For Data Science Learners
R for Data Science
How to Find the Size of a Data Frame in R, we will explore how to find the size of a data frame in R. A data frame is a fundamental data structure in R, and understanding its size is crucial for efficient data analysis. We will discuss three functions that can be used to…
Filter a Vector in R is a fundamental skill that can be applied to a wide range of data analysis tasks. In this article, we’ll explore four different methods for filtering a vector in R, along with practical examples. Method 1: Filter for Elements Equal to Some Value The first method involves filtering a vector…
Split a Vector into Chunks in R can be a useful technique for manipulating and analyzing data. In this article, we’ll explore how to use the split() function in R to split a vector into chunks. Basic Syntax:Split a Vector into Chunks in R The basic syntax for splitting a vector into chunks in R…
Mastering the table() Function in R, The table() function in R is a powerful tool for creating frequency tables, allowing you to quickly summarize the distribution of variables in your data. In this article, we’ll explore the basics of table() and demonstrate its applications through practical examples. Step-by-Step Data Science Coding Course Syntax:Mastering the table()…
Mastering the tapply() Function in R, The tapply() function in R is a powerful tool for applying a function to a vector, grouped by another vector. In this article, we’ll delve into the basics of tapply() and explore its applications through practical examples. Data Science Applications in Banking » Data Science Tutorials Syntax:Mastering the tapply()…
Best Data Visualization Books, “Unlock the Power of Storytelling with Data: Transform Your Visualizations into Compelling Narratives! In this insightful book, you’ll learn the art of weaving data into captivating stories that resonate with your audience. By exploring the fundamentals of data visualization and effective communication, you’ll discover how to turn complex data into a…
Mastering the map() Function in R, available in the purrr package, is a powerful tool in R that enables you to apply a function to each element in a vector or list and return a list as a result. In this article, we’ll delve into the basics of the map() function and explore its applications…
Convert a continuous variable to a categorical in R, it’s often necessary to convert it to categorical data for further analysis or visualization. One effective way to do so is by using the discretize() function from the arules package. In this article, we’ll explore how to use discretize() to convert a continuous variable to a…
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Using describeBy() in R, When working with data in R, it’s often necessary to calculate descriptive statistics for each column in a data frame, grouped by a particular column. This can be a tedious task, especially when dealing with large datasets. Fortunately, the describeBy() function from the psych package in R makes this process much…
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Calculating Autocorrelation in R, Autocorrelation is a statistical technique used to measure the degree of similarity between a time series and a lagged version of itself over successive time intervals. It is also called “serial correlation” or “lagged correlation” since it measures the relationship between a variable’s current and historical values. In this article, we…