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 순수토지 거래현황의 연도별 용도지역별(면적) 데이터입니다.- (단위 : 천㎡)- 공표시기 : 익월 말일경
Author한국부동산원
URLhttps://www.data.go.kr/data/15068326/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 = 33.84900631)Skewed
2007 is highly skewed (γ1 = 33.83985939)Skewed
2008 is highly skewed (γ1 = 33.81193904)Skewed
2009 is highly skewed (γ1 = 35.69618444)Skewed
2010 is highly skewed (γ1 = 35.57417361)Skewed
2011 is highly skewed (γ1 = 35.29204573)Skewed
2012 is highly skewed (γ1 = 34.47697526)Skewed
2013 is highly skewed (γ1 = 34.59902543)Skewed
2014 is highly skewed (γ1 = 33.43400279)Skewed
2015 is highly skewed (γ1 = 33.22434893)Skewed
2016 is highly skewed (γ1 = 31.83521595)Skewed
2017 is highly skewed (γ1 = 33.77275182)Skewed
2018 is highly skewed (γ1 = 34.0726678)Skewed
2019 is highly skewed (γ1 = 33.28914576)Skewed
2020 is highly skewed (γ1 = 31.68175103)Skewed
2021 is highly skewed (γ1 = 31.817305)Skewed
2022 is highly skewed (γ1 = 32.94678952)Skewed
2023 is highly skewed (γ1 = 34.02666883)Skewed
지역_용도지역 has unique valuesUnique
2006 has 638 (26.7%) zerosZeros
2007 has 659 (27.6%) zerosZeros
2008 has 644 (26.9%) zerosZeros
2009 has 647 (27.0%) zerosZeros
2010 has 668 (27.9%) zerosZeros
2011 has 649 (27.1%) zerosZeros
2012 has 676 (28.3%) zerosZeros
2013 has 652 (27.3%) zerosZeros
2014 has 628 (26.3%) zerosZeros
2015 has 610 (25.5%) zerosZeros
2016 has 618 (25.8%) zerosZeros
2017 has 601 (25.1%) zerosZeros
2018 has 625 (26.1%) zerosZeros
2019 has 618 (25.8%) zerosZeros
2020 has 610 (25.5%) zerosZeros
2021 has 612 (25.6%) zerosZeros
2022 has 641 (26.8%) zerosZeros
2023 has 686 (28.7%) zerosZeros

Reproduction

Analysis started2024-03-23 03:42:52.693095
Analysis finished2024-03-23 03:45:27.236980
Duration2 minutes and 34.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역_용도지역
Text

UNIQUE 

Distinct2392
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.8 KiB
2024-03-23T03:45:27.861058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length16.026338
Min length7

Characters and Unicode

Total characters38335
Distinct characters158
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

Unique2392 ?
Unique (%)100.0%

Sample

1st row전국_도시지역_주거지역
2nd row전국_도시지역_상업지역
3rd row전국_도시지역_공업지역
4th row전국_도시지역_녹지지역
5th row전국_도시지역_개발제한구역
ValueCountFrequency (%)
경기 416
 
8.4%
경남 208
 
4.2%
경북 200
 
4.1%
서울 200
 
4.1%
전남 176
 
3.6%
충북 152
 
3.1%
충남 152
 
3.1%
강원 144
 
2.9%
부산 128
 
2.6%
전북 128
 
2.6%
Other values (2205) 3024
61.4%
2024-03-23T03:45:29.317320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4194
 
10.9%
_ 4186
 
10.9%
3887
 
10.1%
2770
 
7.2%
2536
 
6.6%
2133
 
5.6%
1427
 
3.7%
1171
 
3.1%
744
 
1.9%
712
 
1.9%
Other values (148) 14575
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31309
81.7%
Connector Punctuation 4186
 
10.9%
Space Separator 2536
 
6.6%
Open Punctuation 152
 
0.4%
Close Punctuation 152
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4194
 
13.4%
3887
 
12.4%
2770
 
8.8%
2133
 
6.8%
1427
 
4.6%
1171
 
3.7%
744
 
2.4%
712
 
2.3%
699
 
2.2%
675
 
2.2%
Other values (144) 12897
41.2%
Connector Punctuation
ValueCountFrequency (%)
_ 4186
100.0%
Space Separator
ValueCountFrequency (%)
2536
100.0%
Open Punctuation
ValueCountFrequency (%)
( 152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31309
81.7%
Common 7026
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4194
 
13.4%
3887
 
12.4%
2770
 
8.8%
2133
 
6.8%
1427
 
4.6%
1171
 
3.7%
744
 
2.4%
712
 
2.3%
699
 
2.2%
675
 
2.2%
Other values (144) 12897
41.2%
Common
ValueCountFrequency (%)
_ 4186
59.6%
2536
36.1%
( 152
 
2.2%
) 152
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31309
81.7%
ASCII 7026
 
18.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4194
 
13.4%
3887
 
12.4%
2770
 
8.8%
2133
 
6.8%
1427
 
4.6%
1171
 
3.7%
744
 
2.4%
712
 
2.3%
699
 
2.2%
675
 
2.2%
Other values (144) 12897
41.2%
ASCII
ValueCountFrequency (%)
_ 4186
59.6%
2536
36.1%
( 152
 
2.2%
) 152
 
2.2%

2006
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct851
Distinct (%)38.4%
Missing176
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean2624.8023
Minimum0
Maximum1127663
Zeros638
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:29.985582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median42
Q3560.5
95-th percentile8102
Maximum1127663
Range1127663
Interquartile range (IQR)560.5

Descriptive statistics

Standard deviation27130.145
Coefficient of variation (CV)10.336071
Kurtosis1350.9569
Mean2624.8023
Median Absolute Deviation (MAD)42
Skewness33.849006
Sum5816562
Variance7.3604475 × 108
MonotonicityNot monotonic
2024-03-23T03:45:30.678033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 638
26.7%
1 60
 
2.5%
3 31
 
1.3%
2 26
 
1.1%
6 24
 
1.0%
7 23
 
1.0%
4 23
 
1.0%
8 20
 
0.8%
5 20
 
0.8%
15 14
 
0.6%
Other values (841) 1337
55.9%
(Missing) 176
 
7.4%
ValueCountFrequency (%)
0 638
26.7%
1 60
 
2.5%
2 26
 
1.1%
3 31
 
1.3%
4 23
 
1.0%
5 20
 
0.8%
6 24
 
1.0%
7 23
 
1.0%
8 20
 
0.8%
9 14
 
0.6%
ValueCountFrequency (%)
1127663 1
< 0.1%
340207 1
< 0.1%
198335 1
< 0.1%
179929 1
< 0.1%
176921 1
< 0.1%
161539 1
< 0.1%
157443 1
< 0.1%
141384 1
< 0.1%
111405 1
< 0.1%
94482 1
< 0.1%

2007
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct806
Distinct (%)37.0%
Missing216
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean2018.2436
Minimum0
Maximum856500
Zeros659
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:31.408052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median34
Q3431.5
95-th percentile6188.5
Maximum856500
Range856500
Interquartile range (IQR)431.5

Descriptive statistics

Standard deviation20719.758
Coefficient of variation (CV)10.266233
Kurtosis1345.2328
Mean2018.2436
Median Absolute Deviation (MAD)34
Skewness33.839859
Sum4391698
Variance4.2930838 × 108
MonotonicityNot monotonic
2024-03-23T03:45:31.990527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 659
27.6%
1 47
 
2.0%
3 38
 
1.6%
2 30
 
1.3%
4 27
 
1.1%
5 25
 
1.0%
8 19
 
0.8%
11 17
 
0.7%
12 16
 
0.7%
7 14
 
0.6%
Other values (796) 1284
53.7%
(Missing) 216
 
9.0%
ValueCountFrequency (%)
0 659
27.6%
1 47
 
2.0%
2 30
 
1.3%
3 38
 
1.6%
4 27
 
1.1%
5 25
 
1.0%
6 14
 
0.6%
7 14
 
0.6%
8 19
 
0.8%
9 8
 
0.3%
ValueCountFrequency (%)
856500 1
< 0.1%
257496 1
< 0.1%
145767 1
< 0.1%
139130 1
< 0.1%
131432 1
< 0.1%
121800 1
< 0.1%
110217 1
< 0.1%
96693 1
< 0.1%
80294 1
< 0.1%
80270 1
< 0.1%

2008
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct799
Distinct (%)36.5%
Missing200
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean1915.844
Minimum0
Maximum814187
Zeros644
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:32.681618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median33
Q3404
95-th percentile6000.4
Maximum814187
Range814187
Interquartile range (IQR)404

Descriptive statistics

Standard deviation19672.239
Coefficient of variation (CV)10.268184
Kurtosis1343.585
Mean1915.844
Median Absolute Deviation (MAD)33
Skewness33.811939
Sum4199530
Variance3.8699699 × 108
MonotonicityNot monotonic
2024-03-23T03:45:33.462908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 644
26.9%
1 49
 
2.0%
2 43
 
1.8%
3 37
 
1.5%
5 26
 
1.1%
7 22
 
0.9%
11 22
 
0.9%
4 20
 
0.8%
10 19
 
0.8%
6 19
 
0.8%
Other values (789) 1291
54.0%
(Missing) 200
 
8.4%
ValueCountFrequency (%)
0 644
26.9%
1 49
 
2.0%
2 43
 
1.8%
3 37
 
1.5%
4 20
 
0.8%
5 26
 
1.1%
6 19
 
0.8%
7 22
 
0.9%
8 14
 
0.6%
9 12
 
0.5%
ValueCountFrequency (%)
814187 1
< 0.1%
252874 1
< 0.1%
160075 1
< 0.1%
121490 1
< 0.1%
111457 1
< 0.1%
107812 1
< 0.1%
103076 1
< 0.1%
82910 1
< 0.1%
78665 1
< 0.1%
78113 1
< 0.1%

2009
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct794
Distinct (%)36.2%
Missing200
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean2008.3841
Minimum0
Maximum942831
Zeros647
Zeros (%)27.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:34.036743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median37
Q3415.5
95-th percentile6712.05
Maximum942831
Range942831
Interquartile range (IQR)415.5

Descriptive statistics

Standard deviation22237.307
Coefficient of variation (CV)11.072238
Kurtosis1471.3638
Mean2008.3841
Median Absolute Deviation (MAD)37
Skewness35.696184
Sum4402378
Variance4.9449782 × 108
MonotonicityNot monotonic
2024-03-23T03:45:34.573593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 647
27.0%
1 47
 
2.0%
2 37
 
1.5%
5 32
 
1.3%
3 31
 
1.3%
4 31
 
1.3%
7 23
 
1.0%
6 17
 
0.7%
8 17
 
0.7%
9 15
 
0.6%
Other values (784) 1295
54.1%
(Missing) 200
 
8.4%
ValueCountFrequency (%)
0 647
27.0%
1 47
 
2.0%
2 37
 
1.5%
3 31
 
1.3%
4 31
 
1.3%
5 32
 
1.3%
6 17
 
0.7%
7 23
 
1.0%
8 17
 
0.7%
9 15
 
0.6%
ValueCountFrequency (%)
942831 1
< 0.1%
211394 1
< 0.1%
184937 1
< 0.1%
126344 1
< 0.1%
125361 1
< 0.1%
119156 1
< 0.1%
118129 1
< 0.1%
106113 1
< 0.1%
101217 1
< 0.1%
95982 1
< 0.1%

2010
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct799
Distinct (%)35.7%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean1733.6134
Minimum0
Maximum799177
Zeros668
Zeros (%)27.9%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:35.156621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median34
Q3387.5
95-th percentile5783.05
Maximum799177
Range799177
Interquartile range (IQR)387.5

Descriptive statistics

Standard deviation18762.235
Coefficient of variation (CV)10.822618
Kurtosis1468.3552
Mean1733.6134
Median Absolute Deviation (MAD)34
Skewness35.574174
Sum3883294
Variance3.5202146 × 108
MonotonicityNot monotonic
2024-03-23T03:45:35.890992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 668
27.9%
1 55
 
2.3%
2 41
 
1.7%
3 32
 
1.3%
4 29
 
1.2%
6 24
 
1.0%
9 19
 
0.8%
8 19
 
0.8%
10 19
 
0.8%
7 16
 
0.7%
Other values (789) 1318
55.1%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 668
27.9%
1 55
 
2.3%
2 41
 
1.7%
3 32
 
1.3%
4 29
 
1.2%
5 13
 
0.5%
6 24
 
1.0%
7 16
 
0.7%
8 19
 
0.8%
9 19
 
0.8%
ValueCountFrequency (%)
799177 1
< 0.1%
194062 1
< 0.1%
166377 1
< 0.1%
115510 1
< 0.1%
108384 1
< 0.1%
99457 1
< 0.1%
97345 1
< 0.1%
86823 1
< 0.1%
83340 1
< 0.1%
81847 1
< 0.1%

2011
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct804
Distinct (%)36.3%
Missing176
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean1714.9666
Minimum0
Maximum780339
Zeros649
Zeros (%)27.1%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:36.410523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median36.5
Q3396.25
95-th percentile5588
Maximum780339
Range780339
Interquartile range (IQR)396.25

Descriptive statistics

Standard deviation18430.344
Coefficient of variation (CV)10.746766
Kurtosis1448.3041
Mean1714.9666
Median Absolute Deviation (MAD)36.5
Skewness35.292046
Sum3800366
Variance3.3967759 × 108
MonotonicityNot monotonic
2024-03-23T03:45:37.040091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 649
27.1%
1 60
 
2.5%
2 39
 
1.6%
3 32
 
1.3%
4 25
 
1.0%
6 24
 
1.0%
5 22
 
0.9%
7 21
 
0.9%
8 18
 
0.8%
13 16
 
0.7%
Other values (794) 1310
54.8%
(Missing) 176
 
7.4%
ValueCountFrequency (%)
0 649
27.1%
1 60
 
2.5%
2 39
 
1.6%
3 32
 
1.3%
4 25
 
1.0%
5 22
 
0.9%
6 24
 
1.0%
7 21
 
0.9%
8 18
 
0.8%
9 16
 
0.7%
ValueCountFrequency (%)
780339 1
< 0.1%
181641 1
< 0.1%
157484 1
< 0.1%
125472 1
< 0.1%
115743 1
< 0.1%
103269 1
< 0.1%
89941 1
< 0.1%
83620 1
< 0.1%
79478 1
< 0.1%
73385 1
< 0.1%

2012
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct774
Distinct (%)34.7%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean1541.3714
Minimum0
Maximum679981
Zeros676
Zeros (%)28.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:37.594948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median38
Q3389.25
95-th percentile5068.7
Maximum679981
Range679981
Interquartile range (IQR)389.25

Descriptive statistics

Standard deviation16195.506
Coefficient of variation (CV)10.507206
Kurtosis1393.7424
Mean1541.3714
Median Absolute Deviation (MAD)38
Skewness34.476975
Sum3440341
Variance2.6229443 × 108
MonotonicityNot monotonic
2024-03-23T03:45:38.130723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 676
28.3%
2 49
 
2.0%
1 49
 
2.0%
3 29
 
1.2%
4 27
 
1.1%
5 23
 
1.0%
6 19
 
0.8%
9 18
 
0.8%
10 17
 
0.7%
7 16
 
0.7%
Other values (764) 1309
54.7%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 676
28.3%
1 49
 
2.0%
2 49
 
2.0%
3 29
 
1.2%
4 27
 
1.1%
5 23
 
1.0%
6 19
 
0.8%
7 16
 
0.7%
8 10
 
0.4%
9 18
 
0.8%
ValueCountFrequency (%)
679981 1
< 0.1%
176122 1
< 0.1%
148278 1
< 0.1%
124775 1
< 0.1%
109859 1
< 0.1%
98545 1
< 0.1%
79263 1
< 0.1%
71828 1
< 0.1%
63708 1
< 0.1%
59032 1
< 0.1%

2013
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct789
Distinct (%)35.3%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean1513.6783
Minimum0
Maximum666281
Zeros652
Zeros (%)27.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:38.692701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median35
Q3367.25
95-th percentile5006.05
Maximum666281
Range666281
Interquartile range (IQR)367.25

Descriptive statistics

Standard deviation15848.666
Coefficient of variation (CV)10.4703
Kurtosis1401.02
Mean1513.6783
Median Absolute Deviation (MAD)35
Skewness34.599025
Sum3378530
Variance2.5118021 × 108
MonotonicityNot monotonic
2024-03-23T03:45:39.417057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 652
27.3%
1 53
 
2.2%
2 32
 
1.3%
3 29
 
1.2%
9 26
 
1.1%
8 23
 
1.0%
4 23
 
1.0%
5 22
 
0.9%
6 21
 
0.9%
7 21
 
0.9%
Other values (779) 1330
55.6%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 652
27.3%
1 53
 
2.2%
2 32
 
1.3%
3 29
 
1.2%
4 23
 
1.0%
5 22
 
0.9%
6 21
 
0.9%
7 21
 
0.9%
8 23
 
1.0%
9 26
 
1.1%
ValueCountFrequency (%)
666281 1
< 0.1%
174143 1
< 0.1%
148134 1
< 0.1%
117835 1
< 0.1%
107223 1
< 0.1%
85194 1
< 0.1%
76401 1
< 0.1%
71548 1
< 0.1%
69701 1
< 0.1%
54518 1
< 0.1%

2014
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct833
Distinct (%)36.4%
Missing104
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean1596.8444
Minimum0
Maximum671456
Zeros628
Zeros (%)26.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:39.939956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median49
Q3435.25
95-th percentile5193.45
Maximum671456
Range671456
Interquartile range (IQR)435.25

Descriptive statistics

Standard deviation16105.251
Coefficient of variation (CV)10.085674
Kurtosis1327.8826
Mean1596.8444
Median Absolute Deviation (MAD)49
Skewness33.434003
Sum3653580
Variance2.5937912 × 108
MonotonicityNot monotonic
2024-03-23T03:45:40.795302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 628
26.3%
1 47
 
2.0%
2 44
 
1.8%
4 33
 
1.4%
3 25
 
1.0%
5 21
 
0.9%
6 19
 
0.8%
8 18
 
0.8%
7 16
 
0.7%
10 16
 
0.7%
Other values (823) 1421
59.4%
(Missing) 104
 
4.3%
ValueCountFrequency (%)
0 628
26.3%
1 47
 
2.0%
2 44
 
1.8%
3 25
 
1.0%
4 33
 
1.4%
5 21
 
0.9%
6 19
 
0.8%
7 16
 
0.7%
8 18
 
0.8%
9 14
 
0.6%
ValueCountFrequency (%)
671456 1
< 0.1%
189779 1
< 0.1%
172207 1
< 0.1%
150343 1
< 0.1%
113319 1
< 0.1%
88626 1
< 0.1%
70673 1
< 0.1%
70546 1
< 0.1%
69429 1
< 0.1%
57265 1
< 0.1%

2015
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct857
Distinct (%)38.0%
Missing136
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean1784.8723
Minimum0
Maximum745191
Zeros610
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:41.475435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median56
Q3480
95-th percentile5657.25
Maximum745191
Range745191
Interquartile range (IQR)480

Descriptive statistics

Standard deviation18001.293
Coefficient of variation (CV)10.085479
Kurtosis1309.7298
Mean1784.8723
Median Absolute Deviation (MAD)56
Skewness33.224349
Sum4026672
Variance3.2404654 × 108
MonotonicityNot monotonic
2024-03-23T03:45:41.946774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 610
25.5%
1 58
 
2.4%
2 42
 
1.8%
5 30
 
1.3%
4 30
 
1.3%
3 22
 
0.9%
15 17
 
0.7%
7 16
 
0.7%
6 15
 
0.6%
11 14
 
0.6%
Other values (847) 1402
58.6%
(Missing) 136
 
5.7%
ValueCountFrequency (%)
0 610
25.5%
1 58
 
2.4%
2 42
 
1.8%
3 22
 
0.9%
4 30
 
1.3%
5 30
 
1.3%
6 15
 
0.6%
7 16
 
0.7%
8 10
 
0.4%
9 10
 
0.4%
ValueCountFrequency (%)
745191 1
< 0.1%
225681 1
< 0.1%
174247 1
< 0.1%
165019 1
< 0.1%
124655 1
< 0.1%
107514 1
< 0.1%
81776 1
< 0.1%
71213 1
< 0.1%
70827 1
< 0.1%
62533 1
< 0.1%

2016
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct840
Distinct (%)37.2%
Missing136
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean1806.4162
Minimum0
Maximum707794
Zeros618
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:42.422990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median47
Q3441.25
95-th percentile5730
Maximum707794
Range707794
Interquartile range (IQR)441.25

Descriptive statistics

Standard deviation17429.136
Coefficient of variation (CV)9.6484609
Kurtosis1218.9184
Mean1806.4162
Median Absolute Deviation (MAD)47
Skewness31.835216
Sum4075275
Variance3.0377479 × 108
MonotonicityNot monotonic
2024-03-23T03:45:43.112209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 618
25.8%
1 54
 
2.3%
2 37
 
1.5%
5 36
 
1.5%
3 30
 
1.3%
4 27
 
1.1%
6 25
 
1.0%
7 20
 
0.8%
12 17
 
0.7%
8 16
 
0.7%
Other values (830) 1376
57.5%
(Missing) 136
 
5.7%
ValueCountFrequency (%)
0 618
25.8%
1 54
 
2.3%
2 37
 
1.5%
3 30
 
1.3%
4 27
 
1.1%
5 36
 
1.5%
6 25
 
1.0%
7 20
 
0.8%
8 16
 
0.7%
9 11
 
0.5%
ValueCountFrequency (%)
707794 1
< 0.1%
222177 1
< 0.1%
209208 1
< 0.1%
156539 1
< 0.1%
119452 1
< 0.1%
89724 1
< 0.1%
84880 1
< 0.1%
70028 1
< 0.1%
67227 1
< 0.1%
66266 1
< 0.1%

2017
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct856
Distinct (%)38.4%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean1861.0197
Minimum0
Maximum794512
Zeros601
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:44.128396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median55
Q3473.5
95-th percentile5817.6
Maximum794512
Range794512
Interquartile range (IQR)473.5

Descriptive statistics

Standard deviation19101.323
Coefficient of variation (CV)10.263902
Kurtosis1345.2349
Mean1861.0197
Median Absolute Deviation (MAD)55
Skewness33.772752
Sum4153796
Variance3.6486055 × 108
MonotonicityNot monotonic
2024-03-23T03:45:45.062279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 601
25.1%
2 46
 
1.9%
1 41
 
1.7%
3 37
 
1.5%
5 24
 
1.0%
7 23
 
1.0%
6 21
 
0.9%
4 19
 
0.8%
17 17
 
0.7%
9 13
 
0.5%
Other values (846) 1390
58.1%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 601
25.1%
1 41
 
1.7%
2 46
 
1.9%
3 37
 
1.5%
4 19
 
0.8%
5 24
 
1.0%
6 21
 
0.9%
7 23
 
1.0%
8 12
 
0.5%
9 13
 
0.5%
ValueCountFrequency (%)
794512 1
< 0.1%
204923 1
< 0.1%
190220 1
< 0.1%
183495 1
< 0.1%
133159 1
< 0.1%
95360 1
< 0.1%
87992 1
< 0.1%
79230 1
< 0.1%
77477 1
< 0.1%
69646 1
< 0.1%

2018
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct832
Distinct (%)37.1%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean1749.2978
Minimum0
Maximum758986
Zeros625
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:45.842035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median49
Q3445
95-th percentile5670.85
Maximum758986
Range758986
Interquartile range (IQR)445

Descriptive statistics

Standard deviation18153.326
Coefficient of variation (CV)10.377493
Kurtosis1367.1269
Mean1749.2978
Median Absolute Deviation (MAD)49
Skewness34.072668
Sum3918427
Variance3.2954324 × 108
MonotonicityNot monotonic
2024-03-23T03:45:46.432342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 625
26.1%
1 54
 
2.3%
2 31
 
1.3%
4 30
 
1.3%
3 26
 
1.1%
9 26
 
1.1%
7 24
 
1.0%
6 20
 
0.8%
5 20
 
0.8%
10 18
 
0.8%
Other values (822) 1366
57.1%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 625
26.1%
1 54
 
2.3%
2 31
 
1.3%
3 26
 
1.1%
4 30
 
1.3%
5 20
 
0.8%
6 20
 
0.8%
7 24
 
1.0%
8 10
 
0.4%
9 26
 
1.1%
ValueCountFrequency (%)
758986 1
< 0.1%
194936 1
< 0.1%
179438 1
< 0.1%
153673 1
< 0.1%
132725 1
< 0.1%
98142 1
< 0.1%
90137 1
< 0.1%
80301 1
< 0.1%
71212 1
< 0.1%
67226 1
< 0.1%

2019
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct810
Distinct (%)36.3%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean1627.6501
Minimum0
Maximum680397
Zeros618
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:47.074487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median44
Q3412
95-th percentile5231.5
Maximum680397
Range680397
Interquartile range (IQR)412

Descriptive statistics

Standard deviation16457.707
Coefficient of variation (CV)10.11133
Kurtosis1314.3542
Mean1627.6501
Median Absolute Deviation (MAD)44
Skewness33.289146
Sum3632915
Variance2.7085611 × 108
MonotonicityNot monotonic
2024-03-23T03:45:47.657530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 618
25.8%
1 49
 
2.0%
3 37
 
1.5%
2 33
 
1.4%
4 32
 
1.3%
5 32
 
1.3%
7 26
 
1.1%
6 26
 
1.1%
9 18
 
0.8%
8 17
 
0.7%
Other values (800) 1344
56.2%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 618
25.8%
1 49
 
2.0%
2 33
 
1.4%
3 37
 
1.5%
4 32
 
1.3%
5 32
 
1.3%
6 26
 
1.1%
7 26
 
1.1%
8 17
 
0.7%
9 18
 
0.8%
ValueCountFrequency (%)
680397 1
< 0.1%
192779 1
< 0.1%
167329 1
< 0.1%
132175 1
< 0.1%
123064 1
< 0.1%
86005 1
< 0.1%
78369 1
< 0.1%
74827 1
< 0.1%
66951 1
< 0.1%
65385 1
< 0.1%

2020
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct825
Distinct (%)37.0%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean1752.6151
Minimum0
Maximum694446
Zeros610
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:48.245422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median51
Q3449.5
95-th percentile5338.75
Maximum694446
Range694446
Interquartile range (IQR)449.5

Descriptive statistics

Standard deviation17191.275
Coefficient of variation (CV)9.8089276
Kurtosis1206.3361
Mean1752.6151
Median Absolute Deviation (MAD)51
Skewness31.681751
Sum3911837
Variance2.9553994 × 108
MonotonicityNot monotonic
2024-03-23T03:45:48.773205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 610
25.5%
1 50
 
2.1%
3 38
 
1.6%
5 28
 
1.2%
2 24
 
1.0%
4 21
 
0.9%
6 17
 
0.7%
15 16
 
0.7%
13 15
 
0.6%
7 15
 
0.6%
Other values (815) 1398
58.4%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 610
25.5%
1 50
 
2.1%
2 24
 
1.0%
3 38
 
1.6%
4 21
 
0.9%
5 28
 
1.2%
6 17
 
0.7%
7 15
 
0.6%
8 14
 
0.6%
9 12
 
0.5%
ValueCountFrequency (%)
694446 1
< 0.1%
221333 1
< 0.1%
200411 1
< 0.1%
151058 1
< 0.1%
122938 1
< 0.1%
83871 1
< 0.1%
79932 1
< 0.1%
76865 1
< 0.1%
75665 1
< 0.1%
69526 1
< 0.1%

2021
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct866
Distinct (%)38.8%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean1860.6895
Minimum0
Maximum734792
Zeros612
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:49.366731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median56
Q3511
95-th percentile5872.4
Maximum734792
Range734792
Interquartile range (IQR)511

Descriptive statistics

Standard deviation18180.814
Coefficient of variation (CV)9.7710091
Kurtosis1210.8506
Mean1860.6895
Median Absolute Deviation (MAD)56
Skewness31.817305
Sum4153059
Variance3.30542 × 108
MonotonicityNot monotonic
2024-03-23T03:45:49.906983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 612
25.6%
1 40
 
1.7%
3 36
 
1.5%
2 29
 
1.2%
4 27
 
1.1%
5 21
 
0.9%
11 17
 
0.7%
7 16
 
0.7%
8 14
 
0.6%
6 14
 
0.6%
Other values (856) 1406
58.8%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 612
25.6%
1 40
 
1.7%
2 29
 
1.2%
3 36
 
1.5%
4 27
 
1.1%
5 21
 
0.9%
6 14
 
0.6%
7 16
 
0.7%
8 14
 
0.6%
9 14
 
0.6%
ValueCountFrequency (%)
734792 1
< 0.1%
237598 1
< 0.1%
225228 1
< 0.1%
150053 1
< 0.1%
127366 1
< 0.1%
86687 1
< 0.1%
84129 1
< 0.1%
77506 1
< 0.1%
69854 1
< 0.1%
68006 1
< 0.1%

2022
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct787
Distinct (%)35.3%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean1568.8781
Minimum0
Maximum650403
Zeros641
Zeros (%)26.8%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:50.465066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median34
Q3403.5
95-th percentile4859.85
Maximum650403
Range650403
Interquartile range (IQR)403.5

Descriptive statistics

Standard deviation15811.562
Coefficient of variation (CV)10.07826
Kurtosis1290.2747
Mean1568.8781
Median Absolute Deviation (MAD)34
Skewness32.94679
Sum3501736
Variance2.500055 × 108
MonotonicityNot monotonic
2024-03-23T03:45:51.069507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 641
26.8%
1 54
 
2.3%
4 36
 
1.5%
2 34
 
1.4%
3 33
 
1.4%
8 23
 
1.0%
7 23
 
1.0%
5 22
 
0.9%
17 21
 
0.9%
12 17
 
0.7%
Other values (777) 1328
55.5%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 641
26.8%
1 54
 
2.3%
2 34
 
1.4%
3 33
 
1.4%
4 36
 
1.5%
5 22
 
0.9%
6 12
 
0.5%
7 23
 
1.0%
8 23
 
1.0%
9 14
 
0.6%
ValueCountFrequency (%)
650403 1
< 0.1%
188598 1
< 0.1%
169725 1
< 0.1%
133978 1
< 0.1%
113688 1
< 0.1%
78795 1
< 0.1%
77681 1
< 0.1%
76477 1
< 0.1%
56402 1
< 0.1%
55738 1
< 0.1%

2023
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct723
Distinct (%)32.3%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean1194.5433
Minimum0
Maximum518596
Zeros686
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-03-23T03:45:51.661241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24
Q3261.25
95-th percentile3601.7
Maximum518596
Range518596
Interquartile range (IQR)261.25

Descriptive statistics

Standard deviation12399.399
Coefficient of variation (CV)10.380033
Kurtosis1367.6652
Mean1194.5433
Median Absolute Deviation (MAD)24
Skewness34.026669
Sum2675777
Variance1.537451 × 108
MonotonicityNot monotonic
2024-03-23T03:45:52.206869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 686
28.7%
1 74
 
3.1%
2 41
 
1.7%
3 35
 
1.5%
4 28
 
1.2%
5 27
 
1.1%
10 22
 
0.9%
8 22
 
0.9%
6 22
 
0.9%
9 19
 
0.8%
Other values (713) 1264
52.8%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 686
28.7%
1 74
 
3.1%
2 41
 
1.7%
3 35
 
1.5%
4 28
 
1.2%
5 27
 
1.1%
6 22
 
0.9%
7 14
 
0.6%
8 22
 
0.9%
9 19
 
0.8%
ValueCountFrequency (%)
518596 1
< 0.1%
123601 1
< 0.1%
123308 1
< 0.1%
102390 1
< 0.1%
91484 1
< 0.1%
71377 1
< 0.1%
61375 1
< 0.1%
57764 1
< 0.1%
49223 1
< 0.1%
47941 1
< 0.1%

Interactions

2024-03-23T03:45:15.657092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:00.734542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:09.310276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:16.839809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:24.558300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:32.631908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:41.075457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:48.463452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:56.073699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:04.035456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:11.799910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:20.637492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:28.580847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:36.184704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:43.722773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:51.912170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:59.986568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:08.817042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:16.192048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:01.166315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:09.754502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:17.207258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:24.961699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:32.951973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:41.530480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:48.780202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:56.395803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:04.419766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:12.303907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:21.135371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:28.881034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:36.515037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:44.104708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:52.599353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:00.392645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:09.438821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:16.544891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:01.538769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:10.345266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:17.550282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:25.356902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:33.304212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:41.887309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:49.217793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:56.835772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:04.715525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:12.689273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:21.534153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:29.217921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:37.004544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:44.553692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:53.117094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:00.860023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:09.852303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:16.953049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:01.948051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:10.722774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:17.875138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:25.811975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:34.056275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:42.363146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:49.614408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:57.281326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:05.099814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:13.185953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:22.048663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:29.693828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:37.454533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:44.996143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:53.744797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:01.400666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:10.191581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:17.323402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:02.470433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:11.071291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:18.168346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:26.335881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:34.495836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:42.774900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:49.962034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:58.024489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:05.426786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:13.639206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:22.431158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:30.015084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:37.736316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:45.297512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:54.272749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:01.827882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:10.483951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:17.747274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:02.901980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:11.524408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:18.612023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:26.837071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:34.884018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:43.223534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:50.418663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:58.527577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:05.844807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:14.196041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:22.969864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:30.448874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:38.191118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:45.769231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:54.866991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:02.302017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:10.834589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:18.246349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:03.312035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:11.940002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:19.120883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:27.295340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:35.268535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:43.677946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:50.844344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:58.875633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:06.232054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:14.698963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:23.523410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:30.844776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:38.756095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:46.249701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:55.228629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:02.742982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:11.174503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:18.697080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:03.677591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:12.322252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:19.537678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:27.635262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:35.699643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:44.074017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:51.400347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:59.172729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:06.623146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:15.329840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:23.982578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:31.196311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:39.221637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:46.727736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:55.632305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:03.275795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:11.473420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:19.036987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:04.108784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:12.697971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:19.881278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:28.122351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:36.094337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:44.665854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:51.761969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:59.491443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:06.987364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:15.832900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:24.393201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:31.502747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:39.736415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:47.134552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:56.035583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:03.622565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:11.812760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:19.391333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:04.515745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:13.095381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:20.363199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:28.617096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:36.615140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:45.076860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:52.188230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:59.873024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:07.374976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:16.278199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:24.773622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:32.075365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:40.078421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:47.475484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:56.351397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:04.088228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:12.235208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:19.866452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:04.861483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:13.573434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:20.762937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:29.066529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:37.136608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:45.464882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:52.643756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:00.314729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:07.756409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:16.683495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:25.244809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:32.481714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:40.422569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:47.874530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:56.681348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:04.614513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:12.645530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:20.300828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:05.432362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:14.003981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:21.293157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:29.466964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:37.488069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:45.923490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:53.028863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:00.903493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:08.221740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:17.177558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:25.662591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:32.995842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:40.841466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:48.319358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:57.087613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:05.398114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:13.054187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:20.760036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:05.964453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:14.327053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:21.745940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:29.988612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:37.932719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:46.294747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:53.438553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:01.469716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:08.650896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:17.854885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:26.117565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:33.645132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:41.135187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:48.767167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:57.458072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:05.906305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:13.446715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:21.207471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:06.485955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:14.771533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:22.221986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:30.459161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:38.344222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:46.730928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:53.751485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:01.986309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:09.164245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:18.200021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:26.524530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:34.119937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:41.482107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:49.156495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:57.766072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:06.319228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:13.831395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:21.616976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:06.862148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:15.183450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:22.599060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:30.857409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:38.864574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:47.164144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:54.197356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:02.342314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:09.592534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:18.569288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:26.986506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:34.508359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:41.887779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:49.624356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:58.250574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:06.783830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:14.234693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:21.951621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:07.626225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:15.558907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:23.080942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:31.299190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:39.375195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:47.480093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:54.578578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:02.826676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:09.987422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:18.988166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:27.399491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:34.898717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:42.615968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:50.181667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:58.754317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:07.222080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:14.657534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:22.455086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:08.146980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:16.080985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:23.730774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:31.638960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:39.957840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:47.761496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:54.950461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:03.280308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:10.346365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:19.682629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:27.864466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:35.371456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:42.922348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:50.778323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:59.191645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:07.695403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:15.008342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:22.849385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:08.941008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:16.460345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:24.130599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:32.109087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:40.431103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:48.097438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:43:55.336944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:03.631476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:11.058243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:20.322624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:28.177150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:35.842668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:43.369140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:51.393824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:44:59.634885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:08.203070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:45:15.310205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T03:45:52.547083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0001.0000.9990.9990.9800.9830.9860.9830.9750.9490.8760.9840.9790.9860.8410.8590.9790.986
20071.0001.0000.9990.9990.9800.9830.9860.9830.9750.9490.8760.9840.9790.9860.8410.8590.9790.986
20080.9990.9991.0000.9960.9880.9910.9940.9910.9850.9490.8760.9840.9790.9860.8680.8590.9790.986
20090.9990.9990.9961.0000.9890.9850.9800.9850.9770.9220.8500.9760.9820.9890.8440.8670.9820.989
20100.9800.9800.9880.9891.0001.0000.9991.0000.9950.8750.9160.9870.9910.9760.9360.8940.9910.976
20110.9830.9830.9910.9851.0001.0001.0000.9990.9910.8860.9270.9900.9850.9680.9200.8700.9850.968
20120.9860.9860.9940.9800.9991.0001.0001.0000.9930.9010.9440.9930.9880.9730.9360.8820.9880.973
20130.9830.9830.9910.9851.0000.9991.0001.0000.9970.8860.9270.9900.9940.9800.9530.9070.9940.980
20140.9750.9750.9850.9770.9950.9910.9930.9971.0000.9190.9190.9970.9990.9930.9490.9440.9990.993
20150.9490.9490.9490.9220.8750.8860.9010.8860.9191.0000.9951.0000.9380.9010.9860.9910.9380.901
20160.8760.8760.8760.8500.9160.9270.9440.9270.9190.9951.0001.0000.9380.9010.9980.9910.9380.901
20170.9840.9840.9840.9760.9870.9900.9930.9900.9971.0001.0001.0000.9990.9930.9070.9380.9990.993
20180.9790.9790.9790.9820.9910.9850.9880.9940.9990.9380.9380.9991.0000.9970.9271.0001.0000.997
20190.9860.9860.9860.9890.9760.9680.9730.9800.9930.9010.9010.9930.9971.0000.8931.0000.9971.000
20200.8410.8410.8680.8440.9360.9200.9360.9530.9490.9860.9980.9070.9270.8931.0000.9900.9270.893
20210.8590.8590.8590.8670.8940.8700.8820.9070.9440.9910.9910.9381.0001.0000.9901.0001.0001.000
20220.9790.9790.9790.9820.9910.9850.9880.9940.9990.9380.9380.9991.0000.9970.9271.0001.0000.997
20230.9860.9860.9860.9890.9760.9680.9730.9800.9930.9010.9010.9930.9971.0000.8931.0000.9971.000
2024-03-23T03:45:53.230641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.9330.9210.9010.8930.8930.8830.8880.8840.8780.8820.8710.8690.8700.8740.8740.8770.871
20070.9331.0000.9390.9180.9080.9160.9020.9070.8990.8950.8930.8870.8850.8810.8860.8860.8850.882
20080.9210.9391.0000.9350.9190.9250.9130.9170.9110.9100.9080.9000.8960.8920.8930.8960.8980.899
20090.9010.9180.9351.0000.9400.9310.9160.9130.9130.9080.9020.8950.8920.8940.8960.8960.8970.895
20100.8930.9080.9190.9401.0000.9430.9220.9220.9120.9090.9060.8960.8930.8930.8970.8900.8910.888
20110.8930.9160.9250.9310.9431.0000.9440.9320.9240.9200.9180.9060.8990.8980.8990.9030.9010.897
20120.8830.9020.9130.9160.9220.9441.0000.9440.9260.9260.9250.9160.9020.9000.9000.9010.9060.903
20130.8880.9070.9170.9130.9220.9320.9441.0000.9410.9310.9260.9190.9100.9050.9020.9020.9090.904
20140.8840.8990.9110.9130.9120.9240.9260.9411.0000.9510.9370.9280.9160.9110.9110.9070.9110.906
20150.8780.8950.9100.9080.9090.9200.9260.9310.9511.0000.9470.9360.9230.9170.9120.9080.9130.911
20160.8820.8930.9080.9020.9060.9180.9250.9260.9370.9471.0000.9480.9310.9250.9220.9140.9170.916
20170.8710.8870.9000.8950.8960.9060.9160.9190.9280.9360.9481.0000.9460.9360.9240.9180.9190.914
20180.8690.8850.8960.8920.8930.8990.9020.9100.9160.9230.9310.9461.0000.9480.9350.9280.9260.919
20190.8700.8810.8920.8940.8930.8980.9000.9050.9110.9170.9250.9360.9481.0000.9400.9340.9310.927
20200.8740.8860.8930.8960.8970.8990.9000.9020.9110.9120.9220.9240.9350.9401.0000.9460.9360.924
20210.8740.8860.8960.8960.8900.9030.9010.9020.9070.9080.9140.9180.9280.9340.9461.0000.9480.929
20220.8770.8850.8980.8970.8910.9010.9060.9090.9110.9130.9170.9190.9260.9310.9360.9481.0000.947
20230.8710.8820.8990.8950.8880.8970.9030.9040.9060.9110.9160.9140.9190.9270.9240.9290.9471.000

Missing values

2024-03-23T03:45:23.553236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T03:45:24.520220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-23T03:45:25.952013image/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_용도지역200620072008200920102011201220132014201520162017201820192020202120222023
0전국_도시지역_주거지역179929110217103076106113108384115743124775117835172207174247222177190220194936192779221333237598188598123308
1전국_도시지역_상업지역729553244657445141485820631265877818895876219542641767617090863659112871
2전국_도시지역_공업지역262864341227480191982856830393305953964340182341383543934142300863148030742324262979719728
3전국_도시지역_녹지지역340207257496252874211394194062181641176122174143189779225681209208204923179438167329200411225228169725123601
4전국_도시지역_개발제한구역571445153343224431873515540903396063634038727472297002848468419823932934501336532430818834
5전국_도시지역_용도미지정631393895350408156711758691078547816212767120921463120415208261605918476289572139114275
6전국_농림지역1127663856500814187942831799177780339679981666281671456745191707794794512758986680397694446734792650403518596
7전국_자연환경보전지역11140580270786651012178184779478590325451857265625335133647191440864403062966475494707049223
8서울_도시지역_주거지역1477660313500329027462336582430224326482648694435493366546530754687662410
9서울_도시지역_상업지역11854202372191901651331521551602195902882013141827566
지역_용도지역200620072008200920102011201220132014201520162017201820192020202120222023
2382제주 제주시_농림지역28534740240425889034846121414211471710
2383제주 제주시_자연환경보전지역1479178212211243676877151116411831234953210814422243944799
2384제주 서귀포시_도시지역_주거지역281455366308455506506713129213931578746622528345412498296
2385제주 서귀포시_도시지역_상업지역273028203835626758619232333418301615
2386제주 서귀포시_도시지역_공업지역8613111489515286162337534
2387제주 서귀포시_도시지역_녹지지역328057833480404539334080516669368375957776515790512839943737432833992618
2388제주 서귀포시_도시지역_개발제한구역000000000000000000
2389제주 서귀포시_도시지역_용도미지정0000010051302001000
2390제주 서귀포시_농림지역31067041441732421014080000020100
2391제주 서귀포시_자연환경보전지역1112282825076402200443412