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xlslim-code-samples

This repo contains working examples showing how the xlSlim Excel add-in enables you to use Python in Excel.

See https://russelwebber.github.io/xlslim-docs/html/index.html and https://www.xlslim.com

Specific examples are:

Basics

  • Interactive mode where Excel mimics a Jupyter notebook
  • Calling a Python function from Excel
  • Using type hints
  • Passing a dictionary
  • Using optional arguments
  • Reading a csv into Excel using Python
  • Fetching JSON data from the web and showing this in Excel
  • Manipulating data using SQLite and showing the results in Excel
  • Calling VBA and other macro functions from Python

Imports

  • Controlling which Python functions are imported into Excel
  • Adding additional paths to the Python module search path
  • Dynamic imports, creating modules and functions from text in Excel

Remote Imports

  • Importing modules from GitHub and BitBucket
  • Importing a module from a Gist
  • Importing code from a remote ZIP archive

NLP

  • Performaing nlp with Python and Excel

numpy

  • Passing numpy arrays from Excel to Python functions
  • Cacheing numpy arrays returned from Python

pandas

  • Using interactive mode to read data from csv, pivot in pandas, and export as PDF
  • Passing pandas series and dataframes from Excel to Python functions
  • Cacheing pandas series and dataframes returned from Python
  • Calling a Python Monte Carlo option pricer from Excel
  • Reading prices from Yahoo Finance into Excel
  • Using Python sklearn to perform Principal Components Analysis of Index Prices

Streaming

  • Streaming data from Bloomberg into Excel using Python
  • Streaming data from IEX into Excel using Python
  • Streaming data from Kafka into Excel using Python
  • Streaming numpy arrays from Kafa into Excel using Python

VBA

  • Using Python as an Excel replacement.
  • Loading csv data into Excel using PowerQuery.
  • Using Python and pywin32 COM to create a pivot table.
  • Adding items to the context and ribbon menus

Finance

  • Using xlSlim to run scenario analysis for equity index options. This example shows how data classes and dictionaries can be used to structure code neatly.

DuckDB

  • Using DuckDB to query csv, json and Parquet files.

Optimization

  • Using scipy.optimize.linprog to solve a production mix problem.