Hello everyone, welcome back! This post marks the beginning, hopefully, of your foray into the wonderful world of R and RStudio…and my delve into the odd vlog to go with the blog! I’ve brushed my hair for you, and I don’t do that for just anyone, so you’d better watch it at least once! So without further ado.
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This second part of the ‘Python for Data Scientists’ post talks about the specifics of Python for data scientists. Part 1 of Python for Data Scientists talks about Python generally and can be found here.
If you have decided you want to learn Python but your not sure where to start then this post will point you in the right direction.
In R, we often need to get values or perform calculations from information not on the same row. We need to either retrieve specific values or we need to produce some sort of aggregation. This post explores some of the options and explains the weird (to me at least!) behaviours around rolling calculations and alignments.
Hello again everyone! Here’s the step by step instructions for using the googlesheets package in R to enable you to get your data from Google Sheets. This latest blog post comes from this video we published a little while ago.
In this latest blog, I’m responding to a cry for help. Someone got in touch with us recently asking for some advice on image detection algorithms, so let’s see what we can do!