Overview

Dataset statistics

Number of variables19
Number of observations2392
Missing cells2920
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory397.2 KiB
Average record size in memory170.1 B

Variable types

Text1
Numeric18

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산거래현황 중 토지 거래현황의 연도별 거래규모별(필지수) 데이터입니다.- (단위 : 필지수)- 공표시기 : 익월 말일경
Author한국부동산원
URLhttps://www.data.go.kr/data/15068566/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 176 (7.4%) missing valuesMissing
2007 has 216 (9.0%) missing valuesMissing
2008 has 200 (8.4%) missing valuesMissing
2009 has 200 (8.4%) missing valuesMissing
2010 has 152 (6.4%) missing valuesMissing
2011 has 176 (7.4%) missing valuesMissing
2012 has 160 (6.7%) missing valuesMissing
2013 has 160 (6.7%) missing valuesMissing
2014 has 104 (4.3%) missing valuesMissing
2015 has 136 (5.7%) missing valuesMissing
2016 has 136 (5.7%) missing valuesMissing
2017 has 160 (6.7%) missing valuesMissing
2018 has 152 (6.4%) missing valuesMissing
2019 has 160 (6.7%) missing valuesMissing
2020 has 160 (6.7%) missing valuesMissing
2021 has 160 (6.7%) missing valuesMissing
2022 has 160 (6.7%) missing valuesMissing
2023 has 152 (6.4%) missing valuesMissing
2006 is highly skewed (γ1 = 37.76081039)Skewed
2007 is highly skewed (γ1 = 37.92643067)Skewed
2008 is highly skewed (γ1 = 38.53630616)Skewed
2009 is highly skewed (γ1 = 38.43453154)Skewed
2010 is highly skewed (γ1 = 39.32795521)Skewed
2011 is highly skewed (γ1 = 39.66049952)Skewed
2012 is highly skewed (γ1 = 39.59430574)Skewed
2013 is highly skewed (γ1 = 39.74403681)Skewed
2014 is highly skewed (γ1 = 40.31705649)Skewed
2015 is highly skewed (γ1 = 39.72154091)Skewed
2016 is highly skewed (γ1 = 39.31087335)Skewed
2017 is highly skewed (γ1 = 39.04431228)Skewed
2018 is highly skewed (γ1 = 38.70576513)Skewed
2019 is highly skewed (γ1 = 38.83470798)Skewed
2020 is highly skewed (γ1 = 39.10521273)Skewed
2021 is highly skewed (γ1 = 38.87280179)Skewed
2022 is highly skewed (γ1 = 38.79044211)Skewed
2023 is highly skewed (γ1 = 39.3361107)Skewed
지역_거래규모 has unique valuesUnique
2007 has 31 (1.3%) zerosZeros
2008 has 51 (2.1%) zerosZeros
2009 has 58 (2.4%) zerosZeros
2010 has 63 (2.6%) zerosZeros
2011 has 72 (3.0%) zerosZeros
2012 has 64 (2.7%) zerosZeros
2013 has 64 (2.7%) zerosZeros
2014 has 71 (3.0%) zerosZeros
2015 has 55 (2.3%) zerosZeros
2016 has 59 (2.5%) zerosZeros
2017 has 60 (2.5%) zerosZeros
2018 has 50 (2.1%) zerosZeros
2019 has 58 (2.4%) zerosZeros
2020 has 65 (2.7%) zerosZeros
2021 has 49 (2.0%) zerosZeros
2022 has 58 (2.4%) zerosZeros
2023 has 79 (3.3%) zerosZeros

Reproduction

Analysis started2024-04-06 08:28:00.127354
Analysis finished2024-04-06 08:29:24.638294
Duration1 minute and 24.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역_거래규모
Text

UNIQUE 

Distinct2392
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.8 KiB
2024-04-06T17:29:24.940515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length17.874582
Min length9

Characters and Unicode

Total characters42756
Distinct characters157
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2392 ?
Unique (%)100.0%

Sample

1st row전국_330㎡이하
2nd row전국_331~660㎡
3rd row전국_661~1,000㎡
4th row전국_1,001~2,000㎡
5th row전국_2,001~5,000㎡
ValueCountFrequency (%)
경기 416
 
8.5%
경남 208
 
4.2%
서울 200
 
4.1%
경북 200
 
4.1%
전남 176
 
3.6%
충남 152
 
3.1%
충북 152
 
3.1%
강원 144
 
2.9%
부산 128
 
2.6%
전북 128
 
2.6%
Other values (2210) 3000
61.2%
2024-04-06T17:29:25.657748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8970
21.0%
1 2990
 
7.0%
, 2950
 
6.9%
2512
 
5.9%
_ 2392
 
5.6%
3 2392
 
5.6%
2392
 
5.6%
~ 1794
 
4.2%
6 1196
 
2.8%
1128
 
2.6%
Other values (147) 14040
32.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16744
39.2%
Other Letter 13668
32.0%
Other Punctuation 2950
 
6.9%
Space Separator 2512
 
5.9%
Connector Punctuation 2392
 
5.6%
Other Symbol 2392
 
5.6%
Math Symbol 1794
 
4.2%
Close Punctuation 152
 
0.4%
Open Punctuation 152
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1128
 
8.3%
976
 
7.1%
872
 
6.4%
744
 
5.4%
712
 
5.2%
576
 
4.2%
448
 
3.3%
400
 
2.9%
384
 
2.8%
376
 
2.8%
Other values (134) 7052
51.6%
Decimal Number
ValueCountFrequency (%)
0 8970
53.6%
1 2990
 
17.9%
3 2392
 
14.3%
6 1196
 
7.1%
5 598
 
3.6%
2 598
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 2950
100.0%
Space Separator
ValueCountFrequency (%)
2512
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2392
100.0%
Other Symbol
ValueCountFrequency (%)
2392
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1794
100.0%
Close Punctuation
ValueCountFrequency (%)
) 152
100.0%
Open Punctuation
ValueCountFrequency (%)
( 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29088
68.0%
Hangul 13668
32.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1128
 
8.3%
976
 
7.1%
872
 
6.4%
744
 
5.4%
712
 
5.2%
576
 
4.2%
448
 
3.3%
400
 
2.9%
384
 
2.8%
376
 
2.8%
Other values (134) 7052
51.6%
Common
ValueCountFrequency (%)
0 8970
30.8%
1 2990
 
10.3%
, 2950
 
10.1%
2512
 
8.6%
_ 2392
 
8.2%
3 2392
 
8.2%
2392
 
8.2%
~ 1794
 
6.2%
6 1196
 
4.1%
5 598
 
2.1%
Other values (3) 902
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26696
62.4%
Hangul 13668
32.0%
CJK Compat 2392
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8970
33.6%
1 2990
 
11.2%
, 2950
 
11.1%
2512
 
9.4%
_ 2392
 
9.0%
3 2392
 
9.0%
~ 1794
 
6.7%
6 1196
 
4.5%
5 598
 
2.2%
2 598
 
2.2%
Other values (2) 304
 
1.1%
CJK Compat
ValueCountFrequency (%)
2392
100.0%
Hangul
ValueCountFrequency (%)
1128
 
8.3%
976
 
7.1%
872
 
6.4%
744
 
5.4%
712
 
5.2%
576
 
4.2%
448
 
3.3%
400
 
2.9%
384
 
2.8%
376
 
2.8%
Other values (134) 7052
51.6%

2006
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct1175
Distinct (%)53.0%
Missing176
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean3734.2464
Minimum0
Maximum1918420
Zeros23
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:25.951974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q166
median289.5
Q31054.5
95-th percentile13334
Maximum1918420
Range1918420
Interquartile range (IQR)988.5

Descriptive statistics

Standard deviation44311.467
Coefficient of variation (CV)11.866241
Kurtosis1589.1938
Mean3734.2464
Median Absolute Deviation (MAD)271.5
Skewness37.76081
Sum8275090
Variance1.9635061 × 109
MonotonicityNot monotonic
2024-04-06T17:29:26.228200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 26
 
1.1%
0 23
 
1.0%
1 19
 
0.8%
9 18
 
0.8%
6 17
 
0.7%
5 16
 
0.7%
13 15
 
0.6%
3 15
 
0.6%
17 15
 
0.6%
15 14
 
0.6%
Other values (1165) 2038
85.2%
(Missing) 176
 
7.4%
ValueCountFrequency (%)
0 23
1.0%
1 19
0.8%
2 26
1.1%
3 15
0.6%
4 13
0.5%
5 16
0.7%
6 17
0.7%
7 14
0.6%
8 8
 
0.3%
9 18
0.8%
ValueCountFrequency (%)
1918420 1
< 0.1%
559072 1
< 0.1%
387889 1
< 0.1%
189099 1
< 0.1%
179394 1
< 0.1%
151262 1
< 0.1%
120899 1
< 0.1%
116369 1
< 0.1%
111980 1
< 0.1%
101619 1
< 0.1%

2007
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1113
Distinct (%)51.1%
Missing216
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean3201.0813
Minimum0
Maximum1599022
Zeros31
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:26.513184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q150
median228.5
Q3993.25
95-th percentile10473.75
Maximum1599022
Range1599022
Interquartile range (IQR)943.25

Descriptive statistics

Standard deviation36997.005
Coefficient of variation (CV)11.557659
Kurtosis1602.0844
Mean3201.0813
Median Absolute Deviation (MAD)219.5
Skewness37.926431
Sum6965553
Variance1.3687784 × 109
MonotonicityNot monotonic
2024-04-06T17:29:26.855155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31
 
1.3%
1 30
 
1.3%
2 30
 
1.3%
5 25
 
1.0%
6 23
 
1.0%
14 23
 
1.0%
3 22
 
0.9%
10 19
 
0.8%
9 17
 
0.7%
4 17
 
0.7%
Other values (1103) 1939
81.1%
(Missing) 216
 
9.0%
ValueCountFrequency (%)
0 31
1.3%
1 30
1.3%
2 30
1.3%
3 22
0.9%
4 17
0.7%
5 25
1.0%
6 23
1.0%
7 6
 
0.3%
8 16
0.7%
9 17
0.7%
ValueCountFrequency (%)
1599022 1
< 0.1%
417151 1
< 0.1%
274262 1
< 0.1%
177053 1
< 0.1%
162416 1
< 0.1%
132335 1
< 0.1%
130690 1
< 0.1%
110543 1
< 0.1%
108579 1
< 0.1%
88043 1
< 0.1%

2008
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1100
Distinct (%)50.2%
Missing200
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean3242.5201
Minimum0
Maximum1644034
Zeros51
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:27.130561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q141
median208.5
Q31025.25
95-th percentile10133.6
Maximum1644034
Range1644034
Interquartile range (IQR)984.25

Descriptive statistics

Standard deviation37685.607
Coefficient of variation (CV)11.62232
Kurtosis1648.5453
Mean3242.5201
Median Absolute Deviation (MAD)203.5
Skewness38.536306
Sum7107604
Variance1.420205 × 109
MonotonicityNot monotonic
2024-04-06T17:29:27.429263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 51
 
2.1%
2 44
 
1.8%
1 37
 
1.5%
7 27
 
1.1%
6 24
 
1.0%
4 22
 
0.9%
3 21
 
0.9%
5 21
 
0.9%
8 20
 
0.8%
9 19
 
0.8%
Other values (1090) 1906
79.7%
(Missing) 200
 
8.4%
ValueCountFrequency (%)
0 51
2.1%
1 37
1.5%
2 44
1.8%
3 21
0.9%
4 22
0.9%
5 21
0.9%
6 24
1.0%
7 27
1.1%
8 20
 
0.8%
9 19
 
0.8%
ValueCountFrequency (%)
1644034 1
< 0.1%
395421 1
< 0.1%
257363 1
< 0.1%
180120 1
< 0.1%
163553 1
< 0.1%
134206 1
< 0.1%
132390 1
< 0.1%
127224 1
< 0.1%
110815 1
< 0.1%
96678 1
< 0.1%

2009
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1121
Distinct (%)51.1%
Missing200
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean3181.4375
Minimum0
Maximum1597903
Zeros58
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:27.697390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q138
median211
Q31026
95-th percentile10545.7
Maximum1597903
Range1597903
Interquartile range (IQR)988

Descriptive statistics

Standard deviation36676.635
Coefficient of variation (CV)11.528322
Kurtosis1640.6324
Mean3181.4375
Median Absolute Deviation (MAD)207
Skewness38.434532
Sum6973711
Variance1.3451756 × 109
MonotonicityNot monotonic
2024-04-06T17:29:28.088281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
 
2.4%
1 44
 
1.8%
2 40
 
1.7%
4 30
 
1.3%
6 23
 
1.0%
7 23
 
1.0%
8 22
 
0.9%
3 22
 
0.9%
11 20
 
0.8%
5 19
 
0.8%
Other values (1111) 1891
79.1%
(Missing) 200
 
8.4%
ValueCountFrequency (%)
0 58
2.4%
1 44
1.8%
2 40
1.7%
3 22
 
0.9%
4 30
1.3%
5 19
 
0.8%
6 23
 
1.0%
7 23
 
1.0%
8 22
 
0.9%
9 14
 
0.6%
ValueCountFrequency (%)
1597903 1
< 0.1%
403973 1
< 0.1%
229076 1
< 0.1%
183795 1
< 0.1%
158980 1
< 0.1%
123287 1
< 0.1%
122011 1
< 0.1%
111444 1
< 0.1%
111223 1
< 0.1%
100035 1
< 0.1%

2010
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1089
Distinct (%)48.6%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean2895.2558
Minimum0
Maximum1486796
Zeros63
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:28.430559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q132
median181.5
Q3944.25
95-th percentile9539.6
Maximum1486796
Range1486796
Interquartile range (IQR)912.25

Descriptive statistics

Standard deviation33576.339
Coefficient of variation (CV)11.59702
Kurtosis1711.4476
Mean2895.2558
Median Absolute Deviation (MAD)177.5
Skewness39.327955
Sum6485373
Variance1.1273705 × 109
MonotonicityNot monotonic
2024-04-06T17:29:28.775423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 63
 
2.6%
1 50
 
2.1%
2 37
 
1.5%
5 32
 
1.3%
6 31
 
1.3%
3 28
 
1.2%
4 27
 
1.1%
7 23
 
1.0%
12 22
 
0.9%
10 20
 
0.8%
Other values (1079) 1907
79.7%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 63
2.6%
1 50
2.1%
2 37
1.5%
3 28
1.2%
4 27
1.1%
5 32
1.3%
6 31
1.3%
7 23
 
1.0%
8 18
 
0.8%
9 19
 
0.8%
ValueCountFrequency (%)
1486796 1
< 0.1%
348129 1
< 0.1%
173340 1
< 0.1%
163424 1
< 0.1%
146668 1
< 0.1%
135212 1
< 0.1%
122891 1
< 0.1%
112177 1
< 0.1%
102117 1
< 0.1%
89979 1
< 0.1%

2011
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1074
Distinct (%)48.5%
Missing176
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean3299.9228
Minimum0
Maximum1727890
Zeros72
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:29.145975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q135
median191
Q3980.25
95-th percentile10756.25
Maximum1727890
Range1727890
Interquartile range (IQR)945.25

Descriptive statistics

Standard deviation39014.189
Coefficient of variation (CV)11.822758
Kurtosis1730.2191
Mean3299.9228
Median Absolute Deviation (MAD)187
Skewness39.6605
Sum7312629
Variance1.5221069 × 109
MonotonicityNot monotonic
2024-04-06T17:29:29.421141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 72
 
3.0%
1 38
 
1.6%
2 32
 
1.3%
4 29
 
1.2%
3 29
 
1.2%
5 27
 
1.1%
6 25
 
1.0%
9 20
 
0.8%
12 18
 
0.8%
8 18
 
0.8%
Other values (1064) 1908
79.8%
(Missing) 176
 
7.4%
ValueCountFrequency (%)
0 72
3.0%
1 38
1.6%
2 32
1.3%
3 29
1.2%
4 29
1.2%
5 27
 
1.1%
6 25
 
1.0%
7 16
 
0.7%
8 18
 
0.8%
9 20
 
0.8%
ValueCountFrequency (%)
1727890 1
< 0.1%
380112 1
< 0.1%
191854 1
< 0.1%
188286 1
< 0.1%
147053 1
< 0.1%
139071 1
< 0.1%
137985 1
< 0.1%
115522 1
< 0.1%
112409 1
< 0.1%
104429 1
< 0.1%

2012
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1068
Distinct (%)47.8%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean2868.9539
Minimum0
Maximum1475449
Zeros64
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:29.828754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q134
median176
Q3927
95-th percentile9245.6
Maximum1475449
Range1475449
Interquartile range (IQR)893

Descriptive statistics

Standard deviation33253.82
Coefficient of variation (CV)11.590922
Kurtosis1729.9554
Mean2868.9539
Median Absolute Deviation (MAD)173
Skewness39.594306
Sum6403505
Variance1.1058165 × 109
MonotonicityNot monotonic
2024-04-06T17:29:30.221433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64
 
2.7%
1 44
 
1.8%
2 37
 
1.5%
3 35
 
1.5%
6 25
 
1.0%
7 24
 
1.0%
5 24
 
1.0%
4 23
 
1.0%
11 22
 
0.9%
8 21
 
0.9%
Other values (1058) 1913
80.0%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 64
2.7%
1 44
1.8%
2 37
1.5%
3 35
1.5%
4 23
 
1.0%
5 24
 
1.0%
6 25
 
1.0%
7 24
 
1.0%
8 21
 
0.9%
9 20
 
0.8%
ValueCountFrequency (%)
1475449 1
< 0.1%
318944 1
< 0.1%
179232 1
< 0.1%
157008 1
< 0.1%
139918 1
< 0.1%
121313 1
< 0.1%
111953 1
< 0.1%
104761 1
< 0.1%
100170 1
< 0.1%
99876 1
< 0.1%

2013
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1071
Distinct (%)48.0%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean3154.0497
Minimum0
Maximum1666902
Zeros64
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:30.519373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q134
median178
Q3925
95-th percentile10580.5
Maximum1666902
Range1666902
Interquartile range (IQR)891

Descriptive statistics

Standard deviation37529.806
Coefficient of variation (CV)11.898926
Kurtosis1737.9616
Mean3154.0497
Median Absolute Deviation (MAD)174
Skewness39.744037
Sum7039839
Variance1.4084863 × 109
MonotonicityNot monotonic
2024-04-06T17:29:30.820775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64
 
2.7%
1 40
 
1.7%
2 35
 
1.5%
3 29
 
1.2%
4 28
 
1.2%
5 28
 
1.2%
7 24
 
1.0%
6 24
 
1.0%
8 19
 
0.8%
11 19
 
0.8%
Other values (1061) 1922
80.4%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 64
2.7%
1 40
1.7%
2 35
1.5%
3 29
1.2%
4 28
1.2%
5 28
1.2%
6 24
 
1.0%
7 24
 
1.0%
8 19
 
0.8%
9 16
 
0.7%
ValueCountFrequency (%)
1666902 1
< 0.1%
372136 1
< 0.1%
197316 1
< 0.1%
178448 1
< 0.1%
143523 1
< 0.1%
143244 1
< 0.1%
135184 1
< 0.1%
109330 1
< 0.1%
107961 1
< 0.1%
100123 1
< 0.1%

2014
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1117
Distinct (%)48.8%
Missing104
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean3646.288
Minimum0
Maximum2008094
Zeros71
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:31.127285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q139
median188
Q3971
95-th percentile12579
Maximum2008094
Range2008094
Interquartile range (IQR)932

Descriptive statistics

Standard deviation44640.784
Coefficient of variation (CV)12.242802
Kurtosis1784.8353
Mean3646.288
Median Absolute Deviation (MAD)184
Skewness40.317056
Sum8342707
Variance1.9927996 × 109
MonotonicityNot monotonic
2024-04-06T17:29:31.400569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71
 
3.0%
4 33
 
1.4%
1 32
 
1.3%
6 31
 
1.3%
2 29
 
1.2%
3 26
 
1.1%
5 25
 
1.0%
7 21
 
0.9%
8 19
 
0.8%
15 18
 
0.8%
Other values (1107) 1983
82.9%
(Missing) 104
 
4.3%
ValueCountFrequency (%)
0 71
3.0%
1 32
1.3%
2 29
1.2%
3 26
 
1.1%
4 33
1.4%
5 25
 
1.0%
6 31
1.3%
7 21
 
0.9%
8 19
 
0.8%
9 12
 
0.5%
ValueCountFrequency (%)
2008094 1
< 0.1%
460522 1
< 0.1%
258771 1
< 0.1%
199530 1
< 0.1%
172229 1
< 0.1%
162306 1
< 0.1%
158228 1
< 0.1%
125740 1
< 0.1%
117965 1
< 0.1%
110520 1
< 0.1%

2015
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1148
Distinct (%)50.9%
Missing136
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean4318.0168
Minimum0
Maximum2377476
Zeros55
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:31.663930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q146
median211.5
Q31113.25
95-th percentile14920.25
Maximum2377476
Range2377476
Interquartile range (IQR)1067.25

Descriptive statistics

Standard deviation53432.107
Coefficient of variation (CV)12.374224
Kurtosis1734.8757
Mean4318.0168
Median Absolute Deviation (MAD)206.5
Skewness39.721541
Sum9741446
Variance2.85499 × 109
MonotonicityNot monotonic
2024-04-06T17:29:31.933105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 55
 
2.3%
1 31
 
1.3%
8 28
 
1.2%
2 28
 
1.2%
3 27
 
1.1%
5 27
 
1.1%
11 21
 
0.9%
4 20
 
0.8%
7 17
 
0.7%
6 16
 
0.7%
Other values (1138) 1986
83.0%
(Missing) 136
 
5.7%
ValueCountFrequency (%)
0 55
2.3%
1 31
1.3%
2 28
1.2%
3 27
1.1%
4 20
 
0.8%
5 27
1.1%
6 16
 
0.7%
7 17
 
0.7%
8 28
1.2%
9 14
 
0.6%
ValueCountFrequency (%)
2377476 1
< 0.1%
590516 1
< 0.1%
352316 1
< 0.1%
227226 1
< 0.1%
200183 1
< 0.1%
181355 1
< 0.1%
174589 1
< 0.1%
144069 1
< 0.1%
133145 1
< 0.1%
128339 1
< 0.1%

2016
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1134
Distinct (%)50.3%
Missing136
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean4176.711
Minimum0
Maximum2313262
Zeros59
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:32.184203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q141
median202
Q31073.25
95-th percentile13583.25
Maximum2313262
Range2313262
Interquartile range (IQR)1032.25

Descriptive statistics

Standard deviation52262.971
Coefficient of variation (CV)12.512949
Kurtosis1702.0288
Mean4176.711
Median Absolute Deviation (MAD)197
Skewness39.310873
Sum9422660
Variance2.7314182 × 109
MonotonicityNot monotonic
2024-04-06T17:29:32.474924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 59
 
2.5%
1 35
 
1.5%
5 28
 
1.2%
2 24
 
1.0%
3 23
 
1.0%
9 22
 
0.9%
6 21
 
0.9%
13 21
 
0.9%
8 20
 
0.8%
4 20
 
0.8%
Other values (1124) 1983
82.9%
(Missing) 136
 
5.7%
ValueCountFrequency (%)
0 59
2.5%
1 35
1.5%
2 24
1.0%
3 23
 
1.0%
4 20
 
0.8%
5 28
1.2%
6 21
 
0.9%
7 19
 
0.8%
8 20
 
0.8%
9 22
 
0.9%
ValueCountFrequency (%)
2313262 1
< 0.1%
634635 1
< 0.1%
361777 1
< 0.1%
222930 1
< 0.1%
173247 1
< 0.1%
164964 1
< 0.1%
161763 1
< 0.1%
137870 1
< 0.1%
122161 1
< 0.1%
120307 1
< 0.1%

2017
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1154
Distinct (%)51.7%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean4673.0475
Minimum0
Maximum2614289
Zeros60
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:32.804444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q145
median231
Q31141.75
95-th percentile15051.35
Maximum2614289
Range2614289
Interquartile range (IQR)1096.75

Descriptive statistics

Standard deviation59480.548
Coefficient of variation (CV)12.728428
Kurtosis1675.4629
Mean4673.0475
Median Absolute Deviation (MAD)225
Skewness39.044312
Sum10430242
Variance3.5379356 × 109
MonotonicityNot monotonic
2024-04-06T17:29:33.605154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60
 
2.5%
2 29
 
1.2%
6 26
 
1.1%
1 26
 
1.1%
3 24
 
1.0%
5 23
 
1.0%
11 22
 
0.9%
7 21
 
0.9%
8 20
 
0.8%
4 19
 
0.8%
Other values (1144) 1962
82.0%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 60
2.5%
1 26
1.1%
2 29
1.2%
3 24
 
1.0%
4 19
 
0.8%
5 23
 
1.0%
6 26
1.1%
7 21
 
0.9%
8 20
 
0.8%
9 16
 
0.7%
ValueCountFrequency (%)
2614289 1
< 0.1%
769016 1
< 0.1%
382640 1
< 0.1%
226114 1
< 0.1%
178261 1
< 0.1%
173766 1
< 0.1%
172228 1
< 0.1%
170306 1
< 0.1%
126154 1
< 0.1%
125439 1
< 0.1%

2018
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1136
Distinct (%)50.7%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean4482.4634
Minimum0
Maximum2535485
Zeros50
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:33.879162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q142
median212
Q31055
95-th percentile14413.45
Maximum2535485
Range2535485
Interquartile range (IQR)1013

Descriptive statistics

Standard deviation57953.917
Coefficient of variation (CV)12.929033
Kurtosis1645.4499
Mean4482.4634
Median Absolute Deviation (MAD)206
Skewness38.705765
Sum10040718
Variance3.3586564 × 109
MonotonicityNot monotonic
2024-04-06T17:29:34.196634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 50
 
2.1%
1 37
 
1.5%
4 30
 
1.3%
2 28
 
1.2%
7 24
 
1.0%
6 23
 
1.0%
3 21
 
0.9%
20 20
 
0.8%
8 19
 
0.8%
5 19
 
0.8%
Other values (1126) 1969
82.3%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 50
2.1%
1 37
1.5%
2 28
1.2%
3 21
0.9%
4 30
1.3%
5 19
 
0.8%
6 23
1.0%
7 24
1.0%
8 19
 
0.8%
9 18
 
0.8%
ValueCountFrequency (%)
2535485 1
< 0.1%
831539 1
< 0.1%
355308 1
< 0.1%
205087 1
< 0.1%
161550 1
< 0.1%
158078 1
< 0.1%
139094 1
< 0.1%
131301 1
< 0.1%
121171 1
< 0.1%
116916 1
< 0.1%

2019
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1118
Distinct (%)50.1%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean4097.2984
Minimum0
Maximum2299185
Zeros58
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:34.465782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q140.75
median197.5
Q3995.25
95-th percentile13506.55
Maximum2299185
Range2299185
Interquartile range (IQR)954.5

Descriptive statistics

Standard deviation52494.394
Coefficient of variation (CV)12.811953
Kurtosis1656.161
Mean4097.2984
Median Absolute Deviation (MAD)192.5
Skewness38.834708
Sum9145170
Variance2.7556614 × 109
MonotonicityNot monotonic
2024-04-06T17:29:34.944726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
 
2.4%
1 39
 
1.6%
2 30
 
1.3%
4 24
 
1.0%
6 23
 
1.0%
3 22
 
0.9%
5 19
 
0.8%
7 19
 
0.8%
11 19
 
0.8%
14 18
 
0.8%
Other values (1108) 1961
82.0%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 58
2.4%
1 39
1.6%
2 30
1.3%
3 22
 
0.9%
4 24
1.0%
5 19
 
0.8%
6 23
 
1.0%
7 19
 
0.8%
8 12
 
0.5%
9 17
 
0.7%
ValueCountFrequency (%)
2299185 1
< 0.1%
729420 1
< 0.1%
292935 1
< 0.1%
189061 1
< 0.1%
167963 1
< 0.1%
148745 1
< 0.1%
144842 1
< 0.1%
129261 1
< 0.1%
112272 1
< 0.1%
108784 1
< 0.1%

2020
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1124
Distinct (%)50.4%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean4956.0031
Minimum0
Maximum2838734
Zeros65
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:35.258829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q144
median217
Q31096.5
95-th percentile15896.45
Maximum2838734
Range2838734
Interquartile range (IQR)1052.5

Descriptive statistics

Standard deviation64601.886
Coefficient of variation (CV)13.035078
Kurtosis1676.117
Mean4956.0031
Median Absolute Deviation (MAD)212
Skewness39.105213
Sum11061799
Variance4.1734036 × 109
MonotonicityNot monotonic
2024-04-06T17:29:35.536125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65
 
2.7%
1 31
 
1.3%
2 24
 
1.0%
4 23
 
1.0%
8 23
 
1.0%
3 23
 
1.0%
25 17
 
0.7%
5 17
 
0.7%
9 17
 
0.7%
15 17
 
0.7%
Other values (1114) 1975
82.6%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 65
2.7%
1 31
1.3%
2 24
 
1.0%
3 23
 
1.0%
4 23
 
1.0%
5 17
 
0.7%
6 16
 
0.7%
7 16
 
0.7%
8 23
 
1.0%
9 17
 
0.7%
ValueCountFrequency (%)
2838734 1
< 0.1%
870392 1
< 0.1%
367175 1
< 0.1%
213827 1
< 0.1%
212547 1
< 0.1%
205546 1
< 0.1%
166084 1
< 0.1%
158179 1
< 0.1%
140267 1
< 0.1%
138125 1
< 0.1%

2021
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1175
Distinct (%)52.6%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean4649.1375
Minimum0
Maximum2544561
Zeros49
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:35.803374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q149
median244.5
Q31225.25
95-th percentile14686.45
Maximum2544561
Range2544561
Interquartile range (IQR)1176.25

Descriptive statistics

Standard deviation58007.066
Coefficient of variation (CV)12.476952
Kurtosis1663.4764
Mean4649.1375
Median Absolute Deviation (MAD)237.5
Skewness38.872802
Sum10376875
Variance3.3648197 × 109
MonotonicityNot monotonic
2024-04-06T17:29:36.075742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49
 
2.0%
1 27
 
1.1%
2 24
 
1.0%
4 24
 
1.0%
6 23
 
1.0%
5 20
 
0.8%
9 20
 
0.8%
3 20
 
0.8%
12 18
 
0.8%
7 17
 
0.7%
Other values (1165) 1990
83.2%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 49
2.0%
1 27
1.1%
2 24
1.0%
3 20
0.8%
4 24
1.0%
5 20
0.8%
6 23
1.0%
7 17
 
0.7%
8 15
 
0.6%
9 20
0.8%
ValueCountFrequency (%)
2544561 1
< 0.1%
772989 1
< 0.1%
290661 1
< 0.1%
241755 1
< 0.1%
201455 1
< 0.1%
186669 1
< 0.1%
166992 1
< 0.1%
162004 1
< 0.1%
142744 1
< 0.1%
135315 1
< 0.1%

2022
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1070
Distinct (%)47.9%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean3104.7361
Minimum0
Maximum1635183
Zeros58
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:36.362122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q136
median183.5
Q3943.25
95-th percentile9173.45
Maximum1635183
Range1635183
Interquartile range (IQR)907.25

Descriptive statistics

Standard deviation37262.125
Coefficient of variation (CV)12.001704
Kurtosis1663.1731
Mean3104.7361
Median Absolute Deviation (MAD)178.5
Skewness38.790442
Sum6929771
Variance1.388466 × 109
MonotonicityNot monotonic
2024-04-06T17:29:36.629273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
 
2.4%
1 44
 
1.8%
2 35
 
1.5%
3 26
 
1.1%
8 23
 
1.0%
7 23
 
1.0%
6 21
 
0.9%
4 20
 
0.8%
5 18
 
0.8%
9 18
 
0.8%
Other values (1060) 1946
81.4%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 58
2.4%
1 44
1.8%
2 35
1.5%
3 26
1.1%
4 20
 
0.8%
5 18
 
0.8%
6 21
 
0.9%
7 23
 
1.0%
8 23
 
1.0%
9 18
 
0.8%
ValueCountFrequency (%)
1635183 1
< 0.1%
473107 1
< 0.1%
182899 1
< 0.1%
163789 1
< 0.1%
141038 1
< 0.1%
118992 1
< 0.1%
118448 1
< 0.1%
115732 1
< 0.1%
104212 1
< 0.1%
99925 1
< 0.1%

2023
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct990
Distinct (%)44.2%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean2561.7174
Minimum0
Maximum1412046
Zeros79
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:29:36.947155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q124
median132
Q3686.5
95-th percentile7988.75
Maximum1412046
Range1412046
Interquartile range (IQR)662.5

Descriptive statistics

Standard deviation31970.599
Coefficient of variation (CV)12.480143
Kurtosis1700.1388
Mean2561.7174
Median Absolute Deviation (MAD)129
Skewness39.336111
Sum5738247
Variance1.0221192 × 109
MonotonicityNot monotonic
2024-04-06T17:29:37.343593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 79
 
3.3%
1 49
 
2.0%
2 40
 
1.7%
3 36
 
1.5%
4 36
 
1.5%
5 30
 
1.3%
6 30
 
1.3%
8 26
 
1.1%
10 24
 
1.0%
9 22
 
0.9%
Other values (980) 1868
78.1%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 79
3.3%
1 49
2.0%
2 40
1.7%
3 36
1.5%
4 36
1.5%
5 30
 
1.3%
6 30
 
1.3%
7 15
 
0.6%
8 26
 
1.1%
9 22
 
0.9%
ValueCountFrequency (%)
1412046 1
< 0.1%
400299 1
< 0.1%
166577 1
< 0.1%
129008 1
< 0.1%
101014 1
< 0.1%
95386 1
< 0.1%
92996 1
< 0.1%
90165 1
< 0.1%
80187 1
< 0.1%
78235 1
< 0.1%

Interactions

2024-04-06T17:29:18.560545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:05.294007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:10.132954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:14.409874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:18.350173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:22.851963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:27.654283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:31.716789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:37.180153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:41.309703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:45.858825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:50.916145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:54.717386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:58.165871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:02.688103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:06.609057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:10.584083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:14.571591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:18.771301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:05.521939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:10.393339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:14.614256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:18.557671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:23.118127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:27.867330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:31.939823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:37.396983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:41.570003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:46.256235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:51.120183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:54.944951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:58.354919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:02.977609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:06.928460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:10.780080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:14.812904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:19.060565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:05.747137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:10.650034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:14.835128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:18.868294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:23.374258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:28.095345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:32.252985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:37.675205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:41.879663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:46.478312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:51.328037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:55.150200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:58.660102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:03.188582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:07.141727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:10.980844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:15.027788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:19.265943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:05.952942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:10.907434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:15.027769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:19.067771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:23.582888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:28.297076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:32.515716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:38.024516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:42.132985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:47.281188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:51.521493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:55.327927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:58.998657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:03.430177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:07.352239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:11.147804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:15.240084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:19.484213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:06.260134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:11.178154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:15.265674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:19.259702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:23.877392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:28.511173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:32.852535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:38.317845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:42.465858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:47.467958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:51.754415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:55.522159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:59.267470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:03.637481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:07.590954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:11.332594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:15.485312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:19.706231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:06.528531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:11.411745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:15.474658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:19.474338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:24.263507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:28.762993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:33.259619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:38.588769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:42.735291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:47.813717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:52.023687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:55.748670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:59.469996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:03.876851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:07.806178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:11.497513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:15.690495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:19.938478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:06.736245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:11.618279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:15.733429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:19.754733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:24.569215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:29.080598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:33.939268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:38.834518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:42.954400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:48.057500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:52.308012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:55.951218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:59.699387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:04.086896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:08.011956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:11.870841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:15.890032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:20.150766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:07.048396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:11.893234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:15.965849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:20.027645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:24.820925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:29.371732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:34.301445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:39.040666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:43.145306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:48.269989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:52.562045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:56.173006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:59.998597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:04.314722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:08.199853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:12.063606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:16.063511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:20.367164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:07.308593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:12.153988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:16.192052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:20.323392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:25.179401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:29.584794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:34.593007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:39.329098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:43.329525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:48.588988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:52.742405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:56.386111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:00.287074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:04.535496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:08.395689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:12.266279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:16.275933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:20.577806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:07.524581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:12.444051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:16.393276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:20.926144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:25.467010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:29.833812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:34.933681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:39.542967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:43.590963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:48.870454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:52.977079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:56.592517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:00.934963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:04.798098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:08.608617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:12.497820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-04-06T17:29:20.811603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:07.702925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:12.663714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:16.644212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:21.123560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:25.783263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:30.024789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:35.218264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:39.695236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:43.802967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:49.081028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:53.161382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:56.762596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:01.136190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:04.985710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:08.906968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:12.670277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:16.748499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:21.072609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:08.377878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:12.904598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:16.850348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:21.302844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:26.053305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:30.195235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:35.519321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:39.888553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:44.065789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:49.294165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:53.386789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:56.936189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:01.308648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:05.204031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:09.090146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:12.851268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:17.002688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:21.260754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:08.760339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:13.186069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:17.046541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:21.496706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:26.299621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:30.366347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:35.803992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:40.070036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:44.292418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:49.566231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:53.561223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:57.107691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:01.504159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:05.428005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:09.320637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:13.032187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:17.277093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:21.432714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:09.016313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:13.400449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:17.233300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:21.700967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:26.530995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:30.569465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:36.039802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:40.239506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:44.632114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:49.772192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:53.757275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:57.281964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:01.717908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:05.611606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:09.473410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:13.204865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:17.525020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:21.658937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:09.192912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:13.586254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:17.410464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:21.917533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:26.711439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:30.751007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:36.240402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:40.528398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:44.960170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:49.922390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:53.968035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:57.451807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:01.892902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:05.828217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:09.656567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:13.363649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:17.716195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:21.909912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:09.443650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:13.781280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:17.685219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:22.159083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:26.961331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:30.927326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:36.454743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:40.703114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:45.150339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:50.186535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:54.142704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:57.613565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:02.059632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:06.033428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:09.873711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:13.906343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:17.900500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:22.095257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:09.680669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:13.996040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:17.959981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:22.404618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:27.216118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:31.136758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:36.734417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:40.897189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:45.393258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:50.353113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:54.320557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:57.796246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:02.245006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:06.211336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:10.055714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:14.159811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:18.118042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:22.321779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:09.895804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:14.204686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:18.171585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:22.640018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:27.429113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:31.469038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:36.954135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:41.091204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:45.660014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:50.572622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:54.492791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:57.979661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:02.467287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:06.384738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:10.260645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:14.389198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:29:18.330025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:29:37.680750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.8420.8620.8620.8620.8620.8620.8621.0001.0001.0001.0001.0001.0001.0001.0000.8621.000
20070.8421.0000.9980.9980.9980.9980.9980.9980.9930.9930.9930.9930.9930.9930.9930.9930.9980.993
20080.8620.9981.0001.0001.0001.0001.0001.0000.9960.9960.9960.9960.9960.9960.9960.9961.0000.996
20090.8620.9981.0001.0001.0001.0001.0001.0000.9960.9960.9960.9960.9960.9960.9960.9961.0000.996
20100.8620.9981.0001.0001.0001.0001.0001.0000.9960.9960.9960.9960.9960.9960.9960.9961.0000.996
20110.8620.9981.0001.0001.0001.0001.0001.0000.9960.9960.9960.9960.9960.9960.9960.9961.0000.996
20120.8620.9981.0001.0001.0001.0001.0001.0000.9960.9960.9960.9960.9960.9960.9960.9961.0000.996
20130.8620.9981.0001.0001.0001.0001.0001.0000.9960.9960.9960.9960.9960.9960.9960.9961.0000.996
20141.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20151.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20161.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20171.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20181.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20191.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20201.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20211.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
20220.8620.9981.0001.0001.0001.0001.0001.0000.9960.9960.9960.9960.9960.9960.9960.9961.0000.996
20231.0000.9930.9960.9960.9960.9960.9960.9961.0001.0001.0001.0001.0001.0001.0001.0000.9961.000
2024-04-06T17:29:38.047989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.9770.9690.9650.9640.9640.9630.9640.9650.9640.9650.9630.9620.9600.9610.9640.9620.960
20070.9771.0000.9850.9790.9790.9770.9780.9770.9770.9760.9770.9760.9760.9730.9710.9720.9730.973
20080.9690.9851.0000.9820.9800.9810.9810.9780.9780.9760.9770.9760.9740.9720.9710.9700.9710.971
20090.9650.9790.9821.0000.9870.9860.9850.9830.9820.9810.9820.9830.9820.9800.9790.9810.9820.981
20100.9640.9790.9800.9871.0000.9870.9850.9830.9800.9790.9810.9820.9810.9780.9780.9790.9800.980
20110.9640.9770.9810.9860.9871.0000.9910.9890.9860.9850.9840.9840.9810.9800.9800.9800.9800.981
20120.9630.9780.9810.9850.9850.9911.0000.9910.9890.9870.9870.9860.9830.9820.9810.9800.9810.983
20130.9640.9770.9780.9830.9830.9890.9911.0000.9900.9870.9860.9870.9830.9810.9800.9800.9800.981
20140.9650.9770.9780.9820.9800.9860.9890.9901.0000.9910.9890.9870.9840.9830.9820.9800.9790.978
20150.9640.9760.9760.9810.9790.9850.9870.9870.9911.0000.9930.9890.9860.9850.9850.9840.9810.978
20160.9650.9770.9770.9820.9810.9840.9870.9860.9890.9931.0000.9920.9890.9880.9870.9870.9840.983
20170.9630.9760.9760.9830.9820.9840.9860.9870.9870.9890.9921.0000.9910.9900.9890.9880.9860.985
20180.9620.9760.9740.9820.9810.9810.9830.9830.9840.9860.9890.9911.0000.9910.9890.9880.9860.985
20190.9600.9730.9720.9800.9780.9800.9820.9810.9830.9850.9880.9900.9911.0000.9910.9880.9860.985
20200.9610.9710.9710.9790.9780.9800.9810.9800.9820.9850.9870.9890.9890.9911.0000.9920.9870.984
20210.9640.9720.9700.9810.9790.9800.9800.9800.9800.9840.9870.9880.9880.9880.9921.0000.9900.985
20220.9620.9730.9710.9820.9800.9800.9810.9800.9790.9810.9840.9860.9860.9860.9870.9901.0000.989
20230.9600.9730.9710.9810.9800.9810.9830.9810.9780.9780.9830.9850.9850.9850.9840.9850.9891.000

Missing values

2024-04-06T17:29:22.588682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:29:23.052198image/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.
2024-04-06T17:29:24.152128image/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_거래규모200620072008200920102011201220132014201520162017201820192020202120222023
0전국_330㎡이하191842015990221644034159790314867961727890147544916669022008094237747623132622614289253548522991852838734254456116351831412046
1전국_331~660㎡189099177053180120183795173340188286179232178448199530227226222930226114205087189061213827241755182899129008
2전국_661~1,000㎡1208991105431108151114441021171044291001701001231105201257191203071234431132641050221163751328799992571137
3전국_1,001~2,000㎡179394162416163553158980146668147053139918143244158228174589164964170306158078148745166084186669141038101014
4전국_2,001~5,000㎡15126213069013239012201111217711240910476110796111796512833912216112543912117111227212248213531510421278235
5전국_5,001~10,000㎡364502842726840259682394723974219592192924176260422532526529256142343424499279822272216761
6전국_10,001~33,000㎡321452436622130218701867617939165801671318216193571896720627197341765917626202181685712555
7전국_33,000㎡초과15595111129411863375367219689366596893778172438054727164326486724363394972
8서울_330㎡이하387889274262257363229076163424191854157008197316258771352316361777382640355308292935367175290661163789166577
9서울_331~660㎡33612744206626541948191916641731206627122706257527222639317928371757889
지역_거래규모200620072008200920102011201220132014201520162017201820192020202120222023
2382제주 제주시_10,001~33,000㎡22627418221718912217018431340033820620517814515513792
2383제주 제주시_33,000㎡초과858757387443354757867650432218272828
2384제주 서귀포시_330㎡이하1770400936893624371647235610710496241614017646158571399996757682913078356021
2385제주 서귀포시_331~660㎡92518891384134215781837204626093506504346633383275419741767227119131317
2386제주 서귀포시_661~1,000㎡6261249851891953109413361567203029332161153313059328421011912627
2387제주 서귀포시_1,001~2,000㎡11061899124714621395150516292109284833772513196816431313126914481160853
2388제주 서귀포시_2,001~5,000㎡14742446155218891731169318322303319536662842221819691618133315211311946
2389제주 서귀포시_5,001~10,000㎡4216735105554795245115999221214850637522480373425322271
2390제주 서귀포시_10,001~33,000㎡1462912171871481481561903104372752291691251271239375
2391제주 서귀포시_33,000㎡초과42325026262393138613234173212121819