FFT Tools

The Fast Fourier Transform (FFT) is one of the most used algorithms in the world. It has applications in broadcasting, image and data compression, and structural vibrations. These two videos provide some of the best background on the FFT I have found:

The FFT is most conveniently performed in Matlab, but can also be applied in Excel. Many phone-based apps have implemented the FFT either in real-time (such as Vibration Analysis) or as a post-processing step (such as Vibration Pro or PhyPhox). 

FFT Using Python

Python is a robust and open-source programming language. There are excellent resources available to both learn and implement algorithms like the FFT. 

https://pythonnumericalmethods.berkeley.edu/notebooks/chapter24.04-FFT-in-Python.html 

FFT Using Matlab

If you have access to Matlab, it provides very effective tools for computing and plotting the results of an FFT.

https://www.mathworks.com/help/matlab/ref/fft.html 

Octave is a free open-source tool compatible with many Matlab functions: https://octave.org/ 

FFT Using Microsoft Excel

While Excel is not the ideal tool for calculating an FFT, it is possible and worth knowing how for those who use it regularly. 

An excellent tutorial is available here.

FFT ONLINE

Alijah Ahmed has developed a great online calculator that produces an FFT of data uploaded in a CSV file. 

Additional background on signal analysis and measurement using the FFT algorithm is available from National Instruments for those who want to know more about frequency resolution, windows, filters, and aliasing: 

The Fundamentals of FFT-Based Signal Analysis and Measurement by Michael Cerna and Audrey F. Harvey 

If you're curious about the math and want to try your hand at calculating a discrete Fourier Transform, look here:

Hui, J. (2020) Discrete Fourier Transform with a Spreadsheet 

The FFT, implemented in a variety of programming languages, is provided here:

https://www.nayuki.io/page/free-small-fft-in-multiple-languages