Introduction Running R in Jupyter Notebook allows us to use notebooks’ power and simplicity for data analysis and research tasks. This post will cover the benefits and capabilities of using R in a Jupyter Notebook. Firstly, let us briefly introduce the concept of a notebook. A notebook is an interactive document that combines code, visualizations, […]
Running R in Jupyter: Unleash the Simplicity of Notebooks Read More »
Discover the key to data manipulation in R by learning how to check and manage variable types. Learn the nuances of data types and take your data analysis expertise to the next level with the comprehensive insights provided here. Get ready to enhance your data-handling skills and drive more precise analyses!
Check Variable Type in R: How to Use typeof() & str() Read More »
Discover Seaborn’s power in creating insightful confusion matrix plots. Unleash your data visualization skills and assess model performance effectively.
Seaborn Confusion Matrix: How to Plot and Visualize in Python Read More »
Learn how to calculate row means in R, whether you’re analyzing every 5th column, applying conditions, or using dplyr for precise numeric column calculations. Explore the power of R for tailored row averaging.
Row Means in R: Calculating Row Averages with Ease Read More »
Unlock the power of Fisher’s Exact Test in R and find associations in your categorical data. Dive into interpretation, post-hoc analysis, and data visualization. Discover how to go beyond statistics and turn insights into actions.
Fisher’s Exact Test in R: How to Interpret & do Post Hoc Analysis Read More »
Learn to calculate Cronbach’s Alpha in R for assessing internal consistency. Explore manual methods and convenient packages like psych and performance.
Cronbach’s Alpha in R: How to Assess Internal Consistency Read More »
Cross-tabulation in R: Explore diverse methods for analyzing categorical data. Learn basic and advanced techniques using functions like table(), dplyr, and sjPlot. Enhance your data analysis skills now!
Cross-Tabulation in R: Creating & Interpreting Contingency Tables Read More »
Explore how to sum rows in R using dplyr’s powerful functions and enhance your data analysis. Sum across specific rows and based on conditions.
How to Sum Rows in R: Master Summing Specific Rows with dplyr Read More »
In this post, you will learn how to efficiently determine if a file is empty in R using the file.info() and file.size() functions. We will explore practical examples and scenarios, including reading multiple files. Mastering these techniques empowers streamlined file validation for effective data processing and analysis.
How to Check if a File is Empty in R: Practical Examples Read More »
Unlock the potential of Modulo in R with practical applications. Explore data segmentation, odd/even checks, day filtering, and optimized iterations for streamlined coding efficiency.
Modulo in R: Practical Example using the %% Operator Read More »