Regression Analysis in R – How to visualise
Visualization is the process of creating graphical representations of data to make it easier to understand and analyze. In R, there are several ways to visualize data, and one of them is by using the base R functions and packages such as “ggplot2”, “lattice” and “plotly”.
The ggplot2 package is a powerful tool for creating beautiful and informative visualizations. It allows you to create a wide range of plots, such as scatter plots, line plots, bar plots, and histograms. The lattice package is another powerful tool for creating visualizations in R, it allows you to create trellis plots, which are a type of visualization that displays multiple plots in a grid format. Plotly is an interactive visualization library that allows you to create interactive plots, such as scatter plots, line plots, bar plots, and histograms.
When visualizing data in R, it’s important to keep in mind the context of the data, the audience, and the purpose of the visualization. It’s also a good idea to consult with experts before creating visualizations to make sure you are using the best suited method for your data. Additionally, it’s important to use appropriate colors, labels, and scales to make sure your visualizations are clear and easy to understand.
In summary, visualization is the process of creating graphical representations of data to make it easier to understand and analyze. In R, there are several ways to visualize data, and one of them is by using the base R functions and packages such as “ggplot2”, “lattice” and “plotly”. The ggplot2 package is a powerful tool for creating beautiful and informative visualizations. It allows you to create a wide range of plots, such as scatter plots, line plots, bar plots, and histograms. The lattice package is another powerful tool for creating visualizations in R, it allows you to create trellis plots, which are a type of visualization that displays multiple plots in a grid format. Plotly is an interactive visualization library that allows you to create interactive plots, such as scatter plots, line plots, bar plots, and histograms. When visualizing data in R, it’s important to keep in mind the context of the data, the audience, and the purpose of the visualization. It’s also a good idea to consult with experts before creating visualizations to make sure you are using the best suited method for your data. Additionally, it’s important to use appropriate colors, labels, and scales to make sure your visualizations are clear and easy to understand.
In this Applied Machine Learning Recipe, you will learn: Regression Analysis in R – How to visualise.
Regression Analysis in R – How to visualise
Free Machine Learning & Data Science Coding Tutorials in Python & R for Beginners. Subscribe @ Western Australian Center for Applied Machine Learning & Data Science.
Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.
Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners
Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!
Latest end-to-end Learn by Coding Projects (Jupyter Notebooks) in Python and R:
Applied Statistics with R for Beginners and Business Professionals
Data Science and Machine Learning Projects in Python: Tabular Data Analytics
Data Science and Machine Learning Projects in R: Tabular Data Analytics
Python Machine Learning & Data Science Recipes: Learn by Coding