Overview

Dataset statistics

Number of variables19
Number of observations2691
Missing cells3285
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory446.9 KiB
Average record size in memory170.0 B

Variable types

Text1
Numeric18

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산거래현황 중 주택 거래현황의 연도별 거래주체별(면적) 데이터입니다.- (단위 : 천㎡)- 공표시기 : 익월 말일경
Author한국부동산원
URLhttps://www.data.go.kr/data/15068430/fileData.do

Alerts

2006 is highly overall correlated with 2007 and 16 other fieldsHigh correlation
2007 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2008 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2009 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2010 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2011 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2012 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2013 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2014 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2015 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2016 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2017 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2018 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2019 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2020 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2021 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2022 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2023 is highly overall correlated with 2006 and 16 other fieldsHigh correlation
2006 has 198 (7.4%) missing valuesMissing
2007 has 243 (9.0%) missing valuesMissing
2008 has 225 (8.4%) missing valuesMissing
2009 has 225 (8.4%) missing valuesMissing
2010 has 171 (6.4%) missing valuesMissing
2011 has 198 (7.4%) missing valuesMissing
2012 has 180 (6.7%) missing valuesMissing
2013 has 180 (6.7%) missing valuesMissing
2014 has 117 (4.3%) missing valuesMissing
2015 has 153 (5.7%) missing valuesMissing
2016 has 153 (5.7%) missing valuesMissing
2017 has 180 (6.7%) missing valuesMissing
2018 has 171 (6.4%) missing valuesMissing
2019 has 180 (6.7%) missing valuesMissing
2020 has 180 (6.7%) missing valuesMissing
2021 has 180 (6.7%) missing valuesMissing
2022 has 180 (6.7%) missing valuesMissing
2023 has 171 (6.4%) missing valuesMissing
2006 is highly skewed (γ1 = 37.70239772)Skewed
2007 is highly skewed (γ1 = 36.35695995)Skewed
2008 is highly skewed (γ1 = 38.04638425)Skewed
2009 is highly skewed (γ1 = 38.5846737)Skewed
2010 is highly skewed (γ1 = 38.25900275)Skewed
2011 is highly skewed (γ1 = 40.52942863)Skewed
2012 is highly skewed (γ1 = 40.54802952)Skewed
2013 is highly skewed (γ1 = 40.96933872)Skewed
2014 is highly skewed (γ1 = 41.81060345)Skewed
2015 is highly skewed (γ1 = 41.50830518)Skewed
2016 is highly skewed (γ1 = 40.99725231)Skewed
2017 is highly skewed (γ1 = 37.19536943)Skewed
2018 is highly skewed (γ1 = 34.53362604)Skewed
2019 is highly skewed (γ1 = 34.79205532)Skewed
2020 is highly skewed (γ1 = 38.30678911)Skewed
2021 is highly skewed (γ1 = 37.98627153)Skewed
2022 is highly skewed (γ1 = 35.72715489)Skewed
2023 is highly skewed (γ1 = 38.01624871)Skewed
지역 및 거래주체 has unique valuesUnique
2006 has 1010 (37.5%) zerosZeros
2007 has 963 (35.8%) zerosZeros
2008 has 1005 (37.3%) zerosZeros
2009 has 908 (33.7%) zerosZeros
2010 has 928 (34.5%) zerosZeros
2011 has 790 (29.4%) zerosZeros
2012 has 838 (31.1%) zerosZeros
2013 has 888 (33.0%) zerosZeros
2014 has 932 (34.6%) zerosZeros
2015 has 824 (30.6%) zerosZeros
2016 has 871 (32.4%) zerosZeros
2017 has 863 (32.1%) zerosZeros
2018 has 790 (29.4%) zerosZeros
2019 has 764 (28.4%) zerosZeros
2020 has 722 (26.8%) zerosZeros
2021 has 735 (27.3%) zerosZeros
2022 has 774 (28.8%) zerosZeros
2023 has 880 (32.7%) zerosZeros

Reproduction

Analysis started2024-03-23 05:49:41.327562
Analysis finished2024-03-23 05:50:36.286778
Duration54.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct2691
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size21.2 KiB
2024-03-23T14:50:36.596802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length13
Mean length13.327759
Min length10

Characters and Unicode

Total characters35865
Distinct characters153
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2691 ?
Unique (%)100.0%

Sample

1st row전국 /개인->개인
2nd row전국 /개인->법인
3rd row전국 /개인->기타
4th row전국 /법인->개인
5th row전국 /법인->법인
ValueCountFrequency (%)
경기 477
 
8.9%
경남 243
 
4.5%
경북 234
 
4.3%
서울 234
 
4.3%
전남 207
 
3.8%
충남 180
 
3.3%
충북 180
 
3.3%
강원 171
 
3.2%
부산 153
 
2.8%
전북 153
 
2.8%
Other values (2331) 3150
58.5%
2024-03-23T14:50:37.189638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3750
 
10.5%
2691
 
7.5%
/ 2691
 
7.5%
> 2691
 
7.5%
- 2655
 
7.4%
2298
 
6.4%
1794
 
5.0%
1794
 
5.0%
1794
 
5.0%
1269
 
3.5%
Other values (143) 12438
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24795
69.1%
Space Separator 2691
 
7.5%
Other Punctuation 2691
 
7.5%
Math Symbol 2691
 
7.5%
Dash Punctuation 2655
 
7.4%
Open Punctuation 171
 
0.5%
Close Punctuation 171
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3750
15.1%
2298
 
9.3%
1794
 
7.2%
1794
 
7.2%
1794
 
7.2%
1269
 
5.1%
1098
 
4.4%
981
 
4.0%
837
 
3.4%
801
 
3.2%
Other values (137) 8379
33.8%
Space Separator
ValueCountFrequency (%)
2691
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2691
100.0%
Math Symbol
ValueCountFrequency (%)
> 2691
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2655
100.0%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24795
69.1%
Common 11070
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3750
15.1%
2298
 
9.3%
1794
 
7.2%
1794
 
7.2%
1794
 
7.2%
1269
 
5.1%
1098
 
4.4%
981
 
4.0%
837
 
3.4%
801
 
3.2%
Other values (137) 8379
33.8%
Common
ValueCountFrequency (%)
2691
24.3%
/ 2691
24.3%
> 2691
24.3%
- 2655
24.0%
( 171
 
1.5%
) 171
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24795
69.1%
ASCII 11070
30.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3750
15.1%
2298
 
9.3%
1794
 
7.2%
1794
 
7.2%
1794
 
7.2%
1269
 
5.1%
1098
 
4.4%
981
 
4.0%
837
 
3.4%
801
 
3.2%
Other values (137) 8379
33.8%
ASCII
ValueCountFrequency (%)
2691
24.3%
/ 2691
24.3%
> 2691
24.3%
- 2655
24.0%
( 171
 
1.5%
) 171
 
1.5%

2006
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct358
Distinct (%)14.4%
Missing198
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean156.19615
Minimum0
Maximum91864
Zeros1010
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:37.427071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q317
95-th percentile556.2
Maximum91864
Range91864
Interquartile range (IQR)17

Descriptive statistics

Standard deviation2056.4955
Coefficient of variation (CV)13.166109
Kurtosis1612.8873
Mean156.19615
Median Absolute Deviation (MAD)1
Skewness37.702398
Sum389397
Variance4229173.7
MonotonicityNot monotonic
2024-03-23T14:50:37.663086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1010
37.5%
1 314
 
11.7%
2 135
 
5.0%
3 79
 
2.9%
4 47
 
1.7%
5 45
 
1.7%
7 37
 
1.4%
6 33
 
1.2%
9 30
 
1.1%
12 23
 
0.9%
Other values (348) 740
27.5%
(Missing) 198
 
7.4%
ValueCountFrequency (%)
0 1010
37.5%
1 314
 
11.7%
2 135
 
5.0%
3 79
 
2.9%
4 47
 
1.7%
5 45
 
1.7%
6 33
 
1.2%
7 37
 
1.4%
8 22
 
0.8%
9 30
 
1.1%
ValueCountFrequency (%)
91864 1
< 0.1%
28206 1
< 0.1%
22517 1
< 0.1%
22350 1
< 0.1%
6438 1
< 0.1%
5708 1
< 0.1%
5329 1
< 0.1%
4472 1
< 0.1%
4051 1
< 0.1%
3740 1
< 0.1%

2007
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct341
Distinct (%)13.9%
Missing243
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean125.21569
Minimum0
Maximum67602
Zeros963
Zeros (%)35.8%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:37.837372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q315.25
95-th percentile393.25
Maximum67602
Range67602
Interquartile range (IQR)15.25

Descriptive statistics

Standard deviation1546.9114
Coefficient of variation (CV)12.353974
Kurtosis1512.8432
Mean125.21569
Median Absolute Deviation (MAD)1
Skewness36.35696
Sum306528
Variance2392934.8
MonotonicityNot monotonic
2024-03-23T14:50:38.025179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 963
35.8%
1 322
 
12.0%
2 128
 
4.8%
3 83
 
3.1%
4 57
 
2.1%
5 50
 
1.9%
7 41
 
1.5%
6 36
 
1.3%
12 31
 
1.2%
8 28
 
1.0%
Other values (331) 709
26.3%
(Missing) 243
 
9.0%
ValueCountFrequency (%)
0 963
35.8%
1 322
 
12.0%
2 128
 
4.8%
3 83
 
3.1%
4 57
 
2.1%
5 50
 
1.9%
6 36
 
1.3%
7 41
 
1.5%
8 28
 
1.0%
9 24
 
0.9%
ValueCountFrequency (%)
67602 1
< 0.1%
24607 1
< 0.1%
16269 1
< 0.1%
12755 1
< 0.1%
6188 1
< 0.1%
5770 1
< 0.1%
5341 1
< 0.1%
4432 1
< 0.1%
4326 1
< 0.1%
3895 1
< 0.1%

2008
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct332
Distinct (%)13.5%
Missing225
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean118.50608
Minimum0
Maximum66012
Zeros1005
Zeros (%)37.3%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:38.207862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q315
95-th percentile403.75
Maximum66012
Range66012
Interquartile range (IQR)15

Descriptive statistics

Standard deviation1474.2856
Coefficient of variation (CV)12.44059
Kurtosis1641.0394
Mean118.50608
Median Absolute Deviation (MAD)1
Skewness38.046384
Sum292236
Variance2173518.2
MonotonicityNot monotonic
2024-03-23T14:50:38.380490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1005
37.3%
1 281
 
10.4%
2 140
 
5.2%
3 89
 
3.3%
4 62
 
2.3%
5 44
 
1.6%
6 37
 
1.4%
7 28
 
1.0%
8 27
 
1.0%
13 25
 
0.9%
Other values (322) 728
27.1%
(Missing) 225
 
8.4%
ValueCountFrequency (%)
0 1005
37.3%
1 281
 
10.4%
2 140
 
5.2%
3 89
 
3.3%
4 62
 
2.3%
5 44
 
1.6%
6 37
 
1.4%
7 28
 
1.0%
8 27
 
1.0%
9 22
 
0.8%
ValueCountFrequency (%)
66012 1
< 0.1%
20462 1
< 0.1%
15329 1
< 0.1%
11779 1
< 0.1%
5778 1
< 0.1%
4880 1
< 0.1%
4646 1
< 0.1%
4111 1
< 0.1%
3222 1
< 0.1%
3193 1
< 0.1%

2009
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct337
Distinct (%)13.7%
Missing225
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean122.1026
Minimum0
Maximum67985
Zeros908
Zeros (%)33.7%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:38.570091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q316
95-th percentile419.75
Maximum67985
Range67985
Interquartile range (IQR)16

Descriptive statistics

Standard deviation1507.5387
Coefficient of variation (CV)12.346492
Kurtosis1683.5984
Mean122.1026
Median Absolute Deviation (MAD)1
Skewness38.584674
Sum301105
Variance2272673
MonotonicityNot monotonic
2024-03-23T14:50:38.779658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 908
33.7%
1 341
 
12.7%
2 146
 
5.4%
3 91
 
3.4%
4 71
 
2.6%
6 43
 
1.6%
5 38
 
1.4%
7 36
 
1.3%
8 31
 
1.2%
10 24
 
0.9%
Other values (327) 737
27.4%
(Missing) 225
 
8.4%
ValueCountFrequency (%)
0 908
33.7%
1 341
 
12.7%
2 146
 
5.4%
3 91
 
3.4%
4 71
 
2.6%
5 38
 
1.4%
6 43
 
1.6%
7 36
 
1.3%
8 31
 
1.2%
9 22
 
0.8%
ValueCountFrequency (%)
67985 1
< 0.1%
18414 1
< 0.1%
16909 1
< 0.1%
11674 1
< 0.1%
5610 1
< 0.1%
4802 1
< 0.1%
4439 1
< 0.1%
4437 1
< 0.1%
3496 1
< 0.1%
3320 1
< 0.1%

2010
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct346
Distinct (%)13.7%
Missing171
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean114.71349
Minimum0
Maximum62639
Zeros928
Zeros (%)34.5%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:38.995713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q316
95-th percentile375.05
Maximum62639
Range62639
Interquartile range (IQR)16

Descriptive statistics

Standard deviation1387.0479
Coefficient of variation (CV)12.09141
Kurtosis1664.047
Mean114.71349
Median Absolute Deviation (MAD)1
Skewness38.259003
Sum289078
Variance1923901.9
MonotonicityNot monotonic
2024-03-23T14:50:39.203547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 928
34.5%
1 347
 
12.9%
2 189
 
7.0%
3 105
 
3.9%
4 68
 
2.5%
5 50
 
1.9%
6 44
 
1.6%
7 31
 
1.2%
13 19
 
0.7%
8 17
 
0.6%
Other values (336) 722
26.8%
(Missing) 171
 
6.4%
ValueCountFrequency (%)
0 928
34.5%
1 347
 
12.9%
2 189
 
7.0%
3 105
 
3.9%
4 68
 
2.5%
5 50
 
1.9%
6 44
 
1.6%
7 31
 
1.2%
8 17
 
0.6%
9 15
 
0.6%
ValueCountFrequency (%)
62639 1
< 0.1%
21058 1
< 0.1%
12274 1
< 0.1%
7703 1
< 0.1%
7215 1
< 0.1%
6731 1
< 0.1%
5509 1
< 0.1%
3680 1
< 0.1%
3475 1
< 0.1%
3391 1
< 0.1%

2011
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct356
Distinct (%)14.3%
Missing198
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean134.56478
Minimum0
Maximum79353
Zeros790
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:39.445353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316
95-th percentile470.4
Maximum79353
Range79353
Interquartile range (IQR)16

Descriptive statistics

Standard deviation1716.3108
Coefficient of variation (CV)12.754532
Kurtosis1832.2901
Mean134.56478
Median Absolute Deviation (MAD)2
Skewness40.529429
Sum335470
Variance2945722.9
MonotonicityNot monotonic
2024-03-23T14:50:39.715053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 790
29.4%
1 384
14.3%
2 200
 
7.4%
3 112
 
4.2%
4 91
 
3.4%
5 53
 
2.0%
6 53
 
2.0%
7 37
 
1.4%
8 26
 
1.0%
9 26
 
1.0%
Other values (346) 721
26.8%
(Missing) 198
 
7.4%
ValueCountFrequency (%)
0 790
29.4%
1 384
14.3%
2 200
 
7.4%
3 112
 
4.2%
4 91
 
3.4%
5 53
 
2.0%
6 53
 
2.0%
7 37
 
1.4%
8 26
 
1.0%
9 26
 
1.0%
ValueCountFrequency (%)
79353 1
< 0.1%
18751 1
< 0.1%
16506 1
< 0.1%
9726 1
< 0.1%
7871 1
< 0.1%
6275 1
< 0.1%
5347 1
< 0.1%
4722 1
< 0.1%
4147 1
< 0.1%
3961 1
< 0.1%

2012
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct329
Distinct (%)13.1%
Missing180
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean108.54879
Minimum0
Maximum62880
Zeros838
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:39.967593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314
95-th percentile361.5
Maximum62880
Range62880
Interquartile range (IQR)14

Descriptive statistics

Standard deviation1356.8816
Coefficient of variation (CV)12.5002
Kurtosis1836.4115
Mean108.54879
Median Absolute Deviation (MAD)2
Skewness40.54803
Sum272566
Variance1841127.6
MonotonicityNot monotonic
2024-03-23T14:50:40.184969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 838
31.1%
1 385
14.3%
2 189
 
7.0%
3 107
 
4.0%
4 71
 
2.6%
5 57
 
2.1%
7 45
 
1.7%
6 38
 
1.4%
8 36
 
1.3%
9 27
 
1.0%
Other values (319) 718
26.7%
(Missing) 180
 
6.7%
ValueCountFrequency (%)
0 838
31.1%
1 385
14.3%
2 189
 
7.0%
3 107
 
4.0%
4 71
 
2.6%
5 57
 
2.1%
6 38
 
1.4%
7 45
 
1.7%
8 36
 
1.3%
9 27
 
1.0%
ValueCountFrequency (%)
62880 1
< 0.1%
15483 1
< 0.1%
12845 1
< 0.1%
7030 1
< 0.1%
5423 1
< 0.1%
4949 1
< 0.1%
4790 1
< 0.1%
4347 1
< 0.1%
3752 1
< 0.1%
3264 1
< 0.1%

2013
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct349
Distinct (%)13.9%
Missing180
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean125.00996
Minimum0
Maximum75010
Zeros888
Zeros (%)33.0%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:40.764267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315
95-th percentile426
Maximum75010
Range75010
Interquartile range (IQR)15

Descriptive statistics

Standard deviation1611.548
Coefficient of variation (CV)12.891357
Kurtosis1867.5051
Mean125.00996
Median Absolute Deviation (MAD)2
Skewness40.969339
Sum313900
Variance2597087.1
MonotonicityNot monotonic
2024-03-23T14:50:40.932813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 888
33.0%
1 327
 
12.2%
2 184
 
6.8%
3 110
 
4.1%
4 84
 
3.1%
5 44
 
1.6%
6 42
 
1.6%
7 38
 
1.4%
9 32
 
1.2%
10 32
 
1.2%
Other values (339) 730
27.1%
(Missing) 180
 
6.7%
ValueCountFrequency (%)
0 888
33.0%
1 327
 
12.2%
2 184
 
6.8%
3 110
 
4.1%
4 84
 
3.1%
5 44
 
1.6%
6 42
 
1.6%
7 38
 
1.4%
8 22
 
0.8%
9 32
 
1.2%
ValueCountFrequency (%)
75010 1
< 0.1%
16198 1
< 0.1%
16076 1
< 0.1%
9414 1
< 0.1%
6249 1
< 0.1%
6154 1
< 0.1%
5995 1
< 0.1%
4972 1
< 0.1%
4202 1
< 0.1%
3768 1
< 0.1%

2014
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct387
Distinct (%)15.0%
Missing117
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean153.02292
Minimum0
Maximum95654
Zeros932
Zeros (%)34.6%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:41.208932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q317
95-th percentile521.75
Maximum95654
Range95654
Interquartile range (IQR)17

Descriptive statistics

Standard deviation2023.4734
Coefficient of variation (CV)13.223335
Kurtosis1937.9687
Mean153.02292
Median Absolute Deviation (MAD)2
Skewness41.810603
Sum393881
Variance4094444.6
MonotonicityNot monotonic
2024-03-23T14:50:41.431414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 932
34.6%
1 341
 
12.7%
2 158
 
5.9%
3 92
 
3.4%
4 75
 
2.8%
5 54
 
2.0%
6 42
 
1.6%
7 36
 
1.3%
9 28
 
1.0%
8 28
 
1.0%
Other values (377) 788
29.3%
(Missing) 117
 
4.3%
ValueCountFrequency (%)
0 932
34.6%
1 341
 
12.7%
2 158
 
5.9%
3 92
 
3.4%
4 75
 
2.8%
5 54
 
2.0%
6 42
 
1.6%
7 36
 
1.3%
8 28
 
1.0%
9 28
 
1.0%
ValueCountFrequency (%)
95654 1
< 0.1%
21016 1
< 0.1%
18628 1
< 0.1%
13036 1
< 0.1%
8098 1
< 0.1%
7766 1
< 0.1%
7333 1
< 0.1%
5733 1
< 0.1%
4942 1
< 0.1%
4726 1
< 0.1%

2015
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct382
Distinct (%)15.1%
Missing153
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean182.38849
Minimum0
Maximum117096
Zeros824
Zeros (%)30.6%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:41.631782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q321
95-th percentile703.9
Maximum117096
Range117096
Interquartile range (IQR)21

Descriptive statistics

Standard deviation2496.8289
Coefficient of variation (CV)13.689619
Kurtosis1905.8023
Mean182.38849
Median Absolute Deviation (MAD)2
Skewness41.508305
Sum462902
Variance6234154.8
MonotonicityNot monotonic
2024-03-23T14:50:41.835845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 824
30.6%
1 342
12.7%
2 155
 
5.8%
3 112
 
4.2%
4 86
 
3.2%
5 51
 
1.9%
6 51
 
1.9%
7 40
 
1.5%
8 38
 
1.4%
11 33
 
1.2%
Other values (372) 806
30.0%
(Missing) 153
 
5.7%
ValueCountFrequency (%)
0 824
30.6%
1 342
12.7%
2 155
 
5.8%
3 112
 
4.2%
4 86
 
3.2%
5 51
 
1.9%
6 51
 
1.9%
7 40
 
1.5%
8 38
 
1.4%
9 19
 
0.7%
ValueCountFrequency (%)
117096 1
< 0.1%
28084 1
< 0.1%
20722 1
< 0.1%
18874 1
< 0.1%
10187 1
< 0.1%
8156 1
< 0.1%
7003 1
< 0.1%
6532 1
< 0.1%
6471 1
< 0.1%
4457 1
< 0.1%

2016
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct366
Distinct (%)14.4%
Missing153
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean166.19149
Minimum0
Maximum105575
Zeros871
Zeros (%)32.4%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:42.064276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q322
95-th percentile596
Maximum105575
Range105575
Interquartile range (IQR)22

Descriptive statistics

Standard deviation2264.0418
Coefficient of variation (CV)13.623091
Kurtosis1865.5249
Mean166.19149
Median Absolute Deviation (MAD)2
Skewness40.997252
Sum421794
Variance5125885.5
MonotonicityNot monotonic
2024-03-23T14:50:42.307261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 871
32.4%
1 310
 
11.5%
2 169
 
6.3%
3 110
 
4.1%
4 76
 
2.8%
5 54
 
2.0%
6 46
 
1.7%
7 40
 
1.5%
9 26
 
1.0%
10 25
 
0.9%
Other values (356) 811
30.1%
(Missing) 153
 
5.7%
ValueCountFrequency (%)
0 871
32.4%
1 310
 
11.5%
2 169
 
6.3%
3 110
 
4.1%
4 76
 
2.8%
5 54
 
2.0%
6 46
 
1.7%
7 40
 
1.5%
8 23
 
0.9%
9 26
 
1.0%
ValueCountFrequency (%)
105575 1
< 0.1%
27590 1
< 0.1%
19146 1
< 0.1%
17833 1
< 0.1%
9099 1
< 0.1%
7058 1
< 0.1%
6456 1
< 0.1%
4746 1
< 0.1%
4561 1
< 0.1%
4470 1
< 0.1%

2017
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct406
Distinct (%)16.2%
Missing180
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean177.92234
Minimum0
Maximum97933
Zeros863
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:42.530935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q325
95-th percentile628.5
Maximum97933
Range97933
Interquartile range (IQR)25

Descriptive statistics

Standard deviation2203.0111
Coefficient of variation (CV)12.381869
Kurtosis1576.6034
Mean177.92234
Median Absolute Deviation (MAD)2
Skewness37.195369
Sum446763
Variance4853257.8
MonotonicityNot monotonic
2024-03-23T14:50:42.761281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 863
32.1%
1 293
 
10.9%
2 145
 
5.4%
3 106
 
3.9%
4 72
 
2.7%
5 57
 
2.1%
6 52
 
1.9%
8 41
 
1.5%
7 29
 
1.1%
11 28
 
1.0%
Other values (396) 825
30.7%
(Missing) 180
 
6.7%
ValueCountFrequency (%)
0 863
32.1%
1 293
 
10.9%
2 145
 
5.4%
3 106
 
3.9%
4 72
 
2.7%
5 57
 
2.1%
6 52
 
1.9%
7 29
 
1.1%
8 41
 
1.5%
9 24
 
0.9%
ValueCountFrequency (%)
97933 1
< 0.1%
33576 1
< 0.1%
26878 1
< 0.1%
16880 1
< 0.1%
10237 1
< 0.1%
6577 1
< 0.1%
5986 1
< 0.1%
5870 1
< 0.1%
5334 1
< 0.1%
4377 1
< 0.1%

2018
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct405
Distinct (%)16.1%
Missing171
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean172.53056
Minimum0
Maximum85997
Zeros790
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:42.995304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q329
95-th percentile558.1
Maximum85997
Range85997
Interquartile range (IQR)29

Descriptive statistics

Standard deviation2012.6137
Coefficient of variation (CV)11.665259
Kurtosis1373.5634
Mean172.53056
Median Absolute Deviation (MAD)2
Skewness34.533626
Sum434777
Variance4050613.8
MonotonicityNot monotonic
2024-03-23T14:50:43.217476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 790
29.4%
1 319
 
11.9%
2 157
 
5.8%
3 101
 
3.8%
4 63
 
2.3%
7 45
 
1.7%
6 45
 
1.7%
5 40
 
1.5%
8 34
 
1.3%
10 30
 
1.1%
Other values (395) 896
33.3%
(Missing) 171
 
6.4%
ValueCountFrequency (%)
0 790
29.4%
1 319
11.9%
2 157
 
5.8%
3 101
 
3.8%
4 63
 
2.3%
5 40
 
1.5%
6 45
 
1.7%
7 45
 
1.7%
8 34
 
1.3%
9 25
 
0.9%
ValueCountFrequency (%)
85997 1
< 0.1%
37808 1
< 0.1%
25341 1
< 0.1%
15420 1
< 0.1%
14125 1
< 0.1%
5956 1
< 0.1%
5098 1
< 0.1%
4667 1
< 0.1%
4339 1
< 0.1%
4031 1
< 0.1%

2019
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct395
Distinct (%)15.7%
Missing180
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean156.28992
Minimum0
Maximum76280
Zeros764
Zeros (%)28.4%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:43.470970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q327
95-th percentile501
Maximum76280
Range76280
Interquartile range (IQR)27

Descriptive statistics

Standard deviation1780.6516
Coefficient of variation (CV)11.393259
Kurtosis1392.0824
Mean156.28992
Median Absolute Deviation (MAD)3
Skewness34.792055
Sum392444
Variance3170720.2
MonotonicityNot monotonic
2024-03-23T14:50:43.725658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 764
28.4%
1 316
 
11.7%
2 163
 
6.1%
3 88
 
3.3%
4 71
 
2.6%
5 62
 
2.3%
6 58
 
2.2%
7 39
 
1.4%
9 32
 
1.2%
12 30
 
1.1%
Other values (385) 888
33.0%
(Missing) 180
 
6.7%
ValueCountFrequency (%)
0 764
28.4%
1 316
11.7%
2 163
 
6.1%
3 88
 
3.3%
4 71
 
2.6%
5 62
 
2.3%
6 58
 
2.2%
7 39
 
1.4%
8 23
 
0.9%
9 32
 
1.2%
ValueCountFrequency (%)
76280 1
< 0.1%
34102 1
< 0.1%
20582 1
< 0.1%
12199 1
< 0.1%
10920 1
< 0.1%
5458 1
< 0.1%
5141 1
< 0.1%
4763 1
< 0.1%
4392 1
< 0.1%
4382 1
< 0.1%

2020
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct410
Distinct (%)16.3%
Missing180
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean200.65233
Minimum0
Maximum111286
Zeros722
Zeros (%)26.8%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:43.942166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q339
95-th percentile644
Maximum111286
Range111286
Interquartile range (IQR)39

Descriptive statistics

Standard deviation2466.4739
Coefficient of variation (CV)12.292276
Kurtosis1662.9958
Mean200.65233
Median Absolute Deviation (MAD)3
Skewness38.306789
Sum503838
Variance6083493.5
MonotonicityNot monotonic
2024-03-23T14:50:44.159503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 722
26.8%
1 296
 
11.0%
2 142
 
5.3%
3 99
 
3.7%
4 74
 
2.7%
5 60
 
2.2%
6 45
 
1.7%
7 42
 
1.6%
8 34
 
1.3%
12 32
 
1.2%
Other values (400) 965
35.9%
(Missing) 180
 
6.7%
ValueCountFrequency (%)
0 722
26.8%
1 296
11.0%
2 142
 
5.3%
3 99
 
3.7%
4 74
 
2.7%
5 60
 
2.2%
6 45
 
1.7%
7 42
 
1.6%
8 34
 
1.3%
9 29
 
1.1%
ValueCountFrequency (%)
111286 1
< 0.1%
32571 1
< 0.1%
31413 1
< 0.1%
14381 1
< 0.1%
10430 1
< 0.1%
9359 1
< 0.1%
7145 1
< 0.1%
6756 1
< 0.1%
6357 1
< 0.1%
5915 1
< 0.1%

2021
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct393
Distinct (%)15.7%
Missing180
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean156.34409
Minimum0
Maximum82972
Zeros735
Zeros (%)27.3%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:44.345278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q333
95-th percentile483
Maximum82972
Range82972
Interquartile range (IQR)33

Descriptive statistics

Standard deviation1846.0682
Coefficient of variation (CV)11.807726
Kurtosis1639.6686
Mean156.34409
Median Absolute Deviation (MAD)3
Skewness37.986272
Sum392580
Variance3407967.7
MonotonicityNot monotonic
2024-03-23T14:50:44.558764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 735
27.3%
1 286
 
10.6%
2 137
 
5.1%
3 103
 
3.8%
4 76
 
2.8%
5 67
 
2.5%
6 58
 
2.2%
7 43
 
1.6%
8 36
 
1.3%
9 28
 
1.0%
Other values (383) 942
35.0%
(Missing) 180
 
6.7%
ValueCountFrequency (%)
0 735
27.3%
1 286
 
10.6%
2 137
 
5.1%
3 103
 
3.8%
4 76
 
2.8%
5 67
 
2.5%
6 58
 
2.2%
7 43
 
1.6%
8 36
 
1.3%
9 28
 
1.0%
ValueCountFrequency (%)
82972 1
< 0.1%
26652 1
< 0.1%
21949 1
< 0.1%
9377 1
< 0.1%
7285 1
< 0.1%
6489 1
< 0.1%
5695 1
< 0.1%
5436 1
< 0.1%
5305 1
< 0.1%
5023 1
< 0.1%

2022
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct331
Distinct (%)13.2%
Missing180
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean90.802867
Minimum0
Maximum43445
Zeros774
Zeros (%)28.8%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:44.754842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q321
95-th percentile275.5
Maximum43445
Range43445
Interquartile range (IQR)21

Descriptive statistics

Standard deviation1001.2384
Coefficient of variation (CV)11.026506
Kurtosis1459.3586
Mean90.802867
Median Absolute Deviation (MAD)2
Skewness35.727155
Sum228006
Variance1002478.3
MonotonicityNot monotonic
2024-03-23T14:50:44.923333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 774
28.8%
1 320
 
11.9%
2 170
 
6.3%
3 108
 
4.0%
4 94
 
3.5%
6 69
 
2.6%
5 51
 
1.9%
8 43
 
1.6%
7 33
 
1.2%
9 28
 
1.0%
Other values (321) 821
30.5%
(Missing) 180
 
6.7%
ValueCountFrequency (%)
0 774
28.8%
1 320
11.9%
2 170
 
6.3%
3 108
 
4.0%
4 94
 
3.5%
5 51
 
1.9%
6 69
 
2.6%
7 33
 
1.2%
8 43
 
1.6%
9 28
 
1.0%
ValueCountFrequency (%)
43445 1
< 0.1%
19350 1
< 0.1%
9436 1
< 0.1%
5597 1
< 0.1%
3867 1
< 0.1%
3811 1
< 0.1%
3657 1
< 0.1%
3545 1
< 0.1%
2767 1
< 0.1%
2518 1
< 0.1%

2023
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct313
Distinct (%)12.4%
Missing171
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean89.834127
Minimum0
Maximum49187
Zeros880
Zeros (%)32.7%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2024-03-23T14:50:45.079666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q311
95-th percentile297
Maximum49187
Range49187
Interquartile range (IQR)11

Descriptive statistics

Standard deviation1094.3364
Coefficient of variation (CV)12.181744
Kurtosis1638.2935
Mean89.834127
Median Absolute Deviation (MAD)2
Skewness38.016249
Sum226382
Variance1197572.1
MonotonicityNot monotonic
2024-03-23T14:50:45.277014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 880
32.7%
1 356
13.2%
2 205
 
7.6%
3 143
 
5.3%
4 77
 
2.9%
5 54
 
2.0%
6 51
 
1.9%
8 39
 
1.4%
7 31
 
1.2%
10 24
 
0.9%
Other values (303) 660
24.5%
(Missing) 171
 
6.4%
ValueCountFrequency (%)
0 880
32.7%
1 356
13.2%
2 205
 
7.6%
3 143
 
5.3%
4 77
 
2.9%
5 54
 
2.0%
6 51
 
1.9%
7 31
 
1.2%
8 39
 
1.4%
9 21
 
0.8%
ValueCountFrequency (%)
49187 1
< 0.1%
16984 1
< 0.1%
12232 1
< 0.1%
4717 1
< 0.1%
4635 1
< 0.1%
3586 1
< 0.1%
3290 1
< 0.1%
3262 1
< 0.1%
2892 1
< 0.1%
2878 1
< 0.1%

Interactions

2024-03-23T14:50:32.188010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:44.878819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:47.777069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:50.834657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:53.554250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:56.391611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:59.382849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:02.252575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:05.029493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:08.332533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:10.906280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:13.712324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.724330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:19.354412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:22.091097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:24.749079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:27.656384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.963315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:32.278667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:45.058202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:47.920714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:50.960329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:53.689258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:56.513941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:59.552630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:02.433959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:05.183785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:08.467025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:11.069914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:13.864898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.855525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:19.470387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:22.205386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:24.898266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:27.764537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:30.055137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:32.454690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:45.263084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:48.441308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:51.124705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:53.845370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:56.645491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:59.711105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:02.600579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:05.330869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:08.666752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:11.239012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:14.018739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.992169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:19.632101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:22.330677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:25.438127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:27.897537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:30.209038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:32.585040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:45.420837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:48.592487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:51.273650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:53.988525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:56.794754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:59.848089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:02.757541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:05.505443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:08.819295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:11.389244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:14.178629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:17.104378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:19.765614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:22.518614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:25.556023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.028842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:30.346246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:32.734029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:45.592509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:48.746586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:51.437253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:54.132305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:56.940487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:59.973230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:02.896512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:05.672879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:08.968634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:11.533045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:14.362828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:17.237311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:19.892528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:22.685089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:25.667882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.177227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:30.511630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:32.899239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:45.746145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:48.882568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:51.596495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:54.295492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:57.428878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:00.184064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:03.030092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:05.838585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:09.089202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:11.691104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:14.517905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:17.378325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:20.041307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:22.841493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:25.804116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.321637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:30.643987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:33.067183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:45.903897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:49.026967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:51.761443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:54.500442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:57.565674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:00.382509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:03.195133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:06.000907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:09.233719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:11.872256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:14.654773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:17.519714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:20.285459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:22.993597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:25.975276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.464597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:30.768644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:33.220025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:46.056278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:49.178627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:51.892257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:54.689730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:57.718427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:00.548337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:03.327093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:06.624335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:09.378103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:12.067894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:14.828836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:17.652333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:20.476642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:23.151836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:26.116473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.617417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:30.873604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:33.369257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:46.269897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:49.305529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:52.074049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:54.859414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:57.903054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:00.700952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:03.453615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:06.783559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:09.561049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:12.237237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:14.990284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:17.791625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:20.646306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:23.304222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:26.253680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.744208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.016574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:33.542130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:46.414797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:49.427233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:52.234896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:55.012803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.050837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:00.858972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:03.574794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:06.941556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:09.715645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:12.400578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:15.124466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:17.968890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:20.804657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:23.476359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:26.377132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.877422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.139317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:33.685148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:46.574408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:49.557947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:52.365368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:55.155013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.191906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:01.013884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:03.770058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:07.099508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:09.860222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:12.553879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:15.258660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:18.109306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:20.945569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:23.628884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:26.506700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:28.973943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.247352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:33.795756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:46.716371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:49.727981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:52.496340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:55.303530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.302323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:01.162770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:03.949125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:07.292473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:09.972324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:12.680417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:15.372308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:18.251580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:21.121481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:23.783880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:26.643639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.061733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.348941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:33.920265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:46.884705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:49.933002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:52.626015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:55.497484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.423418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:01.291009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:04.105238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:07.460546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:10.096114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:12.821740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:15.909451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:18.385055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:21.294248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:23.909759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:26.798286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.162912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.461229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:34.059632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:47.009635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:50.102564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:52.767100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:55.659606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.544412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:01.455138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:04.256808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:07.612794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:10.204468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:12.947495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.025425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:18.530308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:21.438840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:24.022432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:26.894572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.284849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.579825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:34.621174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:47.162919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:50.268340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:52.943967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:55.805110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.689125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:01.646280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:04.418092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:07.785865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:10.348240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:13.126982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.177577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:18.774259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:21.583597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:24.169922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:27.061584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.461369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.717387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:34.748960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:47.319115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:50.425510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:53.123431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:55.933266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.826641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:01.814985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:04.562019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:07.949030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:10.491023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:13.298170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.308113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:18.929298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:21.705590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:24.296632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:27.221460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.642915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.861950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:34.888171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:47.468903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:50.559768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:53.270933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:56.093001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:58.980490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:01.940859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:04.693272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:08.064931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:10.629951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:13.443555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.432221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:19.079406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:21.813251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:24.444660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:27.371527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.762874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:31.983707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:35.030430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:47.624742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:50.687042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:53.418402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:56.246345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:49:59.169603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:02.090345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:04.867985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:08.192537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:10.743056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:13.578975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:16.584612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:19.223131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:21.939412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:24.610680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:27.521082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:29.864480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:50:32.083286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T14:50:45.420124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0001.0001.0000.9900.9760.9900.9900.9901.0001.0001.0000.9380.9380.9380.9901.0000.9070.996
20071.0001.0001.0001.0000.9071.0001.0001.0001.0001.0001.0000.9980.9980.9981.0001.0000.9911.000
20081.0001.0001.0001.0000.9071.0001.0001.0001.0001.0001.0000.9980.9980.9981.0001.0000.9911.000
20090.9901.0001.0001.0000.9761.0001.0001.0000.9900.9900.9900.9070.9070.9071.0001.0000.8410.982
20100.9760.9070.9070.9761.0000.9760.9760.9760.9760.9760.9760.9380.9380.9380.9760.9070.9070.990
20110.9901.0001.0001.0000.9761.0001.0001.0000.9900.9900.9900.9070.9070.9071.0001.0000.8410.982
20120.9901.0001.0001.0000.9761.0001.0001.0000.9900.9900.9900.9070.9070.9071.0001.0000.8410.982
20130.9901.0001.0001.0000.9761.0001.0001.0000.9900.9900.9900.9070.9070.9071.0001.0000.8410.982
20141.0001.0001.0000.9900.9760.9900.9900.9901.0001.0001.0000.9380.9380.9380.9901.0000.9070.996
20151.0001.0001.0000.9900.9760.9900.9900.9901.0001.0001.0000.9380.9380.9380.9901.0000.9070.996
20161.0001.0001.0000.9900.9760.9900.9900.9901.0001.0001.0000.9380.9380.9380.9901.0000.9070.996
20170.9380.9980.9980.9070.9380.9070.9070.9070.9380.9380.9381.0001.0001.0000.9070.9980.9981.000
20180.9380.9980.9980.9070.9380.9070.9070.9070.9380.9380.9381.0001.0001.0000.9070.9980.9981.000
20190.9380.9980.9980.9070.9380.9070.9070.9070.9380.9380.9381.0001.0001.0000.9070.9980.9981.000
20200.9901.0001.0001.0000.9761.0001.0001.0000.9900.9900.9900.9070.9070.9071.0001.0000.8410.982
20211.0001.0001.0001.0000.9071.0001.0001.0001.0001.0001.0000.9980.9980.9981.0001.0000.9911.000
20220.9070.9910.9910.8410.9070.8410.8410.8410.9070.9070.9070.9980.9980.9980.8410.9911.0001.000
20230.9961.0001.0000.9820.9900.9820.9820.9820.9960.9960.9961.0001.0001.0000.9821.0001.0001.000
2024-03-23T14:50:45.726514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.8840.8430.8290.8430.8390.8240.8320.8240.8470.8360.8420.8350.8410.8430.8190.8090.784
20070.8841.0000.8650.8370.8460.8340.8220.8330.8220.8400.8340.8340.8370.8330.8380.8160.8160.793
20080.8430.8651.0000.8580.8500.8270.8180.8220.8200.8270.8260.8190.8270.8180.8200.8010.7960.781
20090.8290.8370.8581.0000.8570.8330.8280.8340.8120.8250.8170.8200.8150.8100.8140.8030.7990.785
20100.8430.8460.8500.8571.0000.8750.8440.8530.8250.8430.8250.8340.8260.8230.8320.8120.8030.790
20110.8390.8340.8270.8330.8751.0000.8770.8510.8340.8500.8240.8340.8320.8170.8250.8140.8020.791
20120.8240.8220.8180.8280.8440.8771.0000.8640.8400.8420.8290.8330.8280.8280.8300.8190.8120.792
20130.8320.8330.8220.8340.8530.8510.8641.0000.8680.8620.8540.8620.8440.8360.8390.8190.8150.798
20140.8240.8220.8200.8120.8250.8340.8400.8681.0000.8650.8410.8410.8380.8310.8260.8010.8060.781
20150.8470.8400.8270.8250.8430.8500.8420.8620.8651.0000.8910.8690.8670.8550.8470.8350.8250.803
20160.8360.8340.8260.8170.8250.8240.8290.8540.8410.8911.0000.8850.8690.8520.8480.8400.8380.813
20170.8420.8340.8190.8200.8340.8340.8330.8620.8410.8690.8851.0000.8840.8660.8590.8500.8330.814
20180.8350.8370.8270.8150.8260.8320.8280.8440.8380.8670.8690.8841.0000.8960.8680.8480.8410.813
20190.8410.8330.8180.8100.8230.8170.8280.8360.8310.8550.8520.8660.8961.0000.8860.8500.8370.816
20200.8430.8380.8200.8140.8320.8250.8300.8390.8260.8470.8480.8590.8680.8861.0000.8850.8630.842
20210.8190.8160.8010.8030.8120.8140.8190.8190.8010.8350.8400.8500.8480.8500.8851.0000.8890.844
20220.8090.8160.7960.7990.8030.8020.8120.8150.8060.8250.8380.8330.8410.8370.8630.8891.0000.867
20230.7840.7930.7810.7850.7900.7910.7920.7980.7810.8030.8130.8140.8130.8160.8420.8440.8671.000

Missing values

2024-03-23T14:50:35.248577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:50:35.592328image/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.
2024-03-23T14:50:35.935608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

지역 및 거래주체200620072008200920102011201220132014201520162017201820192020202120222023
0전국 /개인->개인918646760266012679856263979353628807501095654117096105575979338599776280111286829724344549187
1전국 /개인->법인372419501927150814741464152517052101255425902302295540975915475725181071
2전국 /개인->기타47544742349443652954451142768367772780896613771395962595
3전국 /법인->개인223502460720462184142105818751154831619818628188741783333576378083410232571266521935016984
4전국 /법인->법인1145133625043496368028112670165522961964159513631870169326781297865532
5전국 /법인->기타1693191262069113712887143188210304308334758581685513
6전국 /기타->개인252113831524242115561882183728903911333137553934595654583347543636572132
7전국 /기타->법인43573944102752927965941554943716213114219454
8전국 /기타->기타193145115139135214184195210179140191265266152159129203
9서울 /개인->개인22517127551177911674770397267030941413036207221914616880154201092014381937738674717
지역 및 거래주체200620072008200920102011201220132014201520162017201820192020202120222023
2681제주 제주시/기타->기타01522147394120353221
2682제주 서귀포시/개인->개인56111100112126148144188251388402289254192224298222181
2683제주 서귀포시/개인->법인2645346141115231526191914105
2684제주 서귀포시/개인->기타110021124431214526
2685제주 서귀포시/법인->개인2143818173332537518518016410374761018453
2686제주 서귀포시/법인->법인1147711137730181527192113813
2687제주 서귀포시/법인->기타0001010001340002730
2688제주 서귀포시/기타->개인0000111211221247183
2689제주 서귀포시/기타->법인000001000001000100
2690제주 서귀포시/기타->기타000000000000000300