The tidyverse is a collection of R packages designed for Data Science.
The scope of this course is restricted to:
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ggplot2 package
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dplyr package
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tidyr package
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readr package
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readxl package
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tibbles package
This course is going to teach how you can use some of these packages for data analysis covering 7 sections as follows.
Section 1: Introduction
In this section, you are going to know what the course is all about and also get a glimpse of some of the tools we will be using throughout the course.
Section 2: Data visualization with ggplot2
In this section, you will learn how to use the ggpot2 package for data visualization, using the diamonds dataset as a case study.
This section will cover major data visualizations such as:
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Barplots
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Boxplots
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Scatterplots
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Line plots
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Histogram
At the end of this section, should be able to know how to plot various visualizations and also give meaningful interpretations of them.
Section 3: Data manipulation with dplyr
In this section, you will learn all about the dplyr package and how you can manipulate your data with the available functions in the dplyr package using the New York flights database of 2013.
At the end of this package, you should be able to perform tasks on the dataset such as
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filtering
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arranging
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renaming
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variable creation
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selection
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Table/Dataset joining
The Practical Quiz at the end of this section will test your understanding of the various concepts treated in the section.
Section 4: Data tidying with tidyr
This section is aimed at showing you how you can tidy a dirty dataset when you come across one.
You are going to learn how to make datasets longer or wider.
You will also be learning how you can separate or unite columns together.
Section 5: Importing data
In this section, you will learn about modernized data frame called tibbles.
This section will also show you how you can import various structured data formats in R such as CSV and XLSX files.
Section 6: Case Study: Adventure Works Database
In this section, you will learn how you can combine various concepts you have learnt in this course and apply them to the Adventure Works database, and also what a data analyst’s workflow process looks like.
Section 7: EXAM
This section consists of 20 multiple choice questions which you are expected to answer to get your final course certificate. It covers everything covered in this course.
Data Visualization with ggplot2
Data Manipulation With dplyr
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4Installing and Loading ggplot2
You will be shown how to install the ggplot2 package
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5Diamonds Dataset
You will learn about the diamonds dataset which we will be using throughout this section
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6US Economic Dataset
You will also learn about the US economic dataset which we will be using also in this section
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7Barplots
You will learn how to create and interpret a plot
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8Boxplots
You will learn how to create and interpret a boxplot
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9Histogram
You will learn how to create and interpret an histogram
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10ScatterPlots
You will learn how to create and interpret a scatterplot
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11LInegraphs
You will learn how to create and interpret a linegraph
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12Labelling
You will learn how to label your created plots
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13Exercise 1
Use the diamonds data set to answer the questions in this exercise.
All the solutions are available in the lecture resources at the end of this section
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14Section 2 Code File With Solution to Exercises
Tidying Data with tidyr
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15Installing and Loading dplyr
Learn how you can install and load the dplyr package in R
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16Installing the New York Flights Database
In this lecture you will have a domain knowledge on the database we will be working with throughout this section
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17Grouping and Summarizing
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18Arranging
Learn how to arrange your data with the arrange() function
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19Filtering
Learn how to filter your data with the filter() function
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20Selecting
Learn how to select variables with the select() function
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21Creating Variables
Learn how to create variables with the mutate() and transmute() function
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22Renaming
Learn how to rename variables with the rename() function
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23Mutating Joins
Learn how to join two tables together
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24Filtering Joins
Learn how to use filtering joins in filtering
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25Exercise 2
Use the New York City database to answer the questions in this exercise.
All the solutions are available in the lecture resources at the end of this section
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26Section 3 Code File With Solution to Exercises
Importing Data
Case Study: AdventureWorks Database
Exam
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37AdventureWorks Database
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38Total Sales By Category
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39Profit Margin
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40Profit Over Time
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41What Happended July 2019?
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42Customers With Higest Profit Margin
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43Exercise 6
Use the adventure works database to answer the questions in this exercise.
All the solutions are available in the lecture resources at the end of this section
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44Section 6 Code File With Solution to Exercises