Homework 9: Data Manipulation

Author

Your Name

Published

Due: April 14, 2023

Note: This assignment must be submitted in github classroom.

Steam Games

This week’s homework data is from TidyTuesday, an organization that provides datasets every Tuesday for people to practice their data tidying and manipulation skills. See the readme for more information.

Data Dictionary

variable	class	description
gamename	character	Name of video games
year	double	Year of measure
month	character	Month of measure
avg	double	Average number of players at the same time
gain	double	Gain (or loss) Difference in average compared to the previous month (NA = 1st month)
peak	double	Highest number of players at the same time
avg_peak_perc	character	Share of the average in the maximum value (avg / peak) in %

games <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-03-16/games.csv')

Rows: 83631 Columns: 7
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): gamename, month, avg_peak_perc
dbl (4): year, avg, gain, peak

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

library(ggplot2) # load ggplot2 package

General Instructions:

Pick one language, R or Python, to start with. Replicating the plots in each language will earn you an additional 4 bonus points on this 10-point assignment.

R: Replicate the plot

Your first goal (in R) is to get to this graph by breaking down the problem (replicating the graph) into smaller steps that make sense and that you can accomplish piece-by-piece.

Problem Steps

Make a list of steps that will be necessary to get the data you have into this form.

Problem Code

Provide code that sequentially works through your list of steps to produce the graph. You might put your steps as comments to remind yourself what you’re doing at each point in the code.

# Code for step 1 goes here

Python: Replicate a (different) plot

# Run this if you haven't installed plotnine already
reticulate::py_install("plotnine")

import pandas as pd
from plotnine import *

games = pd.read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-03-16/games.csv')

This plot shows the 5 games with the most average users in March of 2020. It is ok if you can replicate this plot to the point where the legend doesn’t show up properly, as in this image:

Problem Steps

Make a list of steps below that will be necessary to get the data you have into this form.

Problem Code

Provide code that sequentially works through your list of steps to produce the necessary table of games.

Useful Hints

R

month.name is a vector containing month names that you can use to create a factor variable. Factor variables can be easily converted into numeric variables. This might help you get a numeric month, which might help you get to a fractional year. Alternately, you can use the match() function to get a numeric month by using match(dataframe$month, month.name).
dplyr::filter() is a function that will subset a data frame based on a logical condition. It might be easier to use than logical indexing (though you can use either)
To get a line graph in ggplot2, use geom_line(). Using aes(color = varname) will color the lines by variable name.
Some sample code to make a line graph in ggplot is provided below:

library(dplyr)
# Get only january months so that there's one point a year
jan_data <- filter(games, month == "January")

# x axis is year, y axis is average players
# group = gamename says draw one line for each game
ggplot(data = jan_data, 
       aes(x = year, y = avg, group = gamename)) + 
  geom_line()

Note that you will need to modify this code to use the correct data frame (that you generate) as well as to e.g. use color.

Python

Pandas will let you sort a data frame in decreasing order of variable x using sort_values('x', ascending = False)
You can select rows of a python data frame that match a list using .isin() demo
Using the .assign() function to create new variables will reduce the number of errors you run into. You may be able to get the correct answer without this tip, but if you run into a ‘modify on copy’ or ‘copy on write’ error, consider using .assign().
Sample code to make a line plot in plotnine is provided below:

# Get only january months so that there's one point a year
jan_data = games.query('month == "January"')

# x axis is year, y axis is average players
# group = gamename says draw one line for each game
ggplot(jan_data, aes(x ="year", y = "avg", group = "gamename")) + geom_line()

<Figure Size: (640 x 480)>

Note that you will need to modify this code to use the correct data frame (that you generate) as well as to e.g. use color.