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Joining DataFrames

What is a join? Why would we do it? And how would we do it using DataFrames.jl? These are the questions we're answering in this post.

Recent posts

DataFrames Basics - Index, Sort and Aggregate!

Diving deeper into DataFrames.jl, we'll explore how to do boolean indexing on dataframes, learn how to sort our data and aggregate it to our hearts' content. In the final section, we'll also touch upon the de-facto method for doing data munging: the split-apply-combine paradigm.

DataFrames basics - poke at your data!

Let's explore some of the basic functionalities of DataFrames in Julia. If you've had some experience with R's DataFrames or Python's Pandas then this should be smooth sailing for you. If you have no previous dataframes experience, don't worry this is the most basic intro you can imagine! :)

Reading CSV files - Part II

Now that we know how to read in basic delimited files, let's explore some more the rich features of function. Namely, we'll be looking at how to read in data so that the resulting DataFrame will end up with the right column types.
This is a direct continuation of the previous post: Reading CSV files - Part I.

Reading CSV files - Part I

Have you ever received a .csv file with pipes | as separators? Or a file without headers? Or maybe you have some colleagues in Europe who use , instead of decimal point? Oh, the joys of working with csv files...

In this post, I'll show you how you can read in a variety of delimiter separated file formats in Julia using CSV.jl.