This week, I will analyze Car Fuel Economy dataset from TidyTuesday.
What is TidyTuesday? TidyTuesday is a weekly social data project in R organized by the R for Data Science community.
It is a great way of improving your Data wrangling and visualization techniques, sharing and learning from others.
You can find more information on their github.
Fuel economy data are the result of the work done by the US Environmental Protection Agency.
ggplot2 is a powerful data visualization tool of R. Make quick visualizations to explore or share your insights.
Learning how aesthetics and attributes are defined in ggplot will give you an edge to develop your skills quickly.
ggplot2 tips: distinction between aesthetics and attributes Aesthetics are defined inside aes() in ggplot syntax and attributes are outside the aes().
e.g. ggplot(data, aes(x, y, color=var1) + geom_point(size=6)
We typically understand aesthetics as how something looks, color, size etc.
My ambitious goal is to write a machine learning algorithm that predicts authors. But let’s start with something simpler. An important part in a Data Science workflow is data preparation. Clean it, reformat it and make it usable for further analysis.
Figure 1: Photo by Patrick Tomasso on Unsplash I will work on a Poetry book called “New Poems” from D. H. Lawrence. You can download it from Project Gutenberg website which is a library of over 60,000 free eBooks.
This guide will help you to get your website online in a few minutes. Then, customize and add your own material in RStudio environment, push it to your Github repository and benefit from the continuous deployment feature of Netlify. It took me many days of work, reading tens of blog posts, YouTube videos and a lot of testing to figure out all of this.
Here is an up to date workflow of how I created my Blog on Github and deployed at Netlify.