Overview

Dataset statistics

Number of variables15
Number of observations124
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.8 KiB
Average record size in memory130.1 B

Variable types

Numeric8
Categorical6
DateTime1

Alerts

CHNNEL_CL_NM has constant value ""Constant
UPPER_CTGRY_NM has constant value ""Constant
LWPRT_CTGRY_NM is highly overall correlated with FOLLOWER_CO and 3 other fieldsHigh correlation
CHNNEL_ID is highly overall correlated with FOLLOWER_CO and 8 other fieldsHigh correlation
CHNNEL_URL is highly overall correlated with FOLLOWER_CO and 8 other fieldsHigh correlation
CHNNEL_NM is highly overall correlated with FOLLOWER_CO and 8 other fieldsHigh correlation
FOLLOWER_CO is highly overall correlated with LIKE_CO and 7 other fieldsHigh correlation
LIKE_CO is highly overall correlated with FOLLOWER_CO and 6 other fieldsHigh correlation
COMMENT_CO is highly overall correlated with DPI_VALUE and 4 other fieldsHigh correlation
DPI_VALUE is highly overall correlated with FOLLOWER_CO and 7 other fieldsHigh correlation
DV_VALUE is highly overall correlated with FOLLOWER_CO and 7 other fieldsHigh correlation
RSPN_SM_CO is highly overall correlated with FOLLOWER_CO and 6 other fieldsHigh correlation
SEQ_NO has unique valuesUnique
FOLLOWER_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 09:50:34.009445
Analysis finished2023-12-10 09:50:48.235534
Duration14.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SEQ_NO
Real number (ℝ)

UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14728.266
Minimum14217
Maximum15238
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:50:48.386055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14217
5-th percentile14274.05
Q114469.5
median14729
Q314987.5
95-th percentile15191.5
Maximum15238
Range1021
Interquartile range (IQR)518

Descriptive statistics

Standard deviation297.88201
Coefficient of variation (CV)0.020225192
Kurtosis-1.2030974
Mean14728.266
Median Absolute Deviation (MAD)260
Skewness0.0048863432
Sum1826305
Variance88733.693
MonotonicityNot monotonic
2023-12-10T18:50:48.682722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14230 1
 
0.8%
14807 1
 
0.8%
15215 1
 
0.8%
15199 1
 
0.8%
15158 1
 
0.8%
15117 1
 
0.8%
15101 1
 
0.8%
15050 1
 
0.8%
15022 1
 
0.8%
14999 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
14217 1
0.8%
14226 1
0.8%
14230 1
0.8%
14239 1
0.8%
14258 1
0.8%
14269 1
0.8%
14273 1
0.8%
14280 1
0.8%
14286 1
0.8%
14293 1
0.8%
ValueCountFrequency (%)
15238 1
0.8%
15233 1
0.8%
15225 1
0.8%
15215 1
0.8%
15203 1
0.8%
15199 1
0.8%
15193 1
0.8%
15183 1
0.8%
15165 1
0.8%
15159 1
0.8%

CHNNEL_CL_NM
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
instagram 124
100.0%

Length

2023-12-10T18:50:48.965483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:49.181059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
instagram 124
100.0%

CHNNEL_ID
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
17841406158676308
31 
17841400914760068
31 
17841404882037858
31 
17841403571935240
31 

Length

Max length17
Median length17
Mean length17
Min length17

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row17841406158676308
2nd row17841406158676308
3rd row17841406158676308
4th row17841406158676308
5th row17841406158676308

Common Values

ValueCountFrequency (%)
17841406158676308 31
25.0%
17841400914760068 31
25.0%
17841404882037858 31
25.0%
17841403571935240 31
25.0%

Length

2023-12-10T18:50:49.373631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:49.571556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
17841406158676308 31
25.0%
17841400914760068 31
25.0%
17841404882037858 31
25.0%
17841403571935240 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 
H1GHRMUSIC 하이어뮤직
31 
NCT 127 Official Instagram
31 

Length

Max length26
Median length18.5
Mean length17.25
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%
H1GHRMUSIC 하이어뮤직 31
25.0%
NCT 127 Official Instagram 31
25.0%

Length

2023-12-10T18:50:49.841743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:50.077472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
플레이리스트 31
10.0%
1million 31
10.0%
dance 31
10.0%
studio 31
10.0%
h1ghrmusic 31
10.0%
하이어뮤직 31
10.0%
nct 31
10.0%
127 31
10.0%
official 31
10.0%
instagram 31
10.0%

CHNNEL_URL
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.instagram.com/playlist_studio
31 
https://www.instagram.com/1milliondance
31 
https://www.instagram.com/h1ghrmusic
31 
https://www.instagram.com/nct127
31 

Length

Max length41
Median length37.5
Mean length37
Min length32

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://www.instagram.com/playlist_studio
2nd rowhttps://www.instagram.com/playlist_studio
3rd rowhttps://www.instagram.com/playlist_studio
4th rowhttps://www.instagram.com/playlist_studio
5th rowhttps://www.instagram.com/playlist_studio

Common Values

ValueCountFrequency (%)
https://www.instagram.com/playlist_studio 31
25.0%
https://www.instagram.com/1milliondance 31
25.0%
https://www.instagram.com/h1ghrmusic 31
25.0%
https://www.instagram.com/nct127 31
25.0%

Length

2023-12-10T18:50:50.319600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:50.598875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
https://www.instagram.com/playlist_studio 31
25.0%
https://www.instagram.com/1milliondance 31
25.0%
https://www.instagram.com/h1ghrmusic 31
25.0%
https://www.instagram.com/nct127 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

2023-12-10T18:50:50.896659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:51.105138image/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
음악/댄스
93 
방송
31 

Length

Max length5
Median length5
Mean length4.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2023-12-10T18:50:51.311759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:51.563400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음악/댄스 93
75.0%
방송 31
 
25.0%

COLCT_DE
Date

Distinct31
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2021-01-01 00:00:00
Maximum2021-01-31 00:00:00
2023-12-10T18:50:51.789367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:52.061919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

FOLLOWER_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3039825.4
Minimum331697
Maximum10059936
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:50:52.317610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum331697
5-th percentile333457.05
Q1493093.5
median968313
Q33482277.2
95-th percentile9958472.9
Maximum10059936
Range9728239
Interquartile range (IQR)2989183.8

Descriptive statistics

Standard deviation3985219.8
Coefficient of variation (CV)1.3110028
Kurtosis-0.67130968
Mean3039825.4
Median Absolute Deviation (MAD)531915.5
Skewness1.135262
Sum3.7693835 × 108
Variance1.5881977 × 1013
MonotonicityNot monotonic
2023-12-10T18:50:52.689485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
543502 1
 
0.8%
339307 1
 
0.8%
341868 1
 
0.8%
341791 1
 
0.8%
341628 1
 
0.8%
341506 1
 
0.8%
341257 1
 
0.8%
341215 1
 
0.8%
341042 1
 
0.8%
340871 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
331697 1
0.8%
331927 1
0.8%
332100 1
0.8%
332315 1
0.8%
332569 1
0.8%
333040 1
0.8%
333396 1
0.8%
333803 1
0.8%
334736 1
0.8%
335443 1
0.8%
ValueCountFrequency (%)
10059936 1
0.8%
10048342 1
0.8%
10037889 1
0.8%
10026188 1
0.8%
10010156 1
0.8%
9985508 1
0.8%
9960017 1
0.8%
9949723 1
0.8%
9940594 1
0.8%
9932565 1
0.8%

LIKE_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17511952
Minimum784108
Maximum66441833
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:50:52.973709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum784108
5-th percentile797206.4
Q11149256.5
median1969077.5
Q317788474
95-th percentile65512619
Maximum66441833
Range65657725
Interquartile range (IQR)16639217

Descriptive statistics

Standard deviation27661426
Coefficient of variation (CV)1.579574
Kurtosis-0.6436271
Mean17511952
Median Absolute Deviation (MAD)897380.5
Skewness1.1677743
Sum2.1714821 × 109
Variance7.6515447 × 1014
MonotonicityNot monotonic
2023-12-10T18:50:53.280984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1240992 1
 
0.8%
888726 1
 
0.8%
916578 1
 
0.8%
910878 1
 
0.8%
906407 1
 
0.8%
904992 1
 
0.8%
896786 1
 
0.8%
893572 1
 
0.8%
899606 1
 
0.8%
899240 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
784108 1
0.8%
790120 1
0.8%
792483 1
0.8%
795504 1
0.8%
796037 1
0.8%
796677 1
0.8%
797126 1
0.8%
797662 1
0.8%
837746 1
0.8%
848864 1
0.8%
ValueCountFrequency (%)
66441833 1
0.8%
66239790 1
0.8%
66129521 1
0.8%
65854525 1
0.8%
65595658 1
0.8%
65519322 1
0.8%
65512639 1
0.8%
65512505 1
0.8%
65501569 1
0.8%
65497432 1
0.8%

COMMENT_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean161495.37
Minimum4866
Maximum717364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:50:53.615012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4866
5-th percentile5041.9
Q15899
median9924.5
Q3150886.5
95-th percentile616959.5
Maximum717364
Range712498
Interquartile range (IQR)144987.5

Descriptive statistics

Standard deviation266288.58
Coefficient of variation (CV)1.648893
Kurtosis-0.58083586
Mean161495.37
Median Absolute Deviation (MAD)4246
Skewness1.1838829
Sum20025426
Variance7.090961 × 1010
MonotonicityNot monotonic
2023-12-10T18:50:53.914069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9462 1
 
0.8%
9859 1
 
0.8%
10026 1
 
0.8%
9993 1
 
0.8%
9900 1
 
0.8%
10106 1
 
0.8%
9894 1
 
0.8%
9875 1
 
0.8%
9911 1
 
0.8%
9908 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
4866 1
0.8%
4873 1
0.8%
4884 1
0.8%
4886 1
0.8%
4937 1
0.8%
4950 1
0.8%
5035 1
0.8%
5081 1
0.8%
5144 1
0.8%
5176 1
0.8%
ValueCountFrequency (%)
717364 1
0.8%
710691 1
0.8%
709982 1
0.8%
654164 1
0.8%
620332 1
0.8%
619956 1
0.8%
617378 1
0.8%
614588 1
0.8%
614210 1
0.8%
614200 1
0.8%

DPI_VALUE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1201110.7
Minimum374733.69
Maximum3453899.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:50:54.327459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum374733.69
5-th percentile379688.48
Q1499069.69
median551361.21
Q31148337.2
95-th percentile3354902.9
Maximum3453899.6
Range3079165.9
Interquartile range (IQR)649267.48

Descriptive statistics

Standard deviation1207370.8
Coefficient of variation (CV)1.0052119
Kurtosis-0.59641774
Mean1201110.7
Median Absolute Deviation (MAD)83764.422
Skewness1.1735806
Sum1.4893773 × 108
Variance1.4577441 × 1012
MonotonicityNot monotonic
2023-12-10T18:50:54.820544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
578995.640245503 1
 
0.8%
428687.221216905 1
 
0.8%
417333.397228746 1
 
0.8%
418060.850978945 1
 
0.8%
422491.815024086 1
 
0.8%
424224.32991234 1
 
0.8%
423341.460694685 1
 
0.8%
423320.1814343 1
 
0.8%
423228.481137814 1
 
0.8%
423142.314748212 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
374733.6866995 1
0.8%
375923.085468075 1
0.8%
377255.999054578 1
0.8%
377435.816323949 1
0.8%
378207.927563498 1
0.8%
378729.980712855 1
0.8%
379576.980717782 1
0.8%
380320.278058296 1
0.8%
380710.492984626 1
0.8%
413491.338133524 1
0.8%
ValueCountFrequency (%)
3453899.62146062 1
0.8%
3447046.06263133 1
0.8%
3428544.42123141 1
0.8%
3371652.35122326 1
0.8%
3356527.62387551 1
0.8%
3355752.2404448 1
0.8%
3354965.87542034 1
0.8%
3354546.07286282 1
0.8%
3354280.07809064 1
0.8%
3353480.44014338 1
0.8%

DV_VALUE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37378565
Minimum11661712
Maximum1.0748536 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:50:55.315917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11661712
5-th percentile11815905
Q115531049
median17158361
Q335736253
95-th percentile1.0440458 × 108
Maximum1.0748536 × 108
Range95823644
Interquartile range (IQR)20205204

Descriptive statistics

Standard deviation37573378
Coefficient of variation (CV)1.0052119
Kurtosis-0.59641774
Mean37378565
Median Absolute Deviation (MAD)2606748.8
Skewness1.1735806
Sum4.6349421 × 109
Variance1.4117587 × 1015
MonotonicityNot monotonic
2023-12-10T18:50:55.654020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18018344.3244401 1
 
0.8%
13340746.3242701 1
 
0.8%
12987415.3217586 1
 
0.8%
13010053.6824648 1
 
0.8%
13147945.2835496 1
 
0.8%
13201861.146872 1
 
0.8%
13174386.2568186 1
 
0.8%
13173724.0462354 1
 
0.8%
13170870.3330088 1
 
0.8%
13168188.8349644 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
11661712.3300884 1
0.8%
11698726.4197665 1
0.8%
11740206.6905785 1
0.8%
11745802.6040013 1
0.8%
11769830.7057761 1
0.8%
11786076.999784 1
0.8%
11812435.6399374 1
0.8%
11835567.0531742 1
0.8%
11847710.5416816 1
0.8%
12867850.4427153 1
0.8%
ValueCountFrequency (%)
107485356.219854 1
0.8%
107272073.469087 1
0.8%
106696302.388722 1
0.8%
104925821.170068 1
0.8%
104455139.655006 1
0.8%
104431009.722642 1
0.8%
104406538.043081 1
0.8%
104393473.787491 1
0.8%
104385196.030181 1
0.8%
104360311.297262 1
0.8%

RSPN_SM_CO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17673448
Minimum790195
Maximum67004881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-10T18:50:56.118779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum790195
5-th percentile803249.8
Q11158946.5
median1978515.5
Q317941630
95-th percentile66126653
Maximum67004881
Range66214686
Interquartile range (IQR)16782684

Descriptive statistics

Standard deviation27926979
Coefficient of variation (CV)1.5801659
Kurtosis-0.64369582
Mean17673448
Median Absolute Deviation (MAD)897016.5
Skewness1.1677874
Sum2.1915075 × 109
Variance7.7991614 × 1014
MonotonicityNot monotonic
2023-12-10T18:50:56.968876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1250454 1
 
0.8%
898585 1
 
0.8%
926604 1
 
0.8%
920871 1
 
0.8%
916307 1
 
0.8%
915098 1
 
0.8%
906680 1
 
0.8%
903447 1
 
0.8%
909517 1
 
0.8%
909148 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
790195 1
0.8%
796204 1
0.8%
798509 1
0.8%
801542 1
0.8%
802091 1
0.8%
802717 1
0.8%
803167 1
0.8%
803719 1
0.8%
846449 1
0.8%
857867 1
0.8%
ValueCountFrequency (%)
67004881 1
0.8%
66860122 1
0.8%
66749477 1
0.8%
66416041 1
0.8%
66213036 1
0.8%
66133083 1
0.8%
66126715 1
0.8%
66126301 1
0.8%
66115200 1
0.8%
66111632 1
0.8%

RSPN_IRDS_CO
Real number (ℝ)

UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13678.75
Minimum-1258230
Maximum1056907
Zeros0
Zeros (%)0.0%
Negative21
Negative (%)16.9%
Memory size1.2 KiB
2023-12-10T18:50:57.324231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1258230
5-th percentile-43376.55
Q11006.25
median5483.5
Q322715.75
95-th percentile304551.9
Maximum1056907
Range2315137
Interquartile range (IQR)21709.5

Descriptive statistics

Standard deviation229228.96
Coefficient of variation (CV)16.758035
Kurtosis17.423809
Mean13678.75
Median Absolute Deviation (MAD)6417.5
Skewness-1.353732
Sum1696165
Variance5.2545918 × 1010
MonotonicityNot monotonic
2023-12-10T18:50:57.619501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1012 1
 
0.8%
908 1
 
0.8%
5733 1
 
0.8%
4564 1
 
0.8%
1209 1
 
0.8%
8418 1
 
0.8%
3233 1
 
0.8%
-6070 1
 
0.8%
369 1
 
0.8%
622 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
-1258230 1
0.8%
-1194050 1
0.8%
-444081 1
0.8%
-363397 1
0.8%
-358680 1
0.8%
-327154 1
0.8%
-47115 1
0.8%
-22192 1
0.8%
-21095 1
0.8%
-16005 1
0.8%
ValueCountFrequency (%)
1056907 1
0.8%
794985 1
0.8%
588840 1
0.8%
536441 1
0.8%
407918 1
0.8%
325014 1
0.8%
306564 1
0.8%
293150 1
0.8%
118336 1
0.8%
110645 1
0.8%

Interactions

2023-12-10T18:50:46.216434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:35.012266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:36.487339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:37.842754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:39.505804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:41.250456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:42.686438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:44.183353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:46.367067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:35.176663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:36.667973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:38.020957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:39.811082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:41.429940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:42.901117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:44.372389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:46.548263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:35.422902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:36.831406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:38.193925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:40.028847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:41.609770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:43.078580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:44.544929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:46.747695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:35.602352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:36.992702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:38.376047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:40.238991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:41.779473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:43.260406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:44.818799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:46.949815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:35.801350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:37.167013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:38.554138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:40.470260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:41.947446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:43.433740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:44.984497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:47.129226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:35.988736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:37.354457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:38.759394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:40.675848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:42.144880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:43.610489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:45.162466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:47.284188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:36.156291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:37.514075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:38.967849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:40.850135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:42.313010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:43.774748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:45.325748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:47.460060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:36.338479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:37.688974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:39.261005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:41.082328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:42.496487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:43.992199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:45.512154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:50:57.820378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SEQ_NOCHNNEL_IDCHNNEL_NMCHNNEL_URLLWPRT_CTGRY_NMCOLCT_DEFOLLOWER_COLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_CO
SEQ_NO1.0000.0000.0000.0000.0000.9900.0000.0000.3860.2190.2190.0000.000
CHNNEL_ID0.0001.0001.0001.0001.0000.0001.0001.0000.8870.8870.8871.0000.536
CHNNEL_NM0.0001.0001.0001.0001.0000.0001.0001.0000.8870.8870.8871.0000.536
CHNNEL_URL0.0001.0001.0001.0001.0000.0001.0001.0000.8870.8870.8871.0000.536
LWPRT_CTGRY_NM0.0001.0001.0001.0001.0000.0000.3620.4590.4490.4490.4490.4590.000
COLCT_DE0.9900.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.000
FOLLOWER_CO0.0001.0001.0001.0000.3620.0001.0001.0000.6690.6690.6691.0000.498
LIKE_CO0.0001.0001.0001.0000.4590.0001.0001.0001.0001.0001.0000.9990.745
COMMENT_CO0.3860.8870.8870.8870.4490.0000.6691.0001.0000.9700.9701.0000.918
DPI_VALUE0.2190.8870.8870.8870.4490.0000.6691.0000.9701.0001.0001.0000.981
DV_VALUE0.2190.8870.8870.8870.4490.0000.6691.0000.9701.0001.0001.0000.981
RSPN_SM_CO0.0001.0001.0001.0000.4590.0001.0000.9991.0001.0001.0001.0000.745
RSPN_IRDS_CO0.0000.5360.5360.5360.0000.0000.4980.7450.9180.9810.9810.7451.000
2023-12-10T18:50:58.090665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LWPRT_CTGRY_NMCHNNEL_IDCHNNEL_URLCHNNEL_NM
LWPRT_CTGRY_NM1.0000.9920.9920.992
CHNNEL_ID0.9921.0001.0001.000
CHNNEL_URL0.9921.0001.0001.000
CHNNEL_NM0.9921.0001.0001.000
2023-12-10T18:50:58.317857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SEQ_NOFOLLOWER_COLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_COCHNNEL_IDCHNNEL_NMCHNNEL_URLLWPRT_CTGRY_NM
SEQ_NO1.0000.2340.2270.1950.0830.0830.226-0.1110.0000.0000.0000.000
FOLLOWER_CO0.2341.0000.9950.4050.7720.7720.9940.2640.9960.9960.9960.565
LIKE_CO0.2270.9951.0000.4150.7720.7721.0000.2790.9920.9920.9920.300
COMMENT_CO0.1950.4050.4151.0000.7430.7430.4150.2470.5630.5630.5630.296
DPI_VALUE0.0830.7720.7720.7431.0001.0000.7720.3620.5630.5630.5630.296
DV_VALUE0.0830.7720.7720.7431.0001.0000.7720.3620.5630.5630.5630.296
RSPN_SM_CO0.2260.9941.0000.4150.7720.7721.0000.2800.9920.9920.9920.300
RSPN_IRDS_CO-0.1110.2640.2790.2470.3620.3620.2801.0000.2690.2690.2690.000
CHNNEL_ID0.0000.9960.9920.5630.5630.5630.9920.2691.0001.0001.0000.992
CHNNEL_NM0.0000.9960.9920.5630.5630.5630.9920.2691.0001.0001.0000.992
CHNNEL_URL0.0000.9960.9920.5630.5630.5630.9920.2691.0001.0001.0000.992
LWPRT_CTGRY_NM0.0000.5650.3000.2960.2960.2960.3000.0000.9920.9920.9921.000

Missing values

2023-12-10T18:50:47.729908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:50:48.101627image/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_DEFOLLOWER_COLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_CO
014230instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-0154350212409929462578995.64024618018344.3244412504541012
114273instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-0254402212372509572580066.61845718051673.1663711246822-3632
214295instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-0354410812268169578583058.415818144777.8996861236394-10428
314344instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-0454412712500419897583585.04098618161166.475483125993823544
414374instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-05544353129430210368587421.02278718280542.229142130467044732
514395instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-06544601133572110550588200.86345818304810.870823134627141601
614442instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-07544768136473210724587397.9473218279824.120608137545629185
714463instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-08545029136492510443584115.19888218177664.9892081375368-88
814495instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-09545312135262510394585502.93407218220851.3083241363019-12349
914518instagram17841406158676308플레이리스트https://www.instagram.com/playlist_studio문화방송2021-01-10545593137865010740586023.10844818237039.1349138939026371
SEQ_NOCHNNEL_CL_NMCHNNEL_IDCHNNEL_NMCHNNEL_URLUPPER_CTGRY_NMLWPRT_CTGRY_NMCOLCT_DEFOLLOWER_COLIKE_COCOMMENT_CODPI_VALUEDV_VALUERSPN_SM_CORSPN_IRDS_CO
11414933instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-229932565655015696136313337941.794914103876748.657713661152004588
11514971instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-239940594655126396136623338489.490476103893792.9436216612630111101
11614995instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-249949723655193226137613339148.862227103914312.592515661330836782
11715038instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-259960017651684416012453339846.643497103936027.54562765769686-363397
11815063instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-269985508652863946016283371652.351223104925821.17006865888022118336
11915087instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-2710010156655956586173783354546.072863104393473.78749166213036325014
12015132instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-2810026188661295216199563447046.062631107272073.46908766749477536441
12115165instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-2910037889662397906203323453899.621461107485356.21985466860122110645
12215193instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-3010048342658545255615163428544.421231106696302.38872266416041-444081
12315233instagram17841403571935240NCT 127 Official Instagramhttps://www.instagram.com/nct127문화음악/댄스2021-01-3110059936664418335630483305334.375913102862005.77840367004881588840