Configuración para mejorar la ejecución
knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE)Cargar dataset
ifood <- read.csv("ifood_no_preprocessed.csv", sep=",", header=TRUE)Mostrar las primeras filas
head(ifood)## ID Year_Birth Education Marital_Status Income Kidhome Teenhome Dt_Customer
## 1 5524 1957 Graduation Single 58138 0 0 2012-09-04
## 2 2174 1954 Graduation Single 46344 1 1 2014-03-08
## 3 4141 1965 Graduation Together 71613 0 0 2013-08-21
## 4 6182 1984 Graduation Together 26646 1 0 2014-02-10
## 5 5324 1981 PhD Married 58293 1 0 2014-01-19
## 6 7446 1967 Master Together 62513 0 1 2013-09-09
## Recency MntWines MntFruits MntMeatProducts MntFishProducts MntSweetProducts
## 1 58 635 88 546 172 88
## 2 38 11 1 6 2 1
## 3 26 426 49 127 111 21
## 4 26 11 4 20 10 3
## 5 94 173 43 118 46 27
## 6 16 520 42 98 0 42
## MntGoldProds NumDealsPurchases NumWebPurchases NumCatalogPurchases
## 1 88 3 8 10
## 2 6 2 1 1
## 3 42 1 8 2
## 4 5 2 2 0
## 5 15 5 5 3
## 6 14 2 6 4
## NumStorePurchases NumWebVisitsMonth AcceptedCmp3 AcceptedCmp4 AcceptedCmp5
## 1 4 7 0 0 0
## 2 2 5 0 0 0
## 3 10 4 0 0 0
## 4 4 6 0 0 0
## 5 6 5 0 0 0
## 6 10 6 0 0 0
## AcceptedCmp1 AcceptedCmp2 Complain Z_CostContact Z_Revenue Response
## 1 0 0 0 3 11 1
## 2 0 0 0 3 11 0
## 3 0 0 0 3 11 0
## 4 0 0 0 3 11 0
## 5 0 0 0 3 11 0
## 6 0 0 0 3 11 0Ver estructura del dataset
str(ifood)## 'data.frame': 2240 obs. of 29 variables:
## $ ID : int 5524 2174 4141 6182 5324 7446 965 6177 4855 5899 ...
## $ Year_Birth : int 1957 1954 1965 1984 1981 1967 1971 1985 1974 1950 ...
## $ Education : chr "Graduation" "Graduation" "Graduation" "Graduation" ...
## $ Marital_Status : chr "Single" "Single" "Together" "Together" ...
## $ Income : int 58138 46344 71613 26646 58293 62513 55635 33454 30351 5648 ...
## $ Kidhome : int 0 1 0 1 1 0 0 1 1 1 ...
## $ Teenhome : int 0 1 0 0 0 1 1 0 0 1 ...
## $ Dt_Customer : chr "2012-09-04" "2014-03-08" "2013-08-21" "2014-02-10" ...
## $ Recency : int 58 38 26 26 94 16 34 32 19 68 ...
## $ MntWines : int 635 11 426 11 173 520 235 76 14 28 ...
## $ MntFruits : int 88 1 49 4 43 42 65 10 0 0 ...
## $ MntMeatProducts : int 546 6 127 20 118 98 164 56 24 6 ...
## $ MntFishProducts : int 172 2 111 10 46 0 50 3 3 1 ...
## $ MntSweetProducts : int 88 1 21 3 27 42 49 1 3 1 ...
## $ MntGoldProds : int 88 6 42 5 15 14 27 23 2 13 ...
## $ NumDealsPurchases : int 3 2 1 2 5 2 4 2 1 1 ...
## $ NumWebPurchases : int 8 1 8 2 5 6 7 4 3 1 ...
## $ NumCatalogPurchases: int 10 1 2 0 3 4 3 0 0 0 ...
## $ NumStorePurchases : int 4 2 10 4 6 10 7 4 2 0 ...
## $ NumWebVisitsMonth : int 7 5 4 6 5 6 6 8 9 20 ...
## $ AcceptedCmp3 : int 0 0 0 0 0 0 0 0 0 1 ...
## $ AcceptedCmp4 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ AcceptedCmp5 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ AcceptedCmp1 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ AcceptedCmp2 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Complain : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Z_CostContact : int 3 3 3 3 3 3 3 3 3 3 ...
## $ Z_Revenue : int 11 11 11 11 11 11 11 11 11 11 ...
## $ Response : int 1 0 0 0 0 0 0 0 1 0 ...Resumen EstadÃstico General
# Resumen de todas las variables
summary(ifood)## ID Year_Birth Education Marital_Status
## Min. : 0 Min. :1893 Length:2240 Length:2240
## 1st Qu.: 2828 1st Qu.:1959 Class :character Class :character
## Median : 5458 Median :1970 Mode :character Mode :character
## Mean : 5592 Mean :1969
## 3rd Qu.: 8428 3rd Qu.:1977
## Max. :11191 Max. :1996
##
## Income Kidhome Teenhome Dt_Customer
## Min. : 1730 Min. :0.0000 Min. :0.0000 Length:2240
## 1st Qu.: 35303 1st Qu.:0.0000 1st Qu.:0.0000 Class :character
## Median : 51382 Median :0.0000 Median :0.0000 Mode :character
## Mean : 52247 Mean :0.4442 Mean :0.5062
## 3rd Qu.: 68522 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :666666 Max. :2.0000 Max. :2.0000
## NA's :24
## Recency MntWines MntFruits MntMeatProducts
## Min. : 0.00 Min. : 0.00 Min. : 0.0 Min. : 0.0
## 1st Qu.:24.00 1st Qu.: 23.75 1st Qu.: 1.0 1st Qu.: 16.0
## Median :49.00 Median : 173.50 Median : 8.0 Median : 67.0
## Mean :49.11 Mean : 303.94 Mean : 26.3 Mean : 166.9
## 3rd Qu.:74.00 3rd Qu.: 504.25 3rd Qu.: 33.0 3rd Qu.: 232.0
## Max. :99.00 Max. :1493.00 Max. :199.0 Max. :1725.0
##
## MntFishProducts MntSweetProducts MntGoldProds NumDealsPurchases
## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.000
## 1st Qu.: 3.00 1st Qu.: 1.00 1st Qu.: 9.00 1st Qu.: 1.000
## Median : 12.00 Median : 8.00 Median : 24.00 Median : 2.000
## Mean : 37.53 Mean : 27.06 Mean : 44.02 Mean : 2.325
## 3rd Qu.: 50.00 3rd Qu.: 33.00 3rd Qu.: 56.00 3rd Qu.: 3.000
## Max. :259.00 Max. :263.00 Max. :362.00 Max. :15.000
##
## NumWebPurchases NumCatalogPurchases NumStorePurchases NumWebVisitsMonth
## Min. : 0.000 Min. : 0.000 Min. : 0.00 Min. : 0.000
## 1st Qu.: 2.000 1st Qu.: 0.000 1st Qu.: 3.00 1st Qu.: 3.000
## Median : 4.000 Median : 2.000 Median : 5.00 Median : 6.000
## Mean : 4.085 Mean : 2.662 Mean : 5.79 Mean : 5.317
## 3rd Qu.: 6.000 3rd Qu.: 4.000 3rd Qu.: 8.00 3rd Qu.: 7.000
## Max. :27.000 Max. :28.000 Max. :13.00 Max. :20.000
##
## AcceptedCmp3 AcceptedCmp4 AcceptedCmp5 AcceptedCmp1
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.07277 Mean :0.07455 Mean :0.07277 Mean :0.06429
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
##
## AcceptedCmp2 Complain Z_CostContact Z_Revenue
## Min. :0.00000 Min. :0.000000 Min. :3 Min. :11
## 1st Qu.:0.00000 1st Qu.:0.000000 1st Qu.:3 1st Qu.:11
## Median :0.00000 Median :0.000000 Median :3 Median :11
## Mean :0.01339 Mean :0.009375 Mean :3 Mean :11
## 3rd Qu.:0.00000 3rd Qu.:0.000000 3rd Qu.:3 3rd Qu.:11
## Max. :1.00000 Max. :1.000000 Max. :3 Max. :11
##
## Response
## Min. :0.0000
## 1st Qu.:0.0000
## Median :0.0000
## Mean :0.1491
## 3rd Qu.:0.0000
## Max. :1.0000
## Análisis de Variables Numéricas
# Seleccionar variables numéricas
numericas <- sapply(ifood, is.numeric)
numericas <- names(ifood)[numericas]# Histograma y boxplot para cada variable numérica
for (var in numericas) {
cat("", var, "\n\n")
# Histograma
hist(ifood[[var]], main=paste("Histograma de", var), col="skyblue", border="black")
# Boxplot
boxplot(ifood[[var]], main=paste("Boxplot de", var), col="orange", horizontal=TRUE)
# Tabla de frecuencias y resumen estadÃstico
# Muestra solo los primeros 10 valores
print(head(ifood[[var]], 10))
print(summary(ifood[[var]], 10))
}## ID
## [1] 5524 2174 4141 6182 5324 7446 965 6177 4855 5899
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0 2828 5458 5592 8428 11191
## Year_Birth
## [1] 1957 1954 1965 1984 1981 1967 1971 1985 1974 1950
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1893 1959 1970 1969 1977 1996
## Income
## [1] 58138 46344 71613 26646 58293 62513 55635 33454 30351 5648
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 1730 35303 51382 52247 68522 666666 24
## Kidhome
## [1] 0 1 0 1 1 0 0 1 1 1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.4442 1.0000 2.0000
## Teenhome
## [1] 0 1 0 0 0 1 1 0 0 1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.5062 1.0000 2.0000
## Recency
## [1] 58 38 26 26 94 16 34 32 19 68
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 24.00 49.00 49.11 74.00 99.00
## MntWines
## [1] 635 11 426 11 173 520 235 76 14 28
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 23.75 173.50 303.94 504.25 1493.00
## MntFruits
## [1] 88 1 49 4 43 42 65 10 0 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0 1.0 8.0 26.3 33.0 199.0
## MntMeatProducts
## [1] 546 6 127 20 118 98 164 56 24 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0 16.0 67.0 166.9 232.0 1725.0
## MntFishProducts
## [1] 172 2 111 10 46 0 50 3 3 1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 3.00 12.00 37.53 50.00 259.00
## MntSweetProducts
## [1] 88 1 21 3 27 42 49 1 3 1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 1.00 8.00 27.06 33.00 263.00
## MntGoldProds
## [1] 88 6 42 5 15 14 27 23 2 13
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 9.00 24.00 44.02 56.00 362.00
## NumDealsPurchases
## [1] 3 2 1 2 5 2 4 2 1 1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 1.000 2.000 2.325 3.000 15.000
## NumWebPurchases
## [1] 8 1 8 2 5 6 7 4 3 1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 2.000 4.000 4.085 6.000 27.000
## NumCatalogPurchases
## [1] 10 1 2 0 3 4 3 0 0 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 0.000 2.000 2.662 4.000 28.000
## NumStorePurchases
## [1] 4 2 10 4 6 10 7 4 2 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 3.00 5.00 5.79 8.00 13.00
## NumWebVisitsMonth
## [1] 7 5 4 6 5 6 6 8 9 20
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 3.000 6.000 5.317 7.000 20.000
## AcceptedCmp3
## [1] 0 0 0 0 0 0 0 0 0 1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00000 0.00000 0.00000 0.07277 0.00000 1.00000
## AcceptedCmp4
## [1] 0 0 0 0 0 0 0 0 0 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00000 0.00000 0.00000 0.07455 0.00000 1.00000
## AcceptedCmp5
## [1] 0 0 0 0 0 0 0 0 0 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00000 0.00000 0.00000 0.07277 0.00000 1.00000
## AcceptedCmp1
## [1] 0 0 0 0 0 0 0 0 0 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00000 0.00000 0.00000 0.06429 0.00000 1.00000
## AcceptedCmp2
## [1] 0 0 0 0 0 0 0 0 0 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00000 0.00000 0.00000 0.01339 0.00000 1.00000
## Complain
## [1] 0 0 0 0 0 0 0 0 0 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000000 0.000000 0.000000 0.009375 0.000000 1.000000
## Z_CostContact
## [1] 3 3 3 3 3 3 3 3 3 3
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3 3 3 3 3 3
## Z_Revenue
## [1] 11 11 11 11 11 11 11 11 11 11
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 11 11 11 11 11 11
## Response
## [1] 1 0 0 0 0 0 0 0 1 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.1491 0.0000 1.0000Análisis de Variables Categóricas
# Seleccionar variables categóricas
categoricas <- sapply(ifood, function(x) is.factor(x) | is.character(x))
categoricas <- names(ifood)[categoricas]
# Análisis para cada variable categórica
for (var in categoricas) {
cat("###", var, "\n\n")
# Tabla de frecuencias
print(table(ifood[[var]]))
# Gráfico de barras
barplot(table(ifood[[var]]), main=paste("Distribución de", var), col=rainbow(length(unique(ifood[[var]]))))
# Gráfico de pastel
pie(table(ifood[[var]]), main=paste("Distribución de", var), col=rainbow(length(unique(ifood[[var]]))))
}## ### Education
##
##
## 2n Cycle Basic Graduation Master PhD
## 203 54 1127 370 486
## ### Marital_Status
##
##
## Absurd Alone Divorced Married Single Together Widow YOLO
## 2 3 232 864 480 580 77 2
## ### Dt_Customer
##
##
## 2012-07-30 2012-07-31 2012-08-01 2012-08-02 2012-08-03 2012-08-04 2012-08-05
## 1 1 4 3 5 4 1
## 2012-08-06 2012-08-07 2012-08-08 2012-08-09 2012-08-10 2012-08-11 2012-08-12
## 3 4 7 2 2 3 6
## 2012-08-13 2012-08-14 2012-08-15 2012-08-16 2012-08-17 2012-08-18 2012-08-19
## 2 2 1 3 8 5 2
## 2012-08-20 2012-08-21 2012-08-22 2012-08-23 2012-08-24 2012-08-25 2012-08-26
## 3 2 8 1 2 3 3
## 2012-08-27 2012-08-28 2012-08-29 2012-08-30 2012-08-31 2012-09-01 2012-09-02
## 3 2 8 4 12 1 1
## 2012-09-03 2012-09-04 2012-09-05 2012-09-06 2012-09-07 2012-09-08 2012-09-09
## 4 4 1 4 6 6 3
## 2012-09-10 2012-09-11 2012-09-12 2012-09-14 2012-09-15 2012-09-17 2012-09-18
## 4 3 11 6 2 3 6
## 2012-09-19 2012-09-20 2012-09-21 2012-09-22 2012-09-23 2012-09-24 2012-09-25
## 1 2 4 6 3 2 4
## 2012-09-26 2012-09-27 2012-09-28 2012-09-29 2012-09-30 2012-10-01 2012-10-02
## 3 2 4 2 1 5 1
## 2012-10-04 2012-10-05 2012-10-06 2012-10-07 2012-10-09 2012-10-10 2012-10-11
## 6 6 2 1 1 5 1
## 2012-10-12 2012-10-13 2012-10-14 2012-10-15 2012-10-16 2012-10-17 2012-10-18
## 5 6 5 4 4 2 5
## 2012-10-19 2012-10-20 2012-10-21 2012-10-22 2012-10-23 2012-10-24 2012-10-25
## 1 2 1 3 2 1 2
## 2012-10-26 2012-10-27 2012-10-28 2012-10-29 2012-10-30 2012-10-31 2012-11-01
## 3 2 4 9 1 5 2
## 2012-11-02 2012-11-03 2012-11-04 2012-11-05 2012-11-06 2012-11-07 2012-11-08
## 2 8 1 5 2 5 3
## 2012-11-09 2012-11-10 2012-11-11 2012-11-12 2012-11-13 2012-11-14 2012-11-16
## 8 6 3 3 6 1 2
## 2012-11-17 2012-11-18 2012-11-19 2012-11-20 2012-11-21 2012-11-22 2012-11-23
## 5 1 3 2 2 3 8
## 2012-11-24 2012-11-25 2012-11-26 2012-11-27 2012-11-28 2012-11-29 2012-11-30
## 3 2 2 1 3 4 1
## 2012-12-01 2012-12-02 2012-12-03 2012-12-04 2012-12-05 2012-12-06 2012-12-07
## 4 2 4 2 4 3 5
## 2012-12-08 2012-12-09 2012-12-10 2012-12-11 2012-12-12 2012-12-14 2012-12-15
## 1 2 2 3 6 1 2
## 2012-12-16 2012-12-17 2012-12-18 2012-12-19 2012-12-20 2012-12-21 2012-12-22
## 4 1 2 4 1 1 5
## 2012-12-23 2012-12-24 2012-12-25 2012-12-26 2012-12-27 2012-12-28 2012-12-29
## 2 5 3 1 1 4 2
## 2012-12-30 2012-12-31 2013-01-01 2013-01-02 2013-01-03 2013-01-04 2013-01-05
## 5 1 4 9 1 2 4
## 2013-01-06 2013-01-07 2013-01-08 2013-01-09 2013-01-10 2013-01-11 2013-01-12
## 2 2 5 2 7 5 8
## 2013-01-13 2013-01-14 2013-01-15 2013-01-16 2013-01-17 2013-01-19 2013-01-20
## 6 1 2 7 6 4 5
## 2013-01-21 2013-01-22 2013-01-23 2013-01-24 2013-01-25 2013-01-26 2013-01-27
## 3 2 5 1 4 3 2
## 2013-01-29 2013-01-31 2013-02-01 2013-02-02 2013-02-03 2013-02-04 2013-02-06
## 3 2 3 4 2 2 5
## 2013-02-07 2013-02-08 2013-02-09 2013-02-10 2013-02-11 2013-02-12 2013-02-13
## 2 2 2 3 4 5 7
## 2013-02-14 2013-02-15 2013-02-16 2013-02-17 2013-02-18 2013-02-19 2013-02-20
## 11 3 7 3 5 5 7
## 2013-02-21 2013-02-22 2013-02-23 2013-02-25 2013-02-26 2013-02-27 2013-02-28
## 2 4 2 3 2 3 2
## 2013-03-01 2013-03-02 2013-03-03 2013-03-04 2013-03-05 2013-03-06 2013-03-07
## 3 1 6 4 1 2 4
## 2013-03-08 2013-03-09 2013-03-10 2013-03-11 2013-03-12 2013-03-14 2013-03-15
## 3 1 5 4 5 2 2
## 2013-03-16 2013-03-17 2013-03-18 2013-03-19 2013-03-20 2013-03-21 2013-03-22
## 2 5 5 5 3 2 3
## 2013-03-23 2013-03-24 2013-03-25 2013-03-26 2013-03-27 2013-03-28 2013-03-29
## 3 3 1 4 4 5 5
## 2013-03-30 2013-03-31 2013-04-01 2013-04-02 2013-04-03 2013-04-05 2013-04-06
## 4 5 5 2 3 8 2
## 2013-04-07 2013-04-08 2013-04-09 2013-04-10 2013-04-11 2013-04-12 2013-04-13
## 1 4 1 3 3 1 7
## 2013-04-14 2013-04-15 2013-04-16 2013-04-17 2013-04-18 2013-04-19 2013-04-20
## 1 4 2 2 6 1 3
## 2013-04-21 2013-04-22 2013-04-23 2013-04-24 2013-04-25 2013-04-27 2013-04-28
## 5 6 3 2 2 5 2
## 2013-04-29 2013-04-30 2013-05-01 2013-05-02 2013-05-03 2013-05-04 2013-05-05
## 3 1 3 5 3 3 3
## 2013-05-06 2013-05-07 2013-05-08 2013-05-09 2013-05-10 2013-05-11 2013-05-12
## 5 3 4 3 4 8 4
## 2013-05-13 2013-05-14 2013-05-15 2013-05-16 2013-05-17 2013-05-18 2013-05-19
## 1 1 4 1 6 3 2
## 2013-05-20 2013-05-21 2013-05-22 2013-05-23 2013-05-24 2013-05-25 2013-05-26
## 6 2 7 3 1 1 4
## 2013-05-27 2013-05-28 2013-05-29 2013-05-30 2013-05-31 2013-06-01 2013-06-02
## 1 4 4 2 3 2 2
## 2013-06-03 2013-06-04 2013-06-06 2013-06-08 2013-06-09 2013-06-10 2013-06-11
## 8 7 3 5 1 4 2
## 2013-06-12 2013-06-13 2013-06-14 2013-06-16 2013-06-17 2013-06-18 2013-06-19
## 3 5 3 2 4 2 4
## 2013-06-20 2013-06-21 2013-06-22 2013-06-23 2013-06-24 2013-06-25 2013-06-26
## 5 4 3 4 3 2 1
## 2013-06-27 2013-06-28 2013-06-29 2013-06-30 2013-07-01 2013-07-02 2013-07-03
## 4 3 3 3 3 3 5
## 2013-07-04 2013-07-05 2013-07-06 2013-07-07 2013-07-08 2013-07-09 2013-07-11
## 6 5 4 3 4 3 3
## 2013-07-12 2013-07-13 2013-07-14 2013-07-15 2013-07-16 2013-07-17 2013-07-18
## 4 3 4 2 3 2 3
## 2013-07-19 2013-07-20 2013-07-21 2013-07-22 2013-07-23 2013-07-24 2013-07-25
## 5 1 5 2 3 2 3
## 2013-07-26 2013-07-27 2013-07-28 2013-07-29 2013-07-30 2013-07-31 2013-08-01
## 2 3 1 5 5 2 5
## 2013-08-02 2013-08-03 2013-08-04 2013-08-05 2013-08-06 2013-08-07 2013-08-08
## 4 2 1 4 3 7 2
## 2013-08-09 2013-08-10 2013-08-11 2013-08-12 2013-08-13 2013-08-14 2013-08-15
## 4 1 4 1 1 1 5
## 2013-08-16 2013-08-17 2013-08-18 2013-08-19 2013-08-20 2013-08-21 2013-08-22
## 3 4 1 3 10 4 3
## 2013-08-23 2013-08-24 2013-08-25 2013-08-26 2013-08-27 2013-08-28 2013-08-29
## 4 1 3 3 1 5 3
## 2013-08-30 2013-08-31 2013-09-01 2013-09-02 2013-09-04 2013-09-05 2013-09-06
## 3 8 3 2 2 4 3
## 2013-09-07 2013-09-09 2013-09-10 2013-09-11 2013-09-12 2013-09-13 2013-09-14
## 3 5 4 6 6 1 1
## 2013-09-15 2013-09-16 2013-09-17 2013-09-18 2013-09-19 2013-09-20 2013-09-21
## 4 5 5 5 3 3 1
## 2013-09-22 2013-09-23 2013-09-24 2013-09-25 2013-09-26 2013-09-27 2013-09-28
## 4 2 2 3 3 3 6
## 2013-09-30 2013-10-01 2013-10-02 2013-10-03 2013-10-04 2013-10-05 2013-10-06
## 5 3 7 5 7 2 4
## 2013-10-08 2013-10-09 2013-10-10 2013-10-11 2013-10-12 2013-10-13 2013-10-14
## 6 3 2 4 6 3 4
## 2013-10-15 2013-10-16 2013-10-17 2013-10-18 2013-10-19 2013-10-20 2013-10-21
## 2 6 4 3 2 4 6
## 2013-10-22 2013-10-23 2013-10-24 2013-10-25 2013-10-26 2013-10-27 2013-10-28
## 3 2 4 7 1 3 8
## 2013-10-29 2013-10-30 2013-11-01 2013-11-02 2013-11-03 2013-11-04 2013-11-05
## 3 3 1 5 4 3 4
## 2013-11-06 2013-11-07 2013-11-08 2013-11-09 2013-11-10 2013-11-12 2013-11-13
## 5 8 1 1 3 2 3
## 2013-11-14 2013-11-15 2013-11-17 2013-11-18 2013-11-19 2013-11-20 2013-11-21
## 6 6 4 1 3 3 2
## 2013-11-22 2013-11-23 2013-11-25 2013-11-26 2013-11-27 2013-11-28 2013-11-29
## 3 7 3 3 2 2 4
## 2013-11-30 2013-12-01 2013-12-02 2013-12-03 2013-12-04 2013-12-05 2013-12-06
## 1 5 3 1 4 2 2
## 2013-12-07 2013-12-08 2013-12-09 2013-12-10 2013-12-11 2013-12-12 2013-12-13
## 5 2 5 2 4 3 2
## 2013-12-14 2013-12-15 2013-12-16 2013-12-17 2013-12-18 2013-12-19 2013-12-20
## 2 2 4 4 1 2 3
## 2013-12-21 2013-12-22 2013-12-23 2013-12-24 2013-12-25 2013-12-26 2013-12-27
## 2 1 4 3 4 4 4
## 2013-12-28 2013-12-29 2013-12-30 2013-12-31 2014-01-01 2014-01-02 2014-01-03
## 1 5 3 3 3 3 3
## 2014-01-04 2014-01-05 2014-01-06 2014-01-07 2014-01-09 2014-01-10 2014-01-11
## 2 2 1 3 1 4 5
## 2014-01-12 2014-01-13 2014-01-14 2014-01-15 2014-01-17 2014-01-18 2014-01-19
## 2 1 2 4 4 3 3
## 2014-01-21 2014-01-22 2014-01-23 2014-01-24 2014-01-25 2014-01-26 2014-01-27
## 5 5 5 3 5 7 4
## 2014-01-28 2014-01-29 2014-01-30 2014-01-31 2014-02-01 2014-02-02 2014-02-03
## 4 1 4 1 1 5 1
## 2014-02-04 2014-02-05 2014-02-06 2014-02-07 2014-02-08 2014-02-09 2014-02-10
## 1 3 2 7 1 3 5
## 2014-02-11 2014-02-12 2014-02-13 2014-02-14 2014-02-15 2014-02-16 2014-02-17
## 3 3 4 1 5 4 5
## 2014-02-18 2014-02-19 2014-02-22 2014-02-23 2014-02-24 2014-02-25 2014-02-26
## 3 2 1 2 5 5 2
## 2014-02-27 2014-02-28 2014-03-01 2014-03-02 2014-03-03 2014-03-04 2014-03-05
## 2 2 9 4 3 3 3
## 2014-03-06 2014-03-07 2014-03-08 2014-03-09 2014-03-10 2014-03-11 2014-03-12
## 2 2 5 2 5 2 5
## 2014-03-13 2014-03-16 2014-03-17 2014-03-18 2014-03-19 2014-03-20 2014-03-21
## 1 2 7 5 3 4 3
## 2014-03-22 2014-03-23 2014-03-24 2014-03-25 2014-03-26 2014-03-27 2014-03-28
## 1 9 4 3 2 1 1
## 2014-03-29 2014-03-30 2014-03-31 2014-04-01 2014-04-02 2014-04-03 2014-04-04
## 6 7 5 3 1 3 2
## 2014-04-05 2014-04-06 2014-04-07 2014-04-08 2014-04-09 2014-04-10 2014-04-11
## 9 3 4 2 2 1 4
## 2014-04-12 2014-04-13 2014-04-14 2014-04-15 2014-04-16 2014-04-17 2014-04-18
## 2 6 2 1 4 2 5
## 2014-04-19 2014-04-20 2014-04-21 2014-04-22 2014-04-23 2014-04-24 2014-04-25
## 2 4 4 1 5 6 2
## 2014-04-26 2014-04-27 2014-04-28 2014-04-29 2014-04-30 2014-05-01 2014-05-02
## 1 1 4 4 4 2 7
## 2014-05-03 2014-05-04 2014-05-05 2014-05-06 2014-05-07 2014-05-08 2014-05-09
## 2 4 1 2 5 4 1
## 2014-05-10 2014-05-11 2014-05-12 2014-05-13 2014-05-15 2014-05-16 2014-05-17
## 4 8 11 3 1 2 2
## 2014-05-18 2014-05-19 2014-05-22 2014-05-23 2014-05-24 2014-05-25 2014-05-26
## 5 5 10 8 5 3 3
## 2014-05-27 2014-05-28 2014-05-29 2014-05-30 2014-05-31 2014-06-02 2014-06-03
## 1 4 6 1 2 2 2
## 2014-06-04 2014-06-05 2014-06-06 2014-06-07 2014-06-08 2014-06-09 2014-06-10
## 1 3 1 3 4 3 3
## 2014-06-11 2014-06-12 2014-06-13 2014-06-14 2014-06-15 2014-06-16 2014-06-17
## 1 1 1 1 4 4 3
## 2014-06-18 2014-06-19 2014-06-20 2014-06-21 2014-06-22 2014-06-23 2014-06-24
## 3 4 2 2 5 2 2
## 2014-06-25 2014-06-26 2014-06-27 2014-06-28 2014-06-29
## 5 4 3 3 2
