It is said that two third of our brains is devoted to process vision. We humans are very visual animals, we can detect patters from seeing things rather than looking at a table of numbers. In fact many Data Scientists make their living by creating just visualizations and info news so that people concerned can easily digest it and understand it. I don’t think I will be going to very detail about visualizations, the path for these blogs are not decided yet, but let’s here look at plotting in Julia.

There is a package called Plots in Julia which you can install it as follows:

First launch the Julia REPL by typing in julia in your terminal.

$ julia
   _       _ _(_)_     |  Documentation:
  (_)     | (_) (_)    |
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 1.5.3 (2020-11-09)
 _/ |\__'_|_|_|\__'_|  |  Official release

julia>                    |

Go to packages by typing in ] at the julia> prompt, then in pkg> type this:

(@v1.5) pkg> add Plots

so should see lot of packages getting installed and finally Plots too will get installed. Now the notebook for this blog is here It’s not that you must install Plots from Julia REPL, you can also install it pragmatically as shown below, right from your Jupyter lab:

# Uncomment lines below if you want to install Plots
using Pkg

I have commented it out in the one you can get it from Gitlab because I have already installed it using the REPL. Okay lets tell Julia that we are using Plots with the following statement:

using Plots


┌ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]
└ @ Base loading.jl:1278

This could take a while as it depends on the processing speed of your computer. For my 7-year laptop I think it took nearly 20 minutes, but once the compiling of Plots is doe, from the next time on its fast.

Now let’s plot a simple pie chart which reflects my favorite food platter:

    ["Mutton Briyani", "Tandoori Chicken", "Prawn Roast", "Greens"],
    [60, 20, 10, 10],
    title = "My Favorite Plate"



We will see more of Plots in my upcoming blogs.