Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells10
Missing cells (%)3.7%
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/8ff1ecf1-d05d-4317-bca8-ce60f94bc5ea

Alerts

이용자활동평가생성기간 has constant value ""Constant
이용자활동평가채널조회수 is highly overall correlated with 이용자활동평가구독자수High correlation
이용자활동평가구독자수 is highly overall correlated with 이용자활동평가채널조회수 and 2 other fieldsHigh correlation
이용자활동평가영상조회수 is highly overall correlated with 이용자활동평가긍정평가비율 and 2 other fieldsHigh correlation
이용자활동평가긍정평가비율 is highly overall correlated with 이용자활동평가구독자수 and 2 other fieldsHigh correlation
이용자활동평가부정평가비율 is highly overall correlated with 이용자활동평가구독자수 and 2 other fieldsHigh correlation
수 is highly overall correlated with 이용자활동평가영상조회수High correlation
이용자활동평가긍정평가비율 has 5 (16.7%) missing valuesMissing
이용자활동평가부정평가비율 has 5 (16.7%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가부정평가비율 has 9 (30.0%) zerosZeros
수 has 14 (46.7%) zerosZeros

Reproduction

Analysis started2023-12-10 14:00:15.331650
Analysis finished2023-12-10 14:00:21.868310
Duration6.54 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
2023-12-10T23:00:22.187398image/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/UC3m0s5XAQydCtbLHc8j1Uog
2nd rowhttps://www.youtube.com/channel/UC5qtEpiG-m6qh6Q8FfE8Alg
3rd rowhttps://www.youtube.com/channel/UCKNZsAeQXpvI-Mpoc0ZKhsA
4th rowhttps://www.youtube.com/channel/UCv7HX-7ctqTH4cXxT1nfrIg
5th rowhttps://www.youtube.com/channel/UCkbJc8jMcTXwhtmN5VMwfXg
ValueCountFrequency (%)
https://www.youtube.com/channel/ucakod3x1tn4c7ci0iukcvzq 2
 
6.7%
https://www.youtube.com/channel/uc3m0s5xaqydctblhc8j1uog 1
 
3.3%
https://www.youtube.com/channel/ucl_3lifibxwu0piopc60qhg 1
 
3.3%
https://www.youtube.com/channel/ucu8uafr_iroxrvi6c23q_ba 1
 
3.3%
https://www.youtube.com/channel/ucmjnkt6kitwaztqvwuasplg 1
 
3.3%
https://www.youtube.com/channel/uc5hsw5oy2vfvfsihpib-avq 1
 
3.3%
https://www.youtube.com/channel/ucnr50abyf4e4evi-mb3c5uw 1
 
3.3%
https://www.youtube.com/channel/ucwlv3lz_55uax4jsmj-z__q 1
 
3.3%
https://www.youtube.com/channel/ucpvw9y6pquicy0sgc8ae9ma 1
 
3.3%
https://www.youtube.com/channel/ucelpm9yh_a_qh8n6445g-ow 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:00:22.937117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 106
 
6.3%
t 102
 
6.1%
c 82
 
4.9%
n 68
 
4.0%
e 67
 
4.0%
o 67
 
4.0%
h 66
 
3.9%
u 64
 
3.8%
. 60
 
3.6%
Other values (57) 878
52.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1024
61.0%
Uppercase Letter 299
 
17.8%
Other Punctuation 210
 
12.5%
Decimal Number 121
 
7.2%
Connector Punctuation 14
 
0.8%
Dash Punctuation 12
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 106
 
10.4%
t 102
 
10.0%
c 82
 
8.0%
n 68
 
6.6%
e 67
 
6.5%
o 67
 
6.5%
h 66
 
6.4%
u 64
 
6.2%
s 50
 
4.9%
p 44
 
4.3%
Other values (16) 308
30.1%
Uppercase Letter
ValueCountFrequency (%)
U 46
15.4%
C 39
 
13.0%
A 17
 
5.7%
Q 16
 
5.4%
V 14
 
4.7%
H 12
 
4.0%
K 11
 
3.7%
T 11
 
3.7%
X 11
 
3.7%
L 10
 
3.3%
Other values (16) 112
37.5%
Decimal Number
ValueCountFrequency (%)
4 17
14.0%
5 16
13.2%
3 16
13.2%
7 13
10.7%
0 13
10.7%
8 13
10.7%
6 13
10.7%
1 10
8.3%
9 5
 
4.1%
2 5
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1323
78.8%
Common 357
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 106
 
8.0%
t 102
 
7.7%
c 82
 
6.2%
n 68
 
5.1%
e 67
 
5.1%
o 67
 
5.1%
h 66
 
5.0%
u 64
 
4.8%
s 50
 
3.8%
U 46
 
3.5%
Other values (42) 605
45.7%
Common
ValueCountFrequency (%)
/ 120
33.6%
. 60
16.8%
: 30
 
8.4%
4 17
 
4.8%
5 16
 
4.5%
3 16
 
4.5%
_ 14
 
3.9%
7 13
 
3.6%
0 13
 
3.6%
8 13
 
3.6%
Other values (5) 45
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 106
 
6.3%
t 102
 
6.1%
c 82
 
4.9%
n 68
 
4.0%
e 67
 
4.0%
o 67
 
4.0%
h 66
 
3.9%
u 64
 
3.8%
. 60
 
3.6%
Other values (57) 878
52.3%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:00:23.346402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters1290
Distinct characters68
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=8cdUtrBGe0Y
2nd rowhttps://www.youtube.com/watch?v=5NPcwtz7rKY
3rd rowhttps://www.youtube.com/watch?v=d_yserAgvf8
4th rowhttps://www.youtube.com/watch?v=gKuidXph9z4
5th rowhttps://www.youtube.com/watch?v=nCWfs7P6QfY
ValueCountFrequency (%)
https://www.youtube.com/watch?v=8cdutrbge0y 1
 
3.3%
https://www.youtube.com/watch?v=5npcwtz7rky 1
 
3.3%
https://www.youtube.com/watch?v=suypok-kyvo 1
 
3.3%
https://www.youtube.com/watch?v=itt7syk03-y 1
 
3.3%
https://www.youtube.com/watch?v=4f-br17s69w 1
 
3.3%
https://www.youtube.com/watch?v=doe7kl91yfc 1
 
3.3%
https://www.youtube.com/watch?v=i9sizhnw1vk 1
 
3.3%
https://www.youtube.com/watch?v=thdqs6cthv8 1
 
3.3%
https://www.youtube.com/watch?v=t04-r_ukgjg 1
 
3.3%
https://www.youtube.com/watch?v=xh_f5xil5kw 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:00:24.038429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 127
 
9.8%
w 125
 
9.7%
/ 90
 
7.0%
c 70
 
5.4%
h 66
 
5.1%
u 66
 
5.1%
o 64
 
5.0%
. 60
 
4.7%
s 41
 
3.2%
p 36
 
2.8%
Other values (58) 545
42.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 861
66.7%
Other Punctuation 210
 
16.3%
Uppercase Letter 117
 
9.1%
Decimal Number 64
 
5.0%
Math Symbol 30
 
2.3%
Dash Punctuation 5
 
0.4%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 127
14.8%
w 125
14.5%
c 70
 
8.1%
h 66
 
7.7%
u 66
 
7.7%
o 64
 
7.4%
s 41
 
4.8%
p 36
 
4.2%
y 35
 
4.1%
e 35
 
4.1%
Other values (16) 196
22.8%
Uppercase Letter
ValueCountFrequency (%)
A 10
 
8.5%
K 9
 
7.7%
Y 8
 
6.8%
B 7
 
6.0%
J 6
 
5.1%
I 6
 
5.1%
U 6
 
5.1%
D 6
 
5.1%
H 6
 
5.1%
F 5
 
4.3%
Other values (15) 48
41.0%
Decimal Number
ValueCountFrequency (%)
0 10
15.6%
7 10
15.6%
1 8
12.5%
5 7
10.9%
3 6
9.4%
9 6
9.4%
6 6
9.4%
8 5
7.8%
4 5
7.8%
2 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
? 30
 
14.3%
: 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 978
75.8%
Common 312
 
24.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 127
13.0%
w 125
 
12.8%
c 70
 
7.2%
h 66
 
6.7%
u 66
 
6.7%
o 64
 
6.5%
s 41
 
4.2%
p 36
 
3.7%
y 35
 
3.6%
e 35
 
3.6%
Other values (41) 313
32.0%
Common
ValueCountFrequency (%)
/ 90
28.8%
. 60
19.2%
? 30
 
9.6%
= 30
 
9.6%
: 30
 
9.6%
0 10
 
3.2%
7 10
 
3.2%
1 8
 
2.6%
5 7
 
2.2%
3 6
 
1.9%
Other values (7) 31
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 127
 
9.8%
w 125
 
9.7%
/ 90
 
7.0%
c 70
 
5.4%
h 66
 
5.1%
u 66
 
5.1%
o 64
 
5.0%
. 60
 
4.7%
s 41
 
3.2%
p 36
 
2.8%
Other values (58) 545
42.2%

이용자활동평가생성기간
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-05-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-01
2nd row2021-05-01
3rd row2021-05-01
4th row2021-05-01
5th row2021-05-01

Common Values

ValueCountFrequency (%)
2021-05-01 30
100.0%

Length

2023-12-10T23:00:24.285036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:00:24.437660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 30
100.0%

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4840033 × 109
Minimum217568
Maximum1.3589702 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:24.624365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum217568
5-th percentile622243.8
Q142912875
median3.521511 × 108
Q31.7566262 × 109
95-th percentile5.3402803 × 109
Maximum1.3589702 × 1010
Range1.3589485 × 1010
Interquartile range (IQR)1.7137133 × 109

Descriptive statistics

Standard deviation2.7636081 × 109
Coefficient of variation (CV)1.8622655
Kurtosis12.768049
Mean1.4840033 × 109
Median Absolute Deviation (MAD)3.5096983 × 108
Skewness3.2862179
Sum4.4520099 × 1010
Variance7.6375298 × 1018
MonotonicityNot monotonic
2023-12-10T23:00:24.845681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2932153683 2
 
6.7%
1330491629 1
 
3.3%
2881509 1
 
3.3%
628296 1
 
3.3%
1885370335 1
 
3.3%
6206902742 1
 
3.3%
757089297 1
 
3.3%
6425995 1
 
3.3%
638704107 1
 
3.3%
40475591 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
217568 1
3.3%
617292 1
3.3%
628296 1
3.3%
1147666 1
3.3%
1214878 1
3.3%
2881509 1
3.3%
6425995 1
3.3%
40475591 1
3.3%
50224728 1
3.3%
75998700 1
3.3%
ValueCountFrequency (%)
13589702499 1
3.3%
6206902742 1
3.3%
4281075133 1
3.3%
3993472345 1
3.3%
2932153683 2
6.7%
1951046653 1
3.3%
1885370335 1
3.3%
1370393788 1
3.3%
1330491629 1
3.3%
757089297 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1473095
Minimum2260
Maximum8230000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:25.053227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2260
5-th percentile3392.5
Q196800
median543500
Q32175000
95-th percentile5775000
Maximum8230000
Range8227740
Interquartile range (IQR)2078200

Descriptive statistics

Standard deviation2055871.5
Coefficient of variation (CV)1.3956136
Kurtosis3.4680117
Mean1473095
Median Absolute Deviation (MAD)537395
Skewness1.9144914
Sum44192850
Variance4.2266075 × 1012
MonotonicityNot monotonic
2023-12-10T23:00:25.257271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2370000 2
 
6.7%
1430000 1
 
3.3%
6160 1
 
3.3%
6050 1
 
3.3%
2160000 1
 
3.3%
5500000 1
 
3.3%
1040000 1
 
3.3%
29900 1
 
3.3%
870000 1
 
3.3%
99200 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
2260 1
3.3%
2740 1
3.3%
4190 1
3.3%
6050 1
3.3%
6160 1
3.3%
8350 1
3.3%
29900 1
3.3%
96000 1
3.3%
99200 1
3.3%
134000 1
3.3%
ValueCountFrequency (%)
8230000 1
3.3%
6000000 1
3.3%
5500000 1
3.3%
3940000 1
3.3%
3150000 1
3.3%
2370000 2
6.7%
2180000 1
3.3%
2160000 1
3.3%
1430000 1
3.3%
1410000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86897.467
Minimum6
Maximum1011256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:25.475161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile41.95
Q1275.75
median4803.5
Q355334.75
95-th percentile479937.9
Maximum1011256
Range1011250
Interquartile range (IQR)55059

Descriptive statistics

Standard deviation219124.35
Coefficient of variation (CV)2.5216426
Kurtosis12.37429
Mean86897.467
Median Absolute Deviation (MAD)4707
Skewness3.4721177
Sum2606924
Variance4.8015481 × 1010
MonotonicityNot monotonic
2023-12-10T23:00:25.714039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
5658 1
 
3.3%
198702 1
 
3.3%
128 1
 
3.3%
1011256 1
 
3.3%
133040 1
 
3.3%
48 1
 
3.3%
356 1
 
3.3%
8464 1
 
3.3%
854 1
 
3.3%
14191 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
6 1
3.3%
37 1
3.3%
48 1
3.3%
94 1
3.3%
99 1
3.3%
101 1
3.3%
128 1
3.3%
259 1
3.3%
326 1
3.3%
356 1
3.3%
ValueCountFrequency (%)
1011256 1
3.3%
678054 1
3.3%
237796 1
3.3%
198702 1
3.3%
133040 1
3.3%
106326 1
3.3%
76082 1
3.3%
62019 1
3.3%
35282 1
3.3%
15386 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)68.0%
Missing5
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean93.672
Minimum50
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:25.918961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile77
Q193.3
median96.9
Q3100
95-th percentile100
Maximum100
Range50
Interquartile range (IQR)6.7

Descriptive statistics

Standard deviation10.930672
Coefficient of variation (CV)0.11669093
Kurtosis10.748215
Mean93.672
Median Absolute Deviation (MAD)3.1
Skewness-3.0552547
Sum2341.8
Variance119.4796
MonotonicityNot monotonic
2023-12-10T23:00:26.111517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
100.0 9
30.0%
95.9 1
 
3.3%
94.3 1
 
3.3%
50.0 1
 
3.3%
93.3 1
 
3.3%
87.5 1
 
3.3%
96.8 1
 
3.3%
99.5 1
 
3.3%
97.3 1
 
3.3%
97.1 1
 
3.3%
Other values (7) 7
23.3%
(Missing) 5
16.7%
ValueCountFrequency (%)
50.0 1
3.3%
75.5 1
3.3%
83.0 1
3.3%
87.5 1
3.3%
90.7 1
3.3%
90.9 1
3.3%
93.3 1
3.3%
94.3 1
3.3%
95.9 1
3.3%
96.5 1
3.3%
ValueCountFrequency (%)
100.0 9
30.0%
99.5 1
 
3.3%
97.3 1
 
3.3%
97.1 1
 
3.3%
96.9 1
 
3.3%
96.8 1
 
3.3%
96.6 1
 
3.3%
96.5 1
 
3.3%
95.9 1
 
3.3%
94.3 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct17
Distinct (%)68.0%
Missing5
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean6.328
Minimum0
Maximum50
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:26.479362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.1
Q36.7
95-th percentile23
Maximum50
Range50
Interquartile range (IQR)6.7

Descriptive statistics

Standard deviation10.930672
Coefficient of variation (CV)1.7273503
Kurtosis10.748215
Mean6.328
Median Absolute Deviation (MAD)3.1
Skewness3.0552547
Sum158.2
Variance119.4796
MonotonicityNot monotonic
2023-12-10T23:00:26.694306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 9
30.0%
4.1 1
 
3.3%
5.7 1
 
3.3%
50.0 1
 
3.3%
6.7 1
 
3.3%
12.5 1
 
3.3%
3.2 1
 
3.3%
0.5 1
 
3.3%
2.7 1
 
3.3%
2.9 1
 
3.3%
Other values (7) 7
23.3%
(Missing) 5
16.7%
ValueCountFrequency (%)
0.0 9
30.0%
0.5 1
 
3.3%
2.7 1
 
3.3%
2.9 1
 
3.3%
3.1 1
 
3.3%
3.2 1
 
3.3%
3.4 1
 
3.3%
3.5 1
 
3.3%
4.1 1
 
3.3%
5.7 1
 
3.3%
ValueCountFrequency (%)
50.0 1
3.3%
24.5 1
3.3%
17.0 1
3.3%
12.5 1
3.3%
9.3 1
3.3%
9.1 1
3.3%
6.7 1
3.3%
5.7 1
3.3%
4.1 1
3.3%
3.5 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean468.26667
Minimum0
Maximum10745
Zeros14
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:00:26.870416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q363.25
95-th percentile1221.45
Maximum10745
Range10745
Interquartile range (IQR)63.25

Descriptive statistics

Standard deviation1965.1104
Coefficient of variation (CV)4.1965627
Kurtosis28.395221
Mean468.26667
Median Absolute Deviation (MAD)2
Skewness5.2767551
Sum14048
Variance3861659
MonotonicityNot monotonic
2023-12-10T23:00:27.066812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 14
46.7%
19 1
 
3.3%
10745 1
 
3.3%
113 1
 
3.3%
8 1
 
3.3%
74 1
 
3.3%
3 1
 
3.3%
31 1
 
3.3%
77 1
 
3.3%
1320 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0 14
46.7%
1 1
 
3.3%
3 1
 
3.3%
7 1
 
3.3%
8 1
 
3.3%
12 1
 
3.3%
19 1
 
3.3%
29 1
 
3.3%
31 1
 
3.3%
74 1
 
3.3%
ValueCountFrequency (%)
10745 1
3.3%
1320 1
3.3%
1101 1
3.3%
277 1
3.3%
231 1
3.3%
113 1
3.3%
77 1
3.3%
74 1
3.3%
31 1
3.3%
29 1
3.3%

Interactions

2023-12-10T23:00:20.357015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:16.067319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:16.998747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:17.897463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:18.743737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.576783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.491641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:16.200243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:17.194758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:18.054180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:18.887803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.728850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.577510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:16.331181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:17.381995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:18.171507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.033262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.852703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.691112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:16.471179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:17.529674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:18.312549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.164269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.990204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.877631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:16.611194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:17.648754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:18.465263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.289239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.122042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.970185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:16.757096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:17.764275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:18.596010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:19.426348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:00:20.245053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:00:27.235982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가영상ID1.0001.0001.0001.0001.0001.0001.0001.000
이용자활동평가채널조회수1.0001.0001.0000.9640.4120.5450.5450.000
이용자활동평가구독자수1.0001.0000.9641.0000.6770.7880.7880.000
이용자활동평가영상조회수1.0001.0000.4120.6771.0000.5260.5260.852
이용자활동평가긍정평가비율1.0001.0000.5450.7880.5261.0001.0000.000
이용자활동평가부정평가비율1.0001.0000.5450.7880.5261.0001.0000.000
수1.0001.0000.0000.0000.8520.0000.0001.000
2023-12-10T23:00:27.440773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9840.399-0.4620.4620.028
이용자활동평가구독자수0.9841.0000.460-0.5060.5060.066
이용자활동평가영상조회수0.3990.4601.000-0.5920.5920.736
이용자활동평가긍정평가비율-0.462-0.506-0.5921.000-1.000-0.288
이용자활동평가부정평가비율0.4620.5060.592-1.0001.0000.288
수0.0280.0660.736-0.2880.2881.000

Missing values

2023-12-10T23:00:21.419092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:00:21.627475image/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.
2023-12-10T23:00:21.788038image/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/UC3m0s5XAQydCtbLHc8j1Uoghttps://www.youtube.com/watch?v=8cdUtrBGe0Y2021-05-0113304916291430000565897.32.719
1https://www.youtube.com/channel/UC5qtEpiG-m6qh6Q8FfE8Alghttps://www.youtube.com/watch?v=5NPcwtz7rKY2021-05-0128815096160326100.00.00
2https://www.youtube.com/channel/UCKNZsAeQXpvI-Mpoc0ZKhsAhttps://www.youtube.com/watch?v=d_yserAgvf82021-05-0175998700334000136996.93.112
3https://www.youtube.com/channel/UCv7HX-7ctqTH4cXxT1nfrIghttps://www.youtube.com/watch?v=gKuidXph9z42021-05-01119749307134000101<NA><NA>0
4https://www.youtube.com/channel/UCkbJc8jMcTXwhtmN5VMwfXghttps://www.youtube.com/watch?v=nCWfs7P6QfY2021-05-01399347234539400003528283.017.07
5https://www.youtube.com/channel/UCJ11gB9E0bT1sM5wPTZt45Qhttps://www.youtube.com/watch?v=Tte1YUZS5u42021-05-01217568226094100.00.00
6https://www.youtube.com/channel/UCtlz8pU3IiHf77V8s740-pQhttps://www.youtube.com/watch?v=52gmiJGMJbs2021-05-01350609136337000259100.00.00
7https://www.youtube.com/channel/UCwC8xqx6nDDBRKV2sB-tNBAhttps://www.youtube.com/watch?v=Wc35xBxqEcA2021-05-01121487841906<NA><NA>0
8https://www.youtube.com/channel/UCgsffS7MfKL6YU3r_U3E-aAhttps://www.youtube.com/watch?v=sB6FhIkVlA02021-05-01353693067141000067805496.53.51101
9https://www.youtube.com/channel/UCp77saYy1V_F3dld7GfJrcghttps://www.youtube.com/watch?v=pbAsSgD3ic82021-05-0130250420347300010632690.99.1231
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCgwTccpOFDQVtm3AnUIxDLghttps://www.youtube.com/watch?v=q10IgXEU7Ew2021-05-016172928350841499.50.531
21https://www.youtube.com/channel/UCeLPm9yH_a_QH8n6445G-Owhttps://www.youtube.com/watch?v=xH_F5xiL5kw2021-05-0142810751336000000175396.83.23
22https://www.youtube.com/channel/UCpVw9Y6pqUiCY0Sgc8Ae9mAhttps://www.youtube.com/watch?v=T04-r_UKgJg2021-05-0140475591992001419187.512.574
23https://www.youtube.com/channel/UCWlV3Lz_55UaX4JsMj-z__Qhttps://www.youtube.com/watch?v=tHdQs6cthV82021-05-01638704107870000854100.00.08
24https://www.youtube.com/channel/UCaKod3X1Tn4c7Ci0iUKcvzQhttps://www.youtube.com/watch?v=I9sizHnW1vk2021-05-0129321536832370000846493.36.70
25https://www.youtube.com/channel/UCnr50abYF4E4Evi-mb3c5Uwhttps://www.youtube.com/watch?v=DoE7kl91yFc2021-05-01642599529900356100.00.00
26https://www.youtube.com/channel/UC5HSw5OY2vfVFSihpiB-AVQhttps://www.youtube.com/watch?v=4f-Br17s69w2021-05-0175708929710400004850.050.00
27https://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLghttps://www.youtube.com/watch?v=itT7sYK03-Y2021-05-016206902742550000013304094.35.7113
28https://www.youtube.com/channel/UCU8uafr_iROxRVI6c23Q_bAhttps://www.youtube.com/watch?v=SUypoK-kYvo2021-05-0118853703352160000101125695.94.110745
29https://www.youtube.com/channel/UCNle4Z5UkYVybg6Vj2gGd4Ahttps://www.youtube.com/watch?v=cM6W7jvKKp02021-05-016282966050128100.00.00