---
title: "Week 3 Lecture 1"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(gapminder)
```
### Tidy data
library(tidyverse)
library(ggplot2)
library(gapminder)
### Wide format vs. tidy data
a <- spread(gapminder %>% select(country, year, lifeExp), key=country, value = lifeExp)
### First graph in ggplot
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y=lifeExp))
p + geom_point()
```
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y=lifeExp))
p + geom_point() + geom_smooth(method="loess")
```
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y=lifeExp))
p + geom_point() + geom_smooth(method="loess") + scale_x_continuous(labels=scales::dollar)
```
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y=lifeExp))
p + geom_point() + geom_smooth(method="loess") + scale_x_log10()
```
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y=lifeExp))
p + geom_point(color="black") + geom_smooth(method="loess", color="orange") + scale_x_log10(labels=scales::dollar)
```
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y = lifeExp))
p + geom_point(color = "purple") +
geom_smooth(method = "loess") +
scale_x_log10()
```
```{r}
p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y=lifeExp))
p + geom_point(alpha = 0.3) +
geom_smooth(method = "gam", color="orange") +
scale_x_log10(labels = scales::dollar) +
labs(x = "GDP Per Capita", y = "Life Expectancy in Years",
title = "Economic Growth and Life Expectancy",
subtitle = "Data points are country-years",
caption = "Source: Gapminder.")
```
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y = lifeExp,
color = continent,
fill = continent))
p + geom_point() +
geom_smooth(method = "loess") +
scale_x_log10()
```
```{r}
p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp))
p + geom_point(mapping = aes(color = continent)) +
geom_smooth(method = "lm") +
scale_x_log10()
```
```{r}
p <- ggplot(data = gapminder,
mapping = aes(x = gdpPercap,
y = lifeExp))
p + geom_point(mapping = aes(color = log(pop))) + scale_color_gradientn(colours = terrain.colors(7)) +
scale_x_log10()
```