Complete Data Wrangling & Data Visualisation In R

Complete Data Wrangling & Data Visualisation In R, available at $79.99, has an average rating of 4.55, with 52 lectures, 1 quizzes, based on 198 reviews, and has 2010 subscribers.

You will learn about Read In Data Into The R Environment From Different Sources Carry Out Basic Data Pre-processing & Wrangling In R Studio Learn to IDENTIFY Which Visualisations Should be Used in ANY given Situation Go From A Basic Level To Performing Some Of The MOST COMMON Data Preprocessing, Data Wrangling & Data Visualization Tasks In R How To Use Some Of The MOST IMPORTANT R Data Wrangling & Visualisation Packages Such As Dplyr and Ggplot2 Build POWERFUL Visualisations and Graphs from REAL DATA Apply Data Visualization Concepts For PRACTICAL Data Analysis & Interpretation Gain PROFICIENCY In Data Preprocessing, Data Wrangling & Data Visualization In R By Putting Your Soon-To-Be-Acquired Knowledge Into IMMEDIATE Application This course is ideal for individuals who are Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment or Students Interested in Learning About the Common Pre-processing Data Tasks: Including Cleaning and Munging or Students Interested in Gaining Exposure to Common R Packages Such As ggplot2 or Those Interested in Learning About Different Kinds of Data Visualisations or Those Interested in Learning to Create Publication Quality Visualisations It is particularly useful for Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment or Students Interested in Learning About the Common Pre-processing Data Tasks: Including Cleaning and Munging or Students Interested in Gaining Exposure to Common R Packages Such As ggplot2 or Those Interested in Learning About Different Kinds of Data Visualisations or Those Interested in Learning to Create Publication Quality Visualisations.

Enroll now: Complete Data Wrangling & Data Visualisation In R

Summary

Title: Complete Data Wrangling & Data Visualisation In R

Price: $79.99

Average Rating: 4.55

Number of Lectures: 52

Number of Quizzes: 1

Number of Published Lectures: 51

Number of Published Quizzes: 1

Number of Curriculum Items: 54

Number of Published Curriculum Objects: 53

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Read In Data Into The R Environment From Different Sources
Carry Out Basic Data Pre-processing & Wrangling In R Studio
Learn to IDENTIFY Which Visualisations Should be Used in ANY given Situation
Go From A Basic Level To Performing Some Of The MOST COMMON Data Preprocessing, Data Wrangling & Data Visualization Tasks In R
How To Use Some Of The MOST IMPORTANT R Data Wrangling & Visualisation Packages Such As Dplyr and Ggplot2
Build POWERFUL Visualisations and Graphs from REAL DATA
Apply Data Visualization Concepts For PRACTICAL Data Analysis & Interpretation
Gain PROFICIENCY In Data Preprocessing, Data Wrangling & Data Visualization In R By Putting Your Soon-To-Be-Acquired Knowledge Into IMMEDIATE Application

Who Should Attend

Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment
Students Interested in Learning About the Common Pre-processing Data Tasks: Including Cleaning and Munging
Students Interested in Gaining Exposure to Common R Packages Such As ggplot2
Those Interested in Learning About Different Kinds of Data Visualisations
Those Interested in Learning to Create Publication Quality Visualisations

Target Audiences

Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment
Students Interested in Learning About the Common Pre-processing Data Tasks: Including Cleaning and Munging
Students Interested in Gaining Exposure to Common R Packages Such As ggplot2
Those Interested in Learning About Different Kinds of Data Visualisations
Those Interested in Learning to Create Publication Quality Visualisations

THIS IS YOUR ROADMAP TO LEARNING & BECOMING HIGHLY PROFICIENT IN DATA PREPROCESSING, DATA WRANGLING, & DATA VISUALIZATION IN R!

Hello, My name is Minerva Singh. I am an Oxford University MPhil graduate in Geography & Environment & I finished a PhD at Cambridge University in Tropical Ecology & Conservation.

I have +5 of experience in analyzing real-life data from different sources using statistical modelling and producing publications for international peer-reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!

I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science – data wrangling and visualisation.

THIS COURSE WILL TEACH YOU ALL YOU NEED AND PUT YOUR KNOWLEDGE TO PRACTICE NOW!

This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, the perusal of numerous books and publishing statistically rich papers in the renowned international journal like PLOS One.

HERE IS WHAT THIS COURSE WILL DO FOR YOU:

It will take you (even if you have no prior statistical modelling/analysis background) from a basic level of performing some of the most common data wrangling tasks in R.
It will equip you to use some of the most important R data wrangling and visualisation packages such as dplyr and ggplot2.
It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.
You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results..

The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners

After each video, you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.

ON TOP OF THE COURSE, I’M ALSO OFFERING YOU:

Practice Activities To Reinforce Your Learning
My Continuous Support To Make Sure You Gain Complete Understanding & Proficiency
Access To Future Course Updates Free Of Charge
I’ll Even Go The Extra Mile & Cover Any Topics That Are Related To The Subject That You Need Help With (This is something you can’t get anywhere else).
& Access To A Community Of 25,000 Data Scientists (& growing) All Learning Together & Helping Each Other!

Now, go ahead & enrol in the course. I’m certain you’ll love it, but in case you don’t, you can always request a refund within 30 days. No hard feelings whatsoever. I look forward to seeing you inside!

Course Curriculum

Chapter 1: Welcome To The Course

Lecture 1: Introduction To The Course and Instructor

Lecture 2: Data and Code Used in the Course

Lecture 3: Install R and RStudio

Chapter 2: Read in Data From Different Sources

Lecture 1: Read in CSV and Excel Data

Lecture 2: Read in Online CSV

Lecture 3: Read in Googlesheets

Lecture 4: Read in Data from Online HTML Tables-Part 1

Lecture 5: Read in Data from Online HTML Tables-Part 2

Lecture 6: Read Data from a Database

Chapter 3: Common Data Pre-Processing Techniques

Lecture 1: Basic Data Cleaning in R: Remove NA

Lecture 2: Additional Data Cleaning

Lecture 3: Indexing and Subsetting Data

Lecture 4: Summarising Based on Qualitative Attributes

Lecture 5: Of Long and Wide

Lecture 6: Pre-processing Tasks and the Pipe Operator

Lecture 7: Introduction to dplyr for Data Summarizing-Part 1

Lecture 8: Introduction to dplyr for Data Summarizing-Part 2

Lecture 9: Start with Tidyverse

Lecture 10: Column Renaming

Lecture 11: Tidy Data: Long and Wide

Lecture 12: Joining Tables

Chapter 4: Basic Data Visualization

Lecture 1: What is Data Visualisation?

Lecture 2: Some Principles of Data Visualisation

Lecture 3: Exploratory Data Analysis (EDA) in R

Lecture 4: More Exploratory Data Analysis with xda

Chapter 5: Grammar of Graphics: ggplot2

Lecture 1: Start with qplot

Lecture 2: More qplot Visualizations

Lecture 3: Start with ggplot

Lecture 4: Scatterplots with ggplot2

Lecture 5: Faceting With ggplot2

Lecture 6: More Faceting

Lecture 7: Insert a Smoothing Line

Lecture 8: Boxplots

Lecture 9: More Boxplots

Lecture 10: Histograms

Lecture 11: Barplots For Discrete Numerical Variables

Lecture 12: Insert Error Bars

Lecture 13: Line Charts

Lecture 14: Additional ggplot2 Themes

Chapter 6: Real Life Data Wrangling and Visualisation

Lecture 1: Use dplyr and ggplot

Lecture 2: What and How Can We Learn From Data?: Nobel Prize Winners

Lecture 3: Mining More Information About Nobel Prizes

Lecture 4: Mining and Visualising Information About the Olympic Games-Part 1

Lecture 5: Of Winter and Summer Olympic Games

Lecture 6: Of Men and Women

Chapter 7: Geographic Visualisations

Lecture 1: Brief Introduction

Lecture 2: Work With R's Inbuilt Geospatial Data-Part 2

Lecture 3: Use ggplot2 For Geographic Data Visualisations

Chapter 8: Bonus Section

Lecture 1: 3D Scatterplots

Lecture 2: Data Editing In R

Lecture 3: Group By Time

Instructors

Minerva Singh
Bestselling Instructor & Data Scientist(Cambridge Uni)

Rating Distribution

1 stars: 5 votes
2 stars: 6 votes
3 stars: 23 votes
4 stars: 47 votes
5 stars: 117 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu