Overview

Dataset statistics

Number of variables19
Number of observations299
Missing cells365
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.8 KiB
Average record size in memory170.4 B

Variable types

Text1
Numeric18

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산거래현황 중 건축물 거래현황의 연도별 행정구역별(동(호)수) 데이터입니다.- (단위 : 동(호)수)- 공표시기 : 익월 말일경
Author한국부동산원
URLhttps://www.data.go.kr/data/15048974/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 22 (7.4%) missing valuesMissing
2007 has 27 (9.0%) missing valuesMissing
2008 has 25 (8.4%) missing valuesMissing
2009 has 25 (8.4%) missing valuesMissing
2010 has 19 (6.4%) missing valuesMissing
2011 has 22 (7.4%) missing valuesMissing
2012 has 20 (6.7%) missing valuesMissing
2013 has 20 (6.7%) missing valuesMissing
2014 has 13 (4.3%) missing valuesMissing
2015 has 17 (5.7%) missing valuesMissing
2016 has 17 (5.7%) missing valuesMissing
2017 has 20 (6.7%) missing valuesMissing
2018 has 19 (6.4%) missing valuesMissing
2019 has 20 (6.7%) missing valuesMissing
2020 has 20 (6.7%) missing valuesMissing
2021 has 20 (6.7%) missing valuesMissing
2022 has 20 (6.7%) missing valuesMissing
2023 has 19 (6.4%) missing valuesMissing
지역 has unique valuesUnique

Reproduction

Analysis started2024-03-23 03:51:08.055539
Analysis finished2024-03-23 03:53:20.277914
Duration2 minutes and 12.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Text

UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-23T03:53:20.953874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length6
Mean length6.3712375
Min length2

Characters and Unicode

Total characters1905
Distinct characters147
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)100.0%

Sample

1st row전국
2nd row서울
3rd row서울 종로구
4th row서울 중구
5th row서울 용산구
ValueCountFrequency (%)
경기 53
 
8.6%
경남 27
 
4.4%
경북 26
 
4.2%
서울 26
 
4.2%
전남 23
 
3.7%
충남 20
 
3.2%
충북 20
 
3.2%
강원 19
 
3.1%
전북 17
 
2.8%
부산 17
 
2.8%
Other values (263) 368
59.7%
2024-03-23T03:53:22.389457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
317
 
16.6%
138
 
7.2%
122
 
6.4%
109
 
5.7%
93
 
4.9%
89
 
4.7%
72
 
3.8%
56
 
2.9%
50
 
2.6%
48
 
2.5%
Other values (137) 811
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1556
81.7%
Space Separator 317
 
16.6%
Open Punctuation 16
 
0.8%
Close Punctuation 16
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
138
 
8.9%
122
 
7.8%
109
 
7.0%
93
 
6.0%
89
 
5.7%
72
 
4.6%
56
 
3.6%
50
 
3.2%
48
 
3.1%
47
 
3.0%
Other values (134) 732
47.0%
Space Separator
ValueCountFrequency (%)
317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1556
81.7%
Common 349
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
138
 
8.9%
122
 
7.8%
109
 
7.0%
93
 
6.0%
89
 
5.7%
72
 
4.6%
56
 
3.6%
50
 
3.2%
48
 
3.1%
47
 
3.0%
Other values (134) 732
47.0%
Common
ValueCountFrequency (%)
317
90.8%
( 16
 
4.6%
) 16
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1556
81.7%
ASCII 349
 
18.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317
90.8%
( 16
 
4.6%
) 16
 
4.6%
Hangul
ValueCountFrequency (%)
138
 
8.9%
122
 
7.8%
109
 
7.0%
93
 
6.0%
89
 
5.7%
72
 
4.6%
56
 
3.6%
50
 
3.2%
48
 
3.1%
47
 
3.0%
Other values (134) 732
47.0%

2006
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct273
Distinct (%)98.6%
Missing22
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean19250.783
Minimum116
Maximum1679408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:23.067787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum116
5-th percentile306
Q1990
median6141
Q313615
95-th percentile43780.8
Maximum1679408
Range1679292
Interquartile range (IQR)12625

Descriptive statistics

Standard deviation107711.31
Coefficient of variation (CV)5.5951649
Kurtosis207.90449
Mean19250.783
Median Absolute Deviation (MAD)5377
Skewness13.832235
Sum5332467
Variance1.1601726 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:23.609776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14462 2
 
0.7%
485 2
 
0.7%
6141 2
 
0.7%
911 2
 
0.7%
42817 1
 
0.3%
7098 1
 
0.3%
8702 1
 
0.3%
10861 1
 
0.3%
19563 1
 
0.3%
1083 1
 
0.3%
Other values (263) 263
88.0%
(Missing) 22
 
7.4%
ValueCountFrequency (%)
116 1
0.3%
159 1
0.3%
182 1
0.3%
194 1
0.3%
207 1
0.3%
213 1
0.3%
240 1
0.3%
246 1
0.3%
252 1
0.3%
255 1
0.3%
ValueCountFrequency (%)
1679408 1
0.3%
502383 1
0.3%
379713 1
0.3%
109523 1
0.3%
95199 1
0.3%
83218 1
0.3%
71082 1
0.3%
65349 1
0.3%
55588 1
0.3%
53990 1
0.3%

2007
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct269
Distinct (%)98.9%
Missing27
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean15619.919
Minimum140
Maximum1354274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:24.257069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum140
5-th percentile308.75
Q11026.75
median5255.5
Q39889.5
95-th percentile35141.75
Maximum1354274
Range1354134
Interquartile range (IQR)8862.75

Descriptive statistics

Standard deviation86610.093
Coefficient of variation (CV)5.544849
Kurtosis213.45957
Mean15619.919
Median Absolute Deviation (MAD)4278
Skewness14.053013
Sum4248618
Variance7.5013082 × 109
MonotonicityNot monotonic
2024-03-23T03:53:24.869070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
782 2
 
0.7%
42448 2
 
0.7%
507 2
 
0.7%
861 1
 
0.3%
7009 1
 
0.3%
9319 1
 
0.3%
16328 1
 
0.3%
38769 1
 
0.3%
6864 1
 
0.3%
1325 1
 
0.3%
Other values (259) 259
86.6%
(Missing) 27
 
9.0%
ValueCountFrequency (%)
140 1
0.3%
158 1
0.3%
192 1
0.3%
218 1
0.3%
233 1
0.3%
234 1
0.3%
266 1
0.3%
275 1
0.3%
276 1
0.3%
281 1
0.3%
ValueCountFrequency (%)
1354274 1
0.3%
358839 1
0.3%
262441 1
0.3%
124900 1
0.3%
82265 1
0.3%
78474 1
0.3%
59169 1
0.3%
56937 1
0.3%
53563 1
0.3%
42448 2
0.7%

2008
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct270
Distinct (%)98.5%
Missing25
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean15666.887
Minimum117
Maximum1368059
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:25.723282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum117
5-th percentile354.2
Q11360
median5265.5
Q39459.5
95-th percentile38227.65
Maximum1368059
Range1367942
Interquartile range (IQR)8099.5

Descriptive statistics

Standard deviation86563.465
Coefficient of variation (CV)5.5252499
Kurtosis220.87052
Mean15666.887
Median Absolute Deviation (MAD)4111
Skewness14.322851
Sum4292727
Variance7.4932334 × 109
MonotonicityNot monotonic
2024-03-23T03:53:26.374065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
517 2
 
0.7%
2920 2
 
0.7%
2448 2
 
0.7%
795 2
 
0.7%
927 1
 
0.3%
2252 1
 
0.3%
699 1
 
0.3%
788 1
 
0.3%
22076 1
 
0.3%
245 1
 
0.3%
Other values (260) 260
87.0%
(Missing) 25
 
8.4%
ValueCountFrequency (%)
117 1
0.3%
216 1
0.3%
229 1
0.3%
230 1
0.3%
235 1
0.3%
239 1
0.3%
245 1
0.3%
272 1
0.3%
278 1
0.3%
292 1
0.3%
ValueCountFrequency (%)
1368059 1
0.3%
328966 1
0.3%
239758 1
0.3%
127423 1
0.3%
91813 1
0.3%
90671 1
0.3%
64577 1
0.3%
59635 1
0.3%
55058 1
0.3%
54436 1
0.3%

2009
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct272
Distinct (%)99.3%
Missing25
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean15123.825
Minimum158
Maximum1306976
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:27.104720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum158
5-th percentile337.75
Q11344
median4765.5
Q39759.5
95-th percentile37931.45
Maximum1306976
Range1306818
Interquartile range (IQR)8415.5

Descriptive statistics

Standard deviation82764.17
Coefficient of variation (CV)5.4724364
Kurtosis220.16649
Mean15123.825
Median Absolute Deviation (MAD)3807.5
Skewness14.300603
Sum4143928
Variance6.8499078 × 109
MonotonicityNot monotonic
2024-03-23T03:53:27.791108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1869 2
 
0.7%
243 2
 
0.7%
1009 1
 
0.3%
1668 1
 
0.3%
2869 1
 
0.3%
899 1
 
0.3%
1083 1
 
0.3%
326 1
 
0.3%
12140 1
 
0.3%
1893 1
 
0.3%
Other values (262) 262
87.6%
(Missing) 25
 
8.4%
ValueCountFrequency (%)
158 1
0.3%
199 1
0.3%
215 1
0.3%
243 2
0.7%
252 1
0.3%
261 1
0.3%
282 1
0.3%
289 1
0.3%
314 1
0.3%
319 1
0.3%
ValueCountFrequency (%)
1306976 1
0.3%
331411 1
0.3%
215421 1
0.3%
102346 1
0.3%
90229 1
0.3%
88361 1
0.3%
60861 1
0.3%
57868 1
0.3%
57411 1
0.3%
51605 1
0.3%

2010
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct279
Distinct (%)99.6%
Missing19
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean13736.504
Minimum130
Maximum1212605
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:28.471918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum130
5-th percentile362.45
Q11239.75
median4622
Q39144.25
95-th percentile40632.9
Maximum1212605
Range1212475
Interquartile range (IQR)7904.5

Descriptive statistics

Standard deviation75442.644
Coefficient of variation (CV)5.4921286
Kurtosis231.16583
Mean13736.504
Median Absolute Deviation (MAD)3694
Skewness14.692067
Sum3846221
Variance5.6915925 × 109
MonotonicityNot monotonic
2024-03-23T03:53:29.185017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4238 2
 
0.7%
10849 1
 
0.3%
1153 1
 
0.3%
1417 1
 
0.3%
1974 1
 
0.3%
8351 1
 
0.3%
9573 1
 
0.3%
8678 1
 
0.3%
19527 1
 
0.3%
299 1
 
0.3%
Other values (269) 269
90.0%
(Missing) 19
 
6.4%
ValueCountFrequency (%)
130 1
0.3%
213 1
0.3%
228 1
0.3%
239 1
0.3%
252 1
0.3%
260 1
0.3%
266 1
0.3%
282 1
0.3%
289 1
0.3%
299 1
0.3%
ValueCountFrequency (%)
1212605 1
0.3%
283182 1
0.3%
154353 1
0.3%
114850 1
0.3%
100946 1
0.3%
73470 1
0.3%
60588 1
0.3%
58774 1
0.3%
55079 1
0.3%
46628 1
0.3%

2011
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct274
Distinct (%)98.9%
Missing22
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean16470.838
Minimum181
Maximum1434147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:29.722521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum181
5-th percentile413.8
Q11584
median5542
Q310512
95-th percentile47927.4
Maximum1434147
Range1433966
Interquartile range (IQR)8928

Descriptive statistics

Standard deviation89488.933
Coefficient of variation (CV)5.4331744
Kurtosis230.71768
Mean16470.838
Median Absolute Deviation (MAD)4439
Skewness14.68728
Sum4562422
Variance8.0082691 × 109
MonotonicityNot monotonic
2024-03-23T03:53:30.327251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
592 2
 
0.7%
3031 2
 
0.7%
596 2
 
0.7%
11980 1
 
0.3%
11492 1
 
0.3%
19410 1
 
0.3%
55639 1
 
0.3%
4838 1
 
0.3%
1299 1
 
0.3%
1803 1
 
0.3%
Other values (264) 264
88.3%
(Missing) 22
 
7.4%
ValueCountFrequency (%)
181 1
0.3%
242 1
0.3%
264 1
0.3%
301 1
0.3%
305 1
0.3%
316 1
0.3%
326 1
0.3%
332 1
0.3%
333 1
0.3%
335 1
0.3%
ValueCountFrequency (%)
1434147 1
0.3%
316563 1
0.3%
183334 1
0.3%
131429 1
0.3%
103625 1
0.3%
94615 1
0.3%
80206 1
0.3%
78693 1
0.3%
72938 1
0.3%
57628 1
0.3%

2012
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct275
Distinct (%)98.6%
Missing20
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean13583.065
Minimum169
Maximum1193691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:31.249001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169
5-th percentile349.9
Q11366.5
median4648
Q38607.5
95-th percentile38014.2
Maximum1193691
Range1193522
Interquartile range (IQR)7241

Descriptive statistics

Standard deviation74114.6
Coefficient of variation (CV)5.4563976
Kurtosis233.71813
Mean13583.065
Median Absolute Deviation (MAD)3430
Skewness14.792931
Sum3789675
Variance5.4929739 × 109
MonotonicityNot monotonic
2024-03-23T03:53:31.996510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6965 3
 
1.0%
878 2
 
0.7%
1224 2
 
0.7%
41884 1
 
0.3%
6297 1
 
0.3%
9772 1
 
0.3%
6941 1
 
0.3%
16713 1
 
0.3%
1278 1
 
0.3%
1853 1
 
0.3%
Other values (265) 265
88.6%
(Missing) 20
 
6.7%
ValueCountFrequency (%)
169 1
0.3%
211 1
0.3%
255 1
0.3%
265 1
0.3%
266 1
0.3%
272 1
0.3%
314 1
0.3%
325 1
0.3%
328 1
0.3%
338 1
0.3%
ValueCountFrequency (%)
1193691 1
0.3%
256360 1
0.3%
151169 1
0.3%
104711 1
0.3%
87341 1
0.3%
77962 1
0.3%
73959 1
0.3%
66494 1
0.3%
63503 1
0.3%
46196 1
0.3%

2013
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct273
Distinct (%)97.8%
Missing20
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean15864.52
Minimum122
Maximum1390443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:33.291860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum122
5-th percentile406.3
Q11270
median5438
Q310167
95-th percentile42097.2
Maximum1390443
Range1390321
Interquartile range (IQR)8897

Descriptive statistics

Standard deviation86590.798
Coefficient of variation (CV)5.4581418
Kurtosis230.96249
Mean15864.52
Median Absolute Deviation (MAD)4323
Skewness14.685349
Sum4426201
Variance7.4979663 × 109
MonotonicityNot monotonic
2024-03-23T03:53:34.475178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1149 2
 
0.7%
726 2
 
0.7%
9083 2
 
0.7%
679 2
 
0.7%
4340 2
 
0.7%
381 2
 
0.7%
464 1
 
0.3%
10452 1
 
0.3%
903 1
 
0.3%
4682 1
 
0.3%
Other values (263) 263
88.0%
(Missing) 20
 
6.7%
ValueCountFrequency (%)
122 1
0.3%
257 1
0.3%
275 1
0.3%
280 1
0.3%
326 1
0.3%
349 1
0.3%
353 1
0.3%
364 1
0.3%
372 1
0.3%
374 1
0.3%
ValueCountFrequency (%)
1390443 1
0.3%
311785 1
0.3%
192289 1
0.3%
127221 1
0.3%
109928 1
0.3%
90604 1
0.3%
81565 1
0.3%
75848 1
0.3%
58677 1
0.3%
54777 1
0.3%

2014
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct281
Distinct (%)98.3%
Missing13
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean18925.748
Minimum111
Maximum1692400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:35.686415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111
5-th percentile457.75
Q11826.75
median6160
Q312976.75
95-th percentile48279.75
Maximum1692400
Range1692289
Interquartile range (IQR)11150

Descriptive statistics

Standard deviation104250.77
Coefficient of variation (CV)5.5084095
Kurtosis235.56171
Mean18925.748
Median Absolute Deviation (MAD)5056
Skewness14.8249
Sum5412764
Variance1.0868223 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:36.750679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19461 2
 
0.7%
4877 2
 
0.7%
10745 2
 
0.7%
758 2
 
0.7%
433 2
 
0.7%
12779 1
 
0.3%
22505 1
 
0.3%
52816 1
 
0.3%
2267 1
 
0.3%
1713 1
 
0.3%
Other values (271) 271
90.6%
(Missing) 13
 
4.3%
ValueCountFrequency (%)
111 1
0.3%
273 1
0.3%
286 1
0.3%
378 1
0.3%
386 1
0.3%
389 1
0.3%
399 1
0.3%
420 1
0.3%
433 2
0.7%
436 1
0.3%
ValueCountFrequency (%)
1692400 1
0.3%
386050 1
0.3%
251753 1
0.3%
151904 1
0.3%
133204 1
0.3%
100573 1
0.3%
96504 1
0.3%
88616 1
0.3%
74267 1
0.3%
67097 1
0.3%

2015
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct278
Distinct (%)98.6%
Missing17
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean22824.333
Minimum119
Maximum2015827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:37.945184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum119
5-th percentile451.1
Q11820.75
median7640.5
Q315375
95-th percentile49615.15
Maximum2015827
Range2015708
Interquartile range (IQR)13554.25

Descriptive statistics

Standard deviation125775.16
Coefficient of variation (CV)5.5105731
Kurtosis227.08591
Mean22824.333
Median Absolute Deviation (MAD)6390
Skewness14.526706
Sum6436462
Variance1.581939 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:38.921771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39775 2
 
0.7%
385 2
 
0.7%
818 2
 
0.7%
15375 2
 
0.7%
9713 1
 
0.3%
10766 1
 
0.3%
12018 1
 
0.3%
22784 1
 
0.3%
53370 1
 
0.3%
1688 1
 
0.3%
Other values (268) 268
89.6%
(Missing) 17
 
5.7%
ValueCountFrequency (%)
119 1
0.3%
280 1
0.3%
295 1
0.3%
325 1
0.3%
354 1
0.3%
385 2
0.7%
414 1
0.3%
420 1
0.3%
425 1
0.3%
427 1
0.3%
ValueCountFrequency (%)
2015827 1
0.3%
498790 1
0.3%
343644 1
0.3%
187257 1
0.3%
135779 1
0.3%
124755 1
0.3%
105113 1
0.3%
101315 1
0.3%
78071 1
0.3%
62525 1
0.3%

2016
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct278
Distinct (%)98.6%
Missing17
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean21844.447
Minimum148
Maximum1937529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:40.558363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148
5-th percentile471.05
Q11863.5
median7231
Q314169
95-th percentile45816.65
Maximum1937529
Range1937381
Interquartile range (IQR)12305.5

Descriptive statistics

Standard deviation121596.42
Coefficient of variation (CV)5.5664682
Kurtosis222.20559
Mean21844.447
Median Absolute Deviation (MAD)5885
Skewness14.350134
Sum6160134
Variance1.4785689 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:42.232822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
862 2
 
0.7%
25209 2
 
0.7%
2492 2
 
0.7%
464 2
 
0.7%
1597 1
 
0.3%
13939 1
 
0.3%
10128 1
 
0.3%
24067 1
 
0.3%
52045 1
 
0.3%
4778 1
 
0.3%
Other values (268) 268
89.6%
(Missing) 17
 
5.7%
ValueCountFrequency (%)
148 1
0.3%
283 1
0.3%
320 1
0.3%
330 1
0.3%
365 1
0.3%
368 1
0.3%
377 1
0.3%
382 1
0.3%
396 1
0.3%
423 1
0.3%
ValueCountFrequency (%)
1937529 1
0.3%
524046 1
0.3%
354682 1
0.3%
162630 1
0.3%
129259 1
0.3%
118051 1
0.3%
81397 1
0.3%
77347 1
0.3%
73312 1
0.3%
69126 1
0.3%

2017
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct277
Distinct (%)99.3%
Missing20
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean25139.022
Minimum136
Maximum2208529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:43.219573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum136
5-th percentile512.8
Q11836
median7924
Q316209
95-th percentile53655.6
Maximum2208529
Range2208393
Interquartile range (IQR)14373

Descriptive statistics

Standard deviation139819.21
Coefficient of variation (CV)5.5618398
Kurtosis217.13475
Mean25139.022
Median Absolute Deviation (MAD)6603
Skewness14.181112
Sum7013787
Variance1.9549412 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:43.841887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3626 2
 
0.7%
37489 2
 
0.7%
1450 1
 
0.3%
6665 1
 
0.3%
14020 1
 
0.3%
12612 1
 
0.3%
26632 1
 
0.3%
56780 1
 
0.3%
2412 1
 
0.3%
1471 1
 
0.3%
Other values (267) 267
89.3%
(Missing) 20
 
6.7%
ValueCountFrequency (%)
136 1
0.3%
276 1
0.3%
345 1
0.3%
355 1
0.3%
360 1
0.3%
363 1
0.3%
398 1
0.3%
416 1
0.3%
428 1
0.3%
439 1
0.3%
ValueCountFrequency (%)
2208529 1
0.3%
647982 1
0.3%
374120 1
0.3%
166219 1
0.3%
161772 1
0.3%
134109 1
0.3%
90090 1
0.3%
89647 1
0.3%
83876 1
0.3%
69134 1
0.3%

2018
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct279
Distinct (%)99.6%
Missing19
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean24557.093
Minimum119
Maximum2159022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:44.492637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum119
5-th percentile518.45
Q11827.5
median8218
Q315119
95-th percentile64376.95
Maximum2159022
Range2158903
Interquartile range (IQR)13291.5

Descriptive statistics

Standard deviation137476.11
Coefficient of variation (CV)5.5982239
Kurtosis212.18417
Mean24557.093
Median Absolute Deviation (MAD)6582.5
Skewness14.014415
Sum6875986
Variance1.8899679 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:45.131232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33672 2
 
0.7%
1357 1
 
0.3%
9257 1
 
0.3%
10139 1
 
0.3%
19722 1
 
0.3%
15137 1
 
0.3%
34859 1
 
0.3%
67340 1
 
0.3%
1646 1
 
0.3%
2544 1
 
0.3%
Other values (269) 269
90.0%
(Missing) 19
 
6.4%
ValueCountFrequency (%)
119 1
0.3%
280 1
0.3%
286 1
0.3%
383 1
0.3%
392 1
0.3%
406 1
0.3%
409 1
0.3%
446 1
0.3%
448 1
0.3%
452 1
0.3%
ValueCountFrequency (%)
2159022 1
0.3%
712355 1
0.3%
347608 1
0.3%
150006 1
0.3%
132851 1
0.3%
95294 1
0.3%
88223 1
0.3%
78557 1
0.3%
74264 1
0.3%
71255 1
0.3%

2019
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct276
Distinct (%)98.9%
Missing20
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean22165.047
Minimum134
Maximum1944924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:45.801660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum134
5-th percentile483.7
Q11642
median6722
Q314583.5
95-th percentile53699.7
Maximum1944924
Range1944790
Interquartile range (IQR)12941.5

Descriptive statistics

Standard deviation123582.27
Coefficient of variation (CV)5.5755475
Kurtosis214.41348
Mean22165.047
Median Absolute Deviation (MAD)5578
Skewness14.093595
Sum6184048
Variance1.5272577 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:46.465235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
481 3
 
1.0%
23828 2
 
0.7%
1810 1
 
0.3%
17314 1
 
0.3%
9732 1
 
0.3%
27046 1
 
0.3%
54930 1
 
0.3%
1545 1
 
0.3%
2156 1
 
0.3%
6722 1
 
0.3%
Other values (266) 266
89.0%
(Missing) 20
 
6.7%
ValueCountFrequency (%)
134 1
0.3%
309 1
0.3%
310 1
0.3%
320 1
0.3%
350 1
0.3%
357 1
0.3%
373 1
0.3%
376 1
0.3%
377 1
0.3%
420 1
0.3%
ValueCountFrequency (%)
1944924 1
0.3%
617710 1
0.3%
285081 1
0.3%
157412 1
0.3%
135797 1
0.3%
98217 1
0.3%
95175 1
0.3%
70230 1
0.3%
64418 1
0.3%
61805 1
0.3%

2020
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct277
Distinct (%)99.3%
Missing20
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean27816.756
Minimum192
Maximum2438446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:46.995289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192
5-th percentile570
Q12004
median9045
Q318161.5
95-th percentile62599.8
Maximum2438446
Range2438254
Interquartile range (IQR)16157.5

Descriptive statistics

Standard deviation154372.69
Coefficient of variation (CV)5.5496293
Kurtosis217.23428
Mean27816.756
Median Absolute Deviation (MAD)7378
Skewness14.190062
Sum7760875
Variance2.3830926 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:47.670627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7030 2
 
0.7%
28911 2
 
0.7%
2290 1
 
0.3%
9626 1
 
0.3%
10028 1
 
0.3%
14560 1
 
0.3%
15335 1
 
0.3%
29895 1
 
0.3%
68403 1
 
0.3%
2014 1
 
0.3%
Other values (267) 267
89.3%
(Missing) 20
 
6.7%
ValueCountFrequency (%)
192 1
0.3%
318 1
0.3%
329 1
0.3%
366 1
0.3%
419 1
0.3%
436 1
0.3%
444 1
0.3%
493 1
0.3%
497 1
0.3%
498 1
0.3%
ValueCountFrequency (%)
2438446 1
0.3%
735158 1
0.3%
355610 1
0.3%
201492 1
0.3%
195788 1
0.3%
131277 1
0.3%
126242 1
0.3%
97923 1
0.3%
86807 1
0.3%
76446 1
0.3%

2021
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct278
Distinct (%)99.6%
Missing20
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean24116.982
Minimum276
Maximum2114309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:48.208759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum276
5-th percentile612.9
Q12260
median8116
Q315219
95-th percentile52582.9
Maximum2114309
Range2114033
Interquartile range (IQR)12959

Descriptive statistics

Standard deviation133536.84
Coefficient of variation (CV)5.5370459
Kurtosis219.20485
Mean24116.982
Median Absolute Deviation (MAD)6057
Skewness14.267229
Sum6728638
Variance1.7832087 × 1010
MonotonicityNot monotonic
2024-03-23T03:53:48.772665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17307 2
 
0.7%
1807 1
 
0.3%
11471 1
 
0.3%
12351 1
 
0.3%
11007 1
 
0.3%
10988 1
 
0.3%
21995 1
 
0.3%
62905 1
 
0.3%
2137 1
 
0.3%
4242 1
 
0.3%
Other values (268) 268
89.6%
(Missing) 20
 
6.7%
ValueCountFrequency (%)
276 1
0.3%
331 1
0.3%
348 1
0.3%
371 1
0.3%
413 1
0.3%
423 1
0.3%
439 1
0.3%
516 1
0.3%
535 1
0.3%
542 1
0.3%
ValueCountFrequency (%)
2114309 1
0.3%
628275 1
0.3%
282891 1
0.3%
188619 1
0.3%
132349 1
0.3%
128563 1
0.3%
114227 1
0.3%
103287 1
0.3%
84080 1
0.3%
79121 1
0.3%

2022
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct272
Distinct (%)97.5%
Missing20
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean14630.663
Minimum166
Maximum1287796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:49.293619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum166
5-th percentile499.5
Q11846
median4412
Q38933
95-th percentile32037.5
Maximum1287796
Range1287630
Interquartile range (IQR)7087

Descriptive statistics

Standard deviation80999.661
Coefficient of variation (CV)5.5362946
Kurtosis222.67721
Mean14630.663
Median Absolute Deviation (MAD)3144
Skewness14.397094
Sum4081955
Variance6.560945 × 109
MonotonicityNot monotonic
2024-03-23T03:53:49.920304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2160 2
 
0.7%
2611 2
 
0.7%
1188 2
 
0.7%
8948 2
 
0.7%
5257 2
 
0.7%
1000 2
 
0.7%
4246 2
 
0.7%
2248 1
 
0.3%
6742 1
 
0.3%
16581 1
 
0.3%
Other values (262) 262
87.6%
(Missing) 20
 
6.7%
ValueCountFrequency (%)
166 1
0.3%
258 1
0.3%
307 1
0.3%
315 1
0.3%
318 1
0.3%
356 1
0.3%
375 1
0.3%
418 1
0.3%
459 1
0.3%
462 1
0.3%
ValueCountFrequency (%)
1287796 1
0.3%
366465 1
0.3%
156258 1
0.3%
109128 1
0.3%
81679 1
0.3%
74729 1
0.3%
73125 1
0.3%
69438 1
0.3%
54037 1
0.3%
51974 1
0.3%

2023
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct276
Distinct (%)98.6%
Missing19
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean13078.961
Minimum116
Maximum1154649
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-23T03:53:50.544258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum116
5-th percentile419
Q11368.75
median4082.5
Q37688.25
95-th percentile32959
Maximum1154649
Range1154533
Interquartile range (IQR)6319.5

Descriptive statistics

Standard deviation72466.68
Coefficient of variation (CV)5.5407063
Kurtosis223.75434
Mean13078.961
Median Absolute Deviation (MAD)3045
Skewness14.427644
Sum3662109
Variance5.2514197 × 109
MonotonicityNot monotonic
2024-03-23T03:53:51.151963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
675 2
 
0.7%
7502 2
 
0.7%
419 2
 
0.7%
2605 2
 
0.7%
940 1
 
0.3%
868 1
 
0.3%
1084 1
 
0.3%
379 1
 
0.3%
7942 1
 
0.3%
4073 1
 
0.3%
Other values (266) 266
89.0%
(Missing) 19
 
6.4%
ValueCountFrequency (%)
116 1
0.3%
122 1
0.3%
144 1
0.3%
225 1
0.3%
251 1
0.3%
267 1
0.3%
270 1
0.3%
289 1
0.3%
326 1
0.3%
352 1
0.3%
ValueCountFrequency (%)
1154649 1
0.3%
320990 1
0.3%
159000 1
0.3%
85929 1
0.3%
75847 1
0.3%
66097 1
0.3%
63918 1
0.3%
55269 1
0.3%
45897 1
0.3%
45790 1
0.3%

Interactions

2024-03-23T03:53:10.796926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:10.329024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:19.652561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:26.525301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:31.693012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:37.903897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:44.368875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:51.593045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:58.849533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:06.040740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:13.006377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:20.531999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:28.715050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:36.632368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:43.539986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:49.979827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:56.798466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:03.907857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:11.090379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:10.816971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:19.993552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:26.806382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:32.020214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:38.186856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:44.773633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:52.021260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:59.368958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:06.368938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:13.381638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:20.827469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:29.078051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:36.964882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:43.956656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:50.350985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:57.106279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:04.204113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:11.376123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:11.260255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:20.265827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:27.124565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:32.335657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:38.546789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:45.132241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:52.407102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:59.794315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:06.717892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:13.748095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:21.370170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:29.466627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:37.440658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:44.296864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:50.753299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:57.405838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:04.584592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:11.693065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:11.795124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:20.670164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:27.396609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:32.640308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:38.907990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:45.575792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:52.754047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:00.212461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:07.126503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:14.232539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:21.833434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:29.816720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:37.829550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:44.627122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:51.032465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:57.755319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:04.987683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:11.969857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:12.314319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:21.004802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:27.662725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:32.945727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:39.362844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:45.867512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:53.086513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:00.822814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:07.497098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:14.690976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:22.365368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:30.214028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:38.124556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:45.004883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:51.298985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:58.291780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:05.537354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:12.238944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:12.838080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:21.363259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:27.928544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:33.256257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:39.627048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:46.279076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:53.422326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:01.096200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:07.976265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:15.046100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:23.107869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:30.617495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:38.463378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:45.372395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:51.559047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:58.719991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:06.068084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:12.592438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:13.341944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:21.821647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:28.212593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:33.545767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:39.994601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:46.733451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:53.855474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:01.392998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:08.404367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:15.753101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:23.775484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:31.193668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:38.826575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:45.778350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:51.952136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:59.114541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:06.419643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:13.019244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:13.882129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:22.130198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:28.499530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:33.950749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:40.330025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:47.133073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:54.309917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:01.742352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:08.801967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:16.096556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:24.320229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:31.699414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:39.463919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:46.159530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:52.326548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:59.552363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:06.818238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:13.570302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:14.547168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:22.603222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:28.771459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:34.497836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:40.699339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:47.511748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:55.038285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:02.247745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:09.127166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:16.412184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:25.034090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:32.258971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:39.855505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:46.497635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:52.685051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:59.956410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:07.228105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:13.989258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:14.936692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:23.128497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:29.062046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:34.755867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:41.079907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:47.971320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:55.422643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:02.699079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:09.557433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:16.776807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:25.527375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:32.670958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:40.243084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:46.926560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:53.108545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:00.792058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:07.608214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:14.363870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:16.271832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:23.766670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:29.356677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:35.148877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:41.421801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:48.272114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:55.810307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:03.063572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:09.934088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:17.204240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:25.977734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:33.491507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:40.732033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:47.330063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:53.583199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:01.161827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:08.024219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:14.848258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:16.838506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:24.217650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:29.654260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:35.591654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:41.943342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:48.747045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:56.168280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:03.477247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:10.295062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:17.679790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:26.329542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:33.764051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:41.042180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:47.647392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:53.949107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:01.591448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:08.390459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:15.207594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:17.355883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:24.636235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:29.904697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:35.872613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:42.294177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:49.028266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:56.646904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:03.813297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:10.638470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:18.084426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:26.642323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:33.988783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:41.282442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:47.994251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:54.285647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:01.908871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:08.642095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:15.609805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:17.809343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:25.020802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:30.141791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:36.133241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:42.617595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:49.440146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:56.945341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:04.266091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:11.057200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:18.442194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:26.980334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:34.675731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:41.540992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:48.312562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:54.650347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:02.226290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:09.067614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:15.948016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:18.222654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:25.324818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:30.414818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:36.430341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:43.025959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:49.763044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:57.291029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:04.632488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:11.431487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:18.854773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:27.426103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:35.168611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:41.974538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:48.718322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:55.189638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:02.609687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:09.461587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:16.263180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:18.642494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:25.584559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:30.787366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:36.860451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:43.298230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:50.155996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:57.585497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:04.908939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:11.760774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:19.329744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:27.735686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:35.426651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:42.347519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:49.045201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:55.515653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:02.981391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:09.776994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:16.583045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:18.919657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:25.957543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:31.033259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:37.185641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:43.593097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:50.733687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:58.007744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:05.186208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:12.168203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:19.649572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:27.980282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:35.906331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:42.685791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:49.352930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:55.873125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:03.265211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:10.140822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:16.968811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:19.222715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:26.262166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:31.297295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:37.558054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:43.983481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:51.160418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:51:58.322880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:05.633610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:12.629425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:20.071506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:28.384974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:36.234612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:43.166288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:49.677152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:52:56.362648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:03.642203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T03:53:10.499033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T03:53:51.466284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20071.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20081.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20091.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20101.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20111.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20121.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20131.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20141.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20151.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20161.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20171.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20181.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20191.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20201.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20211.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20221.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20231.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-23T03:53:52.071951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
200620072008200920102011201220132014201520162017201820192020202120222023
20061.0000.9620.9450.9510.9200.9220.9190.9220.9260.9420.9350.9300.9320.9340.9450.9190.8760.904
20070.9621.0000.9750.9630.9430.9420.9380.9360.9360.9430.9340.9280.9230.9240.9350.9270.9020.915
20080.9450.9751.0000.9660.9450.9500.9460.9440.9390.9410.9330.9250.9190.9220.9310.9270.9000.912
20090.9510.9630.9661.0000.9680.9660.9610.9620.9590.9610.9450.9390.9350.9390.9490.9330.9060.937
20100.9200.9430.9450.9681.0000.9760.9700.9650.9540.9440.9260.9220.9200.9280.9340.9280.9020.926
20110.9220.9420.9500.9660.9761.0000.9810.9730.9660.9520.9260.9270.9180.9320.9390.9290.9090.928
20120.9190.9380.9460.9610.9700.9811.0000.9820.9680.9560.9310.9280.9230.9330.9430.9370.9140.931
20130.9220.9360.9440.9620.9650.9730.9821.0000.9760.9670.9400.9400.9310.9380.9470.9300.9040.928
20140.9260.9360.9390.9590.9540.9660.9680.9761.0000.9840.9560.9560.9400.9470.9560.9370.9110.930
20150.9420.9430.9410.9610.9440.9520.9560.9670.9841.0000.9740.9670.9530.9540.9630.9380.9110.930
20160.9350.9340.9330.9450.9260.9260.9310.9400.9560.9741.0000.9800.9660.9610.9600.9440.9140.932
20170.9300.9280.9250.9390.9220.9270.9280.9400.9560.9670.9801.0000.9730.9700.9690.9520.9230.946
20180.9320.9230.9190.9350.9200.9180.9230.9310.9400.9530.9660.9731.0000.9770.9690.9530.9290.943
20190.9340.9240.9220.9390.9280.9320.9330.9380.9470.9540.9610.9700.9771.0000.9780.9470.9210.948
20200.9450.9350.9310.9490.9340.9390.9430.9470.9560.9630.9600.9690.9690.9781.0000.9600.9250.952
20210.9190.9270.9270.9330.9280.9290.9370.9300.9370.9380.9440.9520.9530.9470.9601.0000.9540.953
20220.8760.9020.9000.9060.9020.9090.9140.9040.9110.9110.9140.9230.9290.9210.9250.9541.0000.953
20230.9040.9150.9120.9370.9260.9280.9310.9280.9300.9300.9320.9460.9430.9480.9520.9530.9531.000

Missing values

2024-03-23T03:53:17.652805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T03:53:18.505795image/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.
2024-03-23T03:53:19.186936image/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

지역200620072008200920102011201220132014201520162017201820192020202120222023
0전국167940813542741368059130697612126051434147119369113904431692400201582719375292208529215902219449242438446211430912877961154649
1서울379713262441239758215421154353183334151169192289251753343644354682374120347608285081355610282891156258159000
2서울 종로구830178426606455833263437341742924389519053106382498548306589563334522600
3서울 중구9753112279465767059295779584558577110767775156796706864027345818251203253
4서울 용산구1319388066746556142383803298938975434763483461064210935676510370850846583241
5서울 성동구12102606558546830412149034015559782011179711693122739723794110962757148015749
6서울 광진구10608716257305981382945864630439763899293895410769932395808547769542464471
7서울 동대문구1222111036811672625283688749426633101061301913085121171521115787152949679702113081
8서울 중랑구103348779740648134099564749316547994712283119821094710504846812043960457294781
9서울 성북구192761197110565923367918074589476099513147541419514143152941555113703972747037460
지역200620072008200920102011201220132014201520162017201820192020202120222023
289경남 거창군88483211769059421068107611571505132122601509156611781298215922481044
290경남 합천군492507480556779672734747856938743889797764861884707599
291(구)제주6141<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
292(구)제주 (구)제주시4327<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
293(구)제주 (구)서귀포시673<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
294(구)제주 (구)북제주군737<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
295(구)제주 (구)남제주군404<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296제주560698759427102451406115338161041901021165263852871032021295191958019970234691962213507
297제주 제주시4626758169797917115791212112830146701532416223179602203519639129181399416359138819197
298제주 서귀포시9802294244823282482321732744340584110162107509986988066625976711057414310