Sharon Machlis

Executive Editor, Data & Analytics

Sharon Machlis is Director of Editorial Data & Analytics at IDG, where she works on analyzing data (both for IDG Enterprise Web sites and journalism projects) and in-house editor tools in addition to writing and editing. Her tech interests include data visualization and analysis as well as the intersection of journalism and technology. She holds an Extra class amateur radio license and is currently somewhat obsessed with R. Her book Practical R for Mass Communication and Journalism was published in December 2018.

How to write an R package

How to run Python in R

How to run Python in R

Learn how to run Python code inside an R script using the reticulate R package

Do more with R: Write your own RStudio addins

Do more with R: Write your own RStudio addins

This RStudio addins tutorial walks you step by step through creating an extension for the RStudio IDE

How to create color-coded calendars in R

How to create color-coded calendars in R

Track your goals with color-coded calendars created with R packages ggplot2 and ggcal

Do more with R: RStudio addins and keyboard shortcuts

Do more with R: RStudio addins and keyboard shortcuts

Speed up your R programming workflow with RStudio addins and customized keyboard shortcuts

Do more with R: Quick lookup tables using named vectors

Do more with R: Quick lookup tables using named vectors

Learn how named vectors give R developers an easy to use key-value pairs

R tip: Keep your passwords and tokens secure with the keyring package

R tip: Keep your passwords and tokens secure with the keyring package

Saving tokens and passwords in an R environment variable means they’re stored in an unencrypted, clear text file. With the keyring package, your credentials are more secure

R tutorial: How to import data into R

R tutorial: How to import data into R

In this book excerpt, learn how to import data into R from spreadsheets, HTML tables, and more

How to add sparklines to R tables

How to add sparklines to R tables

When you want to visualize results in each row—such as when each row of data is a trend over time—you can do that inside a new table column with mini inline graphs called sparklines

Do more with R: Quick interactive HTML tables

Do more with R: Quick interactive HTML tables

See how to create an interactive table with one line of code (and the DT package). Plus, easy customizations

Do more with R: drag-and-drop ggplot

Do more with R: drag-and-drop ggplot

A new R package creates a simple graphical user interface for ggplot2—and it generates R code for the visualization you create

Reshape data in R with the tidyr package

Reshape data in R with the tidyr package

See how the tidyr R package’s gather and spread functions work. Plus a bonus look at labeling in ggplot2 with the directlabels package

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