Note: There are often multiple ways to answer each question.
Download nba_free_throws.csv from https://github.com/kjytay/misc/tree/master/data. (Right click on nba_free_throws.csv and select “Save Link As…”). Import this dataset into R as the variable df. Are there columns which need their format changed? (You can read more about the dataset here.)
Select just the rows from the 2015-2016 regular season, remove the column play and save the result in df2.
All questions from here are about df2.
Display the top 10 players who took the most free throws.
Free throw percentage is defined as the percentage of shots taken which were made. Display the top 10 players with the highest free throw percentages. (Hint: modify Qn 3 code to take two summaries.)
The highest free throw percentages are so high because these players didn’t take many shots. Display the top 10 players with the highest free throw percentages among only the players who took at least 100 free throws. (Hint: Filter Qn 4 code at an appropriate step.)
Save the summary table of shots taken, shots made and free throw percentage by player in summary_df (only players who took at least 100 free throws). Using summary_df, make a scatterplot of free throw percentage vs. free throws taken. Set the alpha value of the points to 0.5, and draw a blue dashed horizontal line to show the mean free throw percentage across these players. (Hint: For the horizontal line, use geom_abline.)
Which game (in df2) had the most number of free throws? Save the rows in df2 from that game in df3.
Make a bar plot showing the number of free throws each player took in this game. Add coord_flip() as a layer to the plot so that the bars are horizontal. Sort the bars such that the longest ones go on top. (Hint: The forcats package will be helpful here, as will the last example of Section 15.4 of R4DS.)
The following code joins data from summary_df to df3 and saves it as df4 (treat it as a magical incantation for now: the left_join() function is from the dplyr package):
df4 <- df3 %>% left_join(summary_df, by = "player")Modify your bar plot in Qn 8 so that the fill of the bars is equal to the player’s free throw percentage. Add the layer scale_fill_distiller(palette = "RdYlGn", direction = 1) to give your bars some appropriate colors. Why are some bars grey?
Using tidyr’s separate function, separate the game column in df2 to a home column which has the name of the home team, and an away column which has the name of the away team.