diff --git a/v3/lab 2 - problems.R b/v3/lab 2 - problems.R
index ec4a823..1c2e67a 100644
--- a/v3/lab 2 - problems.R	
+++ b/v3/lab 2 - problems.R	
@@ -1,46 +1,95 @@
-#######################################################################################################################
-#
-# PROBLEMS 
-#
-#######################################################################################################################
-#
-# Load the Movies dataset using the command:
-#
-#	md <- read.table("movies.txt", sep=",", header=TRUE)
-#
-# Answer the following questions:
-#
-# - Are there more movies shorter than 100 min or longer than (or equal to) 100 minutes?
-#   (show your answer numerically and graphically) 
-#
-# - Are there more action comedies or romantic comedies?
-#
-# - Plot a histogram of the ratings for drama movies.
-#
-# - Is the average rating of dramas higher than the average rating of non-dramas?
-#   (show your answer numerically and graphically)
-#
-# - Plot the number of animated movies being produced every year for the period 1995-2005.
-#
-# - Is there a clear boundary between short and feature movies (according to their length)?
-#
-#
-#######################################################################################################################
-#
-# Load the Players dataset using the command:
-#
-#	players <- read.table("players.txt", sep=",", header = T)
-#
-# - Plot the proportion of players according to playing positions.
-#
-# - Compare career rebounds (the "reb" attribute) with respect to playing position.
-#
-# - Show the distribution of free throw percentages.
-#   The percentage is determined by dividing the number of shots made ("ftm") by the total number of shots attempted ("fta").
-#
-# - Compare career 3-pointers made for the players active between 1990 and 2007, with respect to playing position. 
-#
-# - How does the average career length of retired players vary from year to year?
-#
-#######################################################################################################################
-
+#######################################################################################################################
+#
+# PROBLEMS 
+#
+#######################################################################################################################
+#
+# Load the Movies dataset using the command:
+#
+#	md <- read.table("movies.txt", sep=",", header=TRUE)
+#
+# Answer the following questions:
+#
+# - Are there more movies shorter than 100 min or longer than (or equal to) 100 minutes?
+#   (show your answer numerically and graphically) 
+#
+# - Are there more action comedies or romantic comedies?
+#
+# - Plot a histogram of the ratings for drama movies.
+#
+# - Is the average rating of dramas higher than the average rating of non-dramas?
+#   (show your answer numerically and graphically)
+#
+# - Plot the number of animated movies being produced every year for the period 1995-2005.
+#
+# - Is there a clear boundary between short and feature movies (according to their length)?
+#
+#
+#######################################################################################################################
+md <- read.table("movies.txt", sep=",", header=TRUE)
+library(ggplot2)
+library(dplyr)
+
+
+# We will transform binary attributes into nominal variables with a fixed number of possible values (factors)
+md$Action <- as.factor(md$Action)
+md$Animation <- as.factor(md$Animation)
+
+# The remaining columns will be transformed using the for loop
+for (i in 20:24)
+  md[,i] <- as.factor(md[,i])
+
+
+# - Are there more movies shorter than 100 min or longer than (or equal to) 100 minutes?
+#   (show your answer numerically and graphically)
+movies_shorter_or_equal_100_min <- md$length >= 100
+tab <- table(movies_shorter_or_equal_100_min) 
+names(tab) <- c("Less than 100", "More or equal to 100")
+pie(tab)
+
+# - Are there more action comedies or romantic comedies?
+md  %>% filter(Comedy == 1)  %>% mutate(number_of_actions = sum(Action == 1)) %>% 
+  mutate(number_of_action_movies = sum(Action == 1)) %>%
+  mutate(number_of_Romances = sum(Romance == 1)) %>%
+  select(number_of_action_movies, number_of_Romances) %>% 
+  unique()
+
+
+# - Plot a histogram of the ratings for drama movies.
+md %>% filter(Drama == 1) %>%  ggplot(aes(rating))  + geom_histogram(bins = 10)
+
+# - Is the average rating of dramas higher than the average rating of non-dramas?
+#   (show your answer numerically and graphically)
+
+lol <- md %>% filter(Drama == 1) %>% select(rating) %>%
+  mutate(higher_than_avg_rating = rating > mean(rating)) %>%
+  select(higher_than_avg_rating)# %>%
+#  summarise(is_higher = sum(higher_than_avg_rating == TRUE), is_lower = sum(higher_than_avg_rating == FALSE))
+pie(table(lol))
+
+# - Plot the number of animated movies being produced every year for the period 1995-2005.
+sel <- md$year >= 1999 & md$year <= 2005
+tt <- table(md$Animation[sel], md$year[sel])
+barplot(tt[2,], xlab="Year", ylab="Relative frequency", main="Proportion of animated movies")
+
+# - Is there a clear boundary between short and feature movies (according to their length)?
+
+#######################################################################################################################1
+#
+# Load the Players dataset using the command:
+#
+#	players <- read.table("players.txt", sep=",", header = T)
+#
+# - Plot the proportion of players according to playing positions.
+#
+# - Compare career rebounds (the "reb" attribute) with respect to playing position.
+#
+# - Show the distribution of free throw percentages.
+#   The percentage is determined by dividing the number of shots made ("ftm") by the total number of shots attempted ("fta").
+#
+# - Compare career 3-pointers made for the players active between 1990 and 2007, with respect to playing position. 
+#
+# - How does the average career length of retired players vary from year to year?
+#
+#######################################################################################################################
+