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(면적) 데이터입니다.- (단위 : 천㎡)- 공표시기 : 익월 말일경
Author한국부동산원
URLhttps://www.data.go.kr/data/15068561/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 = 28.91353393)Skewed
2007 is highly skewed (γ1 = 26.17481326)Skewed
2008 is highly skewed (γ1 = 23.71187947)Skewed
2009 is highly skewed (γ1 = 24.08091865)Skewed
2010 is highly skewed (γ1 = 23.26500053)Skewed
2011 is highly skewed (γ1 = 22.69074691)Skewed
2012 is highly skewed (γ1 = 22.70642114)Skewed
2013 is highly skewed (γ1 = 22.0699735)Skewed
2014 is highly skewed (γ1 = 21.4317067)Skewed
2015 is highly skewed (γ1 = 21.62085828)Skewed
2016 is highly skewed (γ1 = 22.89872986)Skewed
2017 is highly skewed (γ1 = 21.58071579)Skewed
2018 is highly skewed (γ1 = 21.16841663)Skewed
2019 is highly skewed (γ1 = 20.63634389)Skewed
2020 is highly skewed (γ1 = 21.02048591)Skewed
2021 is highly skewed (γ1 = 20.03375268)Skewed
2022 is highly skewed (γ1 = 21.85268752)Skewed
2023 is highly skewed (γ1 = 22.67626543)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 08:15:30.439628
Analysis finished2024-04-06 08:16:55.138426
Duration1 minute and 24.7 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
2024-04-06T17:16:55.542075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length16.527592
Min length9

Characters and Unicode

Total characters39534
Distinct characters156
Distinct categories8 ?
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_661~1000㎡
4th row전국_1001~2000㎡
5th row전국_2001~5000㎡
ValueCountFrequency (%)
경기 416
 
9.0%
경남 208
 
4.5%
경북 200
 
4.3%
서울 200
 
4.3%
전남 176
 
3.8%
충북 152
 
3.3%
충남 152
 
3.3%
강원 144
 
3.1%
부산 128
 
2.8%
전북 128
 
2.8%
Other values (2208) 2728
58.9%
2024-04-06T17:16:56.596611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8970
22.7%
1 2990
 
7.6%
_ 2392
 
6.1%
3 2392
 
6.1%
2392
 
6.1%
2240
 
5.7%
~ 1794
 
4.5%
6 1196
 
3.0%
1128
 
2.9%
976
 
2.5%
Other values (146) 13064
33.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16744
42.4%
Other Letter 13668
34.6%
Connector Punctuation 2392
 
6.1%
Other Symbol 2392
 
6.1%
Space Separator 2240
 
5.7%
Math Symbol 1794
 
4.5%
Open Punctuation 152
 
0.4%
Close 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%
Connector Punctuation
ValueCountFrequency (%)
_ 2392
100.0%
Other Symbol
ValueCountFrequency (%)
2392
100.0%
Space Separator
ValueCountFrequency (%)
2240
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1794
100.0%
Open Punctuation
ValueCountFrequency (%)
( 152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25866
65.4%
Hangul 13668
34.6%

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
34.7%
1 2990
 
11.6%
_ 2392
 
9.2%
3 2392
 
9.2%
2392
 
9.2%
2240
 
8.7%
~ 1794
 
6.9%
6 1196
 
4.6%
5 598
 
2.3%
2 598
 
2.3%
Other values (2) 304
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23474
59.4%
Hangul 13668
34.6%
CJK Compat 2392
 
6.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8970
38.2%
1 2990
 
12.7%
_ 2392
 
10.2%
3 2392
 
10.2%
2240
 
9.5%
~ 1794
 
7.6%
6 1196
 
5.1%
5 598
 
2.5%
2 598
 
2.5%
( 152
 
0.6%
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 

Distinct1477
Distinct (%)66.7%
Missing176
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean4570.8768
Minimum0
Maximum1461825
Zeros23
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:16:56.986218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile29
Q1194
median662.5
Q32062.75
95-th percentile11741.5
Maximum1461825
Range1461825
Interquartile range (IQR)1868.75

Descriptive statistics

Standard deviation37851.054
Coefficient of variation (CV)8.2809177
Kurtosis1029.4589
Mean4570.8768
Median Absolute Deviation (MAD)573.5
Skewness28.913534
Sum10129063
Variance1.4327023 × 109
MonotonicityNot monotonic
2024-04-06T17:16:57.325833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
 
1.0%
29 9
 
0.4%
61 8
 
0.3%
70 8
 
0.3%
65 8
 
0.3%
16 7
 
0.3%
38 7
 
0.3%
99 7
 
0.3%
74 7
 
0.3%
136 6
 
0.3%
Other values (1467) 2126
88.9%
(Missing) 176
 
7.4%
ValueCountFrequency (%)
0 23
1.0%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 2
 
0.1%
9 2
 
0.1%
10 3
 
0.1%
11 4
 
0.2%
ValueCountFrequency (%)
1461825 1
< 0.1%
575411 1
< 0.1%
464378 1
< 0.1%
288438 1
< 0.1%
260234 1
< 0.1%
256412 1
< 0.1%
232667 1
< 0.1%
197211 1
< 0.1%
178630 1
< 0.1%
132865 1
< 0.1%

2007
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1410
Distinct (%)64.8%
Missing216
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean3579.097
Minimum0
Maximum1007659
Zeros31
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:16:57.656793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21.75
Q1158
median569.5
Q31723.5
95-th percentile8458.75
Maximum1007659
Range1007659
Interquartile range (IQR)1565.5

Descriptive statistics

Standard deviation27660.593
Coefficient of variation (CV)7.728372
Kurtosis853.06908
Mean3579.097
Median Absolute Deviation (MAD)502.5
Skewness26.174813
Sum7788115
Variance7.6510839 × 108
MonotonicityNot monotonic
2024-04-06T17:16:57.952290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31
 
1.3%
27 11
 
0.5%
36 11
 
0.5%
28 10
 
0.4%
40 9
 
0.4%
25 9
 
0.4%
42 9
 
0.4%
77 8
 
0.3%
19 8
 
0.3%
48 7
 
0.3%
Other values (1400) 2063
86.2%
(Missing) 216
 
9.0%
ValueCountFrequency (%)
0 31
1.3%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 2
 
0.1%
5 1
 
< 0.1%
6 3
 
0.1%
7 6
 
0.3%
8 5
 
0.2%
9 1
 
< 0.1%
10 2
 
0.1%
ValueCountFrequency (%)
1007659 1
< 0.1%
446152 1
< 0.1%
396684 1
< 0.1%
235205 1
< 0.1%
232280 1
< 0.1%
198957 1
< 0.1%
135381 1
< 0.1%
129374 1
< 0.1%
128120 1
< 0.1%
106818 1
< 0.1%

2008
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1378
Distinct (%)62.9%
Missing200
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean3215.1177
Minimum0
Maximum803736
Zeros51
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:16:58.231016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q1134
median549
Q31713.5
95-th percentile7286.35
Maximum803736
Range803736
Interquartile range (IQR)1579.5

Descriptive statistics

Standard deviation23474.714
Coefficient of variation (CV)7.3013544
Kurtosis699.19239
Mean3215.1177
Median Absolute Deviation (MAD)503
Skewness23.711879
Sum7047538
Variance5.5106219 × 108
MonotonicityNot monotonic
2024-04-06T17:16:58.543730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 51
 
2.1%
36 12
 
0.5%
33 12
 
0.5%
13 12
 
0.5%
34 11
 
0.5%
5 11
 
0.5%
19 10
 
0.4%
31 9
 
0.4%
14 8
 
0.3%
11 8
 
0.3%
Other values (1368) 2048
85.6%
(Missing) 200
 
8.4%
ValueCountFrequency (%)
0 51
2.1%
2 3
 
0.1%
3 1
 
< 0.1%
4 2
 
0.1%
5 11
 
0.5%
6 8
 
0.3%
7 5
 
0.2%
8 1
 
< 0.1%
9 7
 
0.3%
10 6
 
0.3%
ValueCountFrequency (%)
803736 1
< 0.1%
401368 1
< 0.1%
395777 1
< 0.1%
237228 1
< 0.1%
202242 1
< 0.1%
187022 1
< 0.1%
112389 1
< 0.1%
111069 1
< 0.1%
100373 1
< 0.1%
93883 1
< 0.1%

2009
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1370
Distinct (%)62.5%
Missing200
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean3137.5725
Minimum0
Maximum800634
Zeros58
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:16:58.844179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q1131
median539
Q31606.25
95-th percentile6892.75
Maximum800634
Range800634
Interquartile range (IQR)1475.25

Descriptive statistics

Standard deviation23035.241
Coefficient of variation (CV)7.3417396
Kurtosis727.87966
Mean3137.5725
Median Absolute Deviation (MAD)491
Skewness24.080919
Sum6877559
Variance5.3062231 × 108
MonotonicityNot monotonic
2024-04-06T17:16:59.161724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
 
2.4%
13 12
 
0.5%
27 10
 
0.4%
46 10
 
0.4%
8 9
 
0.4%
7 9
 
0.4%
26 9
 
0.4%
29 8
 
0.3%
10 8
 
0.3%
12 8
 
0.3%
Other values (1360) 2051
85.7%
(Missing) 200
 
8.4%
ValueCountFrequency (%)
0 58
2.4%
1 2
 
0.1%
2 2
 
0.1%
4 5
 
0.2%
5 7
 
0.3%
6 8
 
0.3%
7 9
 
0.4%
8 9
 
0.4%
9 6
 
0.3%
10 8
 
0.3%
ValueCountFrequency (%)
800634 1
< 0.1%
388164 1
< 0.1%
369045 1
< 0.1%
229708 1
< 0.1%
181793 1
< 0.1%
171755 1
< 0.1%
114833 1
< 0.1%
114564 1
< 0.1%
111932 1
< 0.1%
96670 1
< 0.1%

2010
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1349
Distinct (%)60.2%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean2687.5179
Minimum0
Maximum655060
Zeros63
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:16:59.513165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q1110.75
median496
Q31460.5
95-th percentile6418.1
Maximum655060
Range655060
Interquartile range (IQR)1349.75

Descriptive statistics

Standard deviation19266.091
Coefficient of variation (CV)7.1687305
Kurtosis675.25338
Mean2687.5179
Median Absolute Deviation (MAD)449.5
Skewness23.265001
Sum6020040
Variance3.7118228 × 108
MonotonicityNot monotonic
2024-04-06T17:16:59.838092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 63
 
2.6%
11 17
 
0.7%
21 14
 
0.6%
15 13
 
0.5%
17 11
 
0.5%
7 11
 
0.5%
20 11
 
0.5%
261 10
 
0.4%
22 10
 
0.4%
34 9
 
0.4%
Other values (1339) 2071
86.6%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 63
2.6%
1 1
 
< 0.1%
2 4
 
0.2%
3 2
 
0.1%
4 4
 
0.2%
5 7
 
0.3%
6 7
 
0.3%
7 11
 
0.5%
8 6
 
0.3%
9 5
 
0.2%
ValueCountFrequency (%)
655060 1
< 0.1%
339578 1
< 0.1%
327869 1
< 0.1%
211706 1
< 0.1%
166723 1
< 0.1%
149864 1
< 0.1%
105946 1
< 0.1%
83579 1
< 0.1%
82670 1
< 0.1%
81862 1
< 0.1%

2011
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1351
Distinct (%)61.0%
Missing176
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean2713.3069
Minimum0
Maximum638579
Zeros72
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:00.179727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q1126
median526
Q31492.5
95-th percentile5987
Maximum638579
Range638579
Interquartile range (IQR)1366.5

Descriptive statistics

Standard deviation19079.223
Coefficient of variation (CV)7.0317232
Kurtosis644.98379
Mean2713.3069
Median Absolute Deviation (MAD)479
Skewness22.690747
Sum6012688
Variance3.6401674 × 108
MonotonicityNot monotonic
2024-04-06T17:17:00.506478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 72
 
3.0%
8 12
 
0.5%
14 11
 
0.5%
7 11
 
0.5%
37 10
 
0.4%
5 10
 
0.4%
19 9
 
0.4%
12 9
 
0.4%
199 9
 
0.4%
29 8
 
0.3%
Other values (1341) 2055
85.9%
(Missing) 176
 
7.4%
ValueCountFrequency (%)
0 72
3.0%
1 1
 
< 0.1%
2 1
 
< 0.1%
4 5
 
0.2%
5 10
 
0.4%
6 4
 
0.2%
7 11
 
0.5%
8 12
 
0.5%
9 5
 
0.2%
10 7
 
0.3%
ValueCountFrequency (%)
638579 1
< 0.1%
340162 1
< 0.1%
316900 1
< 0.1%
212136 1
< 0.1%
166637 1
< 0.1%
135331 1
< 0.1%
122511 1
< 0.1%
96101 1
< 0.1%
88191 1
< 0.1%
86263 1
< 0.1%

2012
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1328
Distinct (%)59.5%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean2493.552
Minimum0
Maximum586948
Zeros64
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:00.912170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q1124
median499.5
Q31368
95-th percentile5528.2
Maximum586948
Range586948
Interquartile range (IQR)1244

Descriptive statistics

Standard deviation17544.65
Coefficient of variation (CV)7.0360075
Kurtosis643.52436
Mean2493.552
Median Absolute Deviation (MAD)446.5
Skewness22.706421
Sum5565608
Variance3.0781476 × 108
MonotonicityNot monotonic
2024-04-06T17:17:01.293601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64
 
2.7%
15 16
 
0.7%
12 12
 
0.5%
11 12
 
0.5%
38 11
 
0.5%
17 10
 
0.4%
13 10
 
0.4%
10 10
 
0.4%
23 9
 
0.4%
9 9
 
0.4%
Other values (1318) 2069
86.5%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 64
2.7%
1 1
 
< 0.1%
2 3
 
0.1%
3 4
 
0.2%
4 3
 
0.1%
5 3
 
0.1%
6 6
 
0.3%
7 6
 
0.3%
8 7
 
0.3%
9 9
 
0.4%
ValueCountFrequency (%)
586948 1
< 0.1%
317181 1
< 0.1%
292546 1
< 0.1%
201779 1
< 0.1%
152757 1
< 0.1%
137226 1
< 0.1%
106347 1
< 0.1%
84234 1
< 0.1%
81945 1
< 0.1%
78021 1
< 0.1%

2013
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1325
Distinct (%)59.4%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean2499.763
Minimum0
Maximum564959
Zeros64
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:01.634100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q1119.75
median512
Q31380
95-th percentile5619.45
Maximum564959
Range564959
Interquartile range (IQR)1260.25

Descriptive statistics

Standard deviation17324.01
Coefficient of variation (CV)6.930261
Kurtosis602.76256
Mean2499.763
Median Absolute Deviation (MAD)458
Skewness22.069974
Sum5579471
Variance3.0012132 × 108
MonotonicityNot monotonic
2024-04-06T17:17:01.945852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64
 
2.7%
5 11
 
0.5%
9 10
 
0.4%
15 10
 
0.4%
25 10
 
0.4%
13 9
 
0.4%
16 9
 
0.4%
12 9
 
0.4%
21 9
 
0.4%
10 9
 
0.4%
Other values (1315) 2082
87.0%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 64
2.7%
2 1
 
< 0.1%
3 2
 
0.1%
4 4
 
0.2%
5 11
 
0.5%
6 9
 
0.4%
7 5
 
0.2%
8 9
 
0.4%
9 10
 
0.4%
10 9
 
0.4%
ValueCountFrequency (%)
564959 1
< 0.1%
325767 1
< 0.1%
297223 1
< 0.1%
206229 1
< 0.1%
152937 1
< 0.1%
132871 1
< 0.1%
113364 1
< 0.1%
84305 1
< 0.1%
81939 1
< 0.1%
63754 1
< 0.1%

2014
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1388
Distinct (%)60.7%
Missing104
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean2633.333
Minimum0
Maximum576874
Zeros71
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:02.236891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q1137.75
median552.5
Q31479.25
95-th percentile5813.25
Maximum576874
Range576874
Interquartile range (IQR)1341.5

Descriptive statistics

Standard deviation18096.823
Coefficient of variation (CV)6.8722122
Kurtosis564.25541
Mean2633.333
Median Absolute Deviation (MAD)492.5
Skewness21.431707
Sum6025066
Variance3.2749502 × 108
MonotonicityNot monotonic
2024-04-06T17:17:02.543519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71
 
3.0%
33 13
 
0.5%
10 12
 
0.5%
6 12
 
0.5%
26 11
 
0.5%
38 10
 
0.4%
35 9
 
0.4%
17 9
 
0.4%
21 8
 
0.3%
32 7
 
0.3%
Other values (1378) 2126
88.9%
(Missing) 104
 
4.3%
ValueCountFrequency (%)
0 71
3.0%
3 4
 
0.2%
4 6
 
0.3%
5 4
 
0.2%
6 12
 
0.5%
7 5
 
0.2%
8 3
 
0.1%
9 5
 
0.2%
10 12
 
0.5%
11 6
 
0.3%
ValueCountFrequency (%)
576874 1
< 0.1%
355752 1
< 0.1%
321078 1
< 0.1%
227851 1
< 0.1%
168154 1
< 0.1%
136744 1
< 0.1%
134161 1
< 0.1%
94462 1
< 0.1%
90451 1
< 0.1%
78839 1
< 0.1%

2015
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1416
Distinct (%)62.8%
Missing136
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean2963.8435
Minimum0
Maximum653927
Zeros55
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:03.316453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.75
Q1162.75
median641
Q31678.25
95-th percentile6592.5
Maximum653927
Range653927
Interquartile range (IQR)1515.5

Descriptive statistics

Standard deviation20266.709
Coefficient of variation (CV)6.8379821
Kurtosis579.31608
Mean2963.8435
Median Absolute Deviation (MAD)564
Skewness21.620858
Sum6686431
Variance4.1073949 × 108
MonotonicityNot monotonic
2024-04-06T17:17:03.578857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 55
 
2.3%
26 10
 
0.4%
32 9
 
0.4%
20 9
 
0.4%
8 9
 
0.4%
45 8
 
0.3%
11 8
 
0.3%
14 8
 
0.3%
25 7
 
0.3%
15 7
 
0.3%
Other values (1406) 2126
88.9%
(Missing) 136
 
5.7%
ValueCountFrequency (%)
0 55
2.3%
4 3
 
0.1%
5 3
 
0.1%
6 2
 
0.1%
7 1
 
< 0.1%
8 9
 
0.4%
9 6
 
0.3%
10 5
 
0.2%
11 8
 
0.3%
12 6
 
0.3%
ValueCountFrequency (%)
653927 1
< 0.1%
386797 1
< 0.1%
342126 1
< 0.1%
251418 1
< 0.1%
180791 1
< 0.1%
164274 1
< 0.1%
155741 1
< 0.1%
107420 1
< 0.1%
102737 1
< 0.1%
86281 1
< 0.1%

2016
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1432
Distinct (%)63.5%
Missing136
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean2966.3839
Minimum0
Maximum702437
Zeros59
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:03.858553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.75
Q1159
median607.5
Q31633.25
95-th percentile6623.5
Maximum702437
Range702437
Interquartile range (IQR)1474.25

Descriptive statistics

Standard deviation20734.468
Coefficient of variation (CV)6.9898127
Kurtosis659.51869
Mean2966.3839
Median Absolute Deviation (MAD)530.5
Skewness22.89873
Sum6692162
Variance4.2991815 × 108
MonotonicityNot monotonic
2024-04-06T17:17:04.293182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 59
 
2.5%
12 10
 
0.4%
31 9
 
0.4%
26 8
 
0.3%
24 8
 
0.3%
5 7
 
0.3%
34 7
 
0.3%
18 7
 
0.3%
20 7
 
0.3%
25 7
 
0.3%
Other values (1422) 2127
88.9%
(Missing) 136
 
5.7%
ValueCountFrequency (%)
0 59
2.5%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 3
 
0.1%
5 7
 
0.3%
6 5
 
0.2%
7 5
 
0.2%
8 5
 
0.2%
9 4
 
0.2%
10 3
 
0.1%
ValueCountFrequency (%)
702437 1
< 0.1%
370077 1
< 0.1%
336682 1
< 0.1%
237369 1
< 0.1%
176218 1
< 0.1%
161140 1
< 0.1%
149666 1
< 0.1%
105161 1
< 0.1%
98349 1
< 0.1%
97268 1
< 0.1%

2017
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1441
Distinct (%)64.6%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean3031.9839
Minimum0
Maximum666563
Zeros60
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:04.770749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q1175
median648
Q31726.5
95-th percentile7035
Maximum666563
Range666563
Interquartile range (IQR)1551.5

Descriptive statistics

Standard deviation20700.377
Coefficient of variation (CV)6.8273374
Kurtosis577.60245
Mean3031.9839
Median Absolute Deviation (MAD)568.5
Skewness21.580716
Sum6767388
Variance4.285056 × 108
MonotonicityNot monotonic
2024-04-06T17:17:05.132270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60
 
2.5%
27 10
 
0.4%
60 9
 
0.4%
7 9
 
0.4%
45 8
 
0.3%
218 8
 
0.3%
35 8
 
0.3%
14 8
 
0.3%
10 7
 
0.3%
9 7
 
0.3%
Other values (1431) 2098
87.7%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 60
2.5%
2 3
 
0.1%
3 3
 
0.1%
4 1
 
< 0.1%
5 2
 
0.1%
6 2
 
0.1%
7 9
 
0.4%
8 6
 
0.3%
9 7
 
0.3%
10 7
 
0.3%
ValueCountFrequency (%)
666563 1
< 0.1%
378924 1
< 0.1%
364384 1
< 0.1%
245081 1
< 0.1%
185227 1
< 0.1%
173118 1
< 0.1%
158411 1
< 0.1%
106631 1
< 0.1%
100908 1
< 0.1%
80454 1
< 0.1%

2018
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1386
Distinct (%)61.9%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean2831.9094
Minimum0
Maximum610207
Zeros50
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:05.463432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q1163
median582.5
Q31621.25
95-th percentile6167.05
Maximum610207
Range610207
Interquartile range (IQR)1458.25

Descriptive statistics

Standard deviation19322.917
Coefficient of variation (CV)6.8232823
Kurtosis552.11342
Mean2831.9094
Median Absolute Deviation (MAD)517.5
Skewness21.168417
Sum6343477
Variance3.7337513 × 108
MonotonicityNot monotonic
2024-04-06T17:17:05.832125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 50
 
2.1%
16 10
 
0.4%
43 10
 
0.4%
27 9
 
0.4%
18 9
 
0.4%
37 9
 
0.4%
63 8
 
0.3%
26 8
 
0.3%
29 8
 
0.3%
22 8
 
0.3%
Other values (1376) 2111
88.3%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 50
2.1%
3 1
 
< 0.1%
4 2
 
0.1%
5 7
 
0.3%
6 7
 
0.3%
7 4
 
0.2%
8 4
 
0.2%
9 6
 
0.3%
10 7
 
0.3%
11 7
 
0.3%
ValueCountFrequency (%)
610207 1
< 0.1%
367775 1
< 0.1%
348242 1
< 0.1%
227567 1
< 0.1%
178268 1
< 0.1%
149896 1
< 0.1%
147487 1
< 0.1%
96470 1
< 0.1%
92563 1
< 0.1%
88205 1
< 0.1%

2019
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1366
Distinct (%)61.2%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean2576.6344
Minimum0
Maximum529569
Zeros58
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:06.220359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q1158.75
median557.5
Q31478
95-th percentile5255.3
Maximum529569
Range529569
Interquartile range (IQR)1319.25

Descriptive statistics

Standard deviation17234.063
Coefficient of variation (CV)6.6885945
Kurtosis520.32213
Mean2576.6344
Median Absolute Deviation (MAD)489.5
Skewness20.636344
Sum5751048
Variance2.9701292 × 108
MonotonicityNot monotonic
2024-04-06T17:17:06.653398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
 
2.4%
10 14
 
0.6%
13 12
 
0.5%
45 11
 
0.5%
29 11
 
0.5%
26 9
 
0.4%
38 9
 
0.4%
28 9
 
0.4%
19 9
 
0.4%
201 7
 
0.3%
Other values (1356) 2083
87.1%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 58
2.4%
2 1
 
< 0.1%
3 2
 
0.1%
4 2
 
0.1%
5 3
 
0.1%
6 6
 
0.3%
7 3
 
0.1%
8 5
 
0.2%
9 6
 
0.3%
10 14
 
0.6%
ValueCountFrequency (%)
529569 1
< 0.1%
340968 1
< 0.1%
311660 1
< 0.1%
214142 1
< 0.1%
163247 1
< 0.1%
135189 1
< 0.1%
114055 1
< 0.1%
88943 1
< 0.1%
85860 1
< 0.1%
73824 1
< 0.1%

2020
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1417
Distinct (%)63.5%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean2824.4023
Minimum0
Maximum601568
Zeros65
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:06.942569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.55
Q1175
median614.5
Q31594.5
95-th percentile5823.9
Maximum601568
Range601568
Interquartile range (IQR)1419.5

Descriptive statistics

Standard deviation19024.378
Coefficient of variation (CV)6.7357181
Kurtosis549.33014
Mean2824.4023
Median Absolute Deviation (MAD)531.5
Skewness21.020486
Sum6304066
Variance3.6192695 × 108
MonotonicityNot monotonic
2024-04-06T17:17:07.236333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65
 
2.7%
16 10
 
0.4%
19 9
 
0.4%
40 9
 
0.4%
47 9
 
0.4%
14 8
 
0.3%
41 7
 
0.3%
42 7
 
0.3%
15 7
 
0.3%
29 7
 
0.3%
Other values (1407) 2094
87.5%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 65
2.7%
2 3
 
0.1%
5 2
 
0.1%
6 3
 
0.1%
7 3
 
0.1%
8 5
 
0.2%
9 3
 
0.1%
10 7
 
0.3%
11 5
 
0.2%
12 4
 
0.2%
ValueCountFrequency (%)
601568 1
< 0.1%
370526 1
< 0.1%
311329 1
< 0.1%
238307 1
< 0.1%
170229 1
< 0.1%
161852 1
< 0.1%
128788 1
< 0.1%
101431 1
< 0.1%
95538 1
< 0.1%
80933 1
< 0.1%

2021
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1424
Distinct (%)63.8%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean3020.3678
Minimum0
Maximum594504
Zeros49
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:07.519348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q1197
median655
Q31729.75
95-th percentile6264.6
Maximum594504
Range594504
Interquartile range (IQR)1532.75

Descriptive statistics

Standard deviation19943.988
Coefficient of variation (CV)6.6031654
Kurtosis486.38945
Mean3020.3678
Median Absolute Deviation (MAD)567
Skewness20.033753
Sum6741461
Variance3.9776268 × 108
MonotonicityNot monotonic
2024-04-06T17:17:07.785254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49
 
2.0%
42 10
 
0.4%
27 8
 
0.3%
45 7
 
0.3%
28 7
 
0.3%
38 7
 
0.3%
12 7
 
0.3%
13 7
 
0.3%
133 6
 
0.3%
68 6
 
0.3%
Other values (1414) 2118
88.5%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 49
2.0%
2 2
 
0.1%
3 1
 
< 0.1%
4 2
 
0.1%
5 5
 
0.2%
6 3
 
0.1%
8 4
 
0.2%
9 5
 
0.2%
10 3
 
0.1%
11 6
 
0.3%
ValueCountFrequency (%)
594504 1
< 0.1%
408189 1
< 0.1%
355376 1
< 0.1%
267708 1
< 0.1%
195191 1
< 0.1%
149374 1
< 0.1%
136876 1
< 0.1%
115372 1
< 0.1%
109152 1
< 0.1%
81254 1
< 0.1%

2022
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1324
Distinct (%)59.3%
Missing160
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean2470.819
Minimum0
Maximum551185
Zeros58
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:08.094056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q1130.75
median481.5
Q31378.25
95-th percentile5251.6
Maximum551185
Range551185
Interquartile range (IQR)1247.5

Descriptive statistics

Standard deviation16999.69
Coefficient of variation (CV)6.8801844
Kurtosis591.95252
Mean2470.819
Median Absolute Deviation (MAD)425
Skewness21.852688
Sum5514868
Variance2.8898947 × 108
MonotonicityNot monotonic
2024-04-06T17:17:08.420348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
 
2.4%
12 13
 
0.5%
22 11
 
0.5%
16 11
 
0.5%
14 11
 
0.5%
25 11
 
0.5%
59 10
 
0.4%
26 10
 
0.4%
18 10
 
0.4%
35 9
 
0.4%
Other values (1314) 2078
86.9%
(Missing) 160
 
6.7%
ValueCountFrequency (%)
0 58
2.4%
2 2
 
0.1%
3 2
 
0.1%
4 2
 
0.1%
5 4
 
0.2%
6 6
 
0.3%
7 4
 
0.2%
8 9
 
0.4%
9 9
 
0.4%
10 2
 
0.1%
ValueCountFrequency (%)
551185 1
< 0.1%
315573 1
< 0.1%
297935 1
< 0.1%
202137 1
< 0.1%
158600 1
< 0.1%
120677 1
< 0.1%
100669 1
< 0.1%
87260 1
< 0.1%
81997 1
< 0.1%
74208 1
< 0.1%

2023
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1185
Distinct (%)52.9%
Missing152
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean1866.096
Minimum0
Maximum439553
Zeros79
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size21.2 KiB
2024-04-06T17:17:08.746001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q190
median368
Q31015
95-th percentile3961.5
Maximum439553
Range439553
Interquartile range (IQR)925

Descriptive statistics

Standard deviation13126.381
Coefficient of variation (CV)7.0341405
Kurtosis643.74595
Mean1866.096
Median Absolute Deviation (MAD)331
Skewness22.676265
Sum4180055
Variance1.7230189 × 108
MonotonicityNot monotonic
2024-04-06T17:17:09.008395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 79
 
3.3%
12 21
 
0.9%
16 15
 
0.6%
5 14
 
0.6%
8 13
 
0.5%
23 13
 
0.5%
15 12
 
0.5%
53 12
 
0.5%
19 11
 
0.5%
7 11
 
0.5%
Other values (1175) 2039
85.2%
(Missing) 152
 
6.4%
ValueCountFrequency (%)
0 79
3.3%
1 1
 
< 0.1%
2 4
 
0.2%
3 10
 
0.4%
4 7
 
0.3%
5 14
 
0.6%
6 8
 
0.3%
7 11
 
0.5%
8 13
 
0.5%
9 9
 
0.4%
ValueCountFrequency (%)
439553 1
< 0.1%
237817 1
< 0.1%
220779 1
< 0.1%
144981 1
< 0.1%
116576 1
< 0.1%
94504 1
< 0.1%
82919 1
< 0.1%
66108 1
< 0.1%
61406 1
< 0.1%
58382 1
< 0.1%

Interactions

2024-04-06T17:16:49.330097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:36.188036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:40.410766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:44.895611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:49.676999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:53.554393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:57.664488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:01.966192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:06.687693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:10.863873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:14.932029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:19.718403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:24.300034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:28.892406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:33.383414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:37.189330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:42.019661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:45.823226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:49.536916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:36.495025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:40.662821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:45.100104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:49.895554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:53.780990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:57.896156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:02.184150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:07.000064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.047719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:15.171134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:19.967487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:24.621131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:29.107793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:33.616645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:37.410743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:42.331563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:46.018334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:49.724741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:36.685374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:40.892935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:45.297405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:50.098915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:53.974379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:58.212089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:02.540714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:07.209622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.240392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:15.370257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:20.181077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:24.823904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:29.313987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:33.796902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:37.707762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:42.561837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:46.207235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.084920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:36.927866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:41.196955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:45.508331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:50.302950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:54.188017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:58.878617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:02.878804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:07.426762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.448396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:15.585354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:20.422290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:25.091761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:29.525182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:34.023375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:37.961928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:42.838025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:46.436473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.329651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:37.222334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:41.460558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:46.127462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:50.514345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:54.531952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:59.192052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:03.149154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:07.656317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.675954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:15.854571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:20.689696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:25.344221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:29.751647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:34.250118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:38.261774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:43.073773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:46.641262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.512252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:37.516486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:41.740537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:46.335908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:50.704071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:54.870473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:59.443871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:03.371462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:07.871937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.878448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:16.084284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:20.970060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:25.560347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:29.983328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:34.497505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:38.468834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:43.279773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:46.829626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.701404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:37.732611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:41.996633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:46.663285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:50.891961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:55.161575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:59.710183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:03.602994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:08.057343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:12.065895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:16.362286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:21.260238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:25.777929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:30.285629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:34.803733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:38.666953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:43.486975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:47.067907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.894046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:37.946793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:42.295860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:46.875885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:51.103429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:55.392433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:59.901107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:03.800884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:08.267787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:12.669799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:16.625663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:21.481189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:26.018656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:30.482422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:34.993973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:38.938304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:43.687683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:47.274174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.094794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.128512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:42.575327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:47.082123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:51.347627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:55.683630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:00.200956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:04.058147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:08.606588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:12.868893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:16.858365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:21.691171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:26.733723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:30.663607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:35.181567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:39.292439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:43.894031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:47.443442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.265410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.331241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:42.929398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:47.423664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:51.629406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:55.895168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:00.369285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:04.309806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:08.921083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:13.055698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:17.061900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:22.084364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:26.993632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:30.908694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:35.394656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:39.670175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:44.114879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:47.622862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.461199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.523578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:43.177874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:47.721607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:51.858078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:56.109238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:00.534193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:04.548475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:09.140531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:13.232615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:17.454960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:22.386984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:27.192542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:31.149648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:35.589638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:39.932870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:44.324242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:47.799672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.689818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.741655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:43.443330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:47.986998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:52.076791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:56.385137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:00.725495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:04.850657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:09.420575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:13.420725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:17.778614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:22.621075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:27.430235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:31.478681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:35.771606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:40.162247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:44.516602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:47.996134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.874479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.977837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:43.617547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:48.231616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:52.254889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:56.605905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:00.910395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:05.132826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:09.614554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:13.638259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:18.021440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:22.898780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:27.686163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:31.858908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:35.963116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:40.765897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:44.702841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:48.214686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:52.055077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:39.204670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:43.834603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:48.503004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:52.467525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:56.789827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:01.082023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:05.426074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:09.831762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:13.810592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:18.278554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:23.181955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:27.918633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:32.183599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:36.163137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:40.947927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:44.879823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:48.404024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:52.218713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:39.403677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:44.012060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:48.848662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:52.673128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:56.946605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:01.264488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:05.718163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:10.033180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:14.066393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:18.556044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:23.429252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:28.096300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:32.460175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:36.355574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:41.190358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:45.064318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:48.585185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:52.431951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:39.693971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:44.185491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:49.056889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:52.895730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:57.116739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:01.488616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:05.970673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:10.222013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:14.317761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:18.805795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:23.689170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:28.293038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:32.702848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:36.540950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:41.415804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:45.245080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:48.783290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:52.682138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:39.984465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:44.438164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:49.249751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:53.126954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:57.295177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:01.667370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:06.210467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:10.409360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:14.498353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:19.057532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:23.886255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:28.500641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:32.919997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:36.747779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:41.635082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:45.421201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:48.970858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:52.868220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:40.222593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:44.673527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:49.448570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:53.327010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:57.487553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:01.822471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:06.422555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:10.667071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:14.756654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:19.265971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:24.104266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:28.698876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:33.150337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:36.977133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:41.824956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:45.625654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:49.155312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:17:09.361871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.9990.9380.9330.9900.9400.9400.9910.9330.9910.9330.9910.9310.9970.9410.9960.9880.989
20070.9991.0000.9330.9280.9810.9520.9520.9830.9510.9830.9510.9830.9500.9710.9560.9660.9790.980
20080.9380.9331.0001.0000.9630.9550.9550.9520.9380.9520.9380.9520.9320.9460.9430.9400.9470.956
20090.9330.9281.0001.0000.9750.9660.9660.9630.9510.9440.9320.9440.9260.9400.9360.9360.9550.966
20100.9900.9810.9630.9751.0000.9860.9860.9980.9720.9970.9590.9970.9550.9650.9520.9601.0001.000
20110.9400.9520.9550.9660.9861.0001.0000.9610.9990.9610.9990.9610.9990.9720.9980.9690.9821.000
20120.9400.9520.9550.9660.9861.0001.0000.9610.9990.9610.9990.9610.9990.9720.9980.9690.9821.000
20130.9910.9830.9520.9630.9980.9610.9611.0000.9851.0000.9711.0000.9670.9830.9740.9780.9970.998
20140.9330.9510.9380.9510.9720.9990.9990.9851.0000.9711.0000.9710.9990.9760.9990.9730.9590.967
20150.9910.9830.9520.9440.9970.9610.9611.0000.9711.0000.9851.0000.9780.9930.9860.9900.9970.998
20160.9330.9510.9380.9320.9590.9990.9990.9711.0000.9851.0000.9851.0000.9821.0000.9790.9590.967
20170.9910.9830.9520.9440.9970.9610.9611.0000.9711.0000.9851.0000.9780.9930.9860.9900.9970.998
20180.9310.9500.9320.9260.9550.9990.9990.9670.9990.9781.0000.9781.0000.9851.0000.9770.9550.961
20190.9970.9710.9460.9400.9650.9720.9720.9830.9760.9930.9820.9930.9851.0000.9881.0000.9710.969
20200.9410.9560.9430.9360.9520.9980.9980.9740.9990.9861.0000.9861.0000.9881.0000.9870.9600.957
20210.9960.9660.9400.9360.9600.9690.9690.9780.9730.9900.9790.9900.9771.0000.9871.0000.9680.965
20220.9880.9790.9470.9551.0000.9820.9820.9970.9590.9970.9590.9970.9550.9710.9600.9681.0001.000
20230.9890.9800.9560.9661.0001.0001.0000.9980.9670.9980.9670.9980.9610.9690.9570.9651.0001.000
2024-04-06T17:17:09.781183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.9400.9240.9100.9030.9040.8990.9020.8980.9110.9100.9050.9080.9010.8980.9050.8870.894
20070.9401.0000.9550.9370.9380.9330.9360.9340.9330.9340.9330.9350.9370.9230.9230.9270.9230.924
20080.9240.9551.0000.9520.9450.9410.9470.9380.9410.9450.9400.9410.9370.9340.9270.9320.9260.924
20090.9100.9370.9521.0000.9660.9610.9590.9520.9510.9540.9530.9560.9530.9470.9460.9530.9490.950
20100.9030.9380.9450.9661.0000.9650.9580.9560.9490.9480.9490.9550.9510.9430.9470.9480.9450.948
20110.9040.9330.9410.9610.9651.0000.9660.9660.9560.9560.9510.9570.9460.9400.9450.9500.9400.948
20120.8990.9360.9470.9590.9580.9661.0000.9660.9630.9600.9550.9550.9470.9420.9430.9480.9450.948
20130.9020.9340.9380.9520.9560.9660.9661.0000.9680.9620.9570.9610.9530.9410.9430.9470.9440.946
20140.8980.9330.9410.9510.9490.9560.9630.9681.0000.9690.9580.9600.9490.9480.9450.9400.9380.935
20150.9110.9340.9450.9540.9480.9560.9600.9620.9691.0000.9690.9670.9550.9510.9520.9520.9430.942
20160.9100.9330.9400.9530.9490.9510.9550.9570.9580.9691.0000.9700.9620.9560.9580.9560.9490.951
20170.9050.9350.9410.9560.9550.9570.9550.9610.9600.9670.9701.0000.9690.9620.9660.9600.9560.956
20180.9080.9370.9370.9530.9510.9460.9470.9530.9490.9550.9620.9691.0000.9600.9590.9580.9500.956
20190.9010.9230.9340.9470.9430.9400.9420.9410.9480.9510.9560.9620.9601.0000.9630.9560.9430.948
20200.8980.9230.9270.9460.9470.9450.9430.9430.9450.9520.9580.9660.9590.9631.0000.9600.9510.953
20210.9050.9270.9320.9530.9480.9500.9480.9470.9400.9520.9560.9600.9580.9560.9601.0000.9640.958
20220.8870.9230.9260.9490.9450.9400.9450.9440.9380.9430.9490.9560.9500.9430.9510.9641.0000.962
20230.8940.9240.9240.9500.9480.9480.9480.9460.9350.9420.9510.9560.9560.9480.9530.9580.9621.000

Missing values

2024-04-06T17:16:53.564346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:16:54.097836image/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.
2024-04-06T17:16:54.595550image/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㎡이하12657010681811106911193210594612251110634711336413416115574114966615841114989613518916185214937410066982919
1전국_331~660㎡90162837798520886857817478819184234843059446210742010516110663196470889431014311153728726061406
2전국_661~1000㎡994019066790904913358357985413819458193990451102737983491009089256385860955381091528199758382
3전국_1001~2000㎡260234235205237228229708211706212136201779206229227851251418237369245081227567214142238307267708202137144981
4전국_2001~5000㎡464378396684401368369045339578340162317181325767355752386797370077378924367775340968370526408189315573237817
5전국_5001~10000㎡256412198957187022181793166723166637152757152937168154180791176218185227178268163247170229195191158600116576
6전국_10001~33000㎡575411446152395777388164327869316900292546297223321078342126336682364384348242311660311329355376297935220779
7전국_33000㎡초과14618251007659803736800634655060638579586948564959576874653927702437666563610207529569601568594504551185439553
8서울_330㎡이하18151111391090510037717182636429781810774148671496414436130371055413007998052485315
9서울_331~660㎡1509123292012058728477337799231187119111271182114714231276782400
지역_거래규모200620072008200920102011201220132014201520162017201820192020202120222023
2382제주 제주시_10001~33000㎡359845333129340233362090292429495184675554063200324427272377246422471597
2383제주 제주시_33000㎡초과1177094166310257677375009285244596406765261474750432330892254435238473492
2384제주 서귀포시_330㎡이하23149542640442952064176311421646159313621100771692839790558
2385제주 서귀포시_331~660㎡4298626446377298449441216166923722161154712709198341058906619
2386제주 서귀포시_661~1000㎡51310136907257768891089127616572379175212381049763688829743515
2387제주 서귀포시_1001~2000㎡162227711846214020472179237830494146494136932898238719211841209016561211
2388제주 서귀포시_2001~5000㎡4662772449296050547954375854721099861158990216963616851034193482541533017
2389제주 서귀포시_5001~10000㎡283245823497379932573487348240276297825157764392351832552512281621481863
2390제주 서귀포시_10001~33000㎡237947223387300224132412250632264839679842163627260718482047182314981240
2391제주 서귀포시_33000㎡초과5628264239183046122626924945111211065573593396113053598116065112724347