staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

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This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

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revolunet

Python VS ES6 syntax comparison

Python syntax here : 2.7 - online REPL

Javascript ES6 via Babel transpilation - online REPL

Imports

import math

gaearon

function mapValues(obj, fn) {
  return Object.keys(obj).reduce((result, key) => {
    result[key] = fn(obj[key], key);
    return result;
  }, {});
}

function pick(obj, fn) {
  return Object.keys(obj).reduce((result, key) => {
    if (fn(obj[key])) {

acdlite

// getComponent is a function that returns a promise for a component
// It will not be called until the first mount
function asyncComponent(getComponent) {
  return class AsyncComponent extends React.Component {
    static Component = null;
    state = { Component: AsyncComponent.Component };

    componentWillMount() {
      if (!this.state.Component) {
        getComponent().then(Component => {

aparrish

Deryck97

nflfastR Python Guide

August 2021: This serves as the first refresh of this guide. My hope is that this guide is a constant work in progress, receiving updates as I receive requests and discover new things myself. This update features more data visualization examples and a more detailed filtering section. I've also posted all relevant code in the guide to github in a Jupyter Notebook, found here.

This guide serves as an update to my original nflscrapR Python Guide. As of 2020, nflscrapR is defunct and nflfastR has taken its place. As the name implies, the library has made the process of scraping new play by play data much faster.

Using Jupyter Notebooks or Jupyter Lab, which come pre-installed with Anaconda is typically the best way to work with