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You're reading from  Julia Cookbook

Product typeBook
Published inSep 2016
Reading LevelBeginner
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ISBN-139781785882012
Edition1st Edition
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Authors (2):
Jalem Raj Rohit
Jalem Raj Rohit
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Jalem Raj Rohit

Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in recommender systems, machine learning, and serverless and distributed systems. Raj currently works as a senior consultantdata scienceand NLP at Episource, before which he worked at Zomato and Kayako. He contributes to open source projects in Python, Go, and Julia. He also speaks at tech conferences about serverless engineering and machine learning.
Read more about Jalem Raj Rohit

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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.

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Julia Cookbook
Published in: Sep 2016Publisher: ISBN-13: 9781785882012
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Authors (2)

author image
Jalem Raj Rohit

Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in recommender systems, machine learning, and serverless and distributed systems. Raj currently works as a senior consultantdata scienceand NLP at Episource, before which he worked at Zomato and Kayako. He contributes to open source projects in Python, Go, and Julia. He also speaks at tech conferences about serverless engineering and machine learning.
Read more about Jalem Raj Rohit