diff --git a/Exploring_bodyfat.R b/Exploring_bodyfat.R
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+download.file("https://git.embl.de/hsanchez/BTM2016_RDatasets/raw/master/bodyfat.csv", "bodyfat.csv")
+
+bodyfat<-read.csv("bodyfat.csv")
+
+head(bodyfat)
+
+# Names of the columns
+names(bodyfat)
+
+# Dimensions
+dim(bodyfat)
+
+# Checking only one column, try the TAB key
+bodyfat$age
+head( bodyfat[ ,4] )
+head( bodyfat[ ,4], 12 )
+
+# Numeric values describing age
+summary(bodyfat$age)
+
+# Getting the mean of the age values
+summary(bodyfat$age)[4]
+mean(bodyfat$age)
+
+
+
+# How many are younger than 31 years old?
+younger_than_31 <- bodyfat[ (bodyfat$age < 31), ]
+length(younger_than_31)
+
+# Another way
+not_older_than_30 <- bodyfat[ !(bodyfat$age > 30), ]
+length(not_older_than_30)
+
+# Watch out!
+head( bodyfat[  !(bodyfat$age  > 30), ] )
+head( bodyfat[  !which(bodyfat$age  > 30), ] )
+## not equivalent!
+
+
+
+number_of_columns <- length(names(bodyfat))
+number_of_columns <- dim(bodyfat)[2]
+my_vector <- vector(length = number_of_columns)
+for( i in 1:length( names(bodyfat) ) ){
+  one_column <- bodyfat[ ,i]
+  the_mean <- mean(one_column)
+  my_vector[i] <- the_mean
+}
+names(my_vector) <- names(bodyfat)
+
+my_vector
+
+apply(bodyfat, MARGIN = 2, FUN = mean)
+
+usingFor <- function(){
+  my_vector <- vector(length = number_of_columns)
+  for( i in 1:length( names(bodyfat) ) ){
+   one_column <- bodyfat[ ,i]
+   the_mean <- mean(one_column)
+   my_vector[i] <- the_mean
+  }
+  names(my_vector) <- names(bodyfat)
+}
+usingApply <- function(){
+  temp <- apply(bodyfat, MARGIN = 2, FUN = mean)
+}
+
+system.time(replicate(1000000, usingFor))
+system.time(replicate(1000000, usingApply))
+
+library(pryr)
+mem_change(v <- 1:1e6)
+mem_change(rm(v))
+try(rm(new_variable))
+mem_change(new_variable <- bodyfat$age)
+
+
+# Going back!
+
+apply(bodyfat, MARGIN = 2, FUN = mean)
+
+Subset_1_indexes<-which(bodyfat$age < 31)
+Subset_1<-bodyfat[Subset_1_indexes, ]
+
+# Getting the 30+ 
+temp_indexes<-which(bodyfat$age > 30)
+Subset30plus<-bodyfat[temp_indexes, ]
+
+Subset_2_indexes<-which(Subset30plus$age < 51)
+Subset_2<-Subset30plus[Subset_2_indexes, ]
+
+Subset_3_indexes<-which(Subset30plus$age > 50)
+Subset_3<-Subset30plus[Subset_3_indexes, ]
+
+summary(Subset_2$age)
+summary(Subset_3$age)
+
+# Finally, getting the weight per Subset:
+mean(Subset_1$percent.fat)
+mean(Subset_2$percent.fat)
+mean(Subset_3$percent.fat)
+
+# Young people
+mean( bodyfat[  bodyfat$age < 31, ]$percent.fat )
+# Not so young people
+mean( bodyfat[  bodyfat$age > 30 & bodyfat$age < 51, ]$percent.fat )
+# Definitely not young people
+mean( bodyfat[  bodyfat$age > 50, ]$percent.fat )
+
+Option1<-function(){
+  Subset_1_indexes<-which(bodyfat$age < 31)
+  Subset_1<-bodyfat[Subset_1_indexes, ]
+  temp_indexes<-which(bodyfat$age > 30)
+  Subset30plus<-bodyfat[temp_indexes, ]
+  Subset_2_indexes<-which(Subset30plus$age < 51)
+  Subset_2<-Subset30plus[Subset_2_indexes, ]
+  Subset_3_indexes<-which(Subset30plus$age > 50)
+  Subset_3<-Subset30plus[Subset_3_indexes, ]
+  summary(Subset_2$age)
+  summary(Subset_3$age)
+  mean(Subset_1$percent.fat)
+  mean(Subset_2$percent.fat)
+  mean(Subset_3$percent.fat)
+}
+
+Option2<-function(){
+  mean( bodyfat[  bodyfat$age < 31, ]$percent.fat )
+  mean( bodyfat[  bodyfat$age > 30 & bodyfat$age < 51, ]$percent.fat )
+  mean( bodyfat[  bodyfat$age > 50, ]$percent.fat )
+}
+
+system.time(replicate(1000000, Option1))
+system.time(replicate(1000000, Option2))
+
+# Which columns are not the index, nor the age?
+I_do_not_want_these_ones<-which(names(bodyfat)==c("X", "age"))
+names(bodyfat[-I_do_not_want_these_ones])
+
+# I calculate the pearson correlations of age and all the other values
+sapply(bodyfat[-I_do_not_want_these_ones], function(x){
+  cor(bodyfat$age, x)
+})
+
+
+cor(bodyfat$percent.fat, bodyfat$density)
+
+plot(bodyfat$age, bodyfat$percent.fat, main="Age vs Percent fat")
+plot(bodyfat$age, bodyfat$density, main="Age vs Density")
+plot(bodyfat$percent.fat, bodyfat$density, main="Percent fat vs Density")
+
+pairs(bodyfat)
+
+pairs(bodyfat[ , 1:6])
+
+message("Your code is talking to you")
+
+#for(i in c(2, 1, 0, -1)){
+#  sqrt(i)
+#}
+
+for(i in c(2, 1, 0, -1)){
+  if(i >= 0){
+    sqrt(i)
+    print(i)
+  }
+}
+
+# Trying to calculate the mean of the columns 4th, 3rd, and 17th
+# Unknown vector
+UnknownVector <- c(c(4, 3, 17))
+#sapply( UnknonwVector, function(x){
+#  mean(bodyfat[, x])
+#})
+
+# bodyfat[ ,17]
+
+# Lets prevent to have an error:
+# option 1:
+sapply( UnknownVector, function(x){
+  try(mean(bodyfat[, x]))
+} )
+
+# Option 2:
+sapply( UnknownVector[ which( UnknownVector %in% 1:dim(bodyfat)[2] ) ], function(x){
+  mean( bodyfat[, x] )
+} )
+
+# Option 3:
+options(show.error.messages = FALSE)
+sapply( UnknownVector, function(x){
+  to_return <- NA
+  column <- try(bodyfat[, x])
+  if( class(column) == "try-error" ){
+    message( paste0("The column ", x, " does not exist, I'm sorry :( ") )
+  }  else
+    to_return <- mean( column )
+  return(to_return)
+} )
+options(show.error.messages = TRUE)
+                                                                 
+                                                                 
+
+                                                                                                                                  
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