Overview

Dataset statistics

Number of variables17
Number of observations124
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.8 KiB
Average record size in memory147.1 B

Variable types

Numeric10
Categorical7

Alerts

CHNNEL_CL_NM has constant value ""Constant
UPPER_CTGRY_NM has constant value ""Constant
CHNNEL_URL is highly overall correlated with SBSCRB_CO and 11 other fieldsHigh correlation
CHNNEL_ID is highly overall correlated with SBSCRB_CO and 11 other fieldsHigh correlation
CHNNEL_NM is highly overall correlated with SBSCRB_CO and 11 other fieldsHigh correlation
LWPRT_CTGRY_NM is highly overall correlated with SBSCRB_CO and 5 other fieldsHigh correlation
SEQ_NO is highly overall correlated with COLCT_DEHigh correlation
SBSCRB_CO is highly overall correlated with LIKE_CO and 7 other fieldsHigh correlation
VIEWS_CO is highly overall correlated with LIKE_CO and 7 other fieldsHigh correlation
LIKE_CO is highly overall correlated with SBSCRB_CO and 10 other fieldsHigh correlation
DISLIKE_CO is highly overall correlated with SBSCRB_CO and 10 other fieldsHigh correlation
COMMENT_CO is highly overall correlated with VIEWS_CO and 7 other fieldsHigh correlation
DPI_VALUE is highly overall correlated with SBSCRB_CO and 7 other fieldsHigh correlation
DV_VALUE is highly overall correlated with SBSCRB_CO and 7 other fieldsHigh correlation
RSPN_SM_CO is highly overall correlated with VIEWS_CO and 7 other fieldsHigh correlation
RSPN_IRDS_CO is highly overall correlated with VIEWS_CO and 7 other fieldsHigh correlation
COLCT_DE is highly overall correlated with SEQ_NOHigh correlation
SEQ_NO has unique valuesUnique
VIEWS_CO has unique valuesUnique
LIKE_CO has unique valuesUnique
COMMENT_CO has unique valuesUnique
DPI_VALUE has unique valuesUnique
DV_VALUE has unique valuesUnique
RSPN_SM_CO has unique valuesUnique
RSPN_IRDS_CO has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:58:36.981249
Analysis finished2023-12-10 09:59:00.153582
Duration23.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SEQ_NO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73062.766
Minimum72285
Maximum73839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:00.285228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum72285
5-th percentile72364.8
Q172669.25
median73080.5
Q373453.5
95-th percentile73758.45
Maximum73839
Range1554
Interquartile range (IQR)784.25

Descriptive statistics

Standard deviation453.34497
Coefficient of variation (CV)0.00620487
Kurtosis-1.2129226
Mean73062.766
Median Absolute Deviation (MAD)390
Skewness-0.009244602
Sum9059783
Variance205521.66
MonotonicityNot monotonic
2023-12-10T18:59:00.538643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72307 1
 
0.8%
73183 1
 
0.8%
73839 1
 
0.8%
73744 1
 
0.8%
73714 1
 
0.8%
73675 1
 
0.8%
73592 1
 
0.8%
73542 1
 
0.8%
73497 1
 
0.8%
73458 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
72285 1
0.8%
72307 1
0.8%
72311 1
0.8%
72325 1
0.8%
72335 1
0.8%
72360 1
0.8%
72363 1
0.8%
72375 1
0.8%
72386 1
0.8%
72405 1
0.8%
ValueCountFrequency (%)
73839 1
0.8%
73823 1
0.8%
73801 1
0.8%
73799 1
0.8%
73788 1
0.8%
73762 1
0.8%
73761 1
0.8%
73744 1
0.8%
73729 1
0.8%
73722 1
0.8%

CHNNEL_CL_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
youtube
124 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowyoutube
2nd rowyoutube
3rd rowyoutube
4th rowyoutube
5th rowyoutube

Common Values

ValueCountFrequency (%)
youtube 124
100.0%

Length

2023-12-10T18:59:00.775534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:00.994975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
youtube 124
100.0%

CHNNEL_ID
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
UCid83oPnsL-4ZEo8CyQr6Rg
31 
UCw8ZhLPdQ0u_Y-TLKd61hGA
31 
UC3IZKseVpdzPSBaWxBxundA
31 
UCmjNKt6kITwaZTqvWuaSPLg
31 

Length

Max length24
Median length24
Mean length24
Min length24

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUCid83oPnsL-4ZEo8CyQr6Rg
2nd rowUCid83oPnsL-4ZEo8CyQr6Rg
3rd rowUCid83oPnsL-4ZEo8CyQr6Rg
4th rowUCid83oPnsL-4ZEo8CyQr6Rg
5th rowUCid83oPnsL-4ZEo8CyQr6Rg

Common Values

ValueCountFrequency (%)
UCid83oPnsL-4ZEo8CyQr6Rg 31
25.0%
UCw8ZhLPdQ0u_Y-TLKd61hGA 31
25.0%
UC3IZKseVpdzPSBaWxBxundA 31
25.0%
UCmjNKt6kITwaZTqvWuaSPLg 31
25.0%

Length

2023-12-10T18:59:01.158405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:01.333447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ucid83opnsl-4zeo8cyqr6rg 31
25.0%
ucw8zhlpdq0u_y-tlkd61hga 31
25.0%
uc3izksevpdzpsbawxbxunda 31
25.0%
ucmjnkt6kitwaztqvwuasplg 31
25.0%

CHNNEL_NM
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
플레이리스트
31 
1MILLION Dance Studio
31 
ibighit
31 
SBS Entertainment
31 

Length

Max length21
Median length12
Mean length12.75
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row플레이리스트
2nd row플레이리스트
3rd row플레이리스트
4th row플레이리스트
5th row플레이리스트

Common Values

ValueCountFrequency (%)
플레이리스트 31
25.0%
1MILLION Dance Studio 31
25.0%
ibighit 31
25.0%
SBS Entertainment 31
25.0%

Length

2023-12-10T18:59:01.556236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:01.787582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
플레이리스트 31
14.3%
1million 31
14.3%
dance 31
14.3%
studio 31
14.3%
ibighit 31
14.3%
sbs 31
14.3%
entertainment 31
14.3%

CHNNEL_URL
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg
31 
https://www.youtube.com/channel/UCw8ZhLPdQ0u_Y-TLKd61hGA
31 
https://www.youtube.com/user/ibighit
31 
https://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg
31 

Length

Max length56
Median length56
Mean length51
Min length36

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg
2nd rowhttps://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg
3rd rowhttps://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg
4th rowhttps://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg
5th rowhttps://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg

Common Values

ValueCountFrequency (%)
https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg 31
25.0%
https://www.youtube.com/channel/UCw8ZhLPdQ0u_Y-TLKd61hGA 31
25.0%
https://www.youtube.com/user/ibighit 31
25.0%
https://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg 31
25.0%

Length

2023-12-10T18:59:02.026933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:02.297725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
https://www.youtube.com/channel/ucid83opnsl-4zeo8cyqr6rg 31
25.0%
https://www.youtube.com/channel/ucw8zhlpdq0u_y-tlkd61hga 31
25.0%
https://www.youtube.com/user/ibighit 31
25.0%
https://www.youtube.com/channel/ucmjnkt6kitwaztqvwuasplg 31
25.0%

UPPER_CTGRY_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
문화
124 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화
2nd row문화
3rd row문화
4th row문화
5th row문화

Common Values

ValueCountFrequency (%)
문화 124
100.0%

Length

2023-12-10T18:59:02.543911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:02.717020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화 124
100.0%

LWPRT_CTGRY_NM
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
방송
93 
음악/댄스
31 

Length

Max length5
Median length2
Mean length2.75
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row방송
2nd row방송
3rd row방송
4th row방송
5th row방송

Common Values

ValueCountFrequency (%)
방송 93
75.0%
음악/댄스 31
 
25.0%

Length

2023-12-10T18:59:02.953528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:03.197982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방송 93
75.0%
음악/댄스 31
 
25.0%

COLCT_DE
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2021-01-01
 
4
2021-01-02
 
4
2021-01-03
 
4
2021-01-04
 
4
2021-01-05
 
4
Other values (26)
104 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-01
2nd row2021-01-02
3rd row2021-01-03
4th row2021-01-04
5th row2021-01-05

Common Values

ValueCountFrequency (%)
2021-01-01 4
 
3.2%
2021-01-02 4
 
3.2%
2021-01-03 4
 
3.2%
2021-01-04 4
 
3.2%
2021-01-05 4
 
3.2%
2021-01-06 4
 
3.2%
2021-01-07 4
 
3.2%
2021-01-08 4
 
3.2%
2021-01-09 4
 
3.2%
2021-01-10 4
 
3.2%
Other values (21) 84
67.7%

Length

2023-12-10T18:59:03.444618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-01-01 4
 
3.2%
2021-01-17 4
 
3.2%
2021-01-30 4
 
3.2%
2021-01-29 4
 
3.2%
2021-01-28 4
 
3.2%
2021-01-27 4
 
3.2%
2021-01-26 4
 
3.2%
2021-01-25 4
 
3.2%
2021-01-24 4
 
3.2%
2021-01-23 4
 
3.2%
Other values (21) 84
67.7%

SBSCRB_CO
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20239194
Minimum2570000
Maximum50600000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:03.675884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2570000
5-th percentile2580000
Q14482500
median14060000
Q329825000
95-th percentile50400000
Maximum50600000
Range48030000
Interquartile range (IQR)25342500

Descriptive statistics

Standard deviation19063368
Coefficient of variation (CV)0.94190356
Kurtosis-1.1695427
Mean20239194
Median Absolute Deviation (MAD)10300000
Skewness0.66177101
Sum2.50966 × 109
Variance3.6341201 × 1014
MonotonicityNot monotonic
2023-12-10T18:59:03.898786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
23000000 15
 
12.1%
2600000 13
 
10.5%
23100000 11
 
8.9%
2590000 8
 
6.5%
2580000 7
 
5.6%
50000000 4
 
3.2%
50300000 4
 
3.2%
2570000 3
 
2.4%
50600000 3
 
2.4%
5220000 3
 
2.4%
Other values (20) 53
42.7%
ValueCountFrequency (%)
2570000 3
 
2.4%
2580000 7
5.6%
2590000 8
6.5%
2600000 13
10.5%
5110000 2
 
1.6%
5120000 3
 
2.4%
5130000 2
 
1.6%
5140000 2
 
1.6%
5150000 3
 
2.4%
5160000 3
 
2.4%
ValueCountFrequency (%)
50600000 3
2.4%
50500000 3
2.4%
50400000 3
2.4%
50300000 4
3.2%
50200000 3
2.4%
50100000 3
2.4%
50000000 4
3.2%
49900000 3
2.4%
49800000 2
1.6%
49700000 3
2.4%

VIEWS_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5050679 × 108
Minimum248268
Maximum5.6724642 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:04.123440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum248268
5-th percentile658385.25
Q118581988
median36119444
Q31.5930589 × 108
95-th percentile5.4676464 × 108
Maximum5.6724642 × 108
Range5.6699815 × 108
Interquartile range (IQR)1.407239 × 108

Descriptive statistics

Standard deviation2.2048146 × 108
Coefficient of variation (CV)1.464927
Kurtosis-0.6304688
Mean1.5050679 × 108
Median Absolute Deviation (MAD)22870935
Skewness1.1583744
Sum1.8662842 × 1010
Variance4.8612073 × 1016
MonotonicityNot monotonic
2023-12-10T18:59:04.825571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47280412 1
 
0.8%
514321858 1
 
0.8%
548017718 1
 
0.8%
545181983 1
 
0.8%
542671448 1
 
0.8%
540424369 1
 
0.8%
537668972 1
 
0.8%
523323705 1
 
0.8%
520745777 1
 
0.8%
518311103 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
248268 1
0.8%
271107 1
0.8%
438642 1
0.8%
448558 1
0.8%
507943 1
0.8%
647631 1
0.8%
653238 1
0.8%
687553 1
0.8%
705375 1
0.8%
735262 1
0.8%
ValueCountFrequency (%)
567246417 1
0.8%
564162193 1
0.8%
560980003 1
0.8%
549483733 1
0.8%
549073574 1
0.8%
548017718 1
0.8%
547009392 1
0.8%
545377721 1
0.8%
545181983 1
0.8%
542671448 1
0.8%

LIKE_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13925078
Minimum6863
Maximum55505225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:05.117603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6863
5-th percentile9132
Q1588027
median1181456
Q314215289
95-th percentile54890099
Maximum55505225
Range55498362
Interquartile range (IQR)13627262

Descriptive statistics

Standard deviation22798227
Coefficient of variation (CV)1.6372064
Kurtosis-0.63232474
Mean13925078
Median Absolute Deviation (MAD)928991
Skewness1.1700459
Sum1.7267097 × 109
Variance5.1975916 × 1014
MonotonicityNot monotonic
2023-12-10T18:59:05.407916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
911343 1
 
0.8%
52349020 1
 
0.8%
53394050 1
 
0.8%
53332527 1
 
0.8%
53277438 1
 
0.8%
53225737 1
 
0.8%
53162388 1
 
0.8%
51679888 1
 
0.8%
51621120 1
 
0.8%
51560013 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
6863 1
0.8%
6918 1
0.8%
7224 1
0.8%
8221 1
0.8%
8619 1
0.8%
9076 1
0.8%
9081 1
0.8%
9421 1
0.8%
10345 1
0.8%
10357 1
0.8%
ValueCountFrequency (%)
55505225 1
0.8%
55335424 1
0.8%
55278186 1
0.8%
55177785 1
0.8%
55157142 1
0.8%
55057507 1
0.8%
54923653 1
0.8%
54699960 1
0.8%
54646246 1
0.8%
54636995 1
0.8%

DISLIKE_CO
Real number (ℝ)

HIGH CORRELATION 

Distinct123
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120742.44
Minimum115
Maximum483299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:05.722178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum115
5-th percentile234.95
Q17328.25
median14399
Q3120664.5
95-th percentile478104.45
Maximum483299
Range483184
Interquartile range (IQR)113336.25

Descriptive statistics

Standard deviation194969.06
Coefficient of variation (CV)1.6147517
Kurtosis-0.61614151
Mean120742.44
Median Absolute Deviation (MAD)9239.5
Skewness1.1737024
Sum14972062
Variance3.8012933 × 1010
MonotonicityNot monotonic
2023-12-10T18:59:06.097322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15969 2
 
1.6%
446274 1
 
0.8%
459415 1
 
0.8%
458132 1
 
0.8%
456945 1
 
0.8%
455951 1
 
0.8%
454539 1
 
0.8%
437240 1
 
0.8%
436089 1
 
0.8%
434902 1
 
0.8%
Other values (113) 113
91.1%
ValueCountFrequency (%)
115 1
0.8%
127 1
0.8%
157 1
0.8%
183 1
0.8%
186 1
0.8%
194 1
0.8%
233 1
0.8%
246 1
0.8%
249 1
0.8%
251 1
0.8%
ValueCountFrequency (%)
483299 1
0.8%
482839 1
0.8%
482423 1
0.8%
480765 1
0.8%
480545 1
0.8%
479026 1
0.8%
478155 1
0.8%
477818 1
0.8%
476509 1
0.8%
475690 1
0.8%

COMMENT_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1977629.7
Minimum668
Maximum8437450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:06.465087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum668
5-th percentile1051.5
Q124267.25
median57428
Q31931305.8
95-th percentile8071899.5
Maximum8437450
Range8436782
Interquartile range (IQR)1907038.5

Descriptive statistics

Standard deviation3376437.3
Coefficient of variation (CV)1.7073152
Kurtosis-0.61654151
Mean1977629.7
Median Absolute Deviation (MAD)41621
Skewness1.1756213
Sum2.4522608 × 108
Variance1.1400329 × 1013
MonotonicityNot monotonic
2023-12-10T18:59:06.842610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86501 1
 
0.8%
7563601 1
 
0.8%
7730785 1
 
0.8%
7717271 1
 
0.8%
7707453 1
 
0.8%
7699310 1
 
0.8%
7687291 1
 
0.8%
7603807 1
 
0.8%
7592179 1
 
0.8%
7580910 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
668 1
0.8%
709 1
0.8%
919 1
0.8%
932 1
0.8%
989 1
0.8%
1042 1
0.8%
1047 1
0.8%
1077 1
0.8%
1123 1
0.8%
1142 1
0.8%
ValueCountFrequency (%)
8437450 1
0.8%
8419204 1
0.8%
8400824 1
0.8%
8122364 1
0.8%
8105067 1
0.8%
8085738 1
0.8%
8072624 1
0.8%
8067794 1
0.8%
8065237 1
0.8%
8044131 1
0.8%

DPI_VALUE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3486467.8
Minimum1315700.6
Maximum6621033.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:07.463731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1315700.6
5-th percentile1367635.2
Q12042039.4
median3235734.3
Q34040584.1
95-th percentile6568531.5
Maximum6621033.2
Range5305332.6
Interquartile range (IQR)1998544.7

Descriptive statistics

Standard deviation1805876.9
Coefficient of variation (CV)0.51796747
Kurtosis-0.92249261
Mean3486467.8
Median Absolute Deviation (MAD)1401383.1
Skewness0.57604097
Sum4.3232201 × 108
Variance3.2611915 × 1012
MonotonicityNot monotonic
2023-12-10T18:59:08.144499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1329186.2999552 1
 
0.8%
6603479.92390044 1
 
0.8%
5879231.03974491 1
 
0.8%
5953177.29041111 1
 
0.8%
6009629.01718282 1
 
0.8%
6061126.65507634 1
 
0.8%
6168195.61714973 1
 
0.8%
6274259.45402017 1
 
0.8%
6377301.43346996 1
 
0.8%
6452030.80637161 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
1315700.60317547 1
0.8%
1329186.2999552 1
0.8%
1347041.27390014 1
0.8%
1350374.45021149 1
0.8%
1363064.37698071 1
0.8%
1365526.95429582 1
0.8%
1367553.53783964 1
0.8%
1368097.93012567 1
0.8%
1371231.20353027 1
0.8%
1374060.44256195 1
0.8%
ValueCountFrequency (%)
6621033.23695599 1
0.8%
6613688.67335937 1
0.8%
6603479.92390044 1
0.8%
6595020.60225755 1
0.8%
6583310.00764422 1
0.8%
6573082.77137695 1
0.8%
6569691.21520325 1
0.8%
6561960.01868353 1
0.8%
6534260.51011731 1
0.8%
6514329.91963021 1
0.8%

DV_VALUE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16072617
Minimum6065379.8
Maximum30522963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:08.853029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6065379.8
5-th percentile6304798.3
Q19413801.7
median14916735
Q318627093
95-th percentile30280930
Maximum30522963
Range24457583
Interquartile range (IQR)9213291.1

Descriptive statistics

Standard deviation8325092.6
Coefficient of variation (CV)0.51796747
Kurtosis-0.92249261
Mean16072617
Median Absolute Deviation (MAD)6460375.9
Skewness0.57604097
Sum1.9930045 × 109
Variance6.9307167 × 1013
MonotonicityNot monotonic
2023-12-10T18:59:09.191285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6127548.84279346 1
 
0.8%
30442042.449181 1
 
0.8%
27103255.093224 1
 
0.8%
27444147.3087952 1
 
0.8%
27704389.7692128 1
 
0.8%
27941793.8799019 1
 
0.8%
28435381.7950602 1
 
0.8%
28924336.083033 1
 
0.8%
29399359.6082965 1
 
0.8%
29743862.0173731 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
6065379.78063891 1
0.8%
6127548.84279346 1
0.8%
6209860.27267963 1
0.8%
6225226.21547495 1
0.8%
6283726.77788107 1
0.8%
6295079.25930373 1
0.8%
6304421.80944073 1
0.8%
6306931.45787932 1
0.8%
6321375.84827455 1
0.8%
6334418.64021061 1
0.8%
ValueCountFrequency (%)
30522963.2223671 1
0.8%
30489104.7841867 1
0.8%
30442042.449181 1
0.8%
30403044.9764073 1
0.8%
30349059.1352399 1
0.8%
30301911.5760478 1
0.8%
30286276.502087 1
0.8%
30250635.6861311 1
0.8%
30122940.9516408 1
0.8%
30031060.9294952 1
0.8%

RSPN_SM_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6653024 × 108
Minimum257548
Maximum6.3144448 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:59:09.463234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum257548
5-th percentile670890.75
Q119712224
median37532358
Q31.7473227 × 108
95-th percentile6.0955683 × 108
Maximum6.3144448 × 108
Range6.3118693 × 108
Interquartile range (IQR)1.5502005 × 108

Descriptive statistics

Standard deviation2.468022 × 108
Coefficient of variation (CV)1.4820263
Kurtosis-0.63021853
Mean1.6653024 × 108
Median Absolute Deviation (MAD)23520651
Skewness1.1606929
Sum2.064975 × 1010
Variance6.0911323 × 1016
MonotonicityNot monotonic
2023-12-10T18:59:09.804598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48294225 1
 
0.8%
574680753 1
 
0.8%
609601968 1
 
0.8%
606689913 1
 
0.8%
604113284 1
 
0.8%
601805367 1
 
0.8%
598973190 1
 
0.8%
583044640 1
 
0.8%
580395165 1
 
0.8%
577886928 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
257548 1
0.8%
278808 1
0.8%
448495 1
0.8%
456523 1
0.8%
532503 1
0.8%
655750 1
0.8%
666090 1
0.8%
698095 1
0.8%
717068 1
0.8%
754318 1
0.8%
ValueCountFrequency (%)
631444476 1
0.8%
628239947 1
0.8%
624917360 1
0.8%
613184462 1
0.8%
612680421 1
0.8%
610190690 1
0.8%
609601968 1
0.8%
609301051 1
0.8%
606689913 1
0.8%
604958235 1
0.8%

RSPN_IRDS_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-135913.62
Minimum-59491752
Maximum15928550
Zeros0
Zeros (%)0.0%
Negative33
Negative (%)26.6%
Memory size1.2 KiB
2023-12-10T18:59:10.108670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-59491752
5-th percentile-2195306.1
Q1-21876.75
median380403.5
Q3678179.5
95-th percentile3893038.1
Maximum15928550
Range75420302
Interquartile range (IQR)700056.25

Descriptive statistics

Standard deviation7011159.9
Coefficient of variation (CV)-51.58541
Kurtosis51.639292
Mean-135913.62
Median Absolute Deviation (MAD)371856.5
Skewness-6.6410746
Sum-16853289
Variance4.9156363 × 1013
MonotonicityNot monotonic
2023-12-10T18:59:10.610001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
669142 1
 
0.8%
3252122 1
 
0.8%
2912055 1
 
0.8%
2576629 1
 
0.8%
2307917 1
 
0.8%
2832177 1
 
0.8%
15928550 1
 
0.8%
2649475 1
 
0.8%
2508237 1
 
0.8%
2743415 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
-59491752 1
0.8%
-41715968 1
0.8%
-10548816 1
0.8%
-6360361 1
0.8%
-3303831 1
0.8%
-2993772 1
0.8%
-2201001 1
0.8%
-2163035 1
0.8%
-2154148 1
0.8%
-1689626 1
0.8%
ValueCountFrequency (%)
15928550 1
0.8%
6153949 1
0.8%
4828330 1
0.8%
4653939 1
0.8%
4421839 1
0.8%
4342816 1
0.8%
3894737 1
0.8%
3883411 1
0.8%
3803862 1
0.8%
3339569 1
0.8%

Interactions

2023-12-10T18:58:57.526773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:38.294146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:41.062779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:43.158149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:45.078120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:47.151056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:49.367197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:51.441314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:53.858883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:55.630817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:57.734556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:38.613721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:41.222759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:43.373042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:45.294551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:47.346764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:49.584290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:51.666221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:54.021259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:55.795553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:57.929651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:38.914828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:41.374127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:43.538229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:45.481282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:47.549109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:49.767147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:51.890053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:54.219654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:55.962940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:58.078607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:39.161211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:41.550418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:43.714231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:45.656584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:47.742448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:49.953101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:52.162877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:54.368757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:56.119884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:58.229436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:39.851068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:41.789467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:43.903077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:45.813756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:47.959383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:50.193943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:52.358379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:54.509180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:56.272910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:58.351396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:40.017317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:42.039562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:44.095218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:46.001611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:48.150926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:50.389900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:52.529877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:54.696759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:56.433194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:58.480451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:40.223893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:42.279948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:44.253966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:46.193440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:48.369815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:50.617084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:52.689931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:54.849937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:56.614482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:58.590542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:40.405116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:42.482449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:44.429626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:46.464025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:48.611020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:50.791250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:52.874607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:55.082596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:56.890241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:58.722945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:40.625706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:42.689149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:44.611566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:46.765117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:48.805987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:51.041821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:53.080515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:55.252548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:57.126018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:59.049990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:40.856105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:42.881184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:44.844152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:46.951948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:49.134332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:51.239114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:53.670797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:55.454665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:58:57.332249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:59:10.855943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SEQ_NOCHNNEL_IDCHNNEL_NMCHNNEL_URLLWPRT_CTGRY_NMCOLCT_DESBSCRB_COVIEWS_COLIKE_CODISLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_CO
SEQ_NO1.0000.0000.0000.0000.0000.9890.0000.0520.0000.1960.2740.3510.3510.0520.000
CHNNEL_ID0.0001.0001.0001.0001.0000.0001.0000.6691.0000.6690.6690.8580.8580.6690.589
CHNNEL_NM0.0001.0001.0001.0001.0000.0001.0000.6691.0000.6690.6690.8580.8580.6690.589
CHNNEL_URL0.0001.0001.0001.0001.0000.0001.0000.6691.0000.6690.6690.8580.8580.6690.589
LWPRT_CTGRY_NM0.0001.0001.0001.0001.0000.0001.0000.1910.4590.1890.1910.5290.5290.1910.222
COLCT_DE0.9890.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
SBSCRB_CO0.0001.0001.0001.0001.0000.0001.0000.9401.0000.9400.9400.7950.7950.9400.672
VIEWS_CO0.0520.6690.6690.6690.1910.0000.9401.0001.0000.9420.9750.7270.7271.0000.678
LIKE_CO0.0001.0001.0001.0000.4590.0001.0001.0001.0001.0001.0001.0001.0001.0000.801
DISLIKE_CO0.1960.6690.6690.6690.1890.0000.9400.9421.0001.0000.9680.7230.7230.9420.756
COMMENT_CO0.2740.6690.6690.6690.1910.0000.9400.9751.0000.9681.0000.7650.7650.9750.701
DPI_VALUE0.3510.8580.8580.8580.5290.0000.7950.7271.0000.7230.7651.0001.0000.7270.839
DV_VALUE0.3510.8580.8580.8580.5290.0000.7950.7271.0000.7230.7651.0001.0000.7270.839
RSPN_SM_CO0.0520.6690.6690.6690.1910.0000.9401.0001.0000.9420.9750.7270.7271.0000.678
RSPN_IRDS_CO0.0000.5890.5890.5890.2220.0000.6720.6780.8010.7560.7010.8390.8390.6781.000
2023-12-10T18:59:11.231881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CHNNEL_URLCHNNEL_IDCHNNEL_NMLWPRT_CTGRY_NMCOLCT_DE
CHNNEL_URL1.0001.0001.0000.9920.000
CHNNEL_ID1.0001.0001.0000.9920.000
CHNNEL_NM1.0001.0001.0000.9920.000
LWPRT_CTGRY_NM0.9920.9920.9921.0000.000
COLCT_DE0.0000.0000.0000.0001.000
2023-12-10T18:59:11.485075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SEQ_NOSBSCRB_COVIEWS_COLIKE_CODISLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_COCHNNEL_IDCHNNEL_NMCHNNEL_URLLWPRT_CTGRY_NMCOLCT_DE
SEQ_NO1.0000.233-0.038-0.126-0.138-0.139-0.114-0.114-0.0400.0710.0000.0000.0000.0000.827
SBSCRB_CO0.2331.0000.3680.7210.6880.3430.9000.9000.3670.4230.9960.9960.9960.9960.000
VIEWS_CO-0.0380.3681.0000.7910.8250.9810.3370.3371.0000.5220.6950.6950.6950.3090.000
LIKE_CO-0.1260.7210.7911.0000.9820.8050.7060.7060.7920.5250.9920.9920.9920.3000.000
DISLIKE_CO-0.1380.6880.8250.9821.0000.8250.6620.6620.8250.5360.6950.6950.6950.3090.000
COMMENT_CO-0.1390.3430.9810.8050.8251.0000.3450.3450.9810.5000.6950.6950.6950.3090.000
DPI_VALUE-0.1140.9000.3370.7060.6620.3451.0001.0000.3370.4090.8370.8370.8370.6350.000
DV_VALUE-0.1140.9000.3370.7060.6620.3451.0001.0000.3370.4090.8370.8370.8370.6350.000
RSPN_SM_CO-0.0400.3671.0000.7920.8250.9810.3370.3371.0000.5210.6950.6950.6950.3090.000
RSPN_IRDS_CO0.0710.4230.5220.5250.5360.5000.4090.4090.5211.0000.5070.5070.5070.2570.000
CHNNEL_ID0.0000.9960.6950.9920.6950.6950.8370.8370.6950.5071.0001.0001.0000.9920.000
CHNNEL_NM0.0000.9960.6950.9920.6950.6950.8370.8370.6950.5071.0001.0001.0000.9920.000
CHNNEL_URL0.0000.9960.6950.9920.6950.6950.8370.8370.6950.5071.0001.0001.0000.9920.000
LWPRT_CTGRY_NM0.0000.9960.3090.3000.3090.3090.6350.6350.3090.2570.9920.9920.9921.0000.000
COLCT_DE0.8270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-10T18:58:59.524917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:58:59.958217image/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.

Sample

SEQ_NOCHNNEL_CL_NMCHNNEL_IDCHNNEL_NMCHNNEL_URLUPPER_CTGRY_NMLWPRT_CTGRY_NMCOLCT_DESBSCRB_COVIEWS_COLIKE_CODISLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_CO
072307youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0125700004728041291134315969865011329186.2999556127548.84279348294225669142
172360youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0225700004681866088928615904846141350374.4502116225226.21547547808464-485761
272405youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0325700004752537089701416017850221365526.9542966295079.25930448523423714959
372454youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0425800004541545785003614477804181371231.203536321375.84827546360388-2163035
472495youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0525800004509586084252614457801801380664.5062576364863.37384446033023-327365
572559youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0625800004184491279663711164764791383719.298376378945.96548542729192-3303831
672626youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0725800004232172680143911252769141374060.4425626334418.64021143211331482139
772675youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-0825800004165722479615810403762321367553.537846304421.80944142540017-671314
872698youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-092580000412708387870889520753491388121.8628166399241.78758342142795-397222
972782youtubeUCid83oPnsL-4ZEo8CyQr6Rg플레이리스트https://www.youtube.com/channel/UCid83oPnsL-4ZEo8CyQr6Rg문화방송2021-01-102580000419431967935579618757091403682.3185726470975.48861742822080679285
SEQ_NOCHNNEL_CL_NMCHNNEL_IDCHNNEL_NMCHNNEL_URLUPPER_CTGRY_NMLWPRT_CTGRY_NMCOLCT_DESBSCRB_COVIEWS_COLIKE_CODISLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_CO
11473372youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-22519000024611922361961027263190407.43655714707778.2825272488147367887
11573399youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-23519000025815512543666430203169565.20538314611695.5968172610671122524
11673485youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-24520000044855868631839192281320.06806810516885.513792456523-2154148
11773507youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-255200000687553908123312282302563.76348610614818.949671698095241572
11873552youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-26520000010175661170335112722249727.59141310371244.1964121030892332797
11973606youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-2752100001028643942136210472284810.03624610532974.26709310394738581
12073664youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-285210000103753990763829892279282.31749210507491.48363710479868513
12173722youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-29522000012847171366950314342272285.93741310475238.1714751300323252337
12273762youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-30522000027110769181156682257251.94818810405931.481146278808-1021515
12373801youtubeUCmjNKt6kITwaZTqvWuaSPLgSBS Entertainmenthttps://www.youtube.com/channel/UCmjNKt6kITwaZTqvWuaSPLg문화방송2021-01-31522000024826882211279322272532.47301710476374.700607257548-21260