube.com/channel/ucztesxznvjwesizsccsksww 1
 
3.3%
https://www.youtube.com/channel/uc5qsxoislbkeip4di7xwolg 1
 
3.3%
https://www.youtube.com/channel/ucx_dzpi6efsohgtokag43-a 1
 
3.3%
Other values (18) 18
60.0%
2023-12-10T23:25:18.765703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 109
 
6.5%
t 98
 
5.8%
e 77
 
4.6%
h 69
 
4.1%
o 69
 
4.1%
n 69
 
4.1%
c 67
 
4.0%
u 66
 
3.9%
. 60
 
3.6%
Other values (57) 876
52.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1028
61.2%
Uppercase Letter 337
 
20.1%
Other Punctuation 210
 
12.5%
Decimal Number 82
 
4.9%
Connector Punctuation 15
 
0.9%
Dash Punctuation 8
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 109
 
10.6%
t 98
 
9.5%
e 77
 
7.5%
h 69
 
6.7%
o 69
 
6.7%
n 69
 
6.7%
c 67
 
6.5%
u 66
 
6.4%
s 48
 
4.7%
y 44
 
4.3%
Other values (16) 312
30.4%
Uppercase Letter
ValueCountFrequency (%)
U 42
 
12.5%
C 36
 
10.7%
A 17
 
5.0%
Q 16
 
4.7%
I 15
 
4.5%
K 14
 
4.2%
L 14
 
4.2%
Z 13
 
3.9%
O 13
 
3.9%
H 13
 
3.9%
Other values (16) 144
42.7%
Decimal Number
ValueCountFrequency (%)
7 12
14.6%
5 11
13.4%
1 11
13.4%
3 10
12.2%
4 9
11.0%
6 8
9.8%
9 7
8.5%
8 7
8.5%
0 4
 
4.9%
2 3
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1365
81.2%
Common 315
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 109
 
8.0%
t 98
 
7.2%
e 77
 
5.6%
h 69
 
5.1%
o 69
 
5.1%
n 69
 
5.1%
c 67
 
4.9%
u 66
 
4.8%
s 48
 
3.5%
y 44
 
3.2%
Other values (42) 649
47.5%
Common
ValueCountFrequency (%)
/ 120
38.1%
. 60
19.0%
: 30
 
9.5%
_ 15
 
4.8%
7 12
 
3.8%
5 11
 
3.5%
1 11
 
3.5%
3 10
 
3.2%
4 9
 
2.9%
6 8
 
2.5%
Other values (5) 29
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 109
 
6.5%
t 98
 
5.8%
e 77
 
4.6%
h 69
 
4.1%
o 69
 
4.1%
n 69
 
4.1%
c 67
 
4.0%
u 66
 
3.9%
. 60
 
3.6%
Other values (57) 876
52.1%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:25:19.030490image/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=Xcfvzbedhg8
2nd rowhttps://www.youtube.com/watch?v=Mg6LqXJT8nw
3rd rowhttps://www.youtube.com/watch?v=0wS_jETZ-qM
4th rowhttps://www.youtube.com/watch?v=HlWKbwGSKgM
5th rowhttps://www.youtube.com/watch?v=kTYxz6gqGBc
ValueCountFrequency (%)
https://www.youtube.com/watch?v=xcfvzbedhg8 1
 
3.3%
https://www.youtube.com/watch?v=mg6lqxjt8nw 1
 
3.3%
https://www.youtube.com/watch?v=_udy-ygkomw 1
 
3.3%
https://www.youtube.com/watch?v=ala_-nk0xgm 1
 
3.3%
https://www.youtube.com/watch?v=pdlc5o6qexa 1
 
3.3%
https://www.youtube.com/watch?v=rtfljirtcui 1
 
3.3%
https://www.youtube.com/watch?v=ayyhk8wxaik 1
 
3.3%
https://www.youtube.com/watch?v=x_b_yexrggu 1
 
3.3%
https://www.youtube.com/watch?v=lseqpnsk-nc 1
 
3.3%
https://www.youtube.com/watch?v=jhg7s-xtjpa 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:25:19.496889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 130
 
10.1%
t 125
 
9.7%
/ 90
 
7.0%
c 70
 
5.4%
h 65
 
5.0%
u 63
 
4.9%
o 62
 
4.8%
. 60
 
4.7%
p 37
 
2.9%
s 37
 
2.9%
Other values (59) 551
42.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 859
66.6%
Other Punctuation 210
 
16.3%
Uppercase Letter 141
 
10.9%
Decimal Number 35
 
2.7%
Math Symbol 30
 
2.3%
Connector Punctuation 9
 
0.7%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 130
15.1%
t 125
14.6%
c 70
 
8.1%
h 65
 
7.6%
u 63
 
7.3%
o 62
 
7.2%
p 37
 
4.3%
s 37
 
4.3%
v 35
 
4.1%
e 35
 
4.1%
Other values (16) 200
23.3%
Uppercase Letter
ValueCountFrequency (%)
M 12
 
8.5%
A 11
 
7.8%
L 11
 
7.8%
X 10
 
7.1%
U 10
 
7.1%
E 7
 
5.0%
S 7
 
5.0%
Y 6
 
4.3%
D 6
 
4.3%
Q 6
 
4.3%
Other values (16) 55
39.0%
Decimal Number
ValueCountFrequency (%)
8 6
17.1%
6 6
17.1%
0 4
11.4%
4 3
8.6%
1 3
8.6%
7 3
8.6%
2 3
8.6%
3 3
8.6%
5 3
8.6%
9 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
? 30
 
14.3%
: 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

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

Most frequent character per script

Latin
ValueCountFrequency (%)
w 130
 
13.0%
t 125
 
12.5%
c 70
 
7.0%
h 65
 
6.5%
u 63
 
6.3%
o 62
 
6.2%
p 37
 
3.7%
s 37
 
3.7%
v 35
 
3.5%
e 35
 
3.5%
Other values (42) 341
34.1%
Common
ValueCountFrequency (%)
/ 90
31.0%
. 60
20.7%
? 30
 
10.3%
= 30
 
10.3%
: 30
 
10.3%
_ 9
 
3.1%
8 6
 
2.1%
- 6
 
2.1%
6 6
 
2.1%
0 4
 
1.4%
Other values (7) 19
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 130
 
10.1%
t 125
 
9.7%
/ 90
 
7.0%
c 70
 
5.4%
h 65
 
5.0%
u 63
 
4.9%
o 62
 
4.8%
. 60
 
4.7%
p 37
 
2.9%
s 37
 
2.9%
Other values (59) 551
42.7%

이용자활동평가생성기간
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-02-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-01
2nd row2021-02-01
3rd row2021-02-01
4th row2021-02-01
5th row2021-02-01

Common Values

ValueCountFrequency (%)
2021-02-01 30
100.0%

Length

2023-12-10T23:25:19.639969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:25:19.737302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-01 30
100.0%

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5727421 × 109
Minimum54772
Maximum1.1082297 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:25:19.847817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54772
5-th percentile614069.95
Q133910556
median2.2795672 × 108
Q38.1163813 × 108
95-th percentile9.9367188 × 109
Maximum1.1082297 × 1010
Range1.1082242 × 1010
Interquartile range (IQR)7.7772758 × 108

Descriptive statistics

Standard deviation3.1320209 × 109
Coefficient of variation (CV)1.9914396
Kurtosis4.9763318
Mean1.5727421 × 109
Median Absolute Deviation (MAD)2.258041 × 108
Skewness2.4290856
Sum4.7182262 × 1010
Variance9.8095547 × 1018
MonotonicityNot monotonic
2023-12-10T23:25:20.006509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
11082297073 2
 
6.7%
67828092 2
 
6.7%
14505567 1
 
3.3%
450393812 1
 
3.3%
1978870299 1
 
3.3%
3928938028 1
 
3.3%
163587026 1
 
3.3%
197274170 1
 
3.3%
30750885 1
 
3.3%
81817385 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
54772 1
3.3%
328360 1
3.3%
963271 1
3.3%
1551694 1
3.3%
2753536 1
3.3%
3683785 1
3.3%
14505567 1
3.3%
30750885 1
3.3%
43389568 1
3.3%
67828092 2
6.7%
ValueCountFrequency (%)
11082297073 2
6.7%
8536567596 1
3.3%
3928938028 1
3.3%
3886692314 1
3.3%
1978870299 1
3.3%
1826026210 1
3.3%
880466812 1
3.3%
605152102 1
3.3%
586969235 1
3.3%
474036118 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1892709.7
Minimum160
Maximum15400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:25:20.143450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum160
5-th percentile3083
Q181925
median443000
Q3972250
95-th percentile11354500
Maximum15400000
Range15399840
Interquartile range (IQR)890325

Descriptive statistics

Standard deviation3984079.6
Coefficient of variation (CV)2.1049608
Kurtosis8.0072908
Mean1892709.7
Median Absolute Deviation (MAD)422300
Skewness2.9124242
Sum56781290
Variance1.587289 × 1013
MonotonicityNot monotonic
2023-12-10T23:25:20.285091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
15400000 2
 
6.7%
291000 2
 
6.7%
28800 1
 
3.3%
363000 1
 
3.3%
1090000 1
 
3.3%
5760000 1
 
3.3%
430000 1
 
3.3%
529000 1
 
3.3%
63900 1
 
3.3%
188000 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
160 1
3.3%
1670 1
3.3%
4810 1
3.3%
9050 1
3.3%
10300 1
3.3%
12600 1
3.3%
28800 1
3.3%
63900 1
3.3%
136000 1
3.3%
188000 1
3.3%
ValueCountFrequency (%)
15400000 2
6.7%
6410000 1
3.3%
5760000 1
3.3%
3260000 1
3.3%
1510000 1
3.3%
1090000 1
3.3%
981000 1
3.3%
946000 1
3.3%
844000 1
3.3%
834000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41018.6
Minimum15
Maximum597692
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:25:20.485692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile51.8
Q1512
median4773.5
Q329872.25
95-th percentile138727.8
Maximum597692
Range597677
Interquartile range (IQR)29360.25

Descriptive statistics

Standard deviation111387.01
Coefficient of variation (CV)2.7155243
Kurtosis23.192144
Mean41018.6
Median Absolute Deviation (MAD)4750
Skewness4.6353043
Sum1230558
Variance1.2407065 × 1010
MonotonicityNot monotonic
2023-12-10T23:25:20.659173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
527 1
 
3.3%
215 1
 
3.3%
5595 1
 
3.3%
2451 1
 
3.3%
2625 1
 
3.3%
10600 1
 
3.3%
33164 1
 
3.3%
380 1
 
3.3%
153072 1
 
3.3%
57698 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
15 1
3.3%
32 1
3.3%
76 1
3.3%
93 1
3.3%
142 1
3.3%
215 1
3.3%
380 1
3.3%
507 1
3.3%
527 1
3.3%
2055 1
3.3%
ValueCountFrequency (%)
597692 1
3.3%
153072 1
3.3%
121196 1
3.3%
79709 1
3.3%
57698 1
3.3%
36494 1
3.3%
33164 1
3.3%
30771 1
3.3%
27176 1
3.3%
20613 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct18
Distinct (%)69.2%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean91.426923
Minimum0
Maximum100
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:25:20.787111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile75.6
Q195.225
median97.6
Q399.925
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)4.7

Descriptive statistics

Standard deviation19.916437
Coefficient of variation (CV)0.21783995
Kurtosis19.249753
Mean91.426923
Median Absolute Deviation (MAD)2.4
Skewness-4.1936779
Sum2377.1
Variance396.66445
MonotonicityNot monotonic
2023-12-10T23:25:20.959108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
100.0 7
23.3%
97.5 2
 
6.7%
97.7 2
 
6.7%
97.1 1
 
3.3%
96.0 1
 
3.3%
99.7 1
 
3.3%
83.0 1
 
3.3%
99.4 1
 
3.3%
75.0 1
 
3.3%
98.1 1
 
3.3%
Other values (8) 8
26.7%
(Missing) 4
13.3%
ValueCountFrequency (%)
0.0 1
3.3%
75.0 1
3.3%
77.4 1
3.3%
83.0 1
3.3%
87.2 1
3.3%
88.9 1
3.3%
95.2 1
3.3%
95.3 1
3.3%
95.9 1
3.3%
96.0 1
3.3%
ValueCountFrequency (%)
100.0 7
23.3%
99.7 1
 
3.3%
99.4 1
 
3.3%
98.5 1
 
3.3%
98.1 1
 
3.3%
97.7 2
 
6.7%
97.5 2
 
6.7%
97.1 1
 
3.3%
96.0 1
 
3.3%
95.9 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct18
Distinct (%)69.2%
Missing4
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean8.5730769
Minimum0
Maximum100
Zeros7
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:25:21.101957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.075
median2.4
Q34.775
95-th percentile24.4
Maximum100
Range100
Interquartile range (IQR)4.7

Descriptive statistics

Standard deviation19.916437
Coefficient of variation (CV)2.3231375
Kurtosis19.249753
Mean8.5730769
Median Absolute Deviation (MAD)2.4
Skewness4.1936779
Sum222.9
Variance396.66445
MonotonicityNot monotonic
2023-12-10T23:25:21.248096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 7
23.3%
2.5 2
 
6.7%
2.3 2
 
6.7%
2.9 1
 
3.3%
4.0 1
 
3.3%
0.3 1
 
3.3%
17.0 1
 
3.3%
0.6 1
 
3.3%
25.0 1
 
3.3%
1.9 1
 
3.3%
Other values (8) 8
26.7%
(Missing) 4
13.3%
ValueCountFrequency (%)
0.0 7
23.3%
0.3 1
 
3.3%
0.6 1
 
3.3%
1.5 1
 
3.3%
1.9 1
 
3.3%
2.3 2
 
6.7%
2.5 2
 
6.7%
2.9 1
 
3.3%
4.0 1
 
3.3%
4.1 1
 
3.3%
ValueCountFrequency (%)
100.0 1
3.3%
25.0 1
3.3%
22.6 1
3.3%
17.0 1
3.3%
12.8 1
3.3%
11.1 1
3.3%
4.8 1
3.3%
4.7 1
3.3%
4.1 1
3.3%
4.0 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.3
Minimum0
Maximum504
Zeros13
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:25:21.364450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q391.5
95-th percentile337.1
Maximum504
Range504
Interquartile range (IQR)91.5

Descriptive statistics

Standard deviation127.13424
Coefficient of variation (CV)1.8345489
Kurtosis4.5162802
Mean69.3
Median Absolute Deviation (MAD)7
Skewness2.1820496
Sum2079
Variance16163.114
MonotonicityNot monotonic
2023-12-10T23:25:21.483496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 13
43.3%
14 1
 
3.3%
9 1
 
3.3%
11 1
 
3.3%
3 1
 
3.3%
12 1
 
3.3%
383 1
 
3.3%
143 1
 
3.3%
281 1
 
3.3%
8 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
0 13
43.3%
3 1
 
3.3%
6 1
 
3.3%
8 1
 
3.3%
9 1
 
3.3%
11 1
 
3.3%
12 1
 
3.3%
14 1
 
3.3%
19 1
 
3.3%
36 1
 
3.3%
ValueCountFrequency (%)
504 1
3.3%
383 1
3.3%
281 1
3.3%
205 1
3.3%
176 1
3.3%
159 1
3.3%
143 1
3.3%
110 1
3.3%
36 1
3.3%
19 1
3.3%

Interactions

2023-12-10T23:25:17.065328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.272104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.825594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:15.773596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.264135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.667286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:17.148981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.365789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.948291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:15.884150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.328300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.729440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:17.243156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.462524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:15.084842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:15.974368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.399146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.797597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:17.332658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.553616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:15.516849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.051338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.471085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.866367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:17.421407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.654481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:15.593298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.120695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.539630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.931606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:17.501932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:14.737987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:15.670006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.192665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.602374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:25:16.996939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:25:21.570080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0000.5930.6580.6580.717
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0000.9880.0000.0000.0000.000
이용자활동평가구독자수1.0001.0000.9881.0000.0000.0000.0000.000
이용자활동평가영상조회수0.5931.0000.0000.0001.0000.0000.0000.947
이용자활동평가긍정평가비율0.6581.0000.0000.0000.0001.0001.0000.000
이용자활동평가부정평가비율0.6581.0000.0000.0000.0001.0001.0000.000
수0.7171.0000.0000.0000.9470.0000.0001.000
2023-12-10T23:25:21.719586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9820.643-0.1490.1490.471
이용자활동평가구독자수0.9821.0000.663-0.2190.2190.477
이용자활동평가영상조회수0.6430.6631.000-0.2220.2220.891
이용자활동평가긍정평가비율-0.149-0.219-0.2221.000-1.000-0.216
이용자활동평가부정평가비율0.1490.2190.222-1.0001.0000.216
수0.4710.4770.891-0.2160.2161.000

Missing values

2023-12-10T23:25:17.652069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:25:17.883519image/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.
2023-12-10T23:25:18.059536image/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/UC35SH2IZCoDAyjdM_BKNVlAhttps://www.youtube.com/watch?v=Xcfvzbedhg82021-02-0114505567288005270.0100.00
1https://www.youtube.com/channel/UCUj6rrhMTR9pipbAWBAMvUQhttps://www.youtube.com/watch?v=Mg6LqXJT8nw2021-02-0147403611884400012119697.72.3159
2https://www.youtube.com/channel/UCZFTAP8J_0xEjjhreKMHa4Ahttps://www.youtube.com/watch?v=0wS_jETZ-qM2021-02-01963271481032<NA><NA>0
3https://www.youtube.com/channel/UCTNAz5nQtucQBo7wDd_mIUAhttps://www.youtube.com/watch?v=HlWKbwGSKgM2021-02-015477216015<NA><NA>0
4https://www.youtube.com/channel/UCgdZeqgyKQL1durJSAsFAnwhttps://www.youtube.com/watch?v=kTYxz6gqGBc2021-02-0115516949050142100.00.00
5https://www.youtube.com/channel/UCp77saYy1V_F3dld7GfJrcghttps://www.youtube.com/watch?v=XRg5g3UxpNs2021-02-012891108324670002114100.00.06
6https://www.youtube.com/channel/UC7uKMg7lPdCp4Nm1tLesihQhttps://www.youtube.com/watch?v=2nvLdiEDckA2021-02-0158696923594600059769295.94.1504
7https://www.youtube.com/channel/UCFL1sCAksD6_7JIZwwHcwjQhttps://www.youtube.com/watch?v=6jeXYoGABUc2021-02-01853656759664100001418495.34.736
8https://www.youtube.com/channel/UCK2JegInDWoDtwEpjh4HzLghttps://www.youtube.com/watch?v=6JmM7ghwfV82021-02-012753536103002430100.00.00
9https://www.youtube.com/channel/UCbdBIZiwlOl8lkvkrEaHGNQhttps://www.youtube.com/watch?v=9yAMJL74NJE2021-02-01328360167076100.00.00
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCiGeWRkwZJL1ZH_1ImaZwmghttps://www.youtube.com/watch?v=FXwDL1sBZAU2021-02-0136837851260093100.00.00
21https://www.youtube.com/channel/UCx_dzPI6efSohgtOkAG43-Ahttps://www.youtube.com/watch?v=jhG7S-xtJpA2021-02-013886692314326000012200100.00.00
22https://www.youtube.com/channel/UC5qsXOIsLbkEIP4DI7xWOlghttps://www.youtube.com/watch?v=LSEqpnsk-nc2021-02-01818173851880005769898.11.9143
23https://www.youtube.com/channel/UC5BMQOsAB8hKUyHu9KI6yighttps://www.youtube.com/watch?v=X_b_YeXRggU2021-02-011108229707315400000153072<NA><NA>383
24https://www.youtube.com/channel/UCzteSXznVjwESizsCcSKSWwhttps://www.youtube.com/watch?v=AyyHK8wxaik2021-02-01307508856390038075.025.00
25https://www.youtube.com/channel/UCjrwkxVOpN133r1Yp07583Qhttps://www.youtube.com/watch?v=rtFLjirtcuI2021-02-011972741705290003316499.40.612
26https://www.youtube.com/channel/UCZdZVL6_f1ltLyPjeJ3HIhwhttps://www.youtube.com/watch?v=PDLc5O6QeXA2021-02-011635870264300001060083.017.03
27https://www.youtube.com/channel/UCeLPm9yH_a_QH8n6445G-Owhttps://www.youtube.com/watch?v=alA_-Nk0XgM2021-02-0139289380285760000262597.72.30
28https://www.youtube.com/channel/UC0sfSZeoSUeWxys7OKkTelQhttps://www.youtube.com/watch?v=_UDY-YgkOmw2021-02-0167828092291000245199.70.311
29https://www.youtube.com/channel/UCF4Wxdo3inmxP-Y59wXDsFwhttps://www.youtube.com/watch?v=sNmzhvMg8w42021-02-0119788702991090000559596.04.09