Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells14
Missing cells (%)5.2%
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/ed2964d9-c0a7-410c-9122-27d4e717edbd

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 7 (23.3%) missing valuesMissing
이용자활동평가부정평가비율 has 7 (23.3%) missing valuesMissing
이용자활동평가영상ID has unique valuesUnique
이용자활동평가영상조회수 has unique valuesUnique
이용자활동평가부정평가비율 has 5 (16.7%) zerosZeros
수 has 13 (43.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:18:49.158581
Analysis finished2023-12-10 14:18:55.615159
Duration6.46 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
2023-12-10T23:18:55.854861image/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/UCz22EWP6u08x3b3aYSMh5BQ
2nd rowhttps://www.youtube.com/channel/UCGNCf6ibX1HWndVRgiChpqw
3rd rowhttps://www.youtube.com/channel/UCeivPjjK9-cdj8-gw4-7JRg
4th rowhttps://www.youtube.com/channel/UCG9aFJTZ-lMCHAiO1KJsirg
5th rowhttps://www.youtube.com/channel/UCmCq-9yl81BozVhZAiKNe-Q
ValueCountFrequency (%)
https://www.youtube.com/channel/ucb-ogycx9me8np9gegpmjug 2
 
6.7%
https://www.youtube.com/channel/ucz22ewp6u08x3b3aysmh5bq 1
 
3.3%
https://www.youtube.com/channel/ucltpjtnzkhtomeubsquzmkw 1
 
3.3%
https://www.youtube.com/channel/ucckitur4mdl0bsugm4nn66w 1
 
3.3%
https://www.youtube.com/channel/ucj11gb9e0bt1sm5wptzt45q 1
 
3.3%
https://www.youtube.com/channel/ucfv7aelatppbbixhf06jlqg 1
 
3.3%
https://www.youtube.com/channel/ucurmkkmnewckpo__btainsw 1
 
3.3%
https://www.youtube.com/channel/ucwivomszwap5dpuhqjq5qaa 1
 
3.3%
https://www.youtube.com/channel/ucelcfg_jcec3pydd46humkg 1
 
3.3%
https://www.youtube.com/channel/uc-phizjv-ox8h7zd1ccn2nq 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:18:56.374653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 120
 
7.1%
w 104
 
6.2%
t 100
 
6.0%
e 74
 
4.4%
n 72
 
4.3%
c 71
 
4.2%
o 69
 
4.1%
h 68
 
4.0%
u 65
 
3.9%
. 60
 
3.6%
Other values (57) 877
52.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1014
60.4%
Uppercase Letter 331
 
19.7%
Other Punctuation 210
 
12.5%
Decimal Number 103
 
6.1%
Dash Punctuation 15
 
0.9%
Connector Punctuation 7
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 104
 
10.3%
t 100
 
9.9%
e 74
 
7.3%
n 72
 
7.1%
c 71
 
7.0%
o 69
 
6.8%
h 68
 
6.7%
u 65
 
6.4%
p 44
 
4.3%
s 42
 
4.1%
Other values (16) 305
30.1%
Uppercase Letter
ValueCountFrequency (%)
C 43
 
13.0%
U 43
 
13.0%
A 18
 
5.4%
M 17
 
5.1%
Z 14
 
4.2%
K 13
 
3.9%
O 13
 
3.9%
P 12
 
3.6%
H 12
 
3.6%
D 12
 
3.6%
Other values (16) 134
40.5%
Decimal Number
ValueCountFrequency (%)
9 13
12.6%
4 13
12.6%
2 12
11.7%
8 11
10.7%
0 10
9.7%
3 10
9.7%
6 10
9.7%
5 9
8.7%
1 9
8.7%
7 6
5.8%
Other Punctuation
ValueCountFrequency (%)
/ 120
57.1%
. 60
28.6%
: 30
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1345
80.1%
Common 335
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 104
 
7.7%
t 100
 
7.4%
e 74
 
5.5%
n 72
 
5.4%
c 71
 
5.3%
o 69
 
5.1%
h 68
 
5.1%
u 65
 
4.8%
p 44
 
3.3%
C 43
 
3.2%
Other values (42) 635
47.2%
Common
ValueCountFrequency (%)
/ 120
35.8%
. 60
17.9%
: 30
 
9.0%
- 15
 
4.5%
9 13
 
3.9%
4 13
 
3.9%
2 12
 
3.6%
8 11
 
3.3%
0 10
 
3.0%
3 10
 
3.0%
Other values (5) 41
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 120
 
7.1%
w 104
 
6.2%
t 100
 
6.0%
e 74
 
4.4%
n 72
 
4.3%
c 71
 
4.2%
o 69
 
4.1%
h 68
 
4.0%
u 65
 
3.9%
. 60
 
3.6%
Other values (57) 877
52.2%

이용자활동평가영상ID
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:18:56.645545image/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=U4IV0PMv5TI
2nd rowhttps://www.youtube.com/watch?v=htAoY2nL8Hw
3rd rowhttps://www.youtube.com/watch?v=goqcCP5HvSY
4th rowhttps://www.youtube.com/watch?v=Yhoz0FHIVnw
5th rowhttps://www.youtube.com/watch?v=OIxc0RtJcFw
ValueCountFrequency (%)
https://www.youtube.com/watch?v=u4iv0pmv5ti 1
 
3.3%
https://www.youtube.com/watch?v=htaoy2nl8hw 1
 
3.3%
https://www.youtube.com/watch?v=ypnj6o8lhl8 1
 
3.3%
https://www.youtube.com/watch?v=v5okdt-7oum 1
 
3.3%
https://www.youtube.com/watch?v=jianrrd4qvw 1
 
3.3%
https://www.youtube.com/watch?v=pcv1-sdrama 1
 
3.3%
https://www.youtube.com/watch?v=jbpj166mc-g 1
 
3.3%
https://www.youtube.com/watch?v=muz3xo-rlna 1
 
3.3%
https://www.youtube.com/watch?v=3mpqrcuuqis 1
 
3.3%
https://www.youtube.com/watch?v=5m1z2olv1bw 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:18:57.049313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 129
 
10.0%
t 125
 
9.7%
/ 90
 
7.0%
c 70
 
5.4%
o 69
 
5.3%
h 67
 
5.2%
u 65
 
5.0%
. 60
 
4.7%
m 37
 
2.9%
p 36
 
2.8%
Other values (59) 542
42.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 863
66.9%
Other Punctuation 210
 
16.3%
Uppercase Letter 123
 
9.5%
Decimal Number 55
 
4.3%
Math Symbol 30
 
2.3%
Dash Punctuation 8
 
0.6%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 129
14.9%
t 125
14.5%
c 70
 
8.1%
o 69
 
8.0%
h 67
 
7.8%
u 65
 
7.5%
m 37
 
4.3%
p 36
 
4.2%
y 35
 
4.1%
s 35
 
4.1%
Other values (16) 195
22.6%
Uppercase Letter
ValueCountFrequency (%)
M 11
 
8.9%
I 10
 
8.1%
P 9
 
7.3%
D 8
 
6.5%
U 8
 
6.5%
Q 7
 
5.7%
Y 6
 
4.9%
E 6
 
4.9%
X 5
 
4.1%
A 5
 
4.1%
Other values (16) 48
39.0%
Decimal Number
ValueCountFrequency (%)
6 10
18.2%
5 7
12.7%
1 6
10.9%
8 6
10.9%
0 5
9.1%
7 5
9.1%
3 4
 
7.3%
9 4
 
7.3%
4 4
 
7.3%
2 4
 
7.3%
Other Punctuation
ValueCountFrequency (%)
/ 90
42.9%
. 60
28.6%
: 30
 
14.3%
? 30
 
14.3%
Math Symbol
ValueCountFrequency (%)
= 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 986
76.4%
Common 304
 
23.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 129
13.1%
t 125
 
12.7%
c 70
 
7.1%
o 69
 
7.0%
h 67
 
6.8%
u 65
 
6.6%
m 37
 
3.8%
p 36
 
3.7%
y 35
 
3.5%
s 35
 
3.5%
Other values (42) 318
32.3%
Common
ValueCountFrequency (%)
/ 90
29.6%
. 60
19.7%
: 30
 
9.9%
= 30
 
9.9%
? 30
 
9.9%
6 10
 
3.3%
- 8
 
2.6%
5 7
 
2.3%
1 6
 
2.0%
8 6
 
2.0%
Other values (7) 27
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 129
 
10.0%
t 125
 
9.7%
/ 90
 
7.0%
c 70
 
5.4%
o 69
 
5.3%
h 67
 
5.2%
u 65
 
5.0%
. 60
 
4.7%
m 37
 
2.9%
p 36
 
2.8%
Other values (59) 542
42.0%

이용자활동평가생성기간
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-10-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10-01
2nd row2021-10-01
3rd row2021-10-01
4th row2021-10-01
5th row2021-10-01

Common Values

ValueCountFrequency (%)
2021-10-01 30
100.0%

Length

2023-12-10T23:18:57.211727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:18:57.306118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10-01 30
100.0%

이용자활동평가채널조회수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2347153 × 108
Minimum115613
Maximum1.7409567 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:18:57.399776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum115613
5-th percentile218389.6
Q16340119.2
median42884312
Q33.0702592 × 108
95-th percentile7.8368545 × 108
Maximum1.7409567 × 109
Range1.740841 × 109
Interquartile range (IQR)3.006858 × 108

Descriptive statistics

Standard deviation3.7704707 × 108
Coefficient of variation (CV)1.6872264
Kurtosis8.4918489
Mean2.2347153 × 108
Median Absolute Deviation (MAD)42373230
Skewness2.6575897
Sum6.704146 × 109
Variance1.421645 × 1017
MonotonicityNot monotonic
2023-12-10T23:18:57.525671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
542652096 2
 
6.7%
159274 1
 
3.3%
167064429 1
 
3.3%
6228246 1
 
3.3%
32923833 1
 
3.3%
290642 1
 
3.3%
44250782 1
 
3.3%
20508288 1
 
3.3%
18941855 1
 
3.3%
8809204 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
115613 1
3.3%
159274 1
3.3%
290642 1
3.3%
731522 1
3.3%
848249 1
3.3%
2310670 1
3.3%
5340596 1
3.3%
6228246 1
3.3%
6675739 1
3.3%
8809204 1
3.3%
ValueCountFrequency (%)
1740956653 1
3.3%
918929505 1
3.3%
618387166 1
3.3%
593917909 1
3.3%
542652096 2
6.7%
424458977 1
3.3%
321454942 1
3.3%
263738838 1
3.3%
167064429 1
3.3%
115183827 1
3.3%

이용자활동평가구독자수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean298524.37
Minimum931
Maximum1380000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:18:57.652222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum931
5-th percentile2343.5
Q129075
median92350
Q3441250
95-th percentile960950
Maximum1380000
Range1379069
Interquartile range (IQR)412175

Descriptive statistics

Standard deviation350611.33
Coefficient of variation (CV)1.1744814
Kurtosis1.9377065
Mean298524.37
Median Absolute Deviation (MAD)91034.5
Skewness1.4460156
Sum8955731
Variance1.229283 × 1011
MonotonicityNot monotonic
2023-12-10T23:18:57.775555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
25100 2
 
6.7%
430000 2
 
6.7%
3300 1
 
3.3%
49400 1
 
3.3%
73500 1
 
3.3%
3130 1
 
3.3%
77200 1
 
3.3%
41000 1
 
3.3%
70400 1
 
3.3%
85500 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
931 1
3.3%
1700 1
3.3%
3130 1
3.3%
3300 1
3.3%
7570 1
3.3%
21500 1
3.3%
25100 2
6.7%
41000 1
3.3%
49400 1
3.3%
58200 1
3.3%
ValueCountFrequency (%)
1380000 1
3.3%
1010000 1
3.3%
901000 1
3.3%
679000 1
3.3%
678000 1
3.3%
491000 1
3.3%
468000 1
3.3%
445000 1
3.3%
430000 2
6.7%
422000 1
3.3%

이용자활동평가영상조회수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92384.267
Minimum14
Maximum1122456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:18:57.922107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile20.9
Q1158.25
median2621.5
Q321314.75
95-th percentile566653.8
Maximum1122456
Range1122442
Interquartile range (IQR)21156.5

Descriptive statistics

Standard deviation249328.48
Coefficient of variation (CV)2.6988197
Kurtosis12.118693
Mean92384.267
Median Absolute Deviation (MAD)2604.5
Skewness3.4971655
Sum2771528
Variance6.2164692 × 1010
MonotonicityNot monotonic
2023-12-10T23:18:58.046642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
101 1
 
3.3%
18998 1
 
3.3%
146 1
 
3.3%
85393 1
 
3.3%
87 1
 
3.3%
2840 1
 
3.3%
7167 1
 
3.3%
9919 1
 
3.3%
70075 1
 
3.3%
270 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
14 1
3.3%
20 1
3.3%
22 1
3.3%
57 1
3.3%
75 1
3.3%
87 1
3.3%
101 1
3.3%
146 1
3.3%
195 1
3.3%
270 1
3.3%
ValueCountFrequency (%)
1122456 1
3.3%
819858 1
3.3%
257182 1
3.3%
156354 1
3.3%
149171 1
3.3%
85393 1
3.3%
70075 1
3.3%
22044 1
3.3%
19127 1
3.3%
18998 1
3.3%

이용자활동평가긍정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)82.6%
Missing7
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean95.521739
Minimum75
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:18:58.158898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile81.68
Q195.65
median97.3
Q399.4
95-th percentile100
Maximum100
Range25
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation6.3480102
Coefficient of variation (CV)0.066456183
Kurtosis4.9894607
Mean95.521739
Median Absolute Deviation (MAD)2
Skewness-2.246716
Sum2197
Variance40.297233
MonotonicityNot monotonic
2023-12-10T23:18:58.290695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
100.0 5
16.7%
96.6 1
 
3.3%
80.8 1
 
3.3%
75.0 1
 
3.3%
93.8 1
 
3.3%
96.9 1
 
3.3%
99.6 1
 
3.3%
97.9 1
 
3.3%
97.3 1
 
3.3%
96.0 1
 
3.3%
Other values (9) 9
30.0%
(Missing) 7
23.3%
ValueCountFrequency (%)
75.0 1
3.3%
80.8 1
3.3%
89.6 1
3.3%
89.7 1
3.3%
93.8 1
3.3%
95.3 1
3.3%
96.0 1
3.3%
96.4 1
3.3%
96.5 1
3.3%
96.6 1
3.3%
ValueCountFrequency (%)
100.0 5
16.7%
99.6 1
 
3.3%
99.2 1
 
3.3%
99.1 1
 
3.3%
98.8 1
 
3.3%
98.5 1
 
3.3%
97.9 1
 
3.3%
97.3 1
 
3.3%
96.9 1
 
3.3%
96.6 1
 
3.3%

이용자활동평가부정평가비율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)82.6%
Missing7
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean4.4782609
Minimum0
Maximum25
Zeros5
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:18:58.407393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6
median2.7
Q34.35
95-th percentile18.32
Maximum25
Range25
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation6.3480102
Coefficient of variation (CV)1.4175168
Kurtosis4.9894607
Mean4.4782609
Median Absolute Deviation (MAD)2
Skewness2.246716
Sum103
Variance40.297233
MonotonicityNot monotonic
2023-12-10T23:18:58.505256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 5
16.7%
3.4 1
 
3.3%
19.2 1
 
3.3%
25.0 1
 
3.3%
6.2 1
 
3.3%
3.1 1
 
3.3%
0.4 1
 
3.3%
2.1 1
 
3.3%
2.7 1
 
3.3%
4.0 1
 
3.3%
Other values (9) 9
30.0%
(Missing) 7
23.3%
ValueCountFrequency (%)
0.0 5
16.7%
0.4 1
 
3.3%
0.8 1
 
3.3%
0.9 1
 
3.3%
1.2 1
 
3.3%
1.5 1
 
3.3%
2.1 1
 
3.3%
2.7 1
 
3.3%
3.1 1
 
3.3%
3.4 1
 
3.3%
ValueCountFrequency (%)
25.0 1
3.3%
19.2 1
3.3%
10.4 1
3.3%
10.3 1
3.3%
6.2 1
3.3%
4.7 1
3.3%
4.0 1
3.3%
3.6 1
3.3%
3.5 1
3.3%
3.4 1
3.3%

수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205.7
Minimum0
Maximum3458
Zeros13
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:18:58.601603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q388
95-th percentile898.4
Maximum3458
Range3458
Interquartile range (IQR)88

Descriptive statistics

Standard deviation656.39786
Coefficient of variation (CV)3.1910445
Kurtosis22.413406
Mean205.7
Median Absolute Deviation (MAD)5
Skewness4.5849445
Sum6171
Variance430858.15
MonotonicityNot monotonic
2023-12-10T23:18:58.711392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 13
43.3%
5 2
 
6.7%
18 1
 
3.3%
127 1
 
3.3%
92 1
 
3.3%
93 1
 
3.3%
242 1
 
3.3%
17 1
 
3.3%
45 1
 
3.3%
76 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0 13
43.3%
1 1
 
3.3%
5 2
 
6.7%
11 1
 
3.3%
17 1
 
3.3%
18 1
 
3.3%
24 1
 
3.3%
45 1
 
3.3%
76 1
 
3.3%
92 1
 
3.3%
ValueCountFrequency (%)
3458 1
3.3%
1136 1
3.3%
608 1
3.3%
242 1
3.3%
213 1
3.3%
127 1
3.3%
93 1
3.3%
92 1
3.3%
76 1
3.3%
45 1
3.3%

Interactions

2023-12-10T23:18:54.350945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:49.544994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:50.660987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:51.487500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:52.573236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:53.509978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:54.483447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:49.696209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:50.799549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:51.664982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:52.743645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:53.642617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:54.606435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:49.824366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:50.929874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:51.836517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:52.985197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:53.801569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:54.739158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:49.977505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:51.061086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:52.021703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:53.110642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:53.954426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:54.860369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:50.097464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:51.198274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:52.212129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:53.235336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:54.111179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:54.973870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:50.235704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:51.317478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:52.384126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:53.378762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:54.222075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:18:59.094203image/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
이용자활동평가채널조회수1.0001.0001.0000.9050.7880.0000.0000.832
이용자활동평가구독자수1.0001.0000.9051.0000.8410.0000.0000.964
이용자활동평가영상조회수1.0001.0000.7880.8411.0000.5380.5381.000
이용자활동평가긍정평가비율1.0001.0000.0000.0000.5381.0001.0000.629
이용자활동평가부정평가비율1.0001.0000.0000.0000.5381.0001.0000.629
수1.0001.0000.8320.9641.0000.6290.6291.000
2023-12-10T23:18:59.260342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
이용자활동평가채널조회수1.0000.9540.243-0.4230.4230.329
이용자활동평가구독자수0.9541.0000.273-0.4840.4840.322
이용자활동평가영상조회수0.2430.2731.000-0.5150.5150.858
이용자활동평가긍정평가비율-0.423-0.484-0.5151.000-1.000-0.452
이용자활동평가부정평가비율0.4230.4840.515-1.0001.0000.452
수0.3290.3220.858-0.4520.4521.000

Missing values

2023-12-10T23:18:55.182058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:18:55.401370image/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.
2023-12-10T23:18:55.553279image/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/UCz22EWP6u08x3b3aYSMh5BQhttps://www.youtube.com/watch?v=U4IV0PMv5TI2021-10-011592743300101100.00.00
1https://www.youtube.com/channel/UCGNCf6ibX1HWndVRgiChpqwhttps://www.youtube.com/watch?v=htAoY2nL8Hw2021-10-0126373883823700025718298.51.5608
2https://www.youtube.com/channel/UCeivPjjK9-cdj8-gw4-7JRghttps://www.youtube.com/watch?v=goqcCP5HvSY2021-10-0142445897767800081985896.63.41136
3https://www.youtube.com/channel/UCG9aFJTZ-lMCHAiO1KJsirghttps://www.youtube.com/watch?v=Yhoz0FHIVnw2021-10-01918929505901000195<NA><NA>1
4https://www.youtube.com/channel/UCmCq-9yl81BozVhZAiKNe-Qhttps://www.youtube.com/watch?v=OIxc0RtJcFw2021-10-0113261854582002403100.00.011
5https://www.youtube.com/channel/UCNle4Z5UkYVybg6Vj2gGd4Ahttps://www.youtube.com/watch?v=YcxCPI_R-eI2021-10-018482497570342100.00.00
6https://www.youtube.com/channel/UCucybMZtilvYSg2_f3eAIHghttps://www.youtube.com/watch?v=kgvr1urd8ds2021-10-01618387166679000112245680.819.23458
7https://www.youtube.com/channel/UCfWZnsdfiKvOyHDGfzMT3Cghttps://www.youtube.com/watch?v=DMD-dWiTbM42021-10-0132145494246800075<NA><NA>0
8https://www.youtube.com/channel/UCYZv9v_bwfMGc64gLRe34OAhttps://www.youtube.com/watch?v=QL5XPKNMn0Y2021-10-011740956653138000014917196.43.6213
9https://www.youtube.com/channel/UCKNZsAeQXpvI-Mpoc0ZKhsAhttps://www.youtube.com/watch?v=l63896h-5182021-10-0195865092395000190199.20.85
이용자활동평가채널ID이용자활동평가영상ID이용자활동평가생성기간이용자활동평가채널조회수이용자활동평가구독자수이용자활동평가영상조회수이용자활동평가긍정평가비율이용자활동평가부정평가비율수
20https://www.youtube.com/channel/UCH2mJnztSdNh8ADp2KmtUMQhttps://www.youtube.com/watch?v=P9mM9iUrh5s2021-10-0111518382749100015635495.34.7242
21https://www.youtube.com/channel/UC-PHIZjV-oX8H7zD1cCN2NQhttps://www.youtube.com/watch?v=5m1z2oLv1bw2021-10-0176338745445000161596.04.05
22https://www.youtube.com/channel/UCB-ogYCX9Me8nP9gEGpMjUghttps://www.youtube.com/watch?v=3mpqrcuUQis2021-10-01542652096430000270100.00.00
23https://www.youtube.com/channel/UCELCFg_JcEc3PyDd46HUMKghttps://www.youtube.com/watch?v=MUz3XO-rlNA2021-10-018809204855007007597.32.70
24https://www.youtube.com/channel/UCWiVOmszwaP5DPUHQjq5qAAhttps://www.youtube.com/watch?v=jbpJ166mc-g2021-10-011894185570400991997.92.193
25https://www.youtube.com/channel/UCURMKkMneWCkpO__BtAinswhttps://www.youtube.com/watch?v=pCV1-sDraMA2021-10-012050828841000716799.60.492
26https://www.youtube.com/channel/UCfV7aELAtpPBbixhf06Jlqghttps://www.youtube.com/watch?v=JiaNrRD4QVw2021-10-014425078277200284096.93.10
27https://www.youtube.com/channel/UCJ11gB9E0bT1sM5wPTZt45Qhttps://www.youtube.com/watch?v=v5okdt-7ouM2021-10-01290642313087100.00.00
28https://www.youtube.com/channel/UCcKITUR4mDL0BSugm4nn66whttps://www.youtube.com/watch?v=yPnj6O8lHL82021-10-0132923833735008539393.86.2127
29https://www.youtube.com/channel/UC4DgFN9dvM0DPXXvsS3FO-whttps://www.youtube.com/watch?v=gYiXcfQ7Eek2021-10-0162282462510014675.025.00