Effective Data Storytelling using the tidyverse
- 15 hours
- 0 Videos
- 50 Exercises
- 181 Participants
- 4,500 XP
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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
Applying R Basics
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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3
Scatter-plots & Line-graphs
Create and analyze different plots relating two numerical variables via the ggplot2 package using datasets in and derived from the fivethirtyeight R package
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5
Barplots
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
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7
Filtering, Grouping, & Summarizing
Choose a subset of rows and summarize a data frame in total and across different levels of other variables using the dplyr package
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9
Supplement to ModernDive textbook
To supplement learning of the material covered at http://moderndive.com, this chapter provides a playground for you to work with the code and better understand what each of the gray chunks of R code throughout the book does.
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2
Tidy Data
Look into tidy data properties on data sets used in articles from fivethirtyeight.com in the fivethirtyeight R package
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4
Histograms & Boxplots
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
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6
ggplot2 Review
Identifying and creating the appropriate plot based on different types of variables using the ggplot2 package
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8
dplyr Review
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.
-
1
Applying R Basics
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.
-
2
Tidy Data
Look into tidy data properties on data sets used in articles from fivethirtyeight.com in the fivethirtyeight R package
-
3
Scatter-plots & Line-graphs
Create and analyze different plots relating two numerical variables via the ggplot2 package using datasets in and derived from the fivethirtyeight R package
-
4
Histograms & Boxplots
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
Barplots
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
ggplot2 Review
Identifying and creating the appropriate plot based on different types of variables using the ggplot2 package
-
7
Filtering, Grouping, & Summarizing
Choose a subset of rows and summarize a data frame in total and across different levels of other variables using the dplyr package
-
8
dplyr Review
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.
-
9
Supplement to ModernDive textbook
To supplement learning of the material covered at http://moderndive.com, this chapter provides a playground for you to work with the code and better understand what each of the gray chunks of R code throughout the book does.
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Instructor
Albert Y. Kim
Assistant Professor of Statistical & Data Sciences at Smith College
Albert completed his Ph.D. in Statistics at the University of Washington. He is a co-author of the fivethirtyeight R package as well as ModernDive, an online textbook for introductory statistics and data science using R. Previously he worked in the Search Ads Metrics Team at Google Inc. as well as at Reed, Middlebury, and Amherst Colleges. Find out more about his work on Twitter @rudeboybert and on his webpage.