Section 1 : Introduction

 		Lecture 1 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 2 What you need to know 0:44
Lecture 3 Exercise files

Section 2 : Tidy Data

 		Lecture 4 What is tidy data 3:36
Lecture 5 Variables, observations, and values 4:22
Lecture 6 Common data problems 7:39
Lecture 7 Using the tidyverse 4:37

Section 3 : Working with Tibbles

 		Lecture 8 Building and printing tibbles 5:4
Lecture 9 Subsetting tibbles 1:56
Lecture 10 Filtering tibbles 3:2

Section 4 : Importing Data into R

 		Lecture 11 What are CSV files 2:53
Lecture 12 Importing CSV files into R 6:39
Lecture 13 What are TSV files
Lecture 14 Importing TSV files into R 6:3
Lecture 15 Importing delimited files into R 3:33
Lecture 16 Importing fixed-width files into R 3:38
Lecture 17 Importing Excel files into R 5:44
Lecture 18 Reading data from databases and the web 2:20

Section 5 : Data Transformation

 		Lecture 19 Wide vs 3:11
Lecture 20 Making wide datasets long with pivot_longer() 3:54
Lecture 21 Making long datasets wide with pivot_wider() 3:29
Lecture 22 Converting data types in R 7:3
Lecture 23 Working with dates and times in R 4:51

Section 6 : Data Cleaning

 		Lecture 24 Detecting outliers 8:19
Lecture 25 Missing and special values in R 5:21
Lecture 26 Breaking apart columns with separate() 3:48
Lecture 27 Combining columns with unite() 2:29
Lecture 28 Manipulating strings in R with stringr 9:15

Section 7 : Data Wrangling Case Study Coal Consumption

 		Lecture 29 Understanding the coal dataset 1:59
Lecture 30 Reading in the coal dataset 2:39
Lecture 31 Converting the coal dataset from wide to long 2:53
Lecture 32 Segmenting the coal dataset 3:32
Lecture 33 Visualizing the coal dataset 2:29

Section 8 : Data Wrangling Case Study Water Quality

 		Lecture 34 Understanding the water quality dataset 1:32
Lecture 35 Reading in the water quality dataset 1:35
Lecture 36 Filtering the water quality dataset 5:17
Lecture 37 Water quality data types
Lecture 38 Correcting data entry errors 2:43
Lecture 39 Identifying and removing outliers
Lecture 40 Converting temperature from Fahrenheit to Celsius 2:20
Lecture 41 Widening the water quality dataset 4:33

Section 9 : Data Wrangling Case Study Social Security Disability

 		Lecture 42 Understanding the social security disability dataset 2:28
Lecture 43 Importing the social security disability dataset 1:22
Lecture 44 Making the social security disability dataset long 1:34
Lecture 45 Formatting dates in the social security disability dataset 4:6
Lecture 46 Fiscal years in the social security disability dataset 2:21
Lecture 47 Widening the social security disability dataset
Lecture 48 Visualizing the social security disability dataset 1:25