Overview

Dataset statistics

Number of variables16
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory144.3 B

Variable types

Categorical4
Numeric12

Alerts

base_year is highly overall correlated with ovsea_movie_adnc_co and 4 other fieldsHigh correlation
ctprvn_nm is highly overall correlated with korea_movie_scrng_co and 3 other fieldsHigh correlation
base_mt is highly overall correlated with week_odr and 1 other fieldsHigh correlation
base_day is highly overall correlated with mt_week_odrHigh correlation
week_odr is highly overall correlated with base_mt and 1 other fieldsHigh correlation
korea_movie_adnc_co is highly overall correlated with movie_adnc_co and 2 other fieldsHigh correlation
ovsea_movie_adnc_co is highly overall correlated with movie_adnc_co and 3 other fieldsHigh correlation
movie_adnc_co is highly overall correlated with korea_movie_adnc_co and 5 other fieldsHigh correlation
korea_movie_sales_price is highly overall correlated with korea_movie_adnc_co and 2 other fieldsHigh correlation
ovsea_movie_sales_price is highly overall correlated with ovsea_movie_adnc_co and 3 other fieldsHigh correlation
movie_sales_price is highly overall correlated with korea_movie_adnc_co and 5 other fieldsHigh correlation
korea_movie_scrng_co is highly overall correlated with ctprvn_nmHigh correlation
ovsea_movie_scrng_co is highly overall correlated with movie_scrng_co and 1 other fieldsHigh correlation
movie_scrng_co is highly overall correlated with ovsea_movie_scrng_co and 1 other fieldsHigh correlation
base_quarter is highly overall correlated with base_mt and 1 other fieldsHigh correlation
mt_week_odr is highly overall correlated with base_dayHigh correlation
ctprvn_nm is highly imbalanced (80.6%)Imbalance
korea_movie_adnc_co has unique valuesUnique
ovsea_movie_adnc_co has unique valuesUnique
movie_adnc_co has unique valuesUnique
korea_movie_sales_price has unique valuesUnique
ovsea_movie_sales_price has unique valuesUnique
movie_sales_price has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:14:56.215853
Analysis finished2023-12-10 10:15:20.715960
Duration24.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

base_year
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019
50 
2020
47 
2023
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2023
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 50
50.0%
2020 47
47.0%
2023 3
 
3.0%

Length

2023-12-10T19:15:20.793839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:20.930334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 50
50.0%
2020 47
47.0%
2023 3
 
3.0%

base_quarter
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
27 
2
26 
3
25 
4
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 27
27.0%
2 26
26.0%
3 25
25.0%
4 22
22.0%

Length

2023-12-10T19:15:21.079215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:21.239752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 27
27.0%
2 26
26.0%
3 25
25.0%
4 22
22.0%

base_mt
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.22
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:21.376992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile11.05
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3802158
Coefficient of variation (CV)0.54344305
Kurtosis-1.2067698
Mean6.22
Median Absolute Deviation (MAD)3
Skewness0.05133835
Sum622
Variance11.425859
MonotonicityNot monotonic
2023-12-10T19:15:21.527131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 9
9.0%
2 9
9.0%
3 9
9.0%
4 9
9.0%
6 9
9.0%
7 9
9.0%
9 9
9.0%
10 9
9.0%
5 8
8.0%
11 8
8.0%
Other values (2) 12
12.0%
ValueCountFrequency (%)
1 9
9.0%
2 9
9.0%
3 9
9.0%
4 9
9.0%
5 8
8.0%
6 9
9.0%
7 9
9.0%
8 7
7.0%
9 9
9.0%
10 9
9.0%
ValueCountFrequency (%)
12 5
5.0%
11 8
8.0%
10 9
9.0%
9 9
9.0%
8 7
7.0%
7 9
9.0%
6 9
9.0%
5 8
8.0%
4 9
9.0%
3 9
9.0%

base_day
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.96
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:21.698328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18.75
median16
Q324
95-th percentile30
Maximum31
Range30
Interquartile range (IQR)15.25

Descriptive statistics

Standard deviation8.9193015
Coefficient of variation (CV)0.55885348
Kurtosis-1.1868654
Mean15.96
Median Absolute Deviation (MAD)8
Skewness0.0025145561
Sum1596
Variance79.553939
MonotonicityNot monotonic
2023-12-10T19:15:21.890760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
7 5
 
5.0%
14 5
 
5.0%
21 4
 
4.0%
24 4
 
4.0%
17 4
 
4.0%
10 4
 
4.0%
5 4
 
4.0%
12 4
 
4.0%
26 4
 
4.0%
3 4
 
4.0%
Other values (21) 58
58.0%
ValueCountFrequency (%)
1 3
3.0%
2 3
3.0%
3 4
4.0%
4 3
3.0%
5 4
4.0%
6 1
 
1.0%
7 5
5.0%
8 2
 
2.0%
9 3
3.0%
10 4
4.0%
ValueCountFrequency (%)
31 3
3.0%
30 3
3.0%
29 3
3.0%
28 4
4.0%
27 2
2.0%
26 4
4.0%
25 3
3.0%
24 4
4.0%
23 3
3.0%
22 3
3.0%

mt_week_odr
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
24 
3
24 
4
22 
2
22 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row3
4th row4
5th row1

Common Values

ValueCountFrequency (%)
1 24
24.0%
3 24
24.0%
4 22
22.0%
2 22
22.0%
5 8
 
8.0%

Length

2023-12-10T19:15:22.065064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:22.201598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
24.0%
3 24
24.0%
4 22
22.0%
2 22
22.0%
5 8
 
8.0%

week_odr
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.3
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:22.377342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q112.75
median25
Q338
95-th percentile48
Maximum52
Range51
Interquartile range (IQR)25.25

Descriptive statistics

Standard deviation14.655299
Coefficient of variation (CV)0.57926082
Kurtosis-1.2090155
Mean25.3
Median Absolute Deviation (MAD)13
Skewness0.052283802
Sum2530
Variance214.77778
MonotonicityNot monotonic
2023-12-10T19:15:22.621480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 3
 
3.0%
6 3
 
3.0%
7 3
 
3.0%
1 2
 
2.0%
39 2
 
2.0%
30 2
 
2.0%
31 2
 
2.0%
33 2
 
2.0%
34 2
 
2.0%
35 2
 
2.0%
Other values (42) 77
77.0%
ValueCountFrequency (%)
1 2
2.0%
2 1
 
1.0%
3 2
2.0%
4 2
2.0%
5 3
3.0%
6 3
3.0%
7 3
3.0%
8 1
 
1.0%
9 2
2.0%
10 2
2.0%
ValueCountFrequency (%)
52 1
1.0%
51 1
1.0%
50 1
1.0%
49 1
1.0%
48 2
2.0%
47 2
2.0%
46 2
2.0%
45 2
2.0%
44 2
2.0%
43 2
2.0%

ctprvn_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도
97 
충청북도
 
3

Length

Max length4
Median length3
Mean length3.03
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도
2nd row충청북도
3rd row강원도
4th row강원도
5th row강원도

Common Values

ValueCountFrequency (%)
강원도 97
97.0%
충청북도 3
 
3.0%

Length

2023-12-10T19:15:22.817589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:22.928600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 97
97.0%
충청북도 3
 
3.0%

korea_movie_adnc_co
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37834.52
Minimum126
Maximum180464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:23.104215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126
5-th percentile641.75
Q17919.5
median25305.5
Q350630.5
95-th percentile132719.3
Maximum180464
Range180338
Interquartile range (IQR)42711

Descriptive statistics

Standard deviation40941.679
Coefficient of variation (CV)1.082125
Kurtosis2.3531145
Mean37834.52
Median Absolute Deviation (MAD)18563
Skewness1.6483684
Sum3783452
Variance1.676221 × 109
MonotonicityNot monotonic
2023-12-10T19:15:23.726880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29300 1
 
1.0%
698 1
 
1.0%
6894 1
 
1.0%
618 1
 
1.0%
568 1
 
1.0%
643 1
 
1.0%
1651 1
 
1.0%
1910 1
 
1.0%
1625 1
 
1.0%
701 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126 1
1.0%
338 1
1.0%
568 1
1.0%
616 1
1.0%
618 1
1.0%
643 1
1.0%
698 1
1.0%
701 1
1.0%
860 1
1.0%
985 1
1.0%
ValueCountFrequency (%)
180464 1
1.0%
160071 1
1.0%
155929 1
1.0%
154885 1
1.0%
140382 1
1.0%
132316 1
1.0%
119952 1
1.0%
116565 1
1.0%
114372 1
1.0%
108961 1
1.0%

ovsea_movie_adnc_co
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29637.97
Minimum1520
Maximum180661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:24.163191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1520
5-th percentile2222.2
Q14433.75
median14679
Q342343.25
95-th percentile110486.25
Maximum180661
Range179141
Interquartile range (IQR)37909.5

Descriptive statistics

Standard deviation36542.142
Coefficient of variation (CV)1.2329502
Kurtosis4.378187
Mean29637.97
Median Absolute Deviation (MAD)12059.5
Skewness2.0166892
Sum2963797
Variance1.3353281 × 109
MonotonicityNot monotonic
2023-12-10T19:15:24.532130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69717 1
 
1.0%
3953 1
 
1.0%
3646 1
 
1.0%
4834 1
 
1.0%
4439 1
 
1.0%
3772 1
 
1.0%
5226 1
 
1.0%
5318 1
 
1.0%
2233 1
 
1.0%
2376 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1520 1
1.0%
1670 1
1.0%
1686 1
1.0%
1693 1
1.0%
2093 1
1.0%
2229 1
1.0%
2233 1
1.0%
2376 1
1.0%
2492 1
1.0%
2538 1
1.0%
ValueCountFrequency (%)
180661 1
1.0%
164920 1
1.0%
137837 1
1.0%
125218 1
1.0%
114709 1
1.0%
110264 1
1.0%
87068 1
1.0%
85432 1
1.0%
78668 1
1.0%
78469 1
1.0%

movie_adnc_co
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67472.49
Minimum2219
Maximum203639
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:24.870828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2219
5-th percentile4387.15
Q115774.5
median62450
Q398330.75
95-th percentile179307.55
Maximum203639
Range201420
Interquartile range (IQR)82556.25

Descriptive statistics

Standard deviation56287.976
Coefficient of variation (CV)0.83423594
Kurtosis-0.38363615
Mean67472.49
Median Absolute Deviation (MAD)45940
Skewness0.74960596
Sum6747249
Variance3.1683362 × 109
MonotonicityNot monotonic
2023-12-10T19:15:25.156408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99017 1
 
1.0%
4651 1
 
1.0%
10540 1
 
1.0%
5452 1
 
1.0%
5007 1
 
1.0%
4415 1
 
1.0%
6877 1
 
1.0%
7228 1
 
1.0%
3858 1
 
1.0%
3077 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2219 1
1.0%
2901 1
1.0%
3077 1
1.0%
3531 1
1.0%
3858 1
1.0%
4415 1
1.0%
4651 1
1.0%
5007 1
1.0%
5436 1
1.0%
5452 1
1.0%
ValueCountFrequency (%)
203639 1
1.0%
201368 1
1.0%
193955 1
1.0%
190618 1
1.0%
182320 1
1.0%
179149 1
1.0%
171630 1
1.0%
171476 1
1.0%
165175 1
1.0%
161961 1
1.0%

korea_movie_sales_price
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0283951 × 108
Minimum864500
Maximum1.4373096 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:25.400720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum864500
5-th percentile5135749
Q167591748
median1.9718641 × 108
Q33.9556256 × 108
95-th percentile1.0178468 × 109
Maximum1.4373096 × 109
Range1.4364451 × 109
Interquartile range (IQR)3.2797081 × 108

Descriptive statistics

Standard deviation3.2845088 × 108
Coefficient of variation (CV)1.0845708
Kurtosis2.487059
Mean3.0283951 × 108
Median Absolute Deviation (MAD)1.5605234 × 108
Skewness1.6806741
Sum3.0283951 × 1010
Variance1.0787998 × 1017
MonotonicityNot monotonic
2023-12-10T19:15:25.643231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
237617500 1
 
1.0%
4936040 1
 
1.0%
60960960 1
 
1.0%
4319260 1
 
1.0%
3916000 1
 
1.0%
5146260 1
 
1.0%
12859720 1
 
1.0%
15850000 1
 
1.0%
9022820 1
 
1.0%
6255500 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
864500 1
1.0%
2257540 1
1.0%
3916000 1
1.0%
4319260 1
1.0%
4936040 1
1.0%
5146260 1
1.0%
5810680 1
1.0%
6255500 1
1.0%
6298997 1
1.0%
7559300 1
1.0%
ValueCountFrequency (%)
1437309640 1
1.0%
1306478680 1
1.0%
1293268740 1
1.0%
1226227180 1
1.0%
1170605980 1
1.0%
1009806850 1
1.0%
953444380 1
1.0%
947271340 1
1.0%
899366840 1
1.0%
872471400 1
1.0%

ovsea_movie_sales_price
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3593547 × 108
Minimum12054230
Maximum1.4668362 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:25.918540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12054230
5-th percentile16364095
Q135761720
median1.1474144 × 108
Q33.3446429 × 108
95-th percentile8.5162617 × 108
Maximum1.4668362 × 109
Range1.454782 × 109
Interquartile range (IQR)2.9870257 × 108

Descriptive statistics

Standard deviation2.9034411 × 108
Coefficient of variation (CV)1.2306082
Kurtosis4.6361353
Mean2.3593547 × 108
Median Absolute Deviation (MAD)93673995
Skewness2.0427716
Sum2.3593547 × 1010
Variance8.4299701 × 1016
MonotonicityNot monotonic
2023-12-10T19:15:26.588773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
553364650 1
 
1.0%
31164980 1
 
1.0%
27762600 1
 
1.0%
35979460 1
 
1.0%
35108500 1
 
1.0%
32464600 1
 
1.0%
42189380 1
 
1.0%
39925380 1
 
1.0%
15200440 1
 
1.0%
18436460 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
12054230 1
1.0%
12616820 1
1.0%
13075390 1
1.0%
14086620 1
1.0%
15200440 1
1.0%
16425340 1
1.0%
17238030 1
1.0%
18107860 1
1.0%
18436460 1
1.0%
19488380 1
1.0%
ValueCountFrequency (%)
1466836180 1
1.0%
1316875090 1
1.0%
1080266800 1
1.0%
1010764560 1
1.0%
876567950 1
1.0%
850313440 1
1.0%
675318370 1
1.0%
674066790 1
1.0%
649465710 1
1.0%
611260720 1
1.0%

movie_sales_price
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3877497 × 108
Minimum18972360
Maximum1.686329 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:26.875520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18972360
5-th percentile37535368
Q11.3187563 × 108
median4.7822544 × 108
Q37.9488197 × 108
95-th percentile1.3751386 × 109
Maximum1.686329 × 109
Range1.6673566 × 109
Interquartile range (IQR)6.6300634 × 108

Descriptive statistics

Standard deviation4.445848 × 108
Coefficient of variation (CV)0.82517716
Kurtosis-0.27237082
Mean5.3877497 × 108
Median Absolute Deviation (MAD)3.4085913 × 108
Skewness0.77469011
Sum5.3877497 × 1010
Variance1.9765564 × 1017
MonotonicityNot monotonic
2023-12-10T19:15:27.146750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
790982150 1
 
1.0%
36101020 1
 
1.0%
88723560 1
 
1.0%
40298720 1
 
1.0%
39024500 1
 
1.0%
37610860 1
 
1.0%
55049100 1
 
1.0%
55775380 1
 
1.0%
24223260 1
 
1.0%
24691960 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
18972360 1
1.0%
24071780 1
1.0%
24223260 1
1.0%
24691960 1
1.0%
36101020 1
1.0%
37610860 1
1.0%
38507085 1
1.0%
39024500 1
1.0%
40298720 1
1.0%
42706720 1
1.0%
ValueCountFrequency (%)
1686329000 1
1.0%
1613614990 1
1.0%
1560726970 1
1.0%
1494361640 1
1.0%
1415148210 1
1.0%
1373032780 1
1.0%
1369094110 1
1.0%
1346316850 1
1.0%
1334743820 1
1.0%
1293458350 1
1.0%

korea_movie_scrng_co
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.77
Minimum9
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:27.405222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile29.9
Q143
median52
Q371.25
95-th percentile90.15
Maximum117
Range108
Interquartile range (IQR)28.25

Descriptive statistics

Standard deviation20.154381
Coefficient of variation (CV)0.35501817
Kurtosis-0.043623035
Mean56.77
Median Absolute Deviation (MAD)11
Skewness0.59327435
Sum5677
Variance406.19909
MonotonicityNot monotonic
2023-12-10T19:15:27.679251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43 4
 
4.0%
52 4
 
4.0%
55 4
 
4.0%
50 4
 
4.0%
44 3
 
3.0%
81 3
 
3.0%
87 3
 
3.0%
33 3
 
3.0%
49 3
 
3.0%
57 3
 
3.0%
Other values (40) 66
66.0%
ValueCountFrequency (%)
9 1
 
1.0%
25 1
 
1.0%
26 1
 
1.0%
28 2
2.0%
30 1
 
1.0%
33 3
3.0%
34 2
2.0%
37 2
2.0%
38 3
3.0%
39 2
2.0%
ValueCountFrequency (%)
117 1
 
1.0%
99 2
2.0%
97 1
 
1.0%
93 1
 
1.0%
90 1
 
1.0%
89 2
2.0%
88 2
2.0%
87 3
3.0%
85 1
 
1.0%
84 1
 
1.0%

ovsea_movie_scrng_co
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.13
Minimum18
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:27.910914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile64.95
Q180.75
median97.5
Q3119
95-th percentile159.3
Maximum188
Range170
Interquartile range (IQR)38.25

Descriptive statistics

Standard deviation29.307377
Coefficient of variation (CV)0.28979904
Kurtosis0.68669036
Mean101.13
Median Absolute Deviation (MAD)18
Skewness0.54092732
Sum10113
Variance858.92232
MonotonicityNot monotonic
2023-12-10T19:15:28.142160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82 4
 
4.0%
106 4
 
4.0%
101 4
 
4.0%
95 3
 
3.0%
102 3
 
3.0%
81 3
 
3.0%
73 3
 
3.0%
80 3
 
3.0%
88 3
 
3.0%
78 3
 
3.0%
Other values (51) 67
67.0%
ValueCountFrequency (%)
18 1
1.0%
43 1
1.0%
58 1
1.0%
59 1
1.0%
64 1
1.0%
65 2
2.0%
66 1
1.0%
70 1
1.0%
71 2
2.0%
72 1
1.0%
ValueCountFrequency (%)
188 1
1.0%
168 1
1.0%
167 1
1.0%
166 1
1.0%
165 1
1.0%
159 1
1.0%
157 2
2.0%
152 1
1.0%
138 1
1.0%
136 1
1.0%

movie_scrng_co
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.9
Minimum27
Maximum233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:28.399318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile113.95
Q1139
median157
Q3174.5
95-th percentile211.05
Maximum233
Range206
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation31.086552
Coefficient of variation (CV)0.19687494
Kurtosis2.2915679
Mean157.9
Median Absolute Deviation (MAD)18
Skewness-0.4912196
Sum15790
Variance966.37374
MonotonicityNot monotonic
2023-12-10T19:15:28.649316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165 4
 
4.0%
139 3
 
3.0%
156 3
 
3.0%
185 3
 
3.0%
168 3
 
3.0%
155 3
 
3.0%
149 2
 
2.0%
174 2
 
2.0%
142 2
 
2.0%
176 2
 
2.0%
Other values (55) 73
73.0%
ValueCountFrequency (%)
27 1
1.0%
100 1
1.0%
101 1
1.0%
103 1
1.0%
113 1
1.0%
114 2
2.0%
115 1
1.0%
121 2
2.0%
123 2
2.0%
124 1
1.0%
ValueCountFrequency (%)
233 1
1.0%
220 1
1.0%
216 1
1.0%
212 2
2.0%
211 1
1.0%
209 1
1.0%
206 1
1.0%
204 1
1.0%
200 1
1.0%
196 1
1.0%

Interactions

2023-12-10T19:15:18.457219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:57.420560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:59.181259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:01.724657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:04.122065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:06.219257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:08.307595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:10.365854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:12.833494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.279054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.787307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.106918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:18.904762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:57.561222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:59.328910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:01.881835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:04.289370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:06.376926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:08.468024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:10.515392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:12.975471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.378721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.910896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.205145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.026864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:57.722344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:59.470185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:02.035542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:04.469613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:06.523538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:08.636960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:10.708222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.115962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.485574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.045975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.309172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.143440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:57.867781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:59.594841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:02.268471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:04.633456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:06.669507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:08.784718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:10.881090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.223756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.593164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.160174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.398745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.271169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:58.024495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:59.734545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:02.429861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:04.789762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:06.802439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:08.962259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:11.061593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.363348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.774200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.291270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.494992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.404598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:58.181029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:59.929949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:02.936668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:04.955106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:06.910845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:09.130002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:11.300803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.494094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.896118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.400518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.590392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.530997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:58.335351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:00.212765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:03.115210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:05.127741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:07.044333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:09.320259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:11.505502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.626946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.025685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.512492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.725573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.666154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:58.464007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:00.531107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:03.295548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:05.337675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:07.184161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:09.492598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:11.700639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.742955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.148546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.622694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.829824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.789733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:58.602801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:00.872601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:03.461891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:05.542856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:07.357065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:09.681386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:12.245963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.875439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.303291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.736305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.961366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:19.907790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:58.739161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:01.167940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:03.652254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:05.739281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:07.778683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:09.839835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:12.395198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:13.986312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.448764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.841902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:18.143496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:20.021256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:58.901687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:01.357977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:03.817836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:05.891055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:08.051550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:10.000300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:12.551129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.081159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.566505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:16.927369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:18.247349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:20.119570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:59.059253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:01.529719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:03.972592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:06.062932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:08.200146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:10.206183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:12.711408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:14.178667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:15.692999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:17.015994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:18.340765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:15:28.825431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
base_yearbase_quarterbase_mtbase_daymt_week_odrweek_odrctprvn_nmkorea_movie_adnc_coovsea_movie_adnc_comovie_adnc_cokorea_movie_sales_priceovsea_movie_sales_pricemovie_sales_pricekorea_movie_scrng_coovsea_movie_scrng_comovie_scrng_co
base_year1.0000.1540.0000.0000.0000.0001.0000.6060.6660.7200.4030.6740.6980.5320.5750.538
base_quarter0.1541.0001.0000.0000.0000.9640.3520.0000.0000.0870.0000.0000.0000.5500.3090.473
base_mt0.0001.0001.0000.0000.0000.9800.3080.0000.1990.0000.2890.2580.2460.5660.5000.165
base_day0.0000.0000.0001.0000.9850.0000.0000.0000.0000.0000.0000.0930.0000.0000.2410.000
mt_week_odr0.0000.0000.0000.9851.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
week_odr0.0000.9640.9800.0000.0001.0000.1890.0000.2400.0000.3580.2770.3490.6190.5070.444
ctprvn_nm1.0000.3520.3080.0000.0000.1891.0000.0000.0000.2780.0000.0000.0000.6960.6960.722
korea_movie_adnc_co0.6060.0000.0000.0000.0000.0000.0001.0000.2170.7510.9620.0000.7740.0000.3130.231
ovsea_movie_adnc_co0.6660.0000.1990.0000.0000.2400.0000.2171.0000.6550.3260.9900.6780.0000.0000.000
movie_adnc_co0.7200.0870.0000.0000.0000.0000.2780.7510.6551.0000.8590.8160.9910.0750.1130.000
korea_movie_sales_price0.4030.0000.2890.0000.0000.3580.0000.9620.3260.8591.0000.0000.8830.0000.5560.380
ovsea_movie_sales_price0.6740.0000.2580.0930.0000.2770.0000.0000.9900.8160.0001.0000.8380.0000.0000.000
movie_sales_price0.6980.0000.2460.0000.0000.3490.0000.7740.6780.9910.8830.8381.0000.0000.0000.000
korea_movie_scrng_co0.5320.5500.5660.0000.0000.6190.6960.0000.0000.0750.0000.0000.0001.0000.8060.665
ovsea_movie_scrng_co0.5750.3090.5000.2410.0000.5070.6960.3130.0000.1130.5560.0000.0000.8061.0000.792
movie_scrng_co0.5380.4730.1650.0000.0000.4440.7220.2310.0000.0000.3800.0000.0000.6650.7921.000
2023-12-10T19:15:29.128689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
base_yearmt_week_odrctprvn_nmbase_quarter
base_year1.0000.0000.9950.144
mt_week_odr0.0001.0000.0000.000
ctprvn_nm0.9950.0001.0000.232
base_quarter0.1440.0000.2321.000
2023-12-10T19:15:29.322567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
base_mtbase_dayweek_odrkorea_movie_adnc_coovsea_movie_adnc_comovie_adnc_cokorea_movie_sales_priceovsea_movie_sales_pricemovie_sales_pricekorea_movie_scrng_coovsea_movie_scrng_comovie_scrng_cobase_yearbase_quartermt_week_odrctprvn_nm
base_mt1.000-0.0420.9400.085-0.0130.0870.077-0.0280.0860.388-0.1850.1470.0000.9680.0000.225
base_day-0.0421.000-0.0170.114-0.0520.0590.106-0.0620.0500.0970.0450.0910.0000.0000.8010.000
week_odr0.940-0.0171.0000.040-0.0500.0440.033-0.0650.0420.429-0.1800.1890.0000.8720.0000.136
korea_movie_adnc_co0.0850.1140.0401.0000.3740.7880.9980.3510.7890.288-0.463-0.3400.3180.0000.0000.000
ovsea_movie_adnc_co-0.013-0.052-0.0500.3741.0000.7840.3550.9980.7820.101-0.181-0.1670.5320.0000.0000.000
movie_adnc_co0.0870.0590.0440.7880.7841.0000.7750.7690.9990.222-0.368-0.3040.5620.0630.0000.204
korea_movie_sales_price0.0770.1060.0330.9980.3550.7751.0000.3340.7770.279-0.473-0.3560.2600.0000.0000.000
ovsea_movie_sales_price-0.028-0.062-0.0650.3510.9980.7690.3341.0000.7680.097-0.186-0.1730.5080.0000.0000.000
movie_sales_price0.0860.0500.0420.7890.7820.9990.7770.7681.0000.219-0.379-0.3140.5370.0000.0000.000
korea_movie_scrng_co0.3880.0970.4290.2880.1010.2220.2790.0970.2191.000-0.2690.3560.3620.3490.0000.520
ovsea_movie_scrng_co-0.1850.045-0.180-0.463-0.181-0.368-0.473-0.186-0.379-0.2691.0000.7280.4030.1810.0000.520
movie_scrng_co0.1470.0910.189-0.340-0.167-0.304-0.356-0.173-0.3140.3560.7281.0000.3930.2200.0000.535
base_year0.0000.0000.0000.3180.5320.5620.2600.5080.5370.3620.4030.3931.0000.1440.0000.995
base_quarter0.9680.0000.8720.0000.0000.0630.0000.0000.0000.3490.1810.2200.1441.0000.0000.232
mt_week_odr0.0000.8010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
ctprvn_nm0.2250.0000.1360.0000.0000.2040.0000.0000.0000.5200.5200.5350.9950.2320.0001.000

Missing values

2023-12-10T19:15:20.301169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:15:20.611455image/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

base_yearbase_quarterbase_mtbase_daymt_week_odrweek_odrctprvn_nmkorea_movie_adnc_coovsea_movie_adnc_comovie_adnc_cokorea_movie_sales_priceovsea_movie_sales_pricemovie_sales_pricekorea_movie_scrng_coovsea_movie_scrng_comovie_scrng_co
0201911111강원도29300697179901723761750055336465079098215043108151
12023113115충청북도10851233383418911565734724528528836094263549107156
22019111533강원도54527244737900043082556019191692062274248043102145
32019112244강원도116565921012577595344438067738450102118283049107156
42019112915강원도18046423175203639143730964017630535016136149905782139
5201912526강원도15488546483201368129326874039306026016863290005271123
62019121237강원도74173277751019485826311702245038608071350304497141
7202312726충청북도682727209340367153898630439696537593595164129193
82019122619강원도8325010111933616345671807314979070771697052133185
92019135210강원도1947878469979471571157106494657108065814204880128
base_yearbase_quarterbase_mtbase_daymt_week_odrweek_odrctprvn_nmkorea_movie_adnc_coovsea_movie_adnc_comovie_adnc_cokorea_movie_sales_priceovsea_movie_sales_pricemovie_sales_pricekorea_movie_scrng_coovsea_movie_scrng_comovie_scrng_co
9020203922439강원도724354121265561392350455921901069845405566121
9120203929140강원도37910885846768358285510728736704311591808173154
9220204106241강원도15327537420701137437270439635501814008208198179
93202041013342강원도13254222915483116090810172380301333288406693159
94202041020443강원도18115152019635149847550120542301619017806990159
95202041027144강원도17576167019246145038810130753901581142008781168
9620204113245강원도23385249225877195954800164253402123801407192163
97202041110346강원도179161693196091468633401261682015948016084112196
98202041117447강원도12085365215737980028102951318012751599099121220
99202041124548강원도814527861093164239330227700808700941088128216