R Programming – Hacks and Automation

Gain new knowledge about R programming you wouldn't intuitively imagine - Extensive use of the tidyverse packages

4.65 (47 reviews)
Udemy
platform
English
language
Data Science
category
instructor
371
students
7 hours
content
Dec 2020
last update
$59.99
regular price

What you will learn

Up to date R programming

How to loop with the maps family of functions

How to do file management operation like copying and pasting files, deleting them, creating new directories and more and combining these operations with loops

How to use Git and Github combined with R Studio

Create a repository in github and push scripts to it directly from R Studio

How to use the rvest package to scrape valuable data from websites

Download files with R

APIs with R

Get data with a REST API using R

Post data with a REST API using R

Use R to AUTOMATE repetitive task such as scraping dynamic data at a set frequency

Description

You just downloaded datasets online. They came in a zip file. The first thing you do after downloading it, you extract the data with your favorite unzipping software such as WinZip or WinRar. Then you proceed with reading the data in with your analysis software (hopefully R). OK! Where is he going with this, you may wonder.

You are starting a project in R and realize your files are scattered in different paths on your computer. Your immediate reflex is to open the folders involved (say with windows explorer) and proceed to gather those files in one place before starting R. Wait, what's wrong with that? Hold that thought.

You visit a website frequently. This website is full of data—numbers, downloadable documents, and pictures alike. It may or may not have occurred to you that you can access the data programmatically and visualize it differently. Perhaps you had ideas about it but didn’t know how to get it done. Hold this thought also.

There is nothing wrong with unzipping files with a WinZip or WinRar. Still, it can be beneficial to do unzip files within R. After downloading a dataset or any zip files; you can go directly into R and manage your files there before your analysis. You ever thought about unzipping, copying and pasting, deleting files within R? This course will show you examples of that.

One of the goals of this course is to implant in you the thought of scraping data with ease. I want you to think you can scrape data and visualize it differently and doing so promptly. I will show you the commonly used web scraping techniques in R.

With APIs, you go a step further than scraping. In this course, I teach you how to retrieve data using HTTR and jsonlite packages. Specifically, use the GET function to retrieve data and the POST function to update your account. All this without logging onto your account. I use the peer-to-peer lending platform Lending Club to showcase the use of an API. The API, therefore, allows you to interact with your account programmatically. Combining this with a scheduler can prove highly efficient. A well-thought-out algorithm can be automated and handle repetitive tasks that would otherwise be routine.

This course will also introduce you to the version control system Git. You will learn the power of R Studio combined with Git and GitHub. I teach how to keep different versions of your script with Git and push files, including R scripts, datasets, and other files to the GitHub platform. You will also learn how to revert to previous versions of your code if you make mistakes in later versions. When you master this, you will no longer have to save different versions of your scripts in your directory.

To become an efficient data analyst, you have to be skilled at one or more programming languages. Why not R? This course should also serve as a barometer. If you feel comfortable with the material in this course, you should understand most R scripts you will encounter.

This course will not teach you how to hack into servers. The intent here is not to sway you towards criminal activities.

Content

Introduction

Introduction
Resources

Install R, R Studio, Git, and GitHub

Install R and R Studio
About Git and GitHub
Commit Files
GitHub
Exercise 1
Solution to Exercise 1

File Handling and Maps Functional Loops

Loops Lecture
For Loops to Unzip
Walk to Unzip
Exercise 2
Solution to Exercise 2
Copy Files
How I Created the Weather Folder
Exercise 3
Solution to Exercise 3
Map Functions Part 1
Map Functions Part 2

Web Scraping Using the rvest Package

Web Scraping Intro
First Extraction
Selector Gadget More Scraping
Scraping Links and Creating a Dataset
Intro to Zillow
Zillow Continued
Loop Through Pages
About Exercise 4
Exercise 4
Solution to Exercise 4
Creating a dot R File for the ScheduleR
The ScheduleR
Issues with Web Scraping

APIs with httr and jsonlite Packages

Intro to Lending Club
API Documentation
GET Function
GET Data Frame or Tibble
POST Function

Screenshots

R Programming – Hacks and Automation - Screenshot_01R Programming – Hacks and Automation - Screenshot_02R Programming – Hacks and Automation - Screenshot_03R Programming – Hacks and Automation - Screenshot_04

Reviews

Martin
December 30, 2022
Everything was explained with useful examples, even Web-Scraping and REST API was done with examples.
Willie
December 9, 2022
Great course. Will make your life easier as an R user. We need more courses like this. You can tell this guy knows what he's doing.
Gregory
December 7, 2022
Cool things to do in R. These would make your life much easier as a data analyst. I can see the need for file management in R. This way, you can stay in R and focus there. Also, data analysts must know multiple ways to get data into their R session efficiently; that's why knowing how to play with REST APIs and web scraping are a must nowadays. Not to mention automation. I highly recommend this course. He has another course on udemy available. I suggest you take that course first if this one is hard.
Terry
December 7, 2022
It's a great course. It was highly recommended by a friend who took it and I can see why. I'm learning quite a few things that I haven't seen before in other R courses. You can tell this instructor use R programming professionally and he's showing and teaching how to use it. The course is very hands on. He shows you the how and why which is very important when learning any programming language. The pace and the length of the course are excellent. The tone of his voice is also calming. I highly recommend also. There aren't many courses like this online.
David
April 12, 2022
I really missed subtitles for the videos as I'm not a native English speaker. Also, the last section really sounds like covert advertising of a web page.
Ahmed
July 30, 2021
The material would have been useful 'however', there has not been a single lecture or assignment that has not produced some sort of 'error'. I've done other R courses up to introductory ML without having to spend near the time troubleshooting. To be fair, I am inexperienced and have tried starting over from the beginning and then again on another machine entirely but for whatever reason, I've been frustrated more than having gained the benefit of the material leaving me disappointed.
Fred
May 6, 2021
A lot of interesting tips and tricks here, making R more than just a data analysis program. I'm already utilizing some of the new functions I learned here to automate things (task scheduler is pretty awesome). Great course.
Eugenio
April 15, 2021
Definitely one of the best quick courses on automation, looping with map functions and web scraping I´ve ever taken. I highly recommend it!
Shawn
February 15, 2021
This course fills a need for some practical hands-on R programming content that is not yet another R data science / machine learning boot camp / A-Z course that shows you how to import data from a csv, do a few dplyr commands to summarize data, graph it with ggplot, and run a few regressions or machine learning algorithms. There are a dozen similar courses like that but only one or two courses that actually show you how to program in R or do something other than templated data science stuff, and this course is one of them. It’s like the R version of Automate the Boring Stuff with Python. It’s an interesting peek behind the curtain to see what a real professional R programmer does to build something useful in R, and it teaches you some best practices like functional programming using the map family of functions (the tidyverse version of the apply functions). It’s easy to follow along as you can see Robert code as he walks you through what he’s doing and why. The pacing and the length of this course is perfect. I would say it’s for those that are still in the novice category but not total beginners... not quite at intermediate level where you can independently write scripts to do something useful like web scraping or can produce analyses yourself from scratch. As long as you know how to assign variables, use basic dplyr commands like pipes, filter, mutate, and select, you will understand this course. Let’s have more of these applied R programming courses like R Hacks and like Al Sweigart’s Automate the Boring Stuff with Python that show you how to program in R and do useful things with it. This one totally hit the spot. Waiting for Robert to do a follow up to this course (hopefully that is a bit more advanced).
Gabriele
January 6, 2021
A very useful and smart brief course of hacks on R/ RStudio. It should be necessary for all those who, like me, have an intermediate degree of expertise and want to exploit all the power of both scraping the web/ using APIs and dealing with R projects, including lists, loops and functions. The tutor is very trained and explains straightforwardly such a complex matter, motivating and encouraging your learning. I' ve learnt new tools and tricks actually helpful for my everyday use of R. Highly recommended!
Ahmed
December 25, 2020
The course is really easy to follow, Instructor is really knowledgeable and takes time to explain concept and is very responsive.
Valentin
December 23, 2020
This course is just PERFECT!!! Great explanation, Learn by doing, Knowledgeable and Passionate Teacher, Robust Content. I highly recommend this course to anyone who want to dive deep into R programming.
Malick
December 17, 2020
I enjoyed this course. Robert is very knowledgeable and I love his enthusiasm when teaching. I believe in learning by doing and the homework assignments have been good in helping with understanding statistical concepts and R packages to solve problems. The goal here is not just to apply statistical concepts using R but also to have a holistic approach depending on the problem you want to solve. If you are a Pythoner like myself this course will solidify your knowledge using R packages. Overall, 1. Knowledgeable Instructor: It is obvious Robert is well-versed in R and its benefits in solving real-world problems holistically. Not only Robert is knowledgeable but also he explains most coding concepts and syntax in easy and digestible ways. Focus on the results, not the tool. 2. Robust content: the course is very well structured, flows well, adaptative for beginners. But once again start with his first course as that for beginners as well. 3. Enthusiastic instructor: Robert is very enthusiastic when teaching the material and engaging with students needing further explanations. 5. insightful Homeworks: the homework is good practice and provides you with a good opportunity to apply the notions discussed throughout the course. Please don't skip them. I will rate this course 5/5. This is an EXCELLENT course and 100% recommend. Thank you so much Robert for making this course. Keep up the great work.

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3677750
udemy ID
12/3/2020
course created date
12/18/2020
course indexed date
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