| R to python useful data wrangling snippets | |
| The dplyr package in R makes data wrangling significantly easier. | |
| The beauty of dplyr is that, by design, the options available are limited. | |
| Specifically, a set of key verbs form the core of the package. | |
| Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. | |
| Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. | |
| The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package). | |
| dplyr is organised around six key verbs |
This guide will show you how to use Intel graphics for rendering display and NVIDIA graphics for CUDA computing on Ubuntu 18.04 desktop.
I made this work on an ordinary gaming PC with two graphics devices, an Intel UHD Graphics 630 plus an NVIDIA GeForce GTX 1080 Ti.
Both of them can be shown via lspci | grep VGA.
00:02.0 VGA compatible controller: Intel Corporation Device 3e92
01:00.0 VGA compatible controller: NVIDIA Corporation GP102 [GeForce GTX 1080 Ti] (rev a1)