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Mito Efficiency Test for Finance

The Mito Efficiency Test for Finance helps finance professionals test how Mito changes their ability to write Python code. By the end of the test, you will know exactly how much faster or slower you are writing Python code with Mito compared to writing Python code by hand.

Background

Python is the most popular and rapidly growing language for Finance professionals. However, transitioning from tools like Excel to Python can take months or years of training.

This repository contains a sample Finance workflow, that includes:

  • Reading in XLSX and CSV files
  • Handling datatype conversions
  • Generating graphs
  • Creating pivot tables on time series data
  • Exporting data to Excel

Running a Mito Efficiency Test

If you don't already have Python and Jupyter installed, follow these installation instructions.

To run a Mito Efficiency Test:

  1. Download the data folder from this GitHub repository
  2. Download the Efficiency Test.ipynb notebook from this GitHub repository
  3. Complete the workflow described in the notebook with Python only
  4. Complete the workflow for a second time, now with with Python AND Mito -- using Mito for the analysis.

You can either use Python + Mito first, or use Python first. If you are running this test with multiple users, feel free to switch off.

What to track while completing the workflow

  1. How long does it take to complete the workflow when just using Python?
  2. How long does it take to complete the workflow when you using Mito AND Python?
  3. How many times does your code error?
  4. How often and where do you get stuck in either case?
  5. The qualitative experience of using just Python vs. Mito with Python - how did this feel?