class4_solutions.Rmd

---
title: 'Introduction to R, Class 4: Solutions'
output: github_document
---
  
<!--class4_solutions.md is generated from class4_solutions.Rmd. Please edit that file -->
  
  ```{r setup, include=FALSE, purl=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r include=FALSE}
library(tidyverse)
clinical <- read_csv("../data/clinical.csv")
smoke_complete <- read_csv("../data/smoke_complete.csv")
birth_reduced <- read_csv("../data/birth_reduced.csv")
```

## Challenge-scatterplot
```{r scatterplot}
ggplot(data=smoke_complete,
       aes(x=age_at_diagnosis, 
           y=years_smoked, color=gender)) +
  geom_point()
```

#### Challenge-comments
```{r comments}
# assign data and aesthetics to object
my_plot <- ggplot(smoke_complete, aes(x = vital_status, y = cigarettes_per_day))
# start with data/aesthetics object
my_plot +
  # add geometry (boxplot)
  geom_boxplot(outlier.shape = NA) +
  # add jitter
  geom_jitter(alpha = 0.2, color = "purple")
```

#### Challenge-order
Yes, the order matters.
```{r order}
ggplot(data=smoke_complete,
       aes(x=vital_status, y=cigarettes_per_day)) +
  geom_jitter(alpha=0.3, color="tomato") +
  geom_boxplot()
```

#### Challenge-line
```{r line}
yearly_counts2 <- birth_reduced %>%
  count(year_of_birth, gender)
ggplot(data=yearly_counts2, 
       aes(x=year_of_birth, y=n, color=gender)) +
  geom_line(aes(color=gender))
```

#### Challenge-dash
```{r dash}
ggplot(data=yearly_counts2, 
       aes(x=year_of_birth, y=n, color=gender)) +
  geom_line(aes(linetype=gender))
```

#### Challenge-panels
```{r panels}
ggplot(data=yearly_counts2, 
       aes(x=year_of_birth, y=n, color=gender)) +
  geom_line() +
  facet_wrap(~gender)
```

#### Challenge-axis
One possible search result [here](http://www.sthda.com/english/wiki/ggplot2-axis-ticks-a-guide-to-customize-tick-marks-and-labels#set-the-position-of-tick-marks).
```{r axis}
ggplot(data=yearly_counts2, 
       aes(x=year_of_birth, y=n, color=gender)) +
  geom_line() +
  theme(axis.text.x = element_blank(), # hide labels
    axis.text.y = element_blank()) +
  facet_wrap(~gender)
```

## Extra exercises

#### Challenge-improve
There are lots of options for this answer!