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R to python 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:

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	www.youtube.com###donation-shelf
	www.youtube.com##ytd-reel-shelf-renderer.ytd-item-section-renderer.style-scope
	www.youtube.com##+js(set, yt.config_.EXPERIMENT_FLAGS.service_worker_enabled, false)
	www.youtube.com##+js(nano-stb, resolve(1), *, 0.001)
	\|\|googlevideo.com/videoplayback$xhr,3p,method=get,domain=www.youtube.com

	<?php
	/**
	* Enforce anti-spam honeypot on all Gravity forms.
	*
	* @param array $form
	*
	* @return array $form
	*/
	add_filter( 'gform_form_post_get_meta', function ( $form ) {

	using UnityEngine;
	using UnityEditor;

	public class MatcapToCubemap : ScriptableWizard {
	public Texture matcap;
	public float emissionScale = 1f;
	public int size = 256;

	void OnWizardUpdate () {
	this.isValid = this.matcap != null;

	MAKE := make --no-print-directory

	DESCRIBE := $(shell git describe --match "v*" --always --tags)
	DESCRIBE_PARTS := $(subst -, ,$(DESCRIBE))

	VERSION_TAG := $(word 1,$(DESCRIBE_PARTS))
	COMMITS_SINCE_TAG := $(word 2,$(DESCRIBE_PARTS))

	VERSION := $(subst v,,$(VERSION_TAG))
	VERSION_PARTS := $(subst ., ,$(VERSION))

	#!/bin/bash

	set -euo pipefail

	#####
	# Simple bash script to retrieve the selfsigned cert from TAP and install it locally on macOS
	#####

	echo "--- Fetching TAP Ingress Certificate ---"
	kubectl get secret -n cert-manager tap-ingress-selfsigned-root-ca -o yaml \| yq '.data."ca.crt"' \| base64 -d > ca.crt

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R to python data wrangling snippets

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