Explore R, a programming language widely used for statistical analysis and data visualization. This section offers a range of tutorials, from beginner to advanced levels, covering R’s syntax, data types, functions, data manipulation, statistical modeling, and graphical capabilities.
When working with data frames in R, we often come across the need to rename columns. This could be because the original column names are too long, not descriptive, or simply to maintain a standard nomenclature across datasets. The dplyr package in R provides a suite of tools that simplify data manipulation, and one of …
The R programming language provides extensive functionality for data manipulation and analysis. One common task in data analysis is selecting specific columns by name from a data frame or dataset, which allows users to focus on the most relevant pieces of information for their analysis. This how-to guide will teach you several methods to select …
In data analysis, filtering data is a fundamental step that allows analysts to focus on specific subsets of interest. In R, a versatile language used for statistical computing and graphics, several techniques can be applied to filter a DataFrame by column value. Understanding these methods can greatly enhance your data manipulation capabilities. Whether you are …
Filter DataFrame by Column Value in R: Techniques and Tips Read More »
When working with data in R, it is a common task to filter or subset data frames based on the values of columns. This is an important technique in data analysis that allows analysts to focus on specific observations that meet certain criteria, and exclude the rest. Whether you’re looking to isolate a particular group, …
Subsetting data frames in R is a fundamental task in data analysis, allowing you to extract portions of a dataset that are of interest to you. Whether you are looking to select specific columns, filter rows based on certain criteria, or a combination of both, the R programming language provides a variety of functions and …
Subsetting is a fundamental operation in data manipulation that R users frequently encounter across various tasks, such as statistical analyses, data cleaning, or preparation for visualization. Mastery of the subset function in R is not only about knowing syntax; it is about understanding how to efficiently extract parts of vectors, matrices, or data frames based …
Exporting data from R into text files is a common task for data analysts, who may need to share their results with colleagues using different software or for publication purposes. Text files, including CSV and TSV, are among the most widely used due to their simplicity and compatibility across different platforms. In this guide, you’ll …
Reading text files is a fundamental task for any data analyst or statistician. In R, there are multiple ways to read plain text data, ranging from simple text files (.txt) to more complex formats such as comma-separated values (.csv) or tab-delimited files (.tab). Each format may require a different technique or function for the best …
Reading multiple CSV (Comma-Separated Values) files into R is a common task for data analysts, researchers, and anyone working with large datasets distributed over several files. CSV files are a standard file format for storing tabular data and are supported by many data analysis tools and services. In R, there are various functions and packages …
In the world of data analysis and statistics, the R programming language is a powerful tool that provides an extensive set of functions for manipulating data. A fundamental concept to understand when working with data in R is how to create new data frames from existing ones. Whether you are subsetting, merging, or transforming data, …
Create a New DataFrame from an Existing One in R Read More »
