Stream: helpdesk (published)

Topic: Random Selection From Within An Array Of Elements

qu bit (Mar 08 2021 at 22:31):

Hello,

I have

begin
Sessions = "Piano","Guitar","Harmonica"
Wall_E = DataFrame((ID = Any[1:10...], Cost = rand(1:50,10), Sessions = String["$Sessions" for i in 1:10]))
end

How can I create a random array of
elements in the dataframe?

Thank you,

Nils (Mar 09 2021 at 08:53):

This is weird code, why do you have begin and end here? Why are you passing a NamedTuple to the DataFrame constructor rather than just using the keywords? Why are you creating ID as Any[1:10...]?

To answer your question though, rand can sample from any collection, so you want:

DataFrame(ID = 1:10, Cost = rand(1:50,10), Sessions = rand(Sessions, 10))

qu bit (Mar 09 2021 at 09:01):

Hi @Nils ,
I am using Pluto.jl.
Also, I am new to using Julia and used
code that was posted here.
Thanks for your response, saved
me loads of time.

Nils (Mar 09 2021 at 09:43):

As a general aside, there's no need to always quote everyone's messages - they appear right above yours most of the time anyway, so it just adds unnecessary visual clutter.

Understood re Pluto, which I guess is where the begin ... end comes from. I would suggest to leave this out, and when you create minimum working examples to illustrate your issues just run them in a fresh Julia REPL session. If something then doesn't work in Pluto that's a Pluto specific issue and you should ask on the Pluto topic, but when just discussing DataFrame operations it's a bit of a distraction.

FInally, I would strongly encourage you to read through the DataFrames documentation, and work through the tutorial here: https://github.com/bkamins/Julia-DataFrames-Tutorial - I have a feeling that you'll be able to answer 95% of your own questions after doing so.

qu bit (Mar 09 2021 at 09:49):

Hi @Nils ,
Noted -- I will remove the code block designations
for Pluto.jl to not confuse the potential readers &
will not keep the quoted materials from any
respondents. Thank you for the resource will
explore it now!

Best,

Andrey Oskin (Mar 09 2021 at 10:14):

I would also recommend to read series of blog posts in https://bkamins.github.io/ There you will usually find explanations of implementation details, close to real world examples, best practices and so on.

You may start from

• https://bkamins.github.io/julialang/2020/12/24/minilanguage.html
• https://bkamins.github.io/julialang/2021/01/22/transforming.html
• https://bkamins.github.io/julialang/2020/09/13/pseudobroadcasting.html
• https://bkamins.github.io/julialang/2020/09/20/row-aggregation.html

and if you know pandas or R dataframes
https://bkamins.github.io/julialang/2020/09/25/comparisons.html

qu bit (Mar 09 2021 at 10:32):

Andrey Oskin

I will add this to my growing catalog of
Julia references. Thank you very much.

Michael Alexander (Mar 09 2021 at 15:18):

(deleted)

Last updated: Oct 02 2023 at 04:34 UTC