Overview

Dataset statistics

Number of variables9
Number of observations8192
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory576.1 KiB
Average record size in memory72.0 B

Variable types

NUM9

Reproduction

Analysis started2020-08-24 23:55:24.272266
Analysis finished2020-08-24 23:55:39.078387
Duration14.81 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

target has unique values Unique

Variables

theta1
Real number (ℝ)

Distinct count8184
Unique (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.006294776170967964
Minimum-1.8847290277481081
Maximum1.8847349882125852
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:39.129848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.884729028
5-th percentile-1.70457443
Q1-0.9270504862
median0.01816850062
Q30.9401822388
95-th percentile1.686372072
Maximum1.884734988
Range3.769464016
Interquartile range (IQR)1.867232725

Descriptive statistics

Standard deviation1.083438972
Coefficient of variation (CV)172.117156
Kurtosis-1.185551014
Mean0.006294776171
Median Absolute Deviation (MAD)0.9365329742
Skewness-0.01546044654
Sum51.56680639
Variance1.173840007
2020-08-24T23:55:39.251943image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.38542398812< 0.1%
 
1.0371919872< 0.1%
 
0.7309389712< 0.1%
 
-0.35263499622< 0.1%
 
-1.7688729762< 0.1%
 
0.59262901542< 0.1%
 
-0.50704199082< 0.1%
 
-1.0476080182< 0.1%
 
-0.14975099271< 0.1%
 
-1.8215169911< 0.1%
 
-0.56303101781< 0.1%
 
0.18881300091< 0.1%
 
0.74040198331< 0.1%
 
-1.5105210541< 0.1%
 
1.0105259421< 0.1%
 
0.31513199211< 0.1%
 
-0.75584197041< 0.1%
 
0.54202902321< 0.1%
 
-1.1355359551< 0.1%
 
-1.5410970451< 0.1%
 
0.78567802911< 0.1%
 
-0.37763801221< 0.1%
 
1.3855559831< 0.1%
 
-1.2902189491< 0.1%
 
-0.72403198481< 0.1%
 
Other values (8159)815999.6%
 
ValueCountFrequency (%) 
-1.8847290281< 0.1%
 
-1.884688021< 0.1%
 
-1.8846399781< 0.1%
 
-1.8846340181< 0.1%
 
-1.8845440151< 0.1%
 
-1.8827830551< 0.1%
 
-1.8826910261< 0.1%
 
-1.8825769421< 0.1%
 
-1.8819279671< 0.1%
 
-1.8813240531< 0.1%
 
ValueCountFrequency (%) 
1.8847349881< 0.1%
 
1.8846930271< 0.1%
 
1.8846360451< 0.1%
 
1.8843330141< 0.1%
 
1.8836510181< 0.1%
 
1.8835569621< 0.1%
 
1.8834660051< 0.1%
 
1.8832620381< 0.1%
 
1.8829469681< 0.1%
 
1.8824019431< 0.1%
 

theta2
Real number (ℝ)

Distinct count8180
Unique (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.017952333661369835
Minimum-1.8836480379104612
Maximum1.88330602645874
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:39.383878image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.883648038
5-th percentile-1.696199155
Q1-0.911816746
median0.02260699961
Q30.9705884755
95-th percentile1.693699181
Maximum1.883306026
Range3.766954064
Interquartile range (IQR)1.882405221

Descriptive statistics

Standard deviation1.089264548
Coefficient of variation (CV)60.67537338
Kurtosis-1.193557329
Mean0.01795233366
Median Absolute Deviation (MAD)0.9422235191
Skewness-0.02181392684
Sum147.0655174
Variance1.186497256
2020-08-24T23:55:39.491170image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.40312200782< 0.1%
 
-1.4019099472< 0.1%
 
-0.51766502862< 0.1%
 
-0.57375901942< 0.1%
 
-0.047935001552< 0.1%
 
-0.064621001482< 0.1%
 
-0.78717201952< 0.1%
 
1.6381820442< 0.1%
 
1.1601129772< 0.1%
 
-0.31050801282< 0.1%
 
1.1606110332< 0.1%
 
-0.29240301252< 0.1%
 
-1.4831399921< 0.1%
 
-1.5104819541< 0.1%
 
0.26824501161< 0.1%
 
0.56146502491< 0.1%
 
0.88023698331< 0.1%
 
0.64586102961< 0.1%
 
-0.86460798981< 0.1%
 
0.91343599561< 0.1%
 
-0.69273102281< 0.1%
 
0.44890400771< 0.1%
 
1.4109419581< 0.1%
 
0.31037700181< 0.1%
 
0.42449700831< 0.1%
 
Other values (8155)815599.5%
 
ValueCountFrequency (%) 
-1.8836480381< 0.1%
 
-1.8834830521< 0.1%
 
-1.8826529981< 0.1%
 
-1.8820309641< 0.1%
 
-1.8819609881< 0.1%
 
-1.8817160131< 0.1%
 
-1.8817110061< 0.1%
 
-1.8815779691< 0.1%
 
-1.8811500071< 0.1%
 
-1.8793979881< 0.1%
 
ValueCountFrequency (%) 
1.8833060261< 0.1%
 
1.8810759781< 0.1%
 
1.8809109931< 0.1%
 
1.8783739811< 0.1%
 
1.877269031< 0.1%
 
1.8744540211< 0.1%
 
1.8742940431< 0.1%
 
1.8739650251< 0.1%
 
1.8724709751< 0.1%
 
1.8713580371< 0.1%
 

theta3
Real number (ℝ)

Distinct count8183
Unique (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0031538137572308944
Minimum-1.884449005126953
Maximum1.884737014770508
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:39.621290image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.884449005
5-th percentile-1.685176003
Q1-0.923930496
median0.0165275
Q30.9427387565
95-th percentile1.692033094
Maximum1.884737015
Range3.76918602
Interquartile range (IQR)1.866669253

Descriptive statistics

Standard deviation1.084188495
Coefficient of variation (CV)343.770615
Kurtosis-1.190551055
Mean0.003153813757
Median Absolute Deviation (MAD)0.9341560043
Skewness-0.00706741033
Sum25.8360423
Variance1.175464692
2020-08-24T23:55:39.748380image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.70134997372< 0.1%
 
-1.0716099742< 0.1%
 
-1.3938740492< 0.1%
 
1.266816022< 0.1%
 
-0.063271000982< 0.1%
 
-1.7830040452< 0.1%
 
0.47221300012< 0.1%
 
1.1935139892< 0.1%
 
-0.67278397082< 0.1%
 
1.1042640211< 0.1%
 
-0.0032140000261< 0.1%
 
0.4635710121< 0.1%
 
0.63026398421< 0.1%
 
0.87304502731< 0.1%
 
1.8230110411< 0.1%
 
0.73962700371< 0.1%
 
0.072760000821< 0.1%
 
-1.854246021< 0.1%
 
0.32576400041< 0.1%
 
-1.8444720511< 0.1%
 
-1.1355019811< 0.1%
 
1.2649430041< 0.1%
 
-1.1349890231< 0.1%
 
-1.2917319541< 0.1%
 
-0.46013000611< 0.1%
 
Other values (8158)815899.6%
 
ValueCountFrequency (%) 
-1.8844490051< 0.1%
 
-1.884292961< 0.1%
 
-1.8842270371< 0.1%
 
-1.8841550351< 0.1%
 
-1.8841409681< 0.1%
 
-1.8834340571< 0.1%
 
-1.8831360341< 0.1%
 
-1.88291< 0.1%
 
-1.8823579551< 0.1%
 
-1.8822540041< 0.1%
 
ValueCountFrequency (%) 
1.8847370151< 0.1%
 
1.8846030241< 0.1%
 
1.8840459591< 0.1%
 
1.8836799861< 0.1%
 
1.8803449871< 0.1%
 
1.8800539971< 0.1%
 
1.8800009491< 0.1%
 
1.879253031< 0.1%
 
1.8778029681< 0.1%
 
1.8773059841< 0.1%
 

thetad1
Real number (ℝ)

Distinct count8185
Unique (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.007720018143614782
Minimum-1.8846319913864136
Maximum1.8849229812622068
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:39.883088image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.884631991
5-th percentile-1.699520814
Q1-0.95945701
median-0.009736499749
Q30.9318295121
95-th percentile1.692721063
Maximum1.884922981
Range3.769554973
Interquartile range (IQR)1.891286522

Descriptive statistics

Standard deviation1.090345086
Coefficient of variation (CV)-141.2360782
Kurtosis-1.203293543
Mean-0.007720018144
Median Absolute Deviation (MAD)0.9455410028
Skewness0.01108797244
Sum-63.24238863
Variance1.188852406
2020-08-24T23:55:40.001184image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.652985992< 0.1%
 
1.2395290142< 0.1%
 
-1.4183000332< 0.1%
 
-0.039186000822< 0.1%
 
-1.4285149572< 0.1%
 
1.809713962< 0.1%
 
1.240697982< 0.1%
 
1.1666790251< 0.1%
 
0.59896600251< 0.1%
 
-0.20478299261< 0.1%
 
-0.81773000961< 0.1%
 
-1.1666959521< 0.1%
 
-1.4357850551< 0.1%
 
-0.0093590002511< 0.1%
 
1.7590780261< 0.1%
 
0.80378901961< 0.1%
 
-1.7604119781< 0.1%
 
-1.2604399921< 0.1%
 
-0.77085900311< 0.1%
 
-0.91148197651< 0.1%
 
-0.18405300381< 0.1%
 
-0.94755202531< 0.1%
 
-1.3229730131< 0.1%
 
1.3229739671< 0.1%
 
-0.64275097851< 0.1%
 
Other values (8160)816099.6%
 
ValueCountFrequency (%) 
-1.8846319911< 0.1%
 
-1.884608031< 0.1%
 
-1.8845210081< 0.1%
 
-1.8844809531< 0.1%
 
-1.8844510321< 0.1%
 
-1.8840941< 0.1%
 
-1.8836419581< 0.1%
 
-1.8829519751< 0.1%
 
-1.8820639851< 0.1%
 
-1.8817490341< 0.1%
 
ValueCountFrequency (%) 
1.8849229811< 0.1%
 
1.882807971< 0.1%
 
1.8819830421< 0.1%
 
1.8819559811< 0.1%
 
1.8806240561< 0.1%
 
1.8801779751< 0.1%
 
1.8800020221< 0.1%
 
1.8799040321< 0.1%
 
1.8798520571< 0.1%
 
1.8796839711< 0.1%
 

thetad2
Real number (ℝ)

Distinct count8183
Unique (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.014780120676168518
Minimum-1.8847850561141968
Maximum1.8840769529342647
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:40.143820image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.884785056
5-th percentile-1.696153444
Q1-0.959059
median-0.03188999929
Q30.9268667698
95-th percentile1.699071407
Maximum1.884076953
Range3.768862009
Interquartile range (IQR)1.88592577

Descriptive statistics

Standard deviation1.089577196
Coefficient of variation (CV)-73.71910012
Kurtosis-1.195791352
Mean-0.01478012068
Median Absolute Deviation (MAD)0.942684507
Skewness0.01837778548
Sum-121.0787486
Variance1.187178466
2020-08-24T23:55:40.252954image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.5270990132< 0.1%
 
0.14888800682< 0.1%
 
1.2700940372< 0.1%
 
-1.2434220312< 0.1%
 
-0.2806180122< 0.1%
 
0.24369600422< 0.1%
 
1.8148200512< 0.1%
 
0.18514199552< 0.1%
 
-0.20219099522< 0.1%
 
-1.3542510271< 0.1%
 
-0.56774801021< 0.1%
 
-1.5456429721< 0.1%
 
0.27343699341< 0.1%
 
-0.50524401661< 0.1%
 
-1.7292599681< 0.1%
 
1.0417360071< 0.1%
 
1.1354811< 0.1%
 
-1.0729800461< 0.1%
 
-0.40886899831< 0.1%
 
0.55212700371< 0.1%
 
-1.1667660471< 0.1%
 
1.5730129481< 0.1%
 
-0.80210900311< 0.1%
 
0.27606698871< 0.1%
 
0.56776201731< 0.1%
 
Other values (8158)815899.6%
 
ValueCountFrequency (%) 
-1.8847850561< 0.1%
 
-1.8846069571< 0.1%
 
-1.8841359621< 0.1%
 
-1.8837870361< 0.1%
 
-1.882817031< 0.1%
 
-1.8813389541< 0.1%
 
-1.8811440471< 0.1%
 
-1.8811039921< 0.1%
 
-1.8806680441< 0.1%
 
-1.8799409871< 0.1%
 
ValueCountFrequency (%) 
1.8840769531< 0.1%
 
1.8830599781< 0.1%
 
1.8823870421< 0.1%
 
1.8819869761< 0.1%
 
1.8819240331< 0.1%
 
1.8818589451< 0.1%
 
1.8818440441< 0.1%
 
1.8814849851< 0.1%
 
1.8814799791< 0.1%
 
1.8812350031< 0.1%
 

thetad3
Real number (ℝ)

Distinct count8183
Unique (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01344237465453979
Minimum-1.8845579624176023
Maximum1.884745955467224
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:40.378291image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.884557962
5-th percentile-1.685824323
Q1-0.9216982424
median0.02652950026
Q30.9468442351
95-th percentile1.690112782
Maximum1.884745955
Range3.769303918
Interquartile range (IQR)1.868542477

Descriptive statistics

Standard deviation1.085666378
Coefficient of variation (CV)80.76447847
Kurtosis-1.200580355
Mean0.01344237465
Median Absolute Deviation (MAD)0.9353560004
Skewness-0.01941036071
Sum110.1199332
Variance1.178671485
2020-08-24T23:55:40.494190image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.59662997723< 0.1%
 
1.1554290062< 0.1%
 
-1.0573769812< 0.1%
 
-1.7989929912< 0.1%
 
1.0043950082< 0.1%
 
1.6143000132< 0.1%
 
-1.4245740182< 0.1%
 
0.87534797192< 0.1%
 
0.48135501151< 0.1%
 
-0.64580798151< 0.1%
 
-1.6041129831< 0.1%
 
-1.0050439831< 0.1%
 
-0.31358700991< 0.1%
 
0.98896497491< 0.1%
 
-1.4166189431< 0.1%
 
-0.35414901381< 0.1%
 
0.64613199231< 0.1%
 
-1.6978429561< 0.1%
 
-0.99149602651< 0.1%
 
-0.84893399481< 0.1%
 
1.3184939621< 0.1%
 
1.7928830391< 0.1%
 
0.78641498091< 0.1%
 
-0.30728098751< 0.1%
 
0.3642410041< 0.1%
 
Other values (8158)815899.6%
 
ValueCountFrequency (%) 
-1.8845579621< 0.1%
 
-1.883916021< 0.1%
 
-1.8839030271< 0.1%
 
-1.8835940361< 0.1%
 
-1.8833910231< 0.1%
 
-1.8830449581< 0.1%
 
-1.8829020261< 0.1%
 
-1.8812890051< 0.1%
 
-1.8809570071< 0.1%
 
-1.8784949781< 0.1%
 
ValueCountFrequency (%) 
1.8847459551< 0.1%
 
1.8847199681< 0.1%
 
1.8837829831< 0.1%
 
1.8832490441< 0.1%
 
1.8831919431< 0.1%
 
1.8828380111< 0.1%
 
1.8826559781< 0.1%
 
1.8824969531< 0.1%
 
1.882403971< 0.1%
 
1.882225991< 0.1%
 

tau1
Real number (ℝ)

Distinct count8165
Unique (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002217416103470704
Minimum-0.5999950170516968
Maximum0.5999550223350525
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:40.630678image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-0.5999950171
5-th percentile-0.5359626681
Q1-0.29670275
median0.006988999899
Q30.2978440076
95-th percentile0.5411814123
Maximum0.5999550223
Range1.199950039
Interquartile range (IQR)0.5945467576

Descriptive statistics

Standard deviation0.3436914725
Coefficient of variation (CV)154.9963816
Kurtosis-1.186503988
Mean0.002217416103
Median Absolute Deviation (MAD)0.2981095016
Skewness-0.003621819596
Sum18.16507272
Variance0.1181238282
2020-08-24T23:55:40.743217image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.41235598922< 0.1%
 
0.056081999092< 0.1%
 
-0.2820020022< 0.1%
 
-0.52236402032< 0.1%
 
0.19642099742< 0.1%
 
0.054864998912< 0.1%
 
0.049316998572< 0.1%
 
-0.15366399292< 0.1%
 
-0.37206500772< 0.1%
 
-0.19962500042< 0.1%
 
-0.10896299782< 0.1%
 
0.32894700772< 0.1%
 
0.58308202032< 0.1%
 
0.58575701712< 0.1%
 
0.33533099292< 0.1%
 
0.16410599652< 0.1%
 
-0.31433001162< 0.1%
 
0.1227660032< 0.1%
 
0.13104100532< 0.1%
 
-0.10323499892< 0.1%
 
-0.54711902142< 0.1%
 
-0.27943098552< 0.1%
 
-0.24757300322< 0.1%
 
0.020720999692< 0.1%
 
0.32827499512< 0.1%
 
Other values (8140)814299.4%
 
ValueCountFrequency (%) 
-0.59999501711< 0.1%
 
-0.59978300331< 0.1%
 
-0.59953099491< 0.1%
 
-0.59939301011< 0.1%
 
-0.59927099941< 0.1%
 
-0.59917497631< 0.1%
 
-0.59911298751< 0.1%
 
-0.59908699991< 0.1%
 
-0.59906500581< 0.1%
 
-0.59900397061< 0.1%
 
ValueCountFrequency (%) 
0.59995502231< 0.1%
 
0.59976398941< 0.1%
 
0.59913998841< 0.1%
 
0.5990110041< 0.1%
 
0.59891098741< 0.1%
 
0.59885197881< 0.1%
 
0.59877502921< 0.1%
 
0.59873700141< 0.1%
 
0.59872901441< 0.1%
 
0.59872800111< 0.1%
 

tau2
Real number (ℝ)

Distinct count8165
Unique (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.000696704433066575
Minimum-0.5998719930648804
Maximum0.5999119877815247
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:40.862111image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-0.5998719931
5-th percentile-0.5379978031
Q1-0.300827004
median0.005336999893
Q30.3037060052
95-th percentile0.54035981
Maximum0.5999119878
Range1.199783981
Interquartile range (IQR)0.6045330092

Descriptive statistics

Standard deviation0.3467036738
Coefficient of variation (CV)497.6337991
Kurtosis-1.200907281
Mean0.0006967044331
Median Absolute Deviation (MAD)0.3022079915
Skewness-0.008014328074
Sum5.707402716
Variance0.1202034375
2020-08-24T23:55:40.964684image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.098736003042< 0.1%
 
0.20027500392< 0.1%
 
-0.48983201382< 0.1%
 
-0.10969000312< 0.1%
 
-0.37800100452< 0.1%
 
0.50730097292< 0.1%
 
0.18366999922< 0.1%
 
-0.23504500092< 0.1%
 
0.051963999872< 0.1%
 
-0.39007300142< 0.1%
 
0.4993839862< 0.1%
 
-0.4728640022< 0.1%
 
0.41163700822< 0.1%
 
-0.23566499352< 0.1%
 
-0.47045201062< 0.1%
 
-0.018365999682< 0.1%
 
0.24325899782< 0.1%
 
0.13265499472< 0.1%
 
0.022938000042< 0.1%
 
-0.058889999992< 0.1%
 
0.25190100072< 0.1%
 
-0.27484399082< 0.1%
 
0.30250298982< 0.1%
 
0.1388760062< 0.1%
 
0.54946297412< 0.1%
 
Other values (8140)814299.4%
 
ValueCountFrequency (%) 
-0.59987199311< 0.1%
 
-0.59970700741< 0.1%
 
-0.59967702631< 0.1%
 
-0.59948801991< 0.1%
 
-0.59919601681< 0.1%
 
-0.59898799661< 0.1%
 
-0.59896600251< 0.1%
 
-0.59891700741< 0.1%
 
-0.59890300041< 0.1%
 
-0.59878498321< 0.1%
 
ValueCountFrequency (%) 
0.59991198781< 0.1%
 
0.59940999751< 0.1%
 
0.59921902421< 0.1%
 
0.59912800791< 0.1%
 
0.59888100621< 0.1%
 
0.59852498771< 0.1%
 
0.59823101761< 0.1%
 
0.59819602971< 0.1%
 
0.59788900611< 0.1%
 
0.59784698491< 0.1%
 

target
Real number (ℝ)

UNIQUE

Distinct count8192
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1620470815235615
Minimum-12.415322303771973
Maximum11.876190185546875
Zeros0
Zeros (%)0.0%
Memory size64.1 KiB
2020-08-24T23:55:41.084532image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-12.4153223
5-th percentile-8.281291008
Q1-3.183712721
median1.11512202
Q36.319604039
95-th percentile9.255335331
Maximum11.87619019
Range24.29151249
Interquartile range (IQR)9.50331676

Descriptive statistics

Standard deviation5.622332637
Coefficient of variation (CV)4.838300209
Kurtosis-1.082968385
Mean1.162047082
Median Absolute Deviation (MAD)4.771428883
Skewness-0.1500731979
Sum9519.489692
Variance31.61062428
2020-08-24T23:55:41.189608image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
8.249561311< 0.1%
 
7.4999837881< 0.1%
 
8.1460371021< 0.1%
 
6.5948848721< 0.1%
 
1.2655440571< 0.1%
 
1.6978199481< 0.1%
 
9.9201059341< 0.1%
 
-10.08261491< 0.1%
 
8.3326616291< 0.1%
 
-7.2913408281< 0.1%
 
-1.2915920021< 0.1%
 
-5.0468249321< 0.1%
 
8.8929996491< 0.1%
 
-7.6664347651< 0.1%
 
-1.7916109561< 0.1%
 
-1.979117991< 0.1%
 
8.8330354691< 0.1%
 
-2.7785730361< 0.1%
 
-8.833092691< 0.1%
 
-2.2082779411< 0.1%
 
6.7865672111< 0.1%
 
3.768276931< 0.1%
 
-7.78654481< 0.1%
 
1.2603989841< 0.1%
 
9.2152490621< 0.1%
 
Other values (8167)816799.7%
 
ValueCountFrequency (%) 
-12.41532231< 0.1%
 
-12.214976311< 0.1%
 
-12.040122031< 0.1%
 
-11.775140761< 0.1%
 
-11.635149961< 0.1%
 
-11.544735911< 0.1%
 
-11.504540441< 0.1%
 
-11.503409391< 0.1%
 
-11.346838951< 0.1%
 
-11.292937281< 0.1%
 
ValueCountFrequency (%) 
11.876190191< 0.1%
 
11.225419041< 0.1%
 
11.196832661< 0.1%
 
11.141817091< 0.1%
 
10.902876851< 0.1%
 
10.828043941< 0.1%
 
10.758549691< 0.1%
 
10.717030531< 0.1%
 
10.695709231< 0.1%
 
10.684603691< 0.1%
 

Interactions

2020-08-24T23:55:24.820538image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:24.987707image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:25.153519image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:25.488034image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:25.661783image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:25.832173image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:25.997469image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:26.156768image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:26.327661image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:26.479620image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:26.645564image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:26.812599image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:26.981409image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:27.152702image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:27.326426image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:27.497223image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:27.659466image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:27.820474image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:27.976750image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:28.143613image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:28.314025image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:28.483736image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:28.651170image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:28.818130image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:28.990448image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:29.150332image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:29.309551image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:29.471092image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:29.637603image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:29.992428image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:30.173139image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:30.349191image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:30.517190image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:30.683828image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:30.842670image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:31.004606image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:31.153574image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:31.318869image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:31.490517image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:31.663512image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:31.829798image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:32.010533image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:32.178326image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:32.336784image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:32.501435image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:32.653830image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:32.823483image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:32.994210image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:33.165570image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:33.334906image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:33.507062image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:33.674251image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:33.832031image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:33.995121image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:34.145504image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:34.491364image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:34.659848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:34.825007image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:34.984425image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:35.140906image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:35.296592image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:35.444718image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:35.595950image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:35.735104image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:35.892558image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:36.053915image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:36.212705image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:36.371107image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:36.530570image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:36.688778image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:36.844478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:36.993805image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:37.136934image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:37.283772image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:37.427982image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:37.576624image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:37.719929image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:37.864354image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:38.008679image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:38.154496image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:38.294871image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-24T23:55:41.310316image/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.
2020-08-24T23:55:41.523088image/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.
2020-08-24T23:55:41.740263image/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.
2020-08-24T23:55:41.954390image/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

2020-08-24T23:55:38.532810image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-24T23:55:38.972315image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

theta1theta2theta3thetad1thetad2thetad3tau1tau2target
01.537614-0.0593701.2014681.4275481.0902181.530334-0.567986-0.1404636.321392
1-0.2074240.9847671.063136-1.258238-1.7778080.697755-0.326937-0.0249999.122258
2-0.448652-0.6706430.5399961.540304-0.0920911.6588390.515485-0.2361982.887800
31.1882421.5637111.2449871.497807-1.8266471.699286-0.3005880.0226524.631216
41.1150931.1417941.2857450.389825-0.3205030.5105390.0971980.412442-0.443591
5-1.0996901.377836-1.279533-1.537403-0.1547220.832828-0.110465-0.1814885.987181
6-0.1208291.204484-0.654551-0.441483-0.812690-0.4985460.462281-0.4405350.658118
70.840910-0.222823-1.4588300.9546840.624153-1.523538-0.276099-0.0042823.556650
80.506034-0.012869-1.4083750.7191480.3914250.1846120.046232-0.586140-2.681732
90.1541901.5502831.755983-1.822316-0.9122460.1037020.388885-0.412139-5.644916

Last rows

theta1theta2theta3thetad1thetad2thetad3tau1tau2target
81820.391545-1.5727521.3669450.400296-1.508331-1.6409610.3315810.0871630.237481
81830.2140350.783867-1.382864-0.2888870.3174951.721268-0.3023580.263052-2.531025
8184-1.870292-0.482536-0.911004-1.628727-0.6856391.0836590.1968610.246937-1.703908
81850.5114801.048591-0.665991-0.443943-0.6977151.702465-0.095036-0.0734618.301461
8186-1.463180-0.530755-0.7872231.5293700.873134-1.4985270.3293170.422852-5.637154
8187-0.1240060.584276-0.6853971.3893820.514277-0.9539290.2359850.2033464.844252
8188-0.1510911.538648-1.5290840.178763-0.148821-1.789391-0.5454800.1107151.093038
8189-0.6668490.208102-0.915003-0.9866740.8174811.843709-0.4630690.392720-2.430036
81900.3526640.9239180.023086-0.288494-0.605924-1.2288640.5831180.0631728.265306
8191-0.7244700.649090-0.8700600.393417-0.2636971.4519840.2752620.328867-0.628352