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# Effective Data Storytelling using the tidyverse (FREE)

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49 Exercises

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## Course Description

This course is designed to supplement and build on the content covered at http://moderndive.com and the slides at http://bit.ly/soc301-slides. It assumes that you have completed the Introduction to R course on DataCamp.

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1. 1

### Applying R Basics

Free

Exploring the basics of R on a data set based on the fivethirtyeight.com "Most Police Don’t Live In The Cities They Serve" article.

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Investigate the properties of a data frame
100 xp
Identify observational unit
50 xp
Create a vector
100 xp
Subset and index a vector
50 xp
Subset and index a vector again.
100 xp
2. 2

### Tidy Data

Free

Look into tidy data properties on data sets used in articles from fivethirtyeight.com in the fivethirtyeight R package

3. 3

### Scatter-plots & Line-graphs

Free

Create and analyze different plots relating two numerical variables via the ggplot2 package using datasets in and derived from the fivethirtyeight R package

4. 4

### Histograms & Boxplots

Free

Make and interpret different plots relating one categorical variable to one numerical variable via the ggplot2 package using datasets in and derived from the fivethirtyeight R package

5. 5

### Barplots

Free

Generate and examine barplots displaying one categorical variable or relationships between multiple categorical variables via the ggplot2 package using datasets in and derived from the fivethirtyeight R package

6. 6

### ggplot2 Review

Free

Identifying and creating the appropriate plot based on different types of variables using the ggplot2 package

7. 7

### Filtering, Grouping, & Summarizing

Free

Choose a subset of rows and summarize a data frame in total and across different levels of other variables using the dplyr package

8. 8

### dplyr Review

Free

Create a new column in a data frame, modify an existing column, and sort by one or more columns using the dplyr package. Review the main ideas of the Five Main Verbs of dplyr - filter, summarize, group_by, mutate, and arrange.

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Datasets

Cost of livingDivision regionDivisionsIdeologyPolice localsTotal fertility
Chester Ismay

Data Science Evangelist at DataRobot

Chester leads data science, machine learning, and data engineering in-person workshops for DataRobot University with DataRobot. He built (and helped instructors build) R, Python, SQL, and Spreadsheets courses for DataCamp first as a Curriculum Lead and then as Head of Content Development. He obtained a PhD in Statistics from Arizona State University and has taught courses and led workshops in mathematics, computer science, statistics, data science, and sociology. He is co-author of the fivethirtyeight R package and author of the thesisdown R package. He is also a co-author of ModernDive, an open-source textbook for introductory statistics and data science students using R.
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