data-visualization-exercises.Rmd

---
title: "Fundamentals of Data Visualization Exercises"
author: "R for the Rest of Us"
output: 
    html_document:
        css: slides/style.css
        toc: true
        toc_depth: 1
        toc_float: true
        df_print: paged
---


```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

The exercises are part of the Fundamentals of R course. For more, see the [R for the Rest of Us website](https://rfortherestofus.com/courses/fundamentals/).

# Load Packages

Let's load the packages we need. These include `tidyverse` (especially the `dplyr` package) and `janitor`. 

```{r}
# YOUR CODE HERE
```

# Import NHANES Data

Import your data into a data frame called NHANES. Use `clean_names` to make your variable names easy to work with.

```{r}
# YOUR CODE HERE 
```


# Scatterplot

Make a scatterplot that shows weight on the x axis and height on the y axis.

```{r}
# YOUR CODE HERE 
```



# Histogram 

Make a histogram that shows the distribution of the weight variable.


```{r}
# YOUR CODE HERE 
```

Copy your code from above, but adjust it so that there are 50 bins.

```{r}
# YOUR CODE HERE 
```

# Bar Chart

## Bar Chart v1

Use the v1 approach to make a bar chart that shows a count of the number of people who say they smoke. Include NA responses.


```{r}
# YOUR CODE HERE 
```



## Bar Chart v2

Create a new data frame called `sleep_by_gender` that shows the average amount of sleep per night that males and females report getting. Drop any NA (or NaN) responses from this data frame.

```{r}
# YOUR CODE HERE 
```

Plot the average amount of sleep per night for males and females.

```{r}
# YOUR CODE HERE 
```


Make the same graph as above, but use `geom_col` instead of `geom_bar`.

```{r}
# YOUR CODE HERE 
```



# `color` and `fill`

Take your graph from above (the one with `geom_col`) and make the inside of each bar a different color.

```{r}
# YOUR CODE HERE 
```

Make your scatterplot from before that shows weight on the x axis and height on the y axis again, but make the dots show up in different colors based on the `phys_active` variable.

```{r}
# YOUR CODE HERE 
```


# Scales

## color

Take your scatterplot that you just made and add a scale using `scale_color_brewer`. Take a look at the help docs and choose a palette other than the default (hint: look at the `palette` argument). 

```{r}
# YOUR CODE HERE 
```

Do nearly the same thing to change the color of the last bar chart you made (the one about sleep and gender). 

```{r}
# YOUR CODE HERE 
```

## x and y axes

Copy the graph you just made and change the y axis so it goes from 0 to 8.

```{r}
# YOUR CODE HERE 
```

Copy the last code chunk. Then adjust the breaks on the y axis so that it shows 0 to 8 by 1 (i.e. 0, 1, 2, etc).

```{r}
# YOUR CODE HERE 
```


# Text and Labels

Copy your last code chunk. Then do the following:

1. Add text labels to each bar. 
2. Use the `round` argument to just show one decimal place in each label.
3. Use the `vjust` argument to have them show up at the inner edge of the bars.
4. Make the labels all white.

```{r}
# YOUR CODE HERE 
```



Do the same thing as above, but use `geom_label` instead of `geom_text`. Also, do the following:

1. Use the `vjust` argument to have them show up at the outer edge of the bars.
2. Don't show the legend (hint: you'll have to add code in two places to make this happen).

```{r}
# YOUR CODE HERE 
```


# Plot Labels

Use the code chunk from above with `geom_text` (not the last one with `geom_label`). Do the following:

1. Add a title
2. Add a better y axis label
3. Remove the x axis label
4. Remove the legend (hint: use the `show.legend` argument again)

```{r}
# YOUR CODE HERE 
```



# Themes

Install and load the [`hrbrthemes` package](https://hrbrmstr.github.io/hrbrthemes/index.html). It's a package that provides some great default themes. 

It's not available on CRAN, where we normally install packages from, which means you have to install it slightly differently. You'll use the `devtools` package and then use this to install the `hrbrthemes` package. Use the code below.

```{r}
# install.packages("devtools")
# devtools::install_github("hrbrmstr/hrbrthemes")
library(hrbrthemes)
```

Then add the `theme_ipsum` to your plot.

```{r}
# YOUR CODE HERE 
```

# Facets

I've created a data frame called `sleep_by_gender_by_age` for you. Run the code chunk below to load the data frame.

```{r}
sleep_by_gender_by_age <- nhanes %>% 
  group_by(gender, age_decade) %>% 
  summarize(avg_sleep = mean(sleep_hrs_night, na.rm = TRUE)) %>% 
  drop_na()
```

Let's take a look at `sleep_by_gender_by_age`.

```{r}
sleep_by_gender_by_age
```

Now, see if you can recreate this plot. Much of the code will be the same from your previous plots using the `sleep_by_gender` data frame so just make some small changes.

![](plots/sleep-by-gender-by-age.png)

```{r}
# YOUR CODE HERE 
```


# Save Plots

Save your last plot to a PNG that is 8 inches wide and 5 inches high. Put it in the plots directory and call it "my-sleep-plot.png"


```{r}
# YOUR CODE HERE 
```