Overview

Dataset statistics

Number of variables20
Number of observations6435
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1005.6 KiB
Average record size in memory160.0 B

Variable types

NUM20

Reproduction

Analysis started2020-08-25 01:48:43.321098
Analysis finished2020-08-25 01:49:43.537782
Duration1 minute and 0.22 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

A31 is highly correlated with A27 and 1 other fieldsHigh correlation
A27 is highly correlated with A31High correlation
A32 is highly correlated with A36 and 2 other fieldsHigh correlation
A36 is highly correlated with A32 and 1 other fieldsHigh correlation
A13 is highly correlated with A17 and 2 other fieldsHigh correlation
A17 is highly correlated with A13 and 3 other fieldsHigh correlation
A9 is highly correlated with A17 and 1 other fieldsHigh correlation
A18 is highly correlated with A14 and 4 other fieldsHigh correlation
A14 is highly correlated with A18 and 2 other fieldsHigh correlation
A22 is highly correlated with A18 and 3 other fieldsHigh correlation
A10 is highly correlated with A22 and 2 other fieldsHigh correlation
A35 is highly correlated with A31High correlation
A1 is highly correlated with A17 and 2 other fieldsHigh correlation
A5 is highly correlated with A17 and 3 other fieldsHigh correlation
A30 is highly correlated with A14 and 2 other fieldsHigh correlation
A16 is highly correlated with A32 and 1 other fieldsHigh correlation
A20 is highly correlated with A36 and 2 other fieldsHigh correlation
A6 is highly correlated with A14 and 3 other fieldsHigh correlation

Variables

A36
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count104
Unique (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.5053613053613
Minimum29.0
Maximum157.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:43.583546image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile57
Q168
median81
Q392
95-th percentile125
Maximum157
Range128
Interquartile range (IQR)24

Descriptive statistics

Standard deviation19.05427422
Coefficient of variation (CV)0.2309458915
Kurtosis1.235652518
Mean82.50536131
Median Absolute Deviation (MAD)11
Skewness0.8972012558
Sum530922
Variance363.065366
2020-08-25T01:49:43.690588image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
833665.7%
 
873285.1%
 
792784.3%
 
922694.2%
 
962624.1%
 
942313.6%
 
851913.0%
 
781712.7%
 
811682.6%
 
901672.6%
 
761582.5%
 
751492.3%
 
671482.3%
 
581392.2%
 
741382.1%
 
721382.1%
 
621372.1%
 
591372.1%
 
701362.1%
 
681272.0%
 
631241.9%
 
981191.8%
 
651171.8%
 
881101.7%
 
571101.7%
 
Other values (79)201731.3%
 
ValueCountFrequency (%) 
291< 0.1%
 
331< 0.1%
 
342< 0.1%
 
371< 0.1%
 
381< 0.1%
 
391< 0.1%
 
413< 0.1%
 
4240.1%
 
44100.2%
 
4560.1%
 
ValueCountFrequency (%) 
1571< 0.1%
 
1541< 0.1%
 
15150.1%
 
15060.1%
 
1472< 0.1%
 
146100.2%
 
14450.1%
 
143160.2%
 
142100.2%
 
14150.1%
 

A14
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count83
Unique (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.47676767676768
Minimum27.0
Maximum137.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:43.809629image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile34
Q171
median85
Q3103
95-th percentile112
Maximum137
Range110
Interquartile range (IQR)32

Descriptive statistics

Standard deviation22.84989495
Coefficient of variation (CV)0.2737275961
Kurtosis-0.2145872041
Mean83.47676768
Median Absolute Deviation (MAD)15
Skewness-0.6673999446
Sum537173
Variance522.1176992
2020-08-25T01:49:43.913189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
793395.3%
 
753335.2%
 
1112744.3%
 
1032714.2%
 
1072283.5%
 
912213.4%
 
992183.4%
 
952103.3%
 
711943.0%
 
871903.0%
 
831882.9%
 
1061842.9%
 
731672.6%
 
1121542.4%
 
771462.3%
 
1021362.1%
 
341362.1%
 
841302.0%
 
811251.9%
 
881161.8%
 
31931.4%
 
115921.4%
 
32891.4%
 
104891.4%
 
100861.3%
 
Other values (58)202631.5%
 
ValueCountFrequency (%) 
27110.2%
 
281< 0.1%
 
29560.9%
 
30160.2%
 
31931.4%
 
32891.4%
 
341362.1%
 
36160.2%
 
37721.1%
 
3950.1%
 
ValueCountFrequency (%) 
1371< 0.1%
 
1311< 0.1%
 
1301< 0.1%
 
1282< 0.1%
 
1271< 0.1%
 
12660.1%
 
12570.1%
 
1233< 0.1%
 
1223< 0.1%
 
12180.1%
 

A27
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count75
Unique (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.21476301476301
Minimum50.0
Maximum140.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:44.033087image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile73
Q185
median100
Q3113
95-th percentile124
Maximum140
Range90
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.61251423
Coefficient of variation (CV)0.1674399427
Kurtosis-0.8798282135
Mean99.21476301
Median Absolute Deviation (MAD)13
Skewness-0.1173090218
Sum638447
Variance275.9756291
2020-08-25T01:49:44.141939image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1042934.6%
 
1002413.7%
 
1142403.7%
 
962213.4%
 
1132073.2%
 
1052063.2%
 
822043.2%
 
1181892.9%
 
931872.9%
 
1081812.8%
 
1101742.7%
 
1221662.6%
 
1191652.6%
 
741632.5%
 
971502.3%
 
851492.3%
 
1011462.3%
 
1121442.2%
 
901322.1%
 
891312.0%
 
781272.0%
 
1091231.9%
 
1151201.9%
 
861201.9%
 
751191.8%
 
Other values (50)213733.2%
 
ValueCountFrequency (%) 
501< 0.1%
 
532< 0.1%
 
551< 0.1%
 
563< 0.1%
 
6050.1%
 
6270.1%
 
6380.1%
 
6460.1%
 
6570.1%
 
66170.3%
 
ValueCountFrequency (%) 
1401< 0.1%
 
139140.2%
 
13880.1%
 
13660.1%
 
13580.1%
 
134130.2%
 
133250.4%
 
131190.3%
 
130220.3%
 
129150.2%
 

A31
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count77
Unique (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.1118881118881
Minimum50.0
Maximum145.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:44.251490image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile72
Q185
median100
Q3113
95-th percentile124
Maximum145
Range95
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.7043047
Coefficient of variation (CV)0.1685398696
Kurtosis-0.9064466906
Mean99.11188811
Median Absolute Deviation (MAD)14
Skewness-0.120959352
Sum637785
Variance279.0337955
2020-08-25T01:49:44.352696image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1042844.4%
 
1142393.7%
 
1002283.5%
 
962223.4%
 
1132123.3%
 
822063.2%
 
1052003.1%
 
1181903.0%
 
1101832.8%
 
1081822.8%
 
931792.8%
 
1221752.7%
 
741652.6%
 
1191562.4%
 
851512.3%
 
1011512.3%
 
971492.3%
 
1121442.2%
 
901382.1%
 
781282.0%
 
751262.0%
 
891251.9%
 
1151231.9%
 
1091211.9%
 
861151.8%
 
Other values (52)214333.3%
 
ValueCountFrequency (%) 
501< 0.1%
 
532< 0.1%
 
551< 0.1%
 
563< 0.1%
 
571< 0.1%
 
581< 0.1%
 
6050.1%
 
6260.1%
 
6380.1%
 
6440.1%
 
ValueCountFrequency (%) 
1451< 0.1%
 
139120.2%
 
13860.1%
 
13660.1%
 
13570.1%
 
134110.2%
 
133260.4%
 
131180.3%
 
130250.4%
 
129160.2%
 

A17
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count50
Unique (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.04568764568765
Minimum40.0
Maximum104.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:44.464011image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile46
Q160
median68
Q379
95-th percentile92
Maximum104
Range64
Interquartile range (IQR)19

Descriptive statistics

Standard deviation13.53761823
Coefficient of variation (CV)0.1960675415
Kurtosis-0.7026898806
Mean69.04568765
Median Absolute Deviation (MAD)10
Skewness0.03825822866
Sum444309
Variance183.2671072
2020-08-25T01:49:44.580785image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
675087.9%
 
634476.9%
 
713585.6%
 
683024.7%
 
642964.6%
 
882894.5%
 
842413.7%
 
602023.1%
 
701903.0%
 
591862.9%
 
531842.9%
 
661842.9%
 
751772.8%
 
561732.7%
 
921592.5%
 
761582.5%
 
441532.4%
 
801432.2%
 
461382.1%
 
791372.1%
 
821342.1%
 
781292.0%
 
741262.0%
 
571131.8%
 
501111.7%
 
Other values (25)119718.6%
 
ValueCountFrequency (%) 
4080.1%
 
41140.2%
 
42330.5%
 
43500.8%
 
441532.4%
 
461382.1%
 
47651.0%
 
48420.7%
 
49651.0%
 
501111.7%
 
ValueCountFrequency (%) 
1041< 0.1%
 
1021< 0.1%
 
101100.2%
 
9980.1%
 
97530.8%
 
96290.5%
 
95230.4%
 
93951.5%
 
921592.5%
 
90671.0%
 

A32
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count103
Unique (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.61802641802642
Minimum29.0
Maximum157.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:44.910950image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile57
Q169
median81
Q392
95-th percentile125
Maximum157
Range128
Interquartile range (IQR)23

Descriptive statistics

Standard deviation19.04366132
Coefficient of variation (CV)0.2305024962
Kurtosis1.206349203
Mean82.61802642
Median Absolute Deviation (MAD)11
Skewness0.8829188477
Sum531647
Variance362.6610365
2020-08-25T01:49:45.019764image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
833705.7%
 
873184.9%
 
922794.3%
 
792784.3%
 
962654.1%
 
942323.6%
 
851862.9%
 
811782.8%
 
901742.7%
 
781702.6%
 
761602.5%
 
751522.4%
 
671462.3%
 
721432.2%
 
591412.2%
 
701392.2%
 
741362.1%
 
581342.1%
 
621312.0%
 
981241.9%
 
631211.9%
 
681201.9%
 
571141.8%
 
651091.7%
 
881061.6%
 
Other values (78)200931.2%
 
ValueCountFrequency (%) 
291< 0.1%
 
331< 0.1%
 
342< 0.1%
 
371< 0.1%
 
381< 0.1%
 
391< 0.1%
 
413< 0.1%
 
4250.1%
 
44100.2%
 
4560.1%
 
ValueCountFrequency (%) 
1571< 0.1%
 
1541< 0.1%
 
15150.1%
 
15040.1%
 
1471< 0.1%
 
146120.2%
 
14450.1%
 
143170.3%
 
14290.1%
 
14140.1%
 

A22
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count80
Unique (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.86091686091686
Minimum27.0
Maximum130.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:45.138132image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile34
Q171
median84
Q3103
95-th percentile112
Maximum130
Range103
Interquartile range (IQR)32

Descriptive statistics

Standard deviation22.88437955
Coefficient of variation (CV)0.2761782083
Kurtosis-0.2787639815
Mean82.86091686
Median Absolute Deviation (MAD)16
Skewness-0.649578215
Sum533210
Variance523.6948276
2020-08-25T01:49:45.234389image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
793485.4%
 
753305.1%
 
1112674.1%
 
1032644.1%
 
1072283.5%
 
992233.5%
 
912133.3%
 
952023.1%
 
832003.1%
 
711953.0%
 
1061872.9%
 
871672.6%
 
731592.5%
 
771522.4%
 
1121502.3%
 
341412.2%
 
811312.0%
 
1021251.9%
 
881201.9%
 
841181.8%
 
31941.5%
 
104891.4%
 
32881.4%
 
100831.3%
 
109811.3%
 
Other values (55)208032.3%
 
ValueCountFrequency (%) 
27110.2%
 
281< 0.1%
 
29600.9%
 
30160.2%
 
31941.5%
 
32881.4%
 
341412.2%
 
36170.3%
 
37771.2%
 
3950.1%
 
ValueCountFrequency (%) 
1301< 0.1%
 
1281< 0.1%
 
1271< 0.1%
 
12550.1%
 
1232< 0.1%
 
1222< 0.1%
 
12180.1%
 
120220.3%
 
118150.2%
 
117130.2%
 

A13
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count51
Unique (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.28966588966588
Minimum39.0
Maximum104.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:45.345133image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile46
Q160
median68
Q380
95-th percentile92
Maximum104
Range65
Interquartile range (IQR)20

Descriptive statistics

Standard deviation13.6026935
Coefficient of variation (CV)0.1963163385
Kurtosis-0.7098347483
Mean69.28966589
Median Absolute Deviation (MAD)10
Skewness0.03439454901
Sum445879
Variance185.0332706
2020-08-25T01:49:45.460201image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
674987.7%
 
634537.0%
 
713585.6%
 
642964.6%
 
682964.6%
 
882894.5%
 
842413.7%
 
601882.9%
 
591852.9%
 
701832.8%
 
661772.8%
 
751762.7%
 
531762.7%
 
561692.6%
 
921682.6%
 
761612.5%
 
791482.3%
 
801472.3%
 
441432.2%
 
821392.2%
 
461372.1%
 
741332.1%
 
781262.0%
 
571191.8%
 
501161.8%
 
Other values (26)121318.9%
 
ValueCountFrequency (%) 
391< 0.1%
 
4070.1%
 
41140.2%
 
42330.5%
 
43460.7%
 
441432.2%
 
461372.1%
 
47661.0%
 
48430.7%
 
49661.0%
 
ValueCountFrequency (%) 
1041< 0.1%
 
1022< 0.1%
 
101120.2%
 
9990.1%
 
97621.0%
 
96320.5%
 
95220.3%
 
93951.5%
 
921682.6%
 
90761.2%
 

A9
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count50
Unique (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.91235431235431
Minimum40.0
Maximum104.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:45.579570image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile46
Q160
median67
Q379
95-th percentile92
Maximum104
Range64
Interquartile range (IQR)19

Descriptive statistics

Standard deviation13.47059894
Coefficient of variation (CV)0.1954743684
Kurtosis-0.7003081195
Mean68.91235431
Median Absolute Deviation (MAD)9
Skewness0.04441226057
Sum443451
Variance181.4570357
2020-08-25T01:49:45.694385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
675047.8%
 
634807.5%
 
713335.2%
 
683124.8%
 
643104.8%
 
883044.7%
 
842473.8%
 
601983.1%
 
701862.9%
 
591852.9%
 
531852.9%
 
561802.8%
 
661772.8%
 
751702.6%
 
761642.5%
 
921572.4%
 
441522.4%
 
801462.3%
 
461372.1%
 
791352.1%
 
821322.1%
 
781241.9%
 
741191.8%
 
501181.8%
 
571161.8%
 
Other values (25)116418.1%
 
ValueCountFrequency (%) 
4090.1%
 
41140.2%
 
42350.5%
 
43480.7%
 
441522.4%
 
461372.1%
 
47661.0%
 
48380.6%
 
49651.0%
 
501181.8%
 
ValueCountFrequency (%) 
1041< 0.1%
 
1021< 0.1%
 
101110.2%
 
9960.1%
 
97470.7%
 
96270.4%
 
95210.3%
 
93821.3%
 
921572.4%
 
90651.0%
 

A18
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count80
Unique (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.17109557109558
Minimum27.0
Maximum130.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:45.811012image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile34
Q171
median85
Q3103
95-th percentile112
Maximum130
Range103
Interquartile range (IQR)32

Descriptive statistics

Standard deviation22.90506493
Coefficient of variation (CV)0.2753969365
Kurtosis-0.2593268305
Mean83.17109557
Median Absolute Deviation (MAD)16
Skewness-0.6595107293
Sum535206
Variance524.6419993
2020-08-25T01:49:45.909571image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
793345.2%
 
753305.1%
 
1032764.3%
 
1112694.2%
 
1072283.5%
 
992253.5%
 
912063.2%
 
952013.1%
 
831943.0%
 
711903.0%
 
1061862.9%
 
871742.7%
 
731612.5%
 
1121542.4%
 
771492.3%
 
341412.2%
 
1021362.1%
 
841282.0%
 
881201.9%
 
811191.8%
 
31951.5%
 
32931.4%
 
104891.4%
 
115861.3%
 
100841.3%
 
Other values (55)206732.1%
 
ValueCountFrequency (%) 
27120.2%
 
29550.9%
 
30150.2%
 
31951.5%
 
32931.4%
 
341412.2%
 
36170.3%
 
37721.1%
 
3940.1%
 
40320.5%
 
ValueCountFrequency (%) 
1301< 0.1%
 
1282< 0.1%
 
1272< 0.1%
 
1263< 0.1%
 
12550.1%
 
1232< 0.1%
 
1221< 0.1%
 
12180.1%
 
120240.4%
 
118150.2%
 

A10
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count81
Unique (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.89308469308469
Minimum27.0
Maximum130.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:46.017047image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile34
Q171
median85
Q3102
95-th percentile112
Maximum130
Range103
Interquartile range (IQR)31

Descriptive statistics

Standard deviation22.86225475
Coefficient of variation (CV)0.2758041257
Kurtosis-0.2860314297
Mean82.89308469
Median Absolute Deviation (MAD)15
Skewness-0.6494845232
Sum533417
Variance522.6826923
2020-08-25T01:49:46.114558image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
793325.2%
 
753114.8%
 
1112684.2%
 
1032463.8%
 
1072263.5%
 
992173.4%
 
912153.3%
 
952013.1%
 
1062013.1%
 
711923.0%
 
831903.0%
 
871732.7%
 
731652.6%
 
1121542.4%
 
771532.4%
 
341442.2%
 
1021362.1%
 
811312.0%
 
841292.0%
 
881272.0%
 
31911.4%
 
32881.4%
 
100861.3%
 
104811.3%
 
115801.2%
 
Other values (56)209832.6%
 
ValueCountFrequency (%) 
27100.2%
 
281< 0.1%
 
29560.9%
 
30150.2%
 
31911.4%
 
32881.4%
 
341442.2%
 
36170.3%
 
37761.2%
 
3950.1%
 
ValueCountFrequency (%) 
1301< 0.1%
 
1281< 0.1%
 
1271< 0.1%
 
1261< 0.1%
 
12540.1%
 
1232< 0.1%
 
1222< 0.1%
 
12190.1%
 
120230.4%
 
118120.2%
 

A35
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count77
Unique (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.92602952602952
Minimum50.0
Maximum145.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:46.221930image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile72
Q185
median100
Q3113
95-th percentile124
Maximum145
Range95
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.69548804
Coefficient of variation (CV)0.1687673923
Kurtosis-0.9179709624
Mean98.92602953
Median Absolute Deviation (MAD)14
Skewness-0.1076417396
Sum636589
Variance278.7393208
2020-08-25T01:49:46.320520image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1042814.4%
 
1142433.8%
 
962263.5%
 
822233.5%
 
1002193.4%
 
1132113.3%
 
1052023.1%
 
1081872.9%
 
931872.9%
 
1181822.8%
 
1221772.8%
 
1101702.6%
 
741622.5%
 
1191542.4%
 
1011482.3%
 
851442.2%
 
1121392.2%
 
971372.1%
 
901342.1%
 
781312.0%
 
891292.0%
 
751292.0%
 
1091251.9%
 
861181.8%
 
1151171.8%
 
Other values (52)216033.6%
 
ValueCountFrequency (%) 
501< 0.1%
 
532< 0.1%
 
563< 0.1%
 
571< 0.1%
 
581< 0.1%
 
6050.1%
 
6270.1%
 
6390.1%
 
6440.1%
 
6570.1%
 
ValueCountFrequency (%) 
1451< 0.1%
 
1401< 0.1%
 
139110.2%
 
13870.1%
 
13660.1%
 
13570.1%
 
13490.1%
 
133240.4%
 
131180.3%
 
130210.3%
 

A1
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count51
Unique (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.4
Minimum39.0
Maximum104.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:46.431189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile46
Q160
median68
Q380
95-th percentile92
Maximum104
Range65
Interquartile range (IQR)20

Descriptive statistics

Standard deviation13.60587149
Coefficient of variation (CV)0.1960500214
Kurtosis-0.7170802666
Mean69.4
Median Absolute Deviation (MAD)10
Skewness0.02239958093
Sum446589
Variance185.1197389
2020-08-25T01:49:46.548159image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
674957.7%
 
634517.0%
 
713355.2%
 
883124.8%
 
683094.8%
 
642974.6%
 
842503.9%
 
591892.9%
 
531862.9%
 
701852.9%
 
601832.8%
 
751762.7%
 
661732.7%
 
921722.7%
 
761712.7%
 
561672.6%
 
801562.4%
 
441462.3%
 
821382.1%
 
461382.1%
 
791342.1%
 
741312.0%
 
781292.0%
 
571241.9%
 
501141.8%
 
Other values (26)117418.2%
 
ValueCountFrequency (%) 
391< 0.1%
 
4080.1%
 
41130.2%
 
42320.5%
 
43470.7%
 
441462.3%
 
461382.1%
 
47631.0%
 
48360.6%
 
49621.0%
 
ValueCountFrequency (%) 
1041< 0.1%
 
1022< 0.1%
 
101130.2%
 
9980.1%
 
97600.9%
 
96300.5%
 
95230.4%
 
93911.4%
 
921722.7%
 
90731.1%
 

A5
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count51
Unique (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.15027195027196
Minimum39.0
Maximum104.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:46.667567image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile46
Q160
median68
Q380
95-th percentile92
Maximum104
Range65
Interquartile range (IQR)20

Descriptive statistics

Standard deviation13.56119741
Coefficient of variation (CV)0.1961119895
Kurtosis-0.7111452927
Mean69.15027195
Median Absolute Deviation (MAD)10
Skewness0.03617348552
Sum444982
Variance183.9060751
2020-08-25T01:49:46.781454image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
675037.8%
 
634577.1%
 
713315.1%
 
683104.8%
 
883094.8%
 
643034.7%
 
842423.8%
 
602013.1%
 
531862.9%
 
591852.9%
 
661782.8%
 
701772.8%
 
561742.7%
 
761732.7%
 
751712.7%
 
921702.6%
 
441552.4%
 
801482.3%
 
791392.2%
 
821362.1%
 
461312.0%
 
741282.0%
 
781251.9%
 
501181.8%
 
571181.8%
 
Other values (26)116718.1%
 
ValueCountFrequency (%) 
391< 0.1%
 
4080.1%
 
41120.2%
 
42360.6%
 
43470.7%
 
441552.4%
 
461312.0%
 
47621.0%
 
48370.6%
 
49661.0%
 
ValueCountFrequency (%) 
1041< 0.1%
 
1022< 0.1%
 
101130.2%
 
9970.1%
 
97530.8%
 
96290.5%
 
95210.3%
 
93831.3%
 
921702.6%
 
90681.1%
 

A30
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count81
Unique (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.14560994560995
Minimum27.0
Maximum130.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:46.899760image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile34
Q171
median85
Q3103
95-th percentile112
Maximum130
Range103
Interquartile range (IQR)32

Descriptive statistics

Standard deviation22.84719878
Coefficient of variation (CV)0.2747853891
Kurtosis-0.2389844723
Mean83.14560995
Median Absolute Deviation (MAD)15
Skewness-0.6601707059
Sum535042
Variance521.9944923
2020-08-25T01:49:46.997657image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
793415.3%
 
753405.3%
 
1112714.2%
 
1032594.0%
 
992233.5%
 
1072123.3%
 
912123.3%
 
712003.1%
 
951953.0%
 
871943.0%
 
831862.9%
 
1061832.8%
 
731582.5%
 
771512.3%
 
341412.2%
 
1121402.2%
 
841332.1%
 
1021302.0%
 
811241.9%
 
881141.8%
 
1041041.6%
 
32941.5%
 
31921.4%
 
100891.4%
 
109891.4%
 
Other values (56)206032.0%
 
ValueCountFrequency (%) 
27120.2%
 
281< 0.1%
 
29560.9%
 
30170.3%
 
31921.4%
 
32941.5%
 
341412.2%
 
36160.2%
 
37681.1%
 
3950.1%
 
ValueCountFrequency (%) 
1301< 0.1%
 
1282< 0.1%
 
1272< 0.1%
 
1262< 0.1%
 
12560.1%
 
1232< 0.1%
 
1222< 0.1%
 
12180.1%
 
120220.3%
 
118200.3%
 

A16
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count101
Unique (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.64491064491064
Minimum29.0
Maximum154.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:47.112041image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile57
Q169
median81
Q392
95-th percentile125
Maximum154
Range125
Interquartile range (IQR)23

Descriptive statistics

Standard deviation18.93198902
Coefficient of variation (CV)0.229076284
Kurtosis1.207426687
Mean82.64491064
Median Absolute Deviation (MAD)11
Skewness0.8797306474
Sum531820
Variance358.4202084
2020-08-25T01:49:47.224475image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
833625.6%
 
873225.0%
 
792784.3%
 
922674.1%
 
962574.0%
 
942323.6%
 
851993.1%
 
811963.0%
 
901752.7%
 
781672.6%
 
761602.5%
 
741472.3%
 
671452.3%
 
751452.3%
 
721452.3%
 
591422.2%
 
701392.2%
 
581302.0%
 
631251.9%
 
621241.9%
 
981231.9%
 
681191.8%
 
881151.8%
 
651121.7%
 
571101.7%
 
Other values (76)199931.1%
 
ValueCountFrequency (%) 
291< 0.1%
 
331< 0.1%
 
342< 0.1%
 
371< 0.1%
 
413< 0.1%
 
4260.1%
 
4490.1%
 
4550.1%
 
4660.1%
 
4880.1%
 
ValueCountFrequency (%) 
1541< 0.1%
 
15140.1%
 
15060.1%
 
1472< 0.1%
 
14690.1%
 
14460.1%
 
143150.2%
 
14290.1%
 
1413< 0.1%
 
140110.2%
 

A20
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count104
Unique (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.6032634032634
Minimum29.0
Maximum157.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:47.344852image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile57
Q169
median81
Q392
95-th percentile125
Maximum157
Range128
Interquartile range (IQR)23

Descriptive statistics

Standard deviation19.0355431
Coefficient of variation (CV)0.2304454124
Kurtosis1.199657368
Mean82.6032634
Median Absolute Deviation (MAD)11
Skewness0.885559682
Sum531552
Variance362.3519011
2020-08-25T01:49:47.451059image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
833635.6%
 
873245.0%
 
792734.2%
 
922684.2%
 
962554.0%
 
942283.5%
 
851963.0%
 
811832.8%
 
901732.7%
 
781692.6%
 
761602.5%
 
671522.4%
 
751462.3%
 
741412.2%
 
591402.2%
 
701402.2%
 
721392.2%
 
581332.1%
 
631272.0%
 
981272.0%
 
621221.9%
 
681201.9%
 
651191.8%
 
571171.8%
 
881151.8%
 
Other values (79)200531.2%
 
ValueCountFrequency (%) 
291< 0.1%
 
331< 0.1%
 
341< 0.1%
 
371< 0.1%
 
381< 0.1%
 
391< 0.1%
 
413< 0.1%
 
4260.1%
 
44100.2%
 
4560.1%
 
ValueCountFrequency (%) 
1571< 0.1%
 
1541< 0.1%
 
15140.1%
 
15040.1%
 
1472< 0.1%
 
146110.2%
 
14460.1%
 
143150.2%
 
142100.2%
 
14140.1%
 

A6
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count82
Unique (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.24351204351204
Minimum27.0
Maximum137.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:47.565847image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile34
Q171
median85
Q3103
95-th percentile112
Maximum137
Range110
Interquartile range (IQR)32

Descriptive statistics

Standard deviation22.88649472
Coefficient of variation (CV)0.2749342761
Kurtosis-0.2665759428
Mean83.24351204
Median Absolute Deviation (MAD)16
Skewness-0.6559537175
Sum535672
Variance523.7916408
2020-08-25T01:49:47.666528image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
753184.9%
 
793174.9%
 
1112654.1%
 
1032473.8%
 
992283.5%
 
1072253.5%
 
912123.3%
 
1062043.2%
 
952013.1%
 
711872.9%
 
831852.9%
 
871712.7%
 
731632.5%
 
1121552.4%
 
771492.3%
 
1021452.3%
 
341422.2%
 
841392.2%
 
811231.9%
 
881191.8%
 
31911.4%
 
32891.4%
 
115871.4%
 
104851.3%
 
108801.2%
 
Other values (57)210832.8%
 
ValueCountFrequency (%) 
27110.2%
 
281< 0.1%
 
29510.8%
 
30150.2%
 
31911.4%
 
32891.4%
 
341422.2%
 
36160.2%
 
37741.1%
 
3950.1%
 
ValueCountFrequency (%) 
1371< 0.1%
 
1301< 0.1%
 
1282< 0.1%
 
1272< 0.1%
 
12640.1%
 
12550.1%
 
1231< 0.1%
 
1221< 0.1%
 
12190.1%
 
120240.4%
 

A12
Real number (ℝ≥0)

Distinct count104
Unique (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.38818958818959
Minimum29.0
Maximum157.0
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:47.780584image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile57
Q168
median81
Q392
95-th percentile125
Maximum157
Range128
Interquartile range (IQR)24

Descriptive statistics

Standard deviation18.98111189
Coefficient of variation (CV)0.2303863209
Kurtosis1.277343254
Mean82.38818959
Median Absolute Deviation (MAD)11
Skewness0.9187090837
Sum530168
Variance360.2826084
2020-08-25T01:49:47.891561image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
833675.7%
 
873455.4%
 
792864.4%
 
922403.7%
 
962243.5%
 
942223.4%
 
851953.0%
 
811842.9%
 
901742.7%
 
781712.7%
 
761662.6%
 
671552.4%
 
721462.3%
 
681402.2%
 
581392.2%
 
751372.1%
 
591362.1%
 
621352.1%
 
701352.1%
 
741342.1%
 
651302.0%
 
881201.9%
 
981201.9%
 
631181.8%
 
571151.8%
 
Other values (79)200131.1%
 
ValueCountFrequency (%) 
291< 0.1%
 
331< 0.1%
 
342< 0.1%
 
371< 0.1%
 
381< 0.1%
 
391< 0.1%
 
413< 0.1%
 
4240.1%
 
4480.1%
 
4560.1%
 
ValueCountFrequency (%) 
1571< 0.1%
 
1541< 0.1%
 
1513< 0.1%
 
15060.1%
 
1472< 0.1%
 
146110.2%
 
14460.1%
 
143160.2%
 
142100.2%
 
14150.1%
 

target
Real number (ℝ≥0)

Distinct count6
Unique (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6686868686868688
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size50.4 KiB
2020-08-25T01:49:48.220554image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.214052121
Coefficient of variation (CV)0.6034998899
Kurtosis-1.24417209
Mean3.668686869
Median Absolute Deviation (MAD)2
Skewness0.3528573905
Sum23608
Variance4.902026796
2020-08-25T01:49:48.334617image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1153323.8%
 
7150823.4%
 
3135821.1%
 
570711.0%
 
270310.9%
 
46269.7%
 
ValueCountFrequency (%) 
1153323.8%
 
270310.9%
 
3135821.1%
 
46269.7%
 
570711.0%
 
7150823.4%
 
ValueCountFrequency (%) 
7150823.4%
 
570711.0%
 
46269.7%
 
3135821.1%
 
270310.9%
 
1153323.8%
 

Interactions

2020-08-25T01:48:44.934220image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:45.078363image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:45.215829image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:45.352198image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:45.500991image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:45.656512image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:45.832852image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:45.970715image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:46.111561image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:46.263124image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:46.402312image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:46.539205image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:46.673141image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:46.818189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:46.961618image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:47.095361image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:47.234974image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:47.376133image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:47.513470image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:47.651498image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:47.791315image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:47.932134image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:48.065951image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:48.192639image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:48.322439image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:48.461010image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:48.600154image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:48.728870image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:48.866224image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:49.005618image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:49.321688image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:49.455156image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:49.586845image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:49.718877image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:49.852143image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:49.982079image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:50.128302image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:50.269083image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:50.409795image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:50.555642image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:50.691931image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:50.830035image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:50.964076image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:51.102764image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:51.227835image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:51.363148image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:51.493654image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:51.616374image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:51.752256image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:51.883462image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.010602image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.136471image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.262651image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.405170image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.539652image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.668441image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.806692image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:52.944827image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:53.074029image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:53.207109image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:53.339709image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:53.474880image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:53.604524image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:53.926072image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.055076image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.188143image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.323107image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.449180image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.581952image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.714432image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.838225image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:54.963980image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:55.088930image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:55.218075image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:55.349511image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:55.476609image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:55.620917image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:55.753538image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:55.916859image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:56.103040image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:56.235422image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:56.388651image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:56.527866image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:56.662837image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:56.803578image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:56.947497image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:57.096660image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:57.236640image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:57.380359image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:57.527418image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:57.669280image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:57.807891image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:57.944421image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:58.085699image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:58.226413image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:58.358155image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:58.691752image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:58.829733image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:58.973297image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:59.115040image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:59.257213image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:59.394773image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:59.533591image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:59.670362image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:59.810474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:48:59.952149image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:00.095782image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:00.231204image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:00.376554image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:00.518501image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:00.653786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:00.790558image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:00.925171image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:01.065802image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:01.209351image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:01.346110image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:01.488940image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:01.631900image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:01.772649image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:01.915088image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.060048image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.195511image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.321566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.443728image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.569087image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.705098image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.844515image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:02.972791image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:03.318289image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:03.456686image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:03.586786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:03.715136image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:03.842543image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:03.991081image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:04.134026image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:04.262677image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:04.396203image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:04.531623image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:04.668154image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:04.804856image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:04.938874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:05.085524image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:05.229721image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:05.372184image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:05.509697image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:05.656965image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:05.810834image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:05.952590image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:06.104039image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:06.261644image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:06.399770image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:06.536803image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:06.681239image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:06.832991image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:06.982793image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:07.121296image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:07.266500image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:07.407878image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:07.545411image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:07.689083image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:08.032377image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:08.186330image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:08.326879image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:08.463245image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:08.602247image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:08.753787image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:08.902680image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:09.065971image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:09.209323image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:09.354537image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:09.489508image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:09.624665image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:09.760352image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:09.902050image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:10.047385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:10.183709image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:10.328995image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:10.472433image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:10.614414image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:10.758980image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:10.901225image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.035551image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.164899image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.290373image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.415693image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.551125image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.683473image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.808886image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:11.942912image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:12.076409image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:12.207188image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:12.335174image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:12.670188image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:12.818653image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:12.954253image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:13.080246image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:13.213569image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:13.353498image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:13.487414image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:13.622784image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:13.760210image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:13.899200image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.029832image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.157999image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.284392image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.429214image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.561065image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.686326image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.820996image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:14.955339image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.081835image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.209892image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.336783image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.467472image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.596648image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.719686image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.850477image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:15.978375image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:16.108324image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:16.242306image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:16.376935image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:16.509548image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:16.638188image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:16.764351image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:16.890587image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:17.213346image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:17.346650image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:17.471384image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:17.605149image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:17.738918image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:17.868756image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:17.995643image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:18.121071image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:18.252589image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:18.386923image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:18.512936image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:18.645796image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:18.783014image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:18.918135image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:19.055654image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:19.188314image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:19.329747image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:19.478911image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:19.616903image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:19.751460image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:19.900381image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:20.045051image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:20.180516image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:20.322930image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:20.465610image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:20.600259image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:20.736467image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:20.873349image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:21.014448image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:21.156753image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:21.291749image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:21.439405image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:21.784473image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:21.928493image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:22.070624image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:22.213507image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:22.361929image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:22.501476image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:22.636586image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:22.771786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:22.916960image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:23.064610image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:23.198564image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:23.342494image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:23.485756image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:23.621091image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:23.758000image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:23.895670image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:24.040167image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:24.181875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:24.318763image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:24.460403image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:24.604729image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:24.742123image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:24.882758image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.034877image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.164963image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.291371image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.415671image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.543336image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.677407image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.807709image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:25.932075image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:26.064336image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:26.393350image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:26.523608image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:26.652874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:26.780388image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:26.920549image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.054654image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.180047image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.313064image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.446461image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.581485image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.718155image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.851624image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:27.999389image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:28.150115image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:28.289440image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:28.422954image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:28.568390image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:28.714360image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:28.857102image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.005348image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.152108image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.285376image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.421206image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.558258image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.701568image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.844458image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:29.984552image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:30.130177image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:30.278343image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:30.417592image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:30.562186image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:30.709890image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:31.047072image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:31.190664image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:31.329390image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:31.466105image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:31.618906image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:31.762919image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:31.901122image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:32.051054image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:32.196024image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:32.331674image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:32.469574image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:32.610499image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:32.755207image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:32.899384image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:33.042682image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:33.191457image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:33.344568image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:33.493182image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:33.640786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:33.799485image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:33.937814image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:34.074697image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:34.210242image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:34.345130image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:34.500748image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:34.643914image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:34.776861image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:34.917377image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:35.063992image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:35.200021image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:35.329491image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:35.462208image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:35.797657image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:35.937964image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:36.076104image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:36.220504image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:36.364568image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:36.499718image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:36.637283image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:36.778571image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:36.921233image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:37.069938image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:37.207855image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:37.343667image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:37.486821image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:37.638947image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:37.789083image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:37.931794image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:38.074556image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:38.211614image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:38.348764image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:38.488391image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:38.633479image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:38.777463image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:38.916588image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:39.070920image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:39.214161image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:39.354929image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:39.498642image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:39.642144image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:39.786540image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:39.927097image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:40.065778image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:40.211180image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:40.576427image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:40.722249image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:40.860365image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.004966image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.150315image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.288419image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.427652image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.565032image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.709848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.855757image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:41.996374image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:42.142625image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:42.288088image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:42.430173image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:42.574385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-25T01:49:48.488964image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-25T01:49:48.790074image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-25T01:49:49.091644image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-25T01:49:49.391639image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-25T01:49:42.884765image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:49:43.358393image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

A36A14A27A31A17A32A22A13A9A18A10A35A1A5A30A16A20A6A12target
087.0126.0134.0128.092.0100.0103.0101.084.0112.0102.0113.092.084.0121.0103.085.0102.083.03
179.0112.0128.0113.084.087.099.092.080.0103.0102.0104.084.084.0107.085.081.0102.079.03
279.0103.0113.0104.084.079.099.084.084.099.094.0104.084.080.099.081.078.0102.079.03
379.099.0104.0104.084.079.099.084.080.099.094.0104.080.084.099.078.081.094.076.03
487.099.0104.0104.076.079.099.084.080.099.0102.0109.084.080.0103.081.081.094.079.03
587.099.0104.0109.076.087.0103.076.076.099.0102.0109.080.080.0107.081.085.0102.079.03
679.0107.0113.0104.080.083.0107.080.080.0112.098.0104.076.076.0103.088.088.0102.079.03
779.0112.0104.0104.080.079.095.080.076.0107.094.0100.076.080.0103.088.085.098.076.03
871.095.096.096.076.071.095.080.076.091.098.093.076.076.091.074.074.094.072.04
967.091.096.093.076.071.091.076.076.095.094.093.076.076.087.074.078.098.076.04

Last rows

A36A14A27A31A17A32A22A13A9A18A10A35A1A5A30A16A20A6A12target
642592.0103.0117.0108.071.092.099.071.068.099.0103.0112.071.068.0100.092.092.0107.092.01
642692.099.0108.0112.071.092.0103.071.064.099.0103.0117.068.068.0100.092.096.0103.092.01
642789.0111.0112.0112.084.096.079.084.076.0103.0107.0108.076.080.0104.0100.096.0107.096.01
642885.0103.0112.0108.071.089.0103.084.084.079.0116.0100.080.076.083.096.092.0107.0103.01
642996.0103.0100.0104.084.092.0103.079.084.0111.0112.0112.084.092.083.0100.0100.0116.096.01
643085.083.0104.0108.063.089.083.059.064.087.083.0104.060.064.087.083.087.087.088.01
643181.079.0100.0100.059.085.072.063.056.075.068.0100.064.056.083.087.087.071.081.01
643274.072.0100.096.059.081.075.059.053.075.064.092.056.056.087.083.075.064.078.05
643370.079.096.092.063.074.068.059.060.079.064.092.056.060.083.071.075.071.099.05
643492.079.092.092.063.070.075.063.056.068.064.0108.060.060.083.075.092.064.096.05