## <environment: R_GlobalEnv>

Cleaning of Data

Exploratory Analysis

Analysis of purchases and reincidence of purchases

Segmentation RFM

RFM plots

Histograms

Pareto Plots

##                    
## Pareto chart analysis for y[1:10]
##                     Frequency Cum.Freq. Percentage Cum.Percent.
##   Mont Blanc          5614800   5614800  25.440818     25.44082
##   Zara                5524400  11139200  25.031213     50.47203
##   Brissa              2465810  13605010  11.172655     61.64469
##   Pandora             2343000  15948010  10.616199     72.26089
##   Naf Naf             1777800  17725810   8.055262     80.31615
##   Avianca - Deprisa   1397670  19123480   6.332882     86.64903
##   Planeta Sport       1011000  20134480   4.580870     91.22990
##   Nike                 939500  21073980   4.256901     95.48680
##   Café Illy            511465  21585445   2.317462     97.80426
##   Jenos Pizza          484600  22070045   2.195736    100.00000

##                    
## Pareto chart analysis for y[1:10]
##                     Frequency Cum.Freq. Percentage Cum.Percent.
##   Mont Blanc          5614800   5614800  25.440818     25.44082
##   Zara                5524400  11139200  25.031213     50.47203
##   Brissa              2465810  13605010  11.172655     61.64469
##   Pandora             2343000  15948010  10.616199     72.26089
##   Naf Naf             1777800  17725810   8.055262     80.31615
##   Avianca - Deprisa   1397670  19123480   6.332882     86.64903
##   Planeta Sport       1011000  20134480   4.580870     91.22990
##   Nike                 939500  21073980   4.256901     95.48680
##   Café Illy            511465  21585445   2.317462     97.80426
##   Jenos Pizza          484600  22070045   2.195736    100.00000

##                    
## Pareto chart analysis for y[1:10]
##                     Frequency Cum.Freq. Percentage Cum.Percent.
##   Mont Blanc          5614800   5614800  25.440818     25.44082
##   Zara                5524400  11139200  25.031213     50.47203
##   Brissa              2465810  13605010  11.172655     61.64469
##   Pandora             2343000  15948010  10.616199     72.26089
##   Naf Naf             1777800  17725810   8.055262     80.31615
##   Avianca - Deprisa   1397670  19123480   6.332882     86.64903
##   Planeta Sport       1011000  20134480   4.580870     91.22990
##   Nike                 939500  21073980   4.256901     95.48680
##   Café Illy            511465  21585445   2.317462     97.80426
##   Jenos Pizza          484600  22070045   2.195736    100.00000

##     
## Pareto chart analysis for y
##      Frequency Cum.Freq. Percentage Cum.Percent.
##   10  63413619  63413619  43.301451     43.30145
##   9   59236044 122649663  40.448830     83.75028
##   8   15149013 137798676  10.344375     94.09466
##   11   8648191 146446867   5.905344    100.00000

##            
## Pareto chart analysis for y
##             Frequency Cum.Freq. Percentage Cum.Percent.
##   sábado     40293941  40293941  27.514376     27.51438
##   miércoles  24147905  64441846  16.489192     44.00357
##   jueves     22211625  86653471  15.167020     59.17059
##   domingo    16487719 103141190  11.258499     70.42909
##   viernes    15688335 118829525  10.712646     81.14173
##   lunes      14551872 133381397   9.936622     91.07835
##   martes     13065470 146446867   8.921645    100.00000

##          
## Pareto chart analysis for y
##           Frequency Cum.Freq. Percentage Cum.Percent.
##   No det   82021567  82021567   56.00773     56.00773
##   Soltero  32897464 114919031   22.46375     78.47148
##   Casado   31527836 146446867   21.52852    100.00000

##          
## Pareto chart analysis for y
##           Frequency Cum.Freq. Percentage Cum.Percent.
##   No det   257120.9  257120.9   44.30283     44.30283
##   Soltero  205609.2  462730.0   35.42718     79.73001
##   Casado   117641.2  580371.2   20.26999    100.00000

##     
## Pareto chart analysis for y
##      Frequency Cum.Freq. Percentage Cum.Percent.
##   14 289817.14  289817.1   9.960454     9.960454
##   9  280434.37  570251.5   9.637987    19.598441
##   7  258386.87  828638.4   8.880257    28.478698
##   11 245006.83 1073645.2   8.420411    36.899108
##   4  222431.26 1296076.5   7.644532    44.543640
##   10 219479.89 1515556.4   7.543099    52.086739
##   3  205142.11 1720698.5   7.050337    59.137077
##   6  200521.17 1921219.6   6.891525    66.028601
##   13 182801.47 2104021.1   6.282533    72.311134
##   8  178506.19 2282527.3   6.134912    78.446047
##   16 168747.50 2451274.8   5.799525    84.245572
##   12 157094.97 2608369.8   5.399050    89.644622
##   5  115679.26 2724049.0   3.975672    93.620294
##   15  76543.33 2800592.4   2.630646    96.250941
##   2   57252.22 2857844.6   1.967648    98.218589
##   1   51833.33 2909677.9   1.781411   100.000000

##                 
## Pareto chart analysis for y
##                  Frequency Cum.Freq. Percentage Cum.Percent.
##   No det          90307919  90307919  61.665996     61.66600
##   Usaquén         24605135 114913054  16.801408     78.46740
##   Chicó           20812533 135725587  14.211661     92.67906
##   Engativa         3980483 139706070   2.718039     95.39710
##   Suba             3322342 143028412   2.268633     97.66574
##   Puente  Aranda   1871600 144900012   1.278006     98.94374
##   Ciudad Kennedy   1546855 146446867   1.056257    100.00000

##           
## Pareto chart analysis for y
##            Frequency Cum.Freq. Percentage Cum.Percent.
##   (45,65]   72956752  72956752  49.817899     49.81790
##   (35,45]   29847675 102804427  20.381232     70.19913
##   (65,Inf]  16728359 119532786  11.422818     81.62195
##   (-1,18]   13032616 132565402   8.899211     90.52116
##   (25,35]   10854705 143420107   7.412043     97.93320
##   (18,25]    3026760 146446867   2.066797    100.00000

##           
## Pareto chart analysis for y
##            Frequency Cum.Freq. Percentage Cum.Percent.
##   (-1,18]   383312.2  383312.2   26.60859     26.60859
##   (65,Inf]  334567.2  717879.4   23.22483     49.83341
##   (18,25]   216197.1  934076.6   15.00787     64.84128
##   (45,65]   189498.1 1123574.6   13.15449     77.99577
##   (25,35]   166995.5 1290570.1   11.59241     89.58818
##   (35,45]   149988.3 1440558.4   10.41182    100.00000

Tree Analysis: General Case

Boxplot Analysis for Average Invoices

Tree Analysis by reincidence in purchases

Multifactorial Analysis

Predictive Model

## $positive
## [1] "No"
## 
## $table
##           Reference
## Prediction  No  Si
##         No  44   0
##         Si   1 479
## 
## $overall
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   9.980916e-01   9.877214e-01   9.894134e-01   9.999517e-01   9.141221e-01 
## AccuracyPValue  McnemarPValue 
##   1.849936e-19   1.000000e+00 
## 
## $byClass
##          Sensitivity          Specificity       Pos Pred Value 
##           0.97777778           1.00000000           1.00000000 
##       Neg Pred Value            Precision               Recall 
##           0.99791667           1.00000000           0.97777778 
##                   F1           Prevalence       Detection Rate 
##           0.98876404           0.08587786           0.08396947 
## Detection Prevalence    Balanced Accuracy 
##           0.08396947           0.98888889 
## 
## $mode
## [1] "sens_spec"
## 
## $dots
## list()
## 
## attr(,"class")
## [1] "confusionMatrix"
## $positive
## [1] "No"
## 
## $table
##           Reference
## Prediction  No  Si
##         No   2  12
##         Si  16 193
## 
## $overall
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##     0.87443946     0.05850422     0.82366497     0.91491958     0.91928251 
## AccuracyPValue  McnemarPValue 
##     0.99239140     0.57075039 
## 
## $byClass
##          Sensitivity          Specificity       Pos Pred Value 
##           0.11111111           0.94146341           0.14285714 
##       Neg Pred Value            Precision               Recall 
##           0.92344498           0.14285714           0.11111111 
##                   F1           Prevalence       Detection Rate 
##           0.12500000           0.08071749           0.00896861 
## Detection Prevalence    Balanced Accuracy 
##           0.06278027           0.52628726 
## 
## $mode
## [1] "sens_spec"
## 
## $dots
## list()
## 
## attr(,"class")
## [1] "confusionMatrix"