Скачать или смотреть Efficiently Sum Row Values in R with Ease Using cumsum

Discover how to sum row values in a specific fashion using R, from creating unique row names to implementing cumulative sums in a data frame.
---
This video is based on the question https://stackoverflow.com/q/73265012/ asked by the user 'Rachel_data_science' ( https://stackoverflow.com/u/19709304/ ) and on the answer https://stackoverflow.com/a/73265268/ provided by the user 'badgorilla' ( https://stackoverflow.com/u/13012620/ ) 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: R - Sum row values in a specific consecutive fashion

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.
---
Dividing the Problem: Summing Row Values in R

As a newcomer to R, you might find yourself working with large data frames and needing to perform specific calculations. One common requirement is to sum up values in a structured way, creating a new data frame that reflects those calculations. If you have ever struggled with this task or found it tedious, you're not alone. Let’s take a closer look at a scenario where we want to sum the 'avg' values from consecutive rows, and achieve a new data frame based on that summation.

Understanding the Input Data

Let's consider an example of an input data frame which consists of several rows and columns, focusing particularly on the 'avg' column, from which we need to derive our sums:

favgsetotherr1261r24122r33273r4132Our goal is to create a new data frame that includes sums of the 'avg' values from the first row to each subsequent row, in a cumulative fashion.

How to Achieve the Desired Output

To transform the input data frame into our desired output, let's break down the steps you need to follow, using R's built-in functionalities to make the process seamless and less error-prone.

Step 1: Generate Row Names for the Output

To create meaningful identifiers for each row in your output, you can use the paste function. This helps in constructing a unique naming convention for each cumulative sum.

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

With this command:

We start by initiating a new column called 'file'

The sapply function iterates through the rows, and for each row, constructs the string representing the name.

Step 2: Calculate the Cumulative Sums

Next, to aggregate the 'avg' values cumulatively, R provides a convenient function called cumsum.

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

This line of code does the following:

It calculates the cumulative sum of the 'avg' column, creating a new column 'sum_avg' in your data frame.

Resulting Output

Once you have executed the two steps outlined above, your final output will look like this:

filesum_avgr12r1_26r1_2_39r1_2_3_410This table clearly shows you the cumulative rows sums alongside their respective names, labeled appropriately from r1 to r1_2_3_4. It combines the first row’s average, then the first two, then the first three rows, and so forth.

Conclusion

By applying these two straightforward R commands, you can efficiently sum row values in a specific pattern to create a new data frame without the manual hassle. This approach not only speeds up your workflow but also enhances accuracy in your data analysis tasks.

Now that you have this solution at hand, you can tackle large data frames with greater confidence and ease. Happy coding in R!