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Introduction to the Tidyverse
Introduction to the Tidyverse
Run the hidden code cell below to import the data used in this course.
# Load the Tidyverse
library(tidyverse)
# Read in the gapminder file
gapminder <- read.csv("datasets/gapminder.csv", sep = "\t")Ch. 1: Data Wrangling
The filter verb
filter verb- used to look at a subset of observations based on a particular condition.
- used with pipe operator
%>% ==is a logical equals.
# Filter for year 2007
gapminder %>%
filter(year == 2007)# Filtering for one country
gapminder %>%
filter(country == "United States")# Filtering for two variables
gapminder %>%
filter(year == 2007, country == "United States")The arrange verb
arrange verb- sorts a table based on a variable
# Sorting with `arrange`
gapminder %>%
arrange(gdpPercap)# Sorting in descending order
gapminder %>%
arrange(desc(gdpPercap))# Filtering then arranging
gapminder %>%
filter(year == 2007) %>%
arrange(desc(gdpPercap))The mutate verb
mutate verb- mutate changes or adds variables
# Using mutate to change a variable
gapminder %>%
mutate(pop = pop / 1000000)# Using mutate to add a new variable
gapminder %>%
mutate(gdp = gdpPercap * pop)# Combining verbs
gapminder %>%
mutate(gdp = gdpPercap * pop) %>%
filter(year == 2007) %>%
arrange(desc(gdp))Chapter 2: Data Visualization
Visualizing with ggplot2
ggplot2