Скачать или смотреть Creating a New Variable in R Using Multiple Conditions

Learn how to apply multiple conditions in R to create a new variable from existing ones. This guide walks you through a real-world example using clear explanations and code snippets.
---
This video is based on the question https://stackoverflow.com/q/67180630/ asked by the user 'Dflow' ( https://stackoverflow.com/u/15706594/ ) and on the answer https://stackoverflow.com/a/67180923/ provided by the user 'Aurèle' ( https://stackoverflow.com/u/6197649/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How do I apply multiple conditions to create new variable from current variables in R?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Creating a New Variable in R Using Multiple Conditions: A Step-by-Step Guide

In the world of data analysis, you might often find yourself needing to create new variables based on the values of existing ones. This is particularly true in R, where data manipulation holds a crucial place in your analytical toolkit.

Today, we’ll tackle a specific problem: how to apply multiple conditions to existing variables in order to create a new variable. In this example, we will analyze a dataset comprising five variables and determine the average where certain conditions are met.

The Problem

Suppose you have a dataset with five different variables representing various measurements. You want to create a new variable which follows these specific rules:

If 3 or more of the 5 variables are greater than 0, calculate the mean of just those variables that are greater than 0.

If less than 3 variables are greater than 0, the new variable should be NA.

The dataset looks like this:

IDWorkSchoolSchool 2Work 1Work 2New Variable15-2-1-72NA235-1233.253451333.24-12-7242.67The Solution

To achieve this, we will use the apply function in R, which allows us to apply a function to the rows or columns of a dataset. Here's how it works, broken down into easy steps.

Step 1: Setup Your Data

First, ensure your data is loaded into R. We will use the code snippet below to create the dataframe:

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Using the apply Function

We will use apply to loop through each row (ignoring the ID column) and apply our logic to create the new variable.

Here’s the succinct code for your new variable:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Code

df[, -1]: This syntax is used to ignore the first column (ID) so that we only examine the numeric variables.

apply(..., 1, function(row): The 1 indicates that we're applying the function to each row.

sum(row > 0) >= 3: This checks to see if at least three values in the row are greater than zero.

mean(row[row > 0]): If the condition is true, it calculates the mean of those values. If not, it returns NA.

Step 3: Resulting Data Frame

After running the above code, your df dataframe will now include the new variable column filled with the computed means or NA based on the underlying conditions.

Conclusion

Creating new variables based on multiple conditions can significantly enhance your data analysis tasks in R. The example provided illustrates a straightforward method to systematically apply conditions to your variables and generate new meaningful insights.

With these tools in your toolkit, you can now tackle similar problems in your datasets! Happy coding!