Master data manipulation, visualization, and analysis through this comprehensive video series covering the essential Tidyverse ecosystem in R programming. Learn to efficiently wrangle data using dplyr functions including select, filter, mutate, group_by, and summarize while applying 10 practical data filtering techniques. Explore data cleaning methodologies, variable recoding, and categorical data manipulation using the forcats package for factor variables. Develop proficiency in date and time data handling with lubridate, text manipulation using stringr, and data reshaping with tidyr's pivot functions. Create stunning visualizations with ggplot2, covering bar charts, scatter plots, line graphs, boxplots, histograms, and lollipop graphs while mastering themes, colors, annotations, facets, geometries, and error bars. Discover advanced plotting techniques including encircled observations with ggalt, combining ggplot2 with lubridate for time-based visualizations, and saving plots with ggsave. Learn data import from Excel, explore the across() function for efficient data cleaning, transition from R Markdown to Quarto, and implement best practices for reproducible data analysis workflows suitable for data analysts, scientists, students, and R programmers seeking to streamline their data science workflows.

Syllabus

R programming for beginners. Manipulate data using the tidyverse: select, filter and mutate.
10 data filtering tips using R programming. Use the tidyverse to filter and subset your data.
Group by and Summarise functions in R programming - use the tidyverse package to wrangle your data
Explore your data using R programming
Clean your data with R. R programming for beginners.
Recoding data using R programming. Using the tidyverse and dplyr packages to create a new variable
R programming for beginners: Rename variables and reorder columns. Data cleaning and manipulation.
Categorical data with R. Using the forcats package to manipulate factor variables.
Manipulate your data. Data wrangling. R programmning for beginners.
Manipulate and clean your data in R with the dplyr package
Working with factors and categorical variables. Use forcats in R programming to change factor levels
R programming for beginners. Here are my favorite R packages
Lubridate - how to manipulate date and time data in R
Quarto - replacing R Markdown in R Studio.
Using R programming to manage categorial variables or factors using the forcats package
Data visualization with ggplot
Manipulating text using the stringr package in R programming.
Themes in ggplot - make you data visualisation stand out!
Titles and Annotations with ggplot
Advanced ggplot - using facets
Ggplot - using geometries
Ggplot Colors - how to use colors effectively when creating plots with ggplot2
Ggsave - save your ggplot plots
Advanced ggplot #2 - create beautiful plots and graphs using R programming.
Advanced ggplot (episode #1)
Lollipop Graph using ggplot.
Error Bars using R programming
Encircled observations - use ggplot and ggalt to create great plots and data visualization.
Use pivot_wider() to shape your data. R programming from beginners.
Describe and Summarise your data
Using ggplot to create bar charts for 2 categorical variables. R programming for beginners.
Create a boxplot using R programming with the ggplot package.
How to draw a line graph using ggplot with R programming. Plots and graphs to visualize data.
Create a scatter plot using R programming. How to use ggplot for data visualisation.
Bar charts and Histograms using ggplot in R
How to use ggplot to create beautiful scatter plots. This is an R programming for beginners video.
ggplot for plots and graphs. An introduction to data visualization using R programming
The across( ) function in R programming. A tidyverse function to make cleaning data easy.
Importing data from excel into R studio
Advanced ggplot - using ggplot2 and lubridate together for data visualization
Annotate your plots and graphs with ggplot.