Sensitivity Analysis in Python Example - Exploring the Parameter Space

Sensitivity Analysis in Python Example Part of the lecture series "Exploring the Parameter Space": https://nickderobertis.github.io/fin-... Full Course Website: https://nickderobertis.github.io/fin-... Notes -------- Here we will focus only on using the sensitivity package rather than carrying everything out manually We need to go back and add an optional argument to the model about whether it should print the results, otherwise we will have the results printed a huge number of times as we run the sensitivity analysis The sensitivity package is made to work with functions where each input is passed separately, whereas our model function takes a single dataclass instance. To make our model function work with the sensitivity package, we need to create a wrapper function which takes the separate arguments, creates the dataclass from them, passes that into the model function and returns the result. You can copy my snippet to do this with your model. List comprehensions are a nice easy way to specify values in a range, but you can also hard-code these lists Be careful not to look at too many input values as execution could be very slow. The progress bar will tell you how many cases of the model you are running and show how long it is taking. There are a number of options to customize the output from the library. You can change the names of the inputs and results, the color map, change direction of the colors, the grid size on the hexbin plots, and the number formatting in styled DataFrames. Resources ------------ Dynamic Salary Retirement Model - Python: https://nickderobertis.github.io/fin-...