exericse.R

# Exercise 7: DPLYR practice with NBA data
# install.packages("dplyr")
library(dplyr)

# Read in the NBA team data of the 2016-2017 season from the data directory  
# into a variable called `team.data` using `read.csv`
team.data <- read.csv("data/teams.csv", stringsAsFactors = FALSE)


# The data.frame team.data should now be accessible to you. 
# View it, and get some basic information about the number of rows/columns. 
# Note the "X" preceding some of the column titles as well as the "*" 
# following the names of teams that made it to the playoffs that year.
View(team.data)


# Add a column that gives the turnovers to steals ratio (TOV / STL) for each team


# Sort the teams from lowest turnover/steal ratio to highest


#Find the average BLK and STL for teams having a TOV greater than the average TOV of all teams


# Get the team that had the highest Total Rebounds (TRB) only with the columns 
# Team and TRB  *using one line of code*


# Print only the name of the team that had the highest total rebounds
# (that also happens to be the greatest team of all time)


## Let's change gears!

# Read in the Pokemon data from the data directory  
# into a variable called `pokemon` using `read.csv`. Remember to not read strings in as factors.

# First, View() the data set to see what info you have to work with 


# Find all the Pokemon that are "Water" or "Ghost" Type 1 and have a speed higher than 50

# Find the average HP, median HP, min HP and max HP for each of the type of generations

#FIND THE NUMBER OF POKEMONS THAT ARE LEGENDARY AND THE NUMBER OF POKEMONS THAT ARE NOT LEGENDARY 
#THAT HAVE A HIGHER ATTACK THAN DEFENSE VALUE
#NOTE: IT SHOULD BE DONE IN ONE RUN OF DPLYR
#HINT : Look into count() function by dplyr

#Find the generation that has the most number of pokemons with Type.1 as "Fire"

# WHICH Type 1 pokemon has the overall within group max value of SUM of HP, Attack, Defense, Sp..Att, Sp.Def, Speed
#HINT : LOOK AT THE DATASET! - THERE IS A SUPER EASY WAY TO DO THIS.