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Communicating with Data in the Tidyverse

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

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4 Horas15 Videos53 Ejercicios
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Descripción del curso

They say that a picture is worth a thousand words. Indeed, successfully promoting your data analysis is not only a matter of accurate and effective graphics, but also of aesthetics and uniqueness. This course teaches you how to leverage the power of ggplot2 themes for producing publication-quality graphics that stick out from the mass of boilerplate plots out there. It shows you how to tweak and get the most out of ggplot2 in order to produce unconventional plots that draw attention on social media. In the end, you will combine that knowledge to produce a slick and custom-styled report with RMarkdown and CSS – all of that within the powerful tidyverse.
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Tidyverse Fundamentals con R

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  1. 1

    Custom ggplot2 Themes

    Gratuito

    In this chapter, you will have a first look at the data you're going to work with throughout this course: the relationship between weekly working hours and monetary compensation in European countries, according to the International Labour Organization (ILO). After that, you'll dive right in and discover a stunning correlation by employing an exploratory visualization. You will then apply a custom look to that graphic – you'll turn an ordinary plot into an aesthetically pleasing and unique data visualization.

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    Introduction to the data
    50 xp
    Join the two data sets together
    100 xp
    Change variable types
    100 xp
    Filtering and plotting the data
    50 xp
    Filter the data for plotting
    100 xp
    Some summary statistics
    100 xp
    A basic scatter plot
    100 xp
    Add labels to the plot
    100 xp
    Custom ggplot2 themes
    50 xp
    Apply a default theme
    100 xp
    Change the appearance of titles
    100 xp
    Alter background color and add margins
    100 xp
  2. 2

    Creating a Custom and Unique Visualization

    Barcharts, scatter plots, and histograms are probably the most common and effective data visualizations. Yet, sometimes, there are even better ways to visually highlight the finding you want to communicate to your audience. So-called "dot plots" make us better grasp and understand changes in data: development over time, for example. In this chapter, you'll build a custom and unique visualization that emphasizes and explains exactly one aspect of the story you want to tell.

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  3. 3

    Introduction to RMarkdown

    Back in the old days, researchers and data analysts used to generate plots in R and then tediously copy them into their LaTeX or Word documents. Nowadays, whole reports can be produced and reproduced from within R and RStudio, using the RMarkdown language – combining R chunks, formatted prose, tables and plots. In this chapter, you'll take your previous findings, results, and graphics and integrate them into such a report to tell the story that needs to be told.

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  4. 4

    Customizing Your RMarkdown Report

    Your boss, your client, or your professor usually expects your results to be accurate and presented in a clear and concise structure. However, coming up with a nicely formatted and unique report on top of that is certainly a plus and RMarkdown can be customized to accomplish this. In this last chapter, you'll take your report from the last chapter and brand it with your own custom and unique style.

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En las siguientes pistas

Tidyverse Fundamentals con R

Ir a la pista

Sets De Datos

Hourly Compensation (ILO)Weekly Working Hours (ILO)

Colaboradores

Collaborator's avatar
Yashas Roy
Collaborator's avatar
Chester Ismay
Timo Grossenbacher HeadshotTimo Grossenbacher

Head of Newsroom Automation at Tamedia

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