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Showing posts from March, 2018

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 CSV.read() 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.