Book Image

Julia Cookbook

By : Raj R Jalem, Jalem Raj Rohit
Book Image

Julia Cookbook

By: Raj R Jalem, Jalem Raj Rohit

Overview of this book

Want to handle everything that Julia can throw at you and get the most of it every day? This practical guide to programming with Julia for performing numerical computation will make you more productive and able work with data more efficiently. The book starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We’ll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation. Later on, you’ll see how to optimize data science programs with parallel computing and memory allocation. You’ll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform. This book includes recipes on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the book, you will acquire the skills to work more effectively with your data.
Table of Contents (12 chapters)

Handling data with TSV files


In this section, we will explain how to handle Tab Separated Values (TSV) files.

Getting ready

The DataFrames package is needed to deal with TSV files. So, as it is already installed as instructed in the previous section, we can move ahead and make sure that all the packages are up-to-date with the following command:

Pkg.update()

How to do it...

TSV files, as the name suggests, are files whose contents are separated by commas. TSV files can be accessed and read into the REPL process by the following method:

  1. Assign a variable to the local source directory of the file:

    s = "/Users/username/dir/data.tsv"
    
  2. The readtable() command is used to read the data from the source. The data is read in the form of a Julia DataFrame:

    data = readtable(s)
    

Data can be written to TSV files from a Julia DataFrame using the following steps:

  1. Create a data structure with some data inside it. For example, let's create a two-dimensional dataframe like the one we created in the previous example:

    using DataFrames
    df = DataFrame(A = 1:10, B = 11:20)
    
  2. Now, the dataframe, which we created in Step 1, can be exported to an external TSV file using the following command:

    writetable("data.csv",df)
    

The writetable() command is clever enough to make out the format of the file from the filename extension.