Julia-DataFrames-Tutorial
Julia-DataFrames-Tutorial copied to clipboard
A tutorial on Julia DataFrames package
Here is a sample dataset with 7 million rows ``` # some ids have single date entries data = DataFrame( "unique_id" => [i for i in 1:1500000], "datestamp" => [Date("2021-08-16")...
This PR is a WIP with at least 2 goals: 1. Add a spanish translation of the soon-to-be 1.0 DataFrames tutorials 2. Add Literate.jl based notebooks for easier source control...
@pdeffebach - if would be great if you found time to update notebook 13 with DataFramesMeta.jl examples when it is up to DataFrames.jl 0.22 relase. Feel free to remove/change everything...
In your [performance tips]( https://render.githubusercontent.com/view/ipynb?commit=32a08895be41fc20c9f8c9da408909aa404f806c&enc_url=68747470733a2f2f7261772e67697468756275736572636f6e74656e742e636f6d2f626b616d696e732f4a756c69612d446174614672616d65732d5475746f7269616c2f333261303838393562653431666332306339663863396461343038393039616134303466383036632f31315f706572666f726d616e63652e6970796e62&nwo=bkamins%2FJulia-DataFrames-Tutorial&path=11_performance.ipynb&repository_id=112856111&repository_type=Repository#Allowing-missing-as-well-as-categorical-slows-down-computations) at `In [8]` you mentioned: ``` Allowing missing as well as categorical slows down computations ``` I might have an idea on how to fix...
`coalesce` no longer works as you describe. It must returns the first item that is missing. You must perhaps have left out `map(...)`? Sadly, I had to do: ` df[ismissing.(df.mycol),:mycol]...