Overview

Dataset statistics

Number of variables19
Number of observations1495
Missing cells1825
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory248.3 KiB
Average record size in memory170.1 B

Variable types

Text1
Numeric18

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산거래현황 중 주택 거래현황의 연도별 주택유형별(면적) 데이터입니다.- (단위 : 천㎡)- 공표시기 : 익월 말일경
Author한국부동산원
URLhttps://www.data.go.kr/data/15068442/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 110 (7.4%) missing valuesMissing
2007 has 135 (9.0%) missing valuesMissing
2008 has 125 (8.4%) missing valuesMissing
2009 has 125 (8.4%) missing valuesMissing
2010 has 95 (6.4%) missing valuesMissing
2011 has 110 (7.4%) missing valuesMissing
2012 has 100 (6.7%) missing valuesMissing
2013 has 100 (6.7%) missing valuesMissing
2014 has 65 (4.3%) missing valuesMissing
2015 has 85 (5.7%) missing valuesMissing
2016 has 85 (5.7%) missing valuesMissing
2017 has 100 (6.7%) missing valuesMissing
2018 has 95 (6.4%) missing valuesMissing
2019 has 100 (6.7%) missing valuesMissing
2020 has 100 (6.7%) missing valuesMissing
2021 has 100 (6.7%) missing valuesMissing
2022 has 100 (6.7%) missing valuesMissing
2023 has 95 (6.4%) missing valuesMissing
2006 is highly skewed (γ1 = 28.19951615)Skewed
2007 is highly skewed (γ1 = 28.81966368)Skewed
2008 is highly skewed (γ1 = 29.26258334)Skewed
2009 is highly skewed (γ1 = 29.63242877)Skewed
2010 is highly skewed (γ1 = 29.85894073)Skewed
2011 is highly skewed (γ1 = 29.81998693)Skewed
2012 is highly skewed (γ1 = 29.42307117)Skewed
2013 is highly skewed (γ1 = 29.74439831)Skewed
2014 is highly skewed (γ1 = 30.32623954)Skewed
2015 is highly skewed (γ1 = 28.65314196)Skewed
2016 is highly skewed (γ1 = 28.49321784)Skewed
2017 is highly skewed (γ1 = 28.89519256)Skewed
2018 is highly skewed (γ1 = 29.14223551)Skewed
2019 is highly skewed (γ1 = 29.82042334)Skewed
2020 is highly skewed (γ1 = 30.08193634)Skewed
2021 is highly skewed (γ1 = 29.43803121)Skewed
2022 is highly skewed (γ1 = 28.82329019)Skewed
2023 is highly skewed (γ1 = 30.82281198)Skewed
지역 및 주택유형 has unique valuesUnique
2006 has 107 (7.2%) zerosZeros
2007 has 102 (6.8%) zerosZeros
2008 has 86 (5.8%) zerosZeros
2009 has 83 (5.6%) zerosZeros
2010 has 77 (5.2%) zerosZeros
2011 has 58 (3.9%) zerosZeros
2012 has 49 (3.3%) zerosZeros
2013 has 47 (3.1%) zerosZeros
2014 has 37 (2.5%) zerosZeros
2015 has 33 (2.2%) zerosZeros
2016 has 27 (1.8%) zerosZeros
2017 has 61 (4.1%) zerosZeros
2018 has 64 (4.3%) zerosZeros
2019 has 37 (2.5%) zerosZeros
2020 has 35 (2.3%) zerosZeros
2021 has 30 (2.0%) zerosZeros
2022 has 35 (2.3%) zerosZeros
2023 has 56 (3.7%) zerosZeros

Reproduction

Analysis started2024-04-06 08:24:47.754311
Analysis finished2024-04-06 08:26:07.258555
Duration1 minute and 19.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct1495
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2024-04-06T17:26:07.571714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length11.541137
Min length7

Characters and Unicode

Total characters17254
Distinct characters152
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1495 ?
Unique (%)100.0%

Sample

1st row전국 /단독주택
2nd row전국 /다가구주택
3rd row전국 /다세대주택
4th row전국 /연립주택
5th row전국 /아파트
ValueCountFrequency (%)
경기 265
 
8.9%
경남 135
 
4.5%
경북 130
 
4.3%
서울 130
 
4.3%
전남 115
 
3.8%
충남 100
 
3.3%
충북 100
 
3.3%
강원 95
 
3.2%
전북 85
 
2.8%
부산 85
 
2.8%
Other values (1294) 1750
58.5%
2024-04-06T17:26:08.289237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1495
 
8.7%
/ 1495
 
8.7%
1431
 
8.3%
1201
 
7.0%
1004
 
5.8%
610
 
3.5%
598
 
3.5%
545
 
3.2%
465
 
2.7%
445
 
2.6%
Other values (142) 7965
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14074
81.6%
Space Separator 1495
 
8.7%
Other Punctuation 1495
 
8.7%
Close Punctuation 95
 
0.6%
Open Punctuation 95
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1431
 
10.2%
1201
 
8.5%
1004
 
7.1%
610
 
4.3%
598
 
4.2%
545
 
3.9%
465
 
3.3%
445
 
3.2%
399
 
2.8%
360
 
2.6%
Other values (138) 7016
49.9%
Space Separator
ValueCountFrequency (%)
1495
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1495
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14074
81.6%
Common 3180
 
18.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1431
 
10.2%
1201
 
8.5%
1004
 
7.1%
610
 
4.3%
598
 
4.2%
545
 
3.9%
465
 
3.3%
445
 
3.2%
399
 
2.8%
360
 
2.6%
Other values (138) 7016
49.9%
Common
ValueCountFrequency (%)
1495
47.0%
/ 1495
47.0%
) 95
 
3.0%
( 95
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14074
81.6%
ASCII 3180
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1495
47.0%
/ 1495
47.0%
) 95
 
3.0%
( 95
 
3.0%
Hangul
ValueCountFrequency (%)
1431
 
10.2%
1201
 
8.5%
1004
 
7.1%
610
 
4.3%
598
 
4.2%
545
 
3.9%
465
 
3.3%
445
 
3.2%
399
 
2.8%
360
 
2.6%
Other values (138) 7016
49.9%

2006
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct383
Distinct (%)27.7%
Missing110
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean281.20939
Minimum0
Maximum83554
Zeros107
Zeros (%)7.2%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:08.626660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median26
Q3108
95-th percentile810
Maximum83554
Range83554
Interquartile range (IQR)104

Descriptive statistics

Standard deviation2496.6337
Coefficient of variation (CV)8.878202
Kurtosis907.04481
Mean281.20939
Median Absolute Deviation (MAD)25
Skewness28.199516
Sum389475
Variance6233180
MonotonicityNot monotonic
2024-04-06T17:26:08.972034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 107
 
7.2%
1 92
 
6.2%
2 57
 
3.8%
4 49
 
3.3%
3 46
 
3.1%
7 32
 
2.1%
6 28
 
1.9%
8 25
 
1.7%
10 23
 
1.5%
5 21
 
1.4%
Other values (373) 905
60.5%
(Missing) 110
 
7.4%
ValueCountFrequency (%)
0 107
7.2%
1 92
6.2%
2 57
3.8%
3 46
3.1%
4 49
3.3%
5 21
 
1.4%
6 28
 
1.9%
7 32
 
2.1%
8 25
 
1.7%
9 20
 
1.3%
ValueCountFrequency (%)
83554 1
0.1%
26431 1
0.1%
18717 1
0.1%
14330 1
0.1%
10811 1
0.1%
5662 1
0.1%
5597 1
0.1%
4440 1
0.1%
4365 1
0.1%
4213 1
0.1%

2007
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct334
Distinct (%)24.6%
Missing135
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean225.43015
Minimum0
Maximum65520
Zeros102
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:09.360031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median24
Q386
95-th percentile613.5
Maximum65520
Range65520
Interquartile range (IQR)82

Descriptive statistics

Standard deviation1942.2544
Coefficient of variation (CV)8.6157704
Kurtosis946.2737
Mean225.43015
Median Absolute Deviation (MAD)23
Skewness28.819664
Sum306585
Variance3772352.1
MonotonicityNot monotonic
2024-04-06T17:26:09.715851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 102
 
6.8%
1 90
 
6.0%
2 63
 
4.2%
3 46
 
3.1%
4 44
 
2.9%
6 35
 
2.3%
5 32
 
2.1%
9 28
 
1.9%
7 21
 
1.4%
8 21
 
1.4%
Other values (324) 878
58.7%
(Missing) 135
 
9.0%
ValueCountFrequency (%)
0 102
6.8%
1 90
6.0%
2 63
4.2%
3 46
3.1%
4 44
2.9%
5 32
 
2.1%
6 35
 
2.3%
7 21
 
1.4%
8 21
 
1.4%
9 28
 
1.9%
ValueCountFrequency (%)
65520 1
0.1%
15038 1
0.1%
14156 1
0.1%
9958 1
0.1%
7077 1
0.1%
5964 1
0.1%
5462 1
0.1%
5331 1
0.1%
4740 1
0.1%
4639 1
0.1%

2008
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct330
Distinct (%)24.1%
Missing125
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean213.38905
Minimum0
Maximum62569
Zeros86
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:10.006746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median23
Q381
95-th percentile661.4
Maximum62569
Range62569
Interquartile range (IQR)77

Descriptive statistics

Standard deviation1839.5472
Coefficient of variation (CV)8.6206261
Kurtosis970.47254
Mean213.38905
Median Absolute Deviation (MAD)21
Skewness29.262583
Sum292343
Variance3383934
MonotonicityNot monotonic
2024-04-06T17:26:10.703552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 95
 
6.4%
0 86
 
5.8%
2 65
 
4.3%
4 54
 
3.6%
3 45
 
3.0%
5 36
 
2.4%
7 30
 
2.0%
6 30
 
2.0%
19 21
 
1.4%
12 20
 
1.3%
Other values (320) 888
59.4%
(Missing) 125
 
8.4%
ValueCountFrequency (%)
0 86
5.8%
1 95
6.4%
2 65
4.3%
3 45
3.0%
4 54
3.6%
5 36
 
2.4%
6 30
 
2.0%
7 30
 
2.0%
8 19
 
1.3%
9 20
 
1.3%
ValueCountFrequency (%)
62569 1
0.1%
13744 1
0.1%
13321 1
0.1%
9708 1
0.1%
6659 1
0.1%
5278 1
0.1%
5183 1
0.1%
4928 1
0.1%
4049 1
0.1%
3897 1
0.1%

2009
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct320
Distinct (%)23.4%
Missing125
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean219.81387
Minimum0
Maximum68305
Zeros83
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:10.981373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median22
Q372.75
95-th percentile669
Maximum68305
Range68305
Interquartile range (IQR)68.75

Descriptive statistics

Standard deviation2001.7203
Coefficient of variation (CV)9.1064331
Kurtosis985.20645
Mean219.81387
Median Absolute Deviation (MAD)20
Skewness29.632429
Sum301145
Variance4006884.1
MonotonicityNot monotonic
2024-04-06T17:26:11.283189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 100
 
6.7%
0 83
 
5.6%
2 65
 
4.3%
3 49
 
3.3%
4 47
 
3.1%
5 42
 
2.8%
8 32
 
2.1%
6 29
 
1.9%
9 27
 
1.8%
7 20
 
1.3%
Other values (310) 876
58.6%
(Missing) 125
 
8.4%
ValueCountFrequency (%)
0 83
5.6%
1 100
6.7%
2 65
4.3%
3 49
3.3%
4 47
3.1%
5 42
2.8%
6 29
 
1.9%
7 20
 
1.3%
8 32
 
2.1%
9 27
 
1.8%
ValueCountFrequency (%)
68305 1
0.1%
17977 1
0.1%
13176 1
0.1%
8335 1
0.1%
6810 1
0.1%
6142 1
0.1%
4799 1
0.1%
4355 1
0.1%
3861 1
0.1%
3802 1
0.1%

2010
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct322
Distinct (%)23.0%
Missing95
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean206.54143
Minimum0
Maximum64554
Zeros77
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:11.614448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median21
Q374
95-th percentile655.1
Maximum64554
Range64554
Interquartile range (IQR)69

Descriptive statistics

Standard deviation1873.5873
Coefficient of variation (CV)9.071242
Kurtosis1002.0168
Mean206.54143
Median Absolute Deviation (MAD)19
Skewness29.858941
Sum289158
Variance3510329.3
MonotonicityNot monotonic
2024-04-06T17:26:11.996599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 96
 
6.4%
0 77
 
5.2%
2 66
 
4.4%
3 55
 
3.7%
5 49
 
3.3%
4 42
 
2.8%
6 36
 
2.4%
7 31
 
2.1%
8 30
 
2.0%
10 28
 
1.9%
Other values (312) 890
59.5%
(Missing) 95
 
6.4%
ValueCountFrequency (%)
0 77
5.2%
1 96
6.4%
2 66
4.4%
3 55
3.7%
4 42
2.8%
5 49
3.3%
6 36
 
2.4%
7 31
 
2.1%
8 30
 
2.0%
9 24
 
1.6%
ValueCountFrequency (%)
64554 1
0.1%
16111 1
0.1%
13975 1
0.1%
6983 1
0.1%
6639 1
0.1%
6599 1
0.1%
5399 1
0.1%
4171 1
0.1%
3542 1
0.1%
3348 1
0.1%

2011
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct356
Distinct (%)25.7%
Missing110
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean242.25487
Minimum0
Maximum71921
Zeros58
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:12.301245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median26
Q393
95-th percentile734.8
Maximum71921
Range71921
Interquartile range (IQR)86

Descriptive statistics

Standard deviation2092.0876
Coefficient of variation (CV)8.6358946
Kurtosis1001.4984
Mean242.25487
Median Absolute Deviation (MAD)24
Skewness29.819987
Sum335523
Variance4376830.3
MonotonicityNot monotonic
2024-04-06T17:26:12.602663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 69
 
4.6%
0 58
 
3.9%
2 52
 
3.5%
3 50
 
3.3%
7 34
 
2.3%
6 34
 
2.3%
8 33
 
2.2%
4 33
 
2.2%
5 32
 
2.1%
10 31
 
2.1%
Other values (346) 959
64.1%
(Missing) 110
 
7.4%
ValueCountFrequency (%)
0 58
3.9%
1 69
4.6%
2 52
3.5%
3 50
3.3%
4 33
2.2%
5 32
2.1%
6 34
2.3%
7 34
2.3%
8 33
2.2%
9 20
 
1.3%
ValueCountFrequency (%)
71921 1
0.1%
15640 1
0.1%
15235 1
0.1%
8166 1
0.1%
7632 1
0.1%
7010 1
0.1%
6357 1
0.1%
5142 1
0.1%
5137 1
0.1%
4582 1
0.1%

2012
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct334
Distinct (%)23.9%
Missing100
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean195.42796
Minimum0
Maximum56726
Zeros49
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:12.908241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median24
Q379
95-th percentile615.2
Maximum56726
Range56726
Interquartile range (IQR)73

Descriptive statistics

Standard deviation1655.8004
Coefficient of variation (CV)8.4726893
Kurtosis981.45492
Mean195.42796
Median Absolute Deviation (MAD)22
Skewness29.423071
Sum272622
Variance2741674.9
MonotonicityNot monotonic
2024-04-06T17:26:13.213775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 70
 
4.7%
2 68
 
4.5%
3 64
 
4.3%
0 49
 
3.3%
5 42
 
2.8%
6 37
 
2.5%
4 36
 
2.4%
8 30
 
2.0%
7 29
 
1.9%
12 29
 
1.9%
Other values (324) 941
62.9%
(Missing) 100
 
6.7%
ValueCountFrequency (%)
0 49
3.3%
1 70
4.7%
2 68
4.5%
3 64
4.3%
4 36
2.4%
5 42
2.8%
6 37
2.5%
7 29
1.9%
8 30
2.0%
9 24
 
1.6%
ValueCountFrequency (%)
56726 1
0.1%
12935 1
0.1%
12922 1
0.1%
6986 1
0.1%
6952 1
0.1%
4791 1
0.1%
4672 1
0.1%
4484 1
0.1%
4236 1
0.1%
3757 1
0.1%

2013
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct345
Distinct (%)24.7%
Missing100
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean225.0552
Minimum0
Maximum67364
Zeros47
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:13.513640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median25
Q387
95-th percentile700.4
Maximum67364
Range67364
Interquartile range (IQR)81

Descriptive statistics

Standard deviation1957.8975
Coefficient of variation (CV)8.6996324
Kurtosis998.30502
Mean225.0552
Median Absolute Deviation (MAD)22
Skewness29.744398
Sum313952
Variance3833362.5
MonotonicityNot monotonic
2024-04-06T17:26:13.820075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 71
 
4.7%
1 61
 
4.1%
5 54
 
3.6%
4 49
 
3.3%
0 47
 
3.1%
3 42
 
2.8%
6 31
 
2.1%
7 30
 
2.0%
11 25
 
1.7%
9 24
 
1.6%
Other values (335) 961
64.3%
(Missing) 100
 
6.7%
ValueCountFrequency (%)
0 47
3.1%
1 61
4.1%
2 71
4.7%
3 42
2.8%
4 49
3.3%
5 54
3.6%
6 31
2.1%
7 30
2.0%
8 22
 
1.5%
9 24
 
1.6%
ValueCountFrequency (%)
67364 1
0.1%
15947 1
0.1%
13593 1
0.1%
7830 1
0.1%
7427 1
0.1%
6627 1
0.1%
6221 1
0.1%
5622 1
0.1%
5576 1
0.1%
3797 1
0.1%

2014
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct388
Distinct (%)27.1%
Missing65
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean275.48392
Minimum0
Maximum84744
Zeros37
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:14.123623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18
median33
Q3107.75
95-th percentile848.2
Maximum84744
Range84744
Interquartile range (IQR)99.75

Descriptive statistics

Standard deviation2424.9685
Coefficient of variation (CV)8.8025776
Kurtosis1035.8578
Mean275.48392
Median Absolute Deviation (MAD)30
Skewness30.32624
Sum393942
Variance5880472.5
MonotonicityNot monotonic
2024-04-06T17:26:14.409433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 66
 
4.4%
1 62
 
4.1%
2 47
 
3.1%
5 42
 
2.8%
0 37
 
2.5%
6 36
 
2.4%
9 36
 
2.4%
4 34
 
2.3%
7 27
 
1.8%
20 22
 
1.5%
Other values (378) 1021
68.3%
(Missing) 65
 
4.3%
ValueCountFrequency (%)
0 37
2.5%
1 62
4.1%
2 47
3.1%
3 66
4.4%
4 34
2.3%
5 42
2.8%
6 36
2.4%
7 27
1.8%
8 21
 
1.4%
9 36
2.4%
ValueCountFrequency (%)
84744 1
0.1%
18513 1
0.1%
16370 1
0.1%
10656 1
0.1%
9720 1
0.1%
9171 1
0.1%
8048 1
0.1%
7510 1
0.1%
6348 1
0.1%
4905 1
0.1%

2015
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct419
Distinct (%)29.7%
Missing85
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean328.31418
Minimum0
Maximum93129
Zeros33
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:14.725944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median42
Q3143
95-th percentile920.4
Maximum93129
Range93129
Interquartile range (IQR)134

Descriptive statistics

Standard deviation2740.1913
Coefficient of variation (CV)8.3462472
Kurtosis942.05247
Mean328.31418
Median Absolute Deviation (MAD)38
Skewness28.653142
Sum462923
Variance7508648.6
MonotonicityNot monotonic
2024-04-06T17:26:15.046399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 59
 
3.9%
2 57
 
3.8%
4 51
 
3.4%
3 39
 
2.6%
0 33
 
2.2%
10 29
 
1.9%
5 28
 
1.9%
9 28
 
1.9%
8 28
 
1.9%
7 23
 
1.5%
Other values (409) 1035
69.2%
(Missing) 85
 
5.7%
ValueCountFrequency (%)
0 33
2.2%
1 59
3.9%
2 57
3.8%
3 39
2.6%
4 51
3.4%
5 28
1.9%
6 22
 
1.5%
7 23
 
1.5%
8 28
1.9%
9 28
1.9%
ValueCountFrequency (%)
93129 1
0.1%
23581 1
0.1%
21611 1
0.1%
13634 1
0.1%
13501 1
0.1%
12168 1
0.1%
9088 1
0.1%
6977 1
0.1%
5358 1
0.1%
5291 1
0.1%

2016
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct407
Distinct (%)28.9%
Missing85
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean299.18227
Minimum0
Maximum85703
Zeros27
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:15.430789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18
median39
Q3131
95-th percentile861.3
Maximum85703
Range85703
Interquartile range (IQR)123

Descriptive statistics

Standard deviation2530.1786
Coefficient of variation (CV)8.4569803
Kurtosis931.14391
Mean299.18227
Median Absolute Deviation (MAD)36
Skewness28.493218
Sum421847
Variance6401803.6
MonotonicityNot monotonic
2024-04-06T17:26:15.725049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 65
 
4.3%
2 53
 
3.5%
3 49
 
3.3%
4 49
 
3.3%
5 36
 
2.4%
6 35
 
2.3%
10 31
 
2.1%
0 27
 
1.8%
9 24
 
1.6%
12 22
 
1.5%
Other values (397) 1019
68.2%
(Missing) 85
 
5.7%
ValueCountFrequency (%)
0 27
1.8%
1 65
4.3%
2 53
3.5%
3 49
3.3%
4 49
3.3%
5 36
2.4%
6 35
2.3%
7 19
 
1.3%
8 21
 
1.4%
9 24
 
1.6%
ValueCountFrequency (%)
85703 1
0.1%
24006 1
0.1%
19322 1
0.1%
12553 1
0.1%
12228 1
0.1%
11925 1
0.1%
7752 1
0.1%
5858 1
0.1%
4842 1
0.1%
4270 1
0.1%

2017
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct395
Distinct (%)28.3%
Missing100
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean320.30108
Minimum0
Maximum97813
Zeros61
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:15.993832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median31
Q3128.5
95-th percentile979.5
Maximum97813
Range97813
Interquartile range (IQR)121.5

Descriptive statistics

Standard deviation2887.0558
Coefficient of variation (CV)9.0135689
Kurtosis944.5667
Mean320.30108
Median Absolute Deviation (MAD)29
Skewness28.895193
Sum446820
Variance8335091.3
MonotonicityNot monotonic
2024-04-06T17:26:16.316961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 77
 
5.2%
0 61
 
4.1%
3 53
 
3.5%
2 46
 
3.1%
4 38
 
2.5%
5 36
 
2.4%
6 32
 
2.1%
9 32
 
2.1%
7 31
 
2.1%
8 27
 
1.8%
Other values (385) 962
64.3%
(Missing) 100
 
6.7%
ValueCountFrequency (%)
0 61
4.1%
1 77
5.2%
2 46
3.1%
3 53
3.5%
4 38
2.5%
5 36
2.4%
6 32
2.1%
7 31
2.1%
8 27
 
1.8%
9 32
2.1%
ValueCountFrequency (%)
97813 1
0.1%
29506 1
0.1%
22876 1
0.1%
12772 1
0.1%
11744 1
0.1%
7242 1
0.1%
7039 1
0.1%
5889 1
0.1%
5059 1
0.1%
4596 1
0.1%

2018
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct383
Distinct (%)27.4%
Missing95
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean310.585
Minimum0
Maximum100424
Zeros64
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:16.627664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median27
Q3111.25
95-th percentile900.95
Maximum100424
Range100424
Interquartile range (IQR)106.25

Descriptive statistics

Standard deviation2959.5072
Coefficient of variation (CV)9.5288156
Kurtosis951.76486
Mean310.585
Median Absolute Deviation (MAD)25
Skewness29.142236
Sum434819
Variance8758682.8
MonotonicityNot monotonic
2024-04-06T17:26:16.927555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 85
 
5.7%
2 69
 
4.6%
0 64
 
4.3%
4 58
 
3.9%
3 55
 
3.7%
7 36
 
2.4%
5 26
 
1.7%
6 25
 
1.7%
11 23
 
1.5%
8 22
 
1.5%
Other values (373) 937
62.7%
(Missing) 95
 
6.4%
ValueCountFrequency (%)
0 64
4.3%
1 85
5.7%
2 69
4.6%
3 55
3.7%
4 58
3.9%
5 26
 
1.7%
6 25
 
1.7%
7 36
2.4%
8 22
 
1.5%
9 21
 
1.4%
ValueCountFrequency (%)
100424 1
0.1%
34634 1
0.1%
20247 1
0.1%
11979 1
0.1%
9534 1
0.1%
6118 1
0.1%
5814 1
0.1%
5015 1
0.1%
4706 1
0.1%
4517 1
0.1%

2019
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct362
Distinct (%)25.9%
Missing100
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean281.35484
Minimum0
Maximum92125
Zeros37
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:17.243137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median28
Q390.5
95-th percentile863.6
Maximum92125
Range92125
Interquartile range (IQR)84.5

Descriptive statistics

Standard deviation2687.8191
Coefficient of variation (CV)9.5531292
Kurtosis990.54276
Mean281.35484
Median Absolute Deviation (MAD)25
Skewness29.820423
Sum392490
Variance7224371.7
MonotonicityNot monotonic
2024-04-06T17:26:17.635313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 76
 
5.1%
2 73
 
4.9%
3 60
 
4.0%
4 45
 
3.0%
5 39
 
2.6%
0 37
 
2.5%
7 33
 
2.2%
6 31
 
2.1%
9 25
 
1.7%
8 25
 
1.7%
Other values (352) 951
63.6%
(Missing) 100
 
6.7%
ValueCountFrequency (%)
0 37
2.5%
1 76
5.1%
2 73
4.9%
3 60
4.0%
4 45
3.0%
5 39
2.6%
6 31
2.1%
7 33
2.2%
8 25
 
1.7%
9 25
 
1.7%
ValueCountFrequency (%)
92125 1
0.1%
29838 1
0.1%
14452 1
0.1%
9460 1
0.1%
8196 1
0.1%
6881 1
0.1%
6855 1
0.1%
6244 1
0.1%
5306 1
0.1%
5293 1
0.1%

2020
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct395
Distinct (%)28.3%
Missing100
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean361.21792
Minimum0
Maximum118377
Zeros35
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:17.928184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18
median35
Q3118
95-th percentile1123.7
Maximum118377
Range118377
Interquartile range (IQR)110

Descriptive statistics

Standard deviation3437.7547
Coefficient of variation (CV)9.5171211
Kurtosis1006.9035
Mean361.21792
Median Absolute Deviation (MAD)32
Skewness30.081936
Sum503899
Variance11818157
MonotonicityNot monotonic
2024-04-06T17:26:18.647108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 72
 
4.8%
2 57
 
3.8%
3 46
 
3.1%
4 39
 
2.6%
6 38
 
2.5%
0 35
 
2.3%
5 33
 
2.2%
8 27
 
1.8%
7 24
 
1.6%
10 23
 
1.5%
Other values (385) 1001
67.0%
(Missing) 100
 
6.7%
ValueCountFrequency (%)
0 35
2.3%
1 72
4.8%
2 57
3.8%
3 46
3.1%
4 39
2.6%
5 33
2.2%
6 38
2.5%
7 24
 
1.6%
8 27
 
1.8%
9 21
 
1.4%
ValueCountFrequency (%)
118377 1
0.1%
36191 1
0.1%
18245 1
0.1%
11523 1
0.1%
10355 1
0.1%
10167 1
0.1%
9109 1
0.1%
7917 1
0.1%
7833 1
0.1%
7101 1
0.1%

2021
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct373
Distinct (%)26.7%
Missing100
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean281.44301
Minimum0
Maximum84859
Zeros30
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:18.939090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18
median35
Q3109
95-th percentile841.9
Maximum84859
Range84859
Interquartile range (IQR)101

Descriptive statistics

Standard deviation2480.93
Coefficient of variation (CV)8.8150349
Kurtosis977.78455
Mean281.44301
Median Absolute Deviation (MAD)31
Skewness29.438031
Sum392613
Variance6155013.5
MonotonicityNot monotonic
2024-04-06T17:26:19.217455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 76
 
5.1%
2 51
 
3.4%
3 44
 
2.9%
7 41
 
2.7%
6 35
 
2.3%
5 31
 
2.1%
0 30
 
2.0%
9 28
 
1.9%
4 27
 
1.8%
13 26
 
1.7%
Other values (363) 1006
67.3%
(Missing) 100
 
6.7%
ValueCountFrequency (%)
0 30
 
2.0%
1 76
5.1%
2 51
3.4%
3 44
2.9%
4 27
 
1.8%
5 31
2.1%
6 35
2.3%
7 41
2.7%
8 24
 
1.6%
9 28
 
1.9%
ValueCountFrequency (%)
84859 1
0.1%
23565 1
0.1%
17401 1
0.1%
10900 1
0.1%
7147 1
0.1%
7140 1
0.1%
6611 1
0.1%
6290 1
0.1%
5793 1
0.1%
5353 1
0.1%

2022
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct302
Distinct (%)21.6%
Missing100
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean163.46882
Minimum0
Maximum46640
Zeros35
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:19.495584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median22
Q367.5
95-th percentile455.5
Maximum46640
Range46640
Interquartile range (IQR)62.5

Descriptive statistics

Standard deviation1374.1201
Coefficient of variation (CV)8.4060073
Kurtosis947.60599
Mean163.46882
Median Absolute Deviation (MAD)19
Skewness28.82329
Sum228039
Variance1888206
MonotonicityNot monotonic
2024-04-06T17:26:19.777225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 84
 
5.6%
2 70
 
4.7%
3 59
 
3.9%
4 52
 
3.5%
5 51
 
3.4%
6 43
 
2.9%
7 38
 
2.5%
0 35
 
2.3%
9 33
 
2.2%
10 29
 
1.9%
Other values (292) 901
60.3%
(Missing) 100
 
6.7%
ValueCountFrequency (%)
0 35
2.3%
1 84
5.6%
2 70
4.7%
3 59
3.9%
4 52
3.5%
5 51
3.4%
6 43
2.9%
7 38
2.5%
8 25
 
1.7%
9 33
 
2.2%
ValueCountFrequency (%)
46640 1
0.1%
11986 1
0.1%
11409 1
0.1%
6546 1
0.1%
4695 1
0.1%
4098 1
0.1%
3612 1
0.1%
3329 1
0.1%
3137 1
0.1%
2709 1
0.1%

2023
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct289
Distinct (%)20.6%
Missing95
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean161.73429
Minimum0
Maximum54437
Zeros56
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2024-04-06T17:26:20.097678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median15
Q351
95-th percentile502.15
Maximum54437
Range54437
Interquartile range (IQR)47

Descriptive statistics

Standard deviation1561.1711
Coefficient of variation (CV)9.6526912
Kurtosis1051.4329
Mean161.73429
Median Absolute Deviation (MAD)13
Skewness30.822812
Sum226428
Variance2437255.2
MonotonicityNot monotonic
2024-04-06T17:26:20.399602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 103
 
6.9%
2 82
 
5.5%
3 71
 
4.7%
4 63
 
4.2%
0 56
 
3.7%
6 53
 
3.5%
5 41
 
2.7%
8 41
 
2.7%
7 38
 
2.5%
11 29
 
1.9%
Other values (279) 823
55.1%
(Missing) 95
 
6.4%
ValueCountFrequency (%)
0 56
3.7%
1 103
6.9%
2 82
5.5%
3 71
4.7%
4 63
4.2%
5 41
 
2.7%
6 53
3.5%
7 38
 
2.5%
8 41
 
2.7%
9 26
 
1.7%
ValueCountFrequency (%)
54437 1
0.1%
14379 1
0.1%
8409 1
0.1%
5685 1
0.1%
4110 1
0.1%
3962 1
0.1%
3730 1
0.1%
3532 1
0.1%
3199 1
0.1%
2855 1
0.1%

Interactions

2024-04-06T17:26:01.338632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:51.483131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:55.308233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:59.158504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:03.179965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:07.076303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:10.533745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:15.001268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:19.259559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:23.683699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:28.377213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:32.413034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:36.246054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:39.743712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:43.443017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:47.541603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:51.726411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:55.350633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:01.577292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:51.662927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:55.544263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:59.340525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:03.429232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:07.286983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:10.719260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:15.204332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:19.440581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:23.840612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:28.628875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:32.599929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:36.422722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:39.909415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:43.618161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:47.720691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:51.903135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:55.545722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:01.763894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:51.907981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:55.845982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:59.549547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:03.690389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:07.485692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:10.906845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:15.407941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:19.711451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:24.029030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:28.843445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:32.793500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:36.691473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:40.089533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:44.195014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:47.927489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:52.078483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:55.763796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:01.972466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:52.108166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:56.034153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:59.717182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:03.894802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:07.691089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:11.089038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:15.631330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:19.956781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:24.192295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:29.051710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:32.991569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:36.942692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:40.300350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:44.431844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:48.109166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:52.276118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:56.001551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:02.273980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:52.311923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:56.230065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:59.952793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:04.111911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:07.897188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:11.303085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:15.946234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:20.218632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:24.390725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:29.258979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:33.196635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:37.126793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:40.521646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:44.637494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:48.371353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:52.480122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:56.249614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:02.546007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:52.537055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:56.428230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:00.119446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:04.318054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:08.083736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:11.535348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:16.145298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:20.688897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:24.585543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:29.458740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:33.372004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:37.314571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:40.760800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:44.814933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:48.619043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:52.646690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:56.565696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:02.761505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:52.904670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:56.677324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:00.404272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:04.526810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:08.299906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:11.743701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:16.395477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:20.933269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:24.814408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:30.181306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:33.568427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:37.519938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:40.994324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:45.006816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:48.852115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:52.838996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:56.846771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:03.027595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:53.136279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:56.868238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:00.582887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:04.729758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:08.499516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:11.935522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:16.603633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:21.154921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:25.080108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:30.360758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:33.832441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:37.712382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:41.195330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:45.180859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:49.022620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:53.040930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:57.258428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:03.347138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:53.387743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:57.065052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:00.783169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:04.976130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:08.725577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:12.125796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:16.862887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:21.405819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:25.330899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:30.561874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:34.110483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:37.917823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:41.391783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:45.375243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:49.288865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:53.257458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:57.533848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:03.586864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:53.659781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:57.246217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:00.963296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:05.171551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:08.909335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:12.315847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:17.083444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:21.620651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:25.517533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:30.746289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:34.373631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:38.094915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:41.617491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:45.553334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:49.481672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:53.485714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:57.730537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:03.811342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:53.828966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:57.417713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:01.136270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:05.403935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:09.069262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:12.597867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:17.287477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:21.851022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:25.839336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:30.935904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:34.649276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:38.279673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:41.781933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:45.756198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:49.696570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:53.620901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:57.925457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:04.089001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:54.007710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:57.594877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:01.313185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:05.656124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:09.282331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:13.045193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:17.521481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:22.079983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:26.127189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:31.094509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:34.924380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:38.452744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:42.095226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:45.980893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:49.967588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:53.776838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:58.091958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:04.346783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:54.176882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:57.770347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:01.498693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:05.919511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:09.447812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:13.320595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:17.828789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:22.381077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:26.516950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:31.263162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:35.203295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:38.634711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:42.309119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:46.172289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:50.178997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:53.938356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:58.298214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:04.575118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:54.359363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:58.022555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:02.056421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:06.116948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:09.615950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:13.536577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:18.010334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:22.683526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:26.864852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:31.435719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:35.398651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:38.818361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:42.500524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:46.355597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:50.421676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:54.113065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:58.916528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:04.759181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:54.547992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:58.374805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:02.219563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:06.308078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:09.785321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:13.775651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:18.296971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:22.888509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:27.409347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:31.604629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:35.582202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:38.991958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:42.688084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:46.569076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:50.779117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:54.273875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:59.095439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:04.955983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:54.738991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:58.594261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:02.426412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:06.510976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:09.969967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:13.996759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:18.530597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:23.157760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:27.731515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:31.811755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:35.756097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:39.186944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:42.888945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:46.814717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:51.105817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:54.468426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:59.707836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:05.210206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:54.900231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:58.814712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:02.740086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:06.689085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:10.133797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:14.194954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:18.801698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:23.338890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:27.965971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:32.025851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:35.915478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:39.367320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:43.059986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:47.008363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:51.349118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:54.851753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:00.288505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:05.427766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:55.089432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:58.986952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:02.970234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:06.853897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:10.318475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:14.808490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:19.036798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:23.506649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:28.189076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:32.216105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:36.063481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:39.563235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:43.261535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:47.230057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:51.542029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:55.065789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:00.935368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:26:20.703994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0001.0001.0000.9380.8640.8750.8750.8750.9380.9270.9271.0000.9980.9381.0000.9070.8750.938
20071.0001.0001.0000.9820.9880.9900.9900.9900.9860.9980.9981.0000.9070.9820.9820.9960.9900.982
20081.0001.0001.0000.9820.9880.9900.9900.9900.9860.9980.9981.0000.9070.9820.9820.9960.9900.982
20090.9380.9820.9821.0000.9690.9690.9690.9690.9960.9780.9780.9381.0001.0000.9960.9690.9691.000
20100.8640.9880.9880.9691.0000.9880.9880.9880.9670.9860.9860.8640.8410.9690.9820.9930.9880.969
20110.8750.9900.9900.9690.9881.0001.0001.0000.9860.9980.9980.8750.8410.9690.9820.9961.0000.969
20120.8750.9900.9900.9690.9881.0001.0001.0000.9860.9980.9980.8750.8410.9690.9820.9961.0000.969
20130.8750.9900.9900.9690.9881.0001.0001.0000.9860.9980.9980.8750.8410.9690.9820.9961.0000.969
20140.9380.9860.9860.9960.9670.9860.9860.9861.0000.9940.9940.9380.9070.9960.9900.9760.9860.996
20150.9270.9980.9980.9780.9860.9980.9980.9980.9941.0001.0000.9270.8860.9780.9820.9930.9980.978
20160.9270.9980.9980.9780.9860.9980.9980.9980.9941.0001.0000.9270.8860.9780.9820.9930.9980.978
20171.0001.0001.0000.9380.8640.8750.8750.8750.9380.9270.9271.0000.9980.9381.0000.9070.8750.938
20180.9980.9070.9071.0000.8410.8410.8410.8410.9070.8860.8860.9981.0001.0001.0000.8410.8411.000
20190.9380.9820.9821.0000.9690.9690.9690.9690.9960.9780.9780.9381.0001.0000.9960.9690.9691.000
20201.0000.9820.9820.9960.9820.9820.9820.9820.9900.9820.9821.0001.0000.9961.0000.9820.9820.996
20210.9070.9960.9960.9690.9930.9960.9960.9960.9760.9930.9930.9070.8410.9690.9821.0000.9960.969
20220.8750.9900.9900.9690.9881.0001.0001.0000.9860.9980.9980.8750.8410.9690.9820.9961.0000.969
20230.9380.9820.9821.0000.9690.9690.9690.9690.9960.9780.9780.9381.0001.0000.9960.9690.9691.000
2024-04-06T17:26:21.106734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.9690.9550.9490.9290.9070.8880.8950.8920.9120.9120.9360.9330.9120.9200.9050.8740.870
20070.9691.0000.9800.9650.9510.9300.9170.9180.9150.9270.9270.9440.9390.9250.9300.9290.9090.902
20080.9550.9801.0000.9740.9600.9410.9280.9270.9240.9340.9320.9460.9420.9320.9380.9370.9200.914
20090.9490.9650.9741.0000.9740.9580.9440.9430.9390.9460.9420.9570.9520.9420.9470.9440.9310.930
20100.9290.9510.9600.9741.0000.9670.9560.9540.9440.9460.9400.9530.9450.9430.9450.9460.9380.933
20110.9070.9300.9410.9580.9671.0000.9780.9740.9680.9630.9530.9360.9200.9430.9480.9460.9350.924
20120.8880.9170.9280.9440.9560.9781.0000.9760.9640.9520.9430.9230.9070.9370.9420.9460.9380.927
20130.8950.9180.9270.9430.9540.9740.9761.0000.9700.9630.9530.9320.9160.9450.9480.9480.9380.929
20140.8920.9150.9240.9390.9440.9680.9640.9701.0000.9680.9590.9290.9130.9430.9460.9460.9350.922
20150.9120.9270.9340.9460.9460.9630.9520.9630.9681.0000.9770.9460.9290.9540.9550.9500.9310.920
20160.9120.9270.9320.9420.9400.9530.9430.9530.9590.9771.0000.9540.9350.9590.9580.9530.9340.922
20170.9360.9440.9460.9570.9530.9360.9230.9320.9290.9460.9541.0000.9780.9570.9550.9500.9320.932
20180.9330.9390.9420.9520.9450.9200.9070.9160.9130.9290.9350.9781.0000.9630.9570.9520.9340.936
20190.9120.9250.9320.9420.9430.9430.9370.9450.9430.9540.9590.9570.9631.0000.9790.9690.9510.947
20200.9200.9300.9380.9470.9450.9480.9420.9480.9460.9550.9580.9550.9570.9791.0000.9780.9520.946
20210.9050.9290.9370.9440.9460.9460.9460.9480.9460.9500.9530.9500.9520.9690.9781.0000.9700.960
20220.8740.9090.9200.9310.9380.9350.9380.9380.9350.9310.9340.9320.9340.9510.9520.9701.0000.970
20230.8700.9020.9140.9300.9330.9240.9270.9290.9220.9200.9220.9320.9360.9470.9460.9600.9701.000

Missing values

2024-04-06T17:26:05.726742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:26:06.240944image/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.
2024-04-06T17:26:06.689705image/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 주택유형200620072008200920102011201220132014201520162017201820192020202120222023
0전국 /단독주택18717141561332113176139751523512922135931637021611193222287620247144521824517401119868409
1전국 /다가구주택566253314928435541718166698678301065613501119254596348062447917714046952855
2전국 /다세대주택108119958970868106639763269527427917113634125531174495348196103551090065464110
3전국 /연립주택373928822606206118312263195621152493308830273349271923423324309019381458
4전국 /아파트83554655206256968305645547192156726673648474493129857039781310042492125118377848594664054437
5서울 /단독주택37372466218717361452187412641401189029542921303332772004259919671150586
6서울 /다가구주택213615241349928667917755906121123682113961878100813081143675348
7서울 /다세대주택421333153066214215971924182419672418502141953753318224473299314617171152
8서울 /연립주택1404894731503352406296343500735717670612481643483273210
9서울 /아파트143307077665983355399635744846627972012168122281277211979946011523661125215685
지역 및 주택유형200620072008200920102011201220132014201520162017201820192020202120222023
1485제주 제주시/단독주택88142145166164228220274333430406362354288283319243185
1486제주 제주시/다가구주택101912122638506080808616214246553721
1487제주 제주시/다세대주택27545355751059815212714319719313712011212611978
1488제주 제주시/연립주택205749536493901049410815617317112314314016099
1489제주 제주시/아파트157224172183363363356357392335297350300230256343240170
1490제주 서귀포시/단독주택3157506267787910713617817316615510512413111287
1491제주 서귀포시/다가구주택242436101729555114122416282016
1492제주 서귀포시/다세대주택61212151613141626324341482730292726
1493제주 서귀포시/연립주택111920253336392557989710585677211610766
1494제주 서귀포시/아파트13406438376657102102273270160112841081468267