1 Introduction
Hello!
For the first half of this workshop, we will be plotting datasets about HIV prevalence or incidence from countries around the world.
They number of persons that are estimated to be infected by HIV, including those without symptoms, those sick from AIDS and those healthy due to treatment of the HIV infection
Prevalence is a measure of the number of total cases in a year, and incidence is a measure of the number of new cases in a given time period.
The data also gives you the population for a given country-year.
The assignment should be submitted individually, but you are encouraged to brainstorm with partners.
The final due date for the assignment is Tuesday, November 29th at 23:59 PM UTC+2.
2 Get the assignment repo
To get started, you should download and look through the assignment folder.
First download the repo to your local computer here.
You should ideally work on your local computer, but if you would rather work on RStudio Cloud, you can upload the zip file to RStudio Cloud through the Files pane. Consult one of the instructors for guidance on this.
Unzip/Extract the downloaded folder.
If you are on macOS, you can simply double-click on a file to unzip it.
If you are on Windows and are not sure how to “unzip” a file, see this image. You need to right-click on the file and then select “extract all”.
Once done, click on the RStudio Project file in the unzipped folder to open the project in RStudio.
In RStudio, navigate to the Files tab and open the “rmd” folder. The instructions for your exercise are outlined there (these are the same instructions you see here).
Open the “data” folder and observe its components. Chose one of the two HIV datasets - would you like to analyze incidence or prevalence? Discuss with your partner and choose.
3 Load the data
Now that you understand the structure of the repo, you can load your chosen dataset.
In the code section below, load in the needed packages.
Now, read the dataset into R. Remember to use the
here() function to allow your Rmd to use project-relative
paths.
## Rows: 1020 Columns: 4
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): country
## dbl (3): year, new_cases, population
##
## 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.3.1 Step 1: Inspect the data types of your variables
The kinds of plots you can make is dependent on the data classes of
your variable. Take a look at these types with summary() or
typeof().
## country year new_cases population
## Length:1020 Min. :1995 Min. : 60 Min. :2.070e+05
## Class :character 1st Qu.:1998 1st Qu.: 1400 1st Qu.:3.299e+06
## Mode :character Median :2002 Median : 7000 Median :9.819e+06
## Mean :2002 Mean : 38898 Mean :4.269e+07
## 3rd Qu.:2006 3rd Qu.: 26000 3rd Qu.:2.587e+07
## Max. :2009 Max. :720000 Max. :1.190e+09## [1] "double"Note that this dataset is structured very similarly to the
nigerm dataset we used in Lesson 1.
3.2 Step 2: Choose your countries.
In this exercises you will be comparing patterns between countries. Since there are dozens of countries in the data, this may be too much to visualize at once. Choose 3-5 countries you would like to analyze.
(Hint: use dplyr::filter() to subset your data.)
You will be using hiv_mini to plot.
4 Creating a ggplot in layers
4.1 Time series plot
Using the subset you just made above, plot the number of cases over time as line graph. Line graphs are great for visualizing time series.
Think about what x and y aesthetic you need, and then which
geom_*() function.
Now, add color to this plot so that you can distinguish between countries. Then, increase the line width. Think about whether these aesthetic are mapping or fixed aesthetics!
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
Chaining together functions to add layers is a key feature of
{ggplot2}. In the scatter plots lesson, we added
geom_smooth() to geom_point() .
Think about what other types of plots besides line graphs can visualize the relationship between two continuous numeric variables.
You can check the Cheatsheets tab in your RStudio Help menu and browse the different geoms.
Next, add your another geom_*() layer to this plot.
Hint: there’s a very common plot type that works for this!
Now, add at least 2 more aesthetics (fixed or mapped) to your plot.
The aesthetic we have covered so far are: - color -
point color or point outline color
size- point sizealpha- point opacityshape- point shapefill- point fill color (only applies if the point has an outline)
Lastly, you can add a title to your plot with the
ggtitle() function. See ?ggtitle for more
information.
4.2 Extra: explore scatter plots
Next you get to exercise your creativity! You task for this section is to use one of the datasets in the “extra” folder under “data”. Both these datasets contain continuous data that excellent for scatter plots.
- Create a scatter plot with
geom_point(), and show a relationship between two variables.
## Rows: 142 Columns: 9
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): sex, status, oms_recommendation
## dbl (6): personal_id, household_id, bmi, sedentary_ap_s_day, light_ap_s_day,...
##
## 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.## [1] "double"## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 10 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 3 rows containing missing values (`geom_line()`).## Warning: Removed 10 rows containing missing values (`geom_point()`).
Group or scale the points by a third variable. You can use color, shape, are any other aesthetic to display information about an additional variable.
Add a smoothing line!
5 Submission: Upload HTML
Once you have finished the tasks above, you should knit this Rmd into an HTML and upload it on the assignment page.