Assess Your DATA QUALITY in R with skimr

    Written by Matt Dancho on March 9, 2021

    Skimr is my go-to R package for fast data quality assessment, and Skimr is my first step in exploratory data analysis. Before I do anything else, I check data quality with skimr.

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    DataExplorer: Exploratory Data Analysis in R

    Written by Matt Dancho on March 2, 2021

    Did you know most Data Scientists spend 80% of their time just trying to understand and prepare data for analysis? R has an Insane Exploratory Data Analysis productivity-enhancer. It's called DataExplorer.

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    5 Reasons You Should Learn Shiny

    Written by Matt Dancho and Jarrell Chalmers on February 25, 2021

    Many data scientists struggle with distributing their work, however, you can make that a problem of the past thanks to Shiny. Here are five reasons you should learn Shiny and why it is a game-changer for upskilling your career.

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    How to Add Shiny to Rmarkdown

    Written by Matt Dancho on February 24, 2021

    Shiny is an R web framework with a HUGE ECOSYSTEM of interactive widgets, themes, and customizable user interfaces called the Shinyverse. In this article, we use Shiny to make our R Markdown Report interactive.

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    R is for Research, Python is for Production

    Written by Matt Dancho and Jarrell Chalmers on February 18, 2021

    Both R and Python are great. We’ll showcase some of the strengths of each language in this article by showcasing where the major development efforts are within each ecosystem.

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    4 Ways to make Data Frames in R!

    Written by Matt Dancho on February 2, 2021

    Data frames (like Excel tables) are the main way for storing, organizing, and analyzing data in R. Here are 4 ways using the tidyverse.

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    Should you learn Python or R in 2021?

    Written by Matt Dancho on January 28, 2021

    For years Python and R have been pitted as mortal enemies in the world of data science, enticing its practitioners to choose a side and never look back - not anymore. It's time for these two titans to join forces through reticulate which allows us to use Python and R together!

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