## This is my population
n = 30
pop <- iris[,1]
hist(pop)
library(Lock5Data) | |
library(tidyverse) | |
dplyr::glimpse(Lock5Data::NutritionStudy) | |
## Get X | |
table(X <- Lock5Data::NutritionStudy$Smoke) | |
## Encode as "Does this person Smoke | |
table(X <- (X == "Yes")) | |
## How many people smoke |
Add the following to LocalSettings.php
:
$wgHooks['SkinAfterContent'][]='backlinks_func';
function backlinks_func( &$data, Skin $skin ) {
$title = $skin->getTitle()->getPrefixedText();
$wikitext = "{{Special:WhatLinksHere/{$title}}}";
$parserOptions = ParserOptions::newFromUser( $skin->getUser() );
Create a location for
doas zfs create -o compression=lzf tank/chroots
doas zfs create -o compression=lzf tank/chroots/fedora
cd /tank/chroots/fedora
wget 'https://dl.fedoraproject.org/pub/fedora/linux/releases/38/Container/x86_64/images/Fedora-Container-Base-38-1.6.x86_64.tar.xz'
tar xvpf Fedora-Container-Base-38-1.6.x86_64.tar.xz
# Do all the mounting (or `emerge arch-chroot`
This page is a curated collection of Jupyter/IPython notebooks that are notable for some reason. Feel free to add new content here, but please try to only include links to notebooks that include interesting visual or technical content; this should not simply be a dump of a Google search on every ipynb file out there.
Important contribution instructions: If you add new content, please ensure that for any notebook you link to, the link is to the rendered version using nbviewer, rather than the raw file. Simply paste the notebook URL in the nbviewer box and copy the resulting URL of the rendered version. This will make it much easier for visitors to be able to immediately access the new content.
Note that Matt Davis has conveniently written a set of bookmarklets and extensions to make it a one-click affair to load a Notebook URL into your browser of choice, directly opening into nbviewer.
## Write in the data | |
o <- rbind( | |
c(264, 127, 99), | |
c(161, 116, 67) | |
) | |
colnames(o) <- c("Border", "Grass", "Sand") | |
rownames(o) <- c("Moringa", "Vicinus") | |
## First let's get our chi value | |
## Expected values |
First install Fezzik, this has been around since 2019 and actively maintained, but it's only available from source:
using Pkg