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Practical Business Python

Taking care of business, one python script at a time

Article Roadmap

The roadmap is a guide to finding and reading all the articles on the site. All articles are grouped and ordered in a more natural progression than the publish date. This is a good starting point for the first time reader or a returning reader trying to find some specific content.

2024

Sun 14 January 2024: Introduction to Polars

2022

Mon 26 September 2022: Pandas Groupby Warning
Mon 13 June 2022: Using Document Properties to Track Your Excel Reports

2021

Mon 15 November 2021: 16 Reasons to Use VS Code for Developing Jupyter Notebooks
Tue 16 February 2021: Efficiently Cleaning Text with Pandas
Mon 18 January 2021: Case Study: Automating Excel File Creation and Distribution with Pandas and Outlook
Mon 11 January 2021: Pandas DataFrame Visualization Tools

2020

Mon 09 November 2020: Comprehensive Guide to Grouping and Aggregating with Pandas
Mon 19 October 2020: Reading Poorly Structured Excel Files with Pandas
Mon 12 October 2020: Case Study: Processing Historical Weather Pattern Data
Mon 21 September 2020: PB Python Article Roadmap
Mon 14 September 2020: Reading HTML tables with Pandas
Mon 17 August 2020: Taking Another Look at Plotly
Tue 02 June 2020: sidetable - Create Simple Summary Tables in Pandas
Mon 04 May 2020: Exploring an Alternative to Jupyter Notebooks for Python Development
Mon 30 March 2020: Using WSL to Build a Python Development Environment on Windows
Tue 18 February 2020: Python Tools for Record Linking and Fuzzy Matching
Mon 20 January 2020: Using Markdown to Create Responsive HTML Emails

2019

Mon 23 December 2019: Creating Interactive Dashboards from Jupyter Notebooks
Mon 16 December 2019: Finding Natural Breaks in Data with the Fisher-Jenks Algorithm
Mon 02 December 2019: Building a Windows Shortcut with Python
Tue 26 November 2019: Tips for Selecting Columns in a DataFrame
Mon 11 November 2019: Book Review: Machine Learning Pocket Reference
Mon 28 October 2019: Cleaning Up Currency Data with Pandas
Mon 14 October 2019: Binning Data with Pandas qcut and cut
Tue 17 September 2019: Happy Birthday Practical Business Python!
Mon 26 August 2019: Combine Multiple Excel Worksheets Into a Single Pandas Dataframe
Mon 29 July 2019: Automated Report Generation with Papermill: Part 2
Mon 22 July 2019: Automated Report Generation with Papermill: Part 1
Mon 08 July 2019: Build a Celebrity Look-Alike Detector with Azure’s Face Detect and Python
Mon 03 June 2019: Evangelizing Python for Business
Mon 13 May 2019: Stylin’ with Pandas
Mon 18 February 2019: Monte Carlo Simulation with Python
Mon 28 January 2019: Updated: Using Pandas To Create an Excel Diff
Mon 07 January 2019: Using The Pandas Category Data Type

2018

Tue 20 November 2018: Building a Repeatable Data Analysis Process with Jupyter Notebooks
Mon 08 October 2018: Pandas Crosstab Explained
Mon 06 August 2018: New Plot Types in Seaborn’s Latest Release
Mon 02 July 2018: Automating Windows Applications Using COM
Tue 29 May 2018: Book Review: Machine Learning with Python Cookbook
Mon 07 May 2018: Building Bullet Graphs and Waterfall Charts with Bokeh
Mon 30 April 2018: Choosing a Python Visualization Tool
Mon 26 March 2018: Overview of Pandas Data Types
Tue 20 February 2018: Intro to pdvega - Plotting for Pandas using Vega-Lite
Mon 29 January 2018: Building a PDF Splitter Application
Tue 02 January 2018: Interactive Visualization of Australian Wine Ratings

2017

Mon 27 November 2017: Using Python’s Pathlib Module
Mon 09 October 2017: Creating Interactive Visualizations with Plotly’s Dash Framework
Mon 28 August 2017: Building a Bullet Graph in Python
Mon 31 July 2017: Pandas Grouper and Agg Functions Explained
Mon 03 July 2017: Introduction to Market Basket Analysis in Python
Tue 23 May 2017: How Accurately Can Prophet Project Website Traffic?
Tue 25 April 2017: Effectively Using Matplotlib
Tue 04 April 2017: Understanding the Transform Function in Pandas
Mon 06 March 2017: Forecasting Website Traffic Using Facebook’s Prophet Library
Tue 21 February 2017: Populating MS Word Templates with Python
Mon 06 February 2017: Guide to Encoding Categorical Values in Python
Tue 17 January 2017: Data Science Challenge - Predicting Baseball Fanduel Points

2016

Mon 19 December 2016: Building a Financial Model with Pandas - Version 2
Mon 21 November 2016: Building a Financial Model with Pandas
Tue 06 September 2016: Creating Pandas DataFrames from Lists and Dictionaries
Mon 29 August 2016: Introduction to Data Visualization with Altair
Tue 23 August 2016: Lessons Learned from Analyze This! Challenge
Wed 15 June 2016: Excel “Filter and Edit” - Demonstrated in Pandas
Mon 16 May 2016: Sharing Your Python Case Studies
Wed 06 April 2016: Interactive Data Analysis with Python and Excel
Tue 26 January 2016: Learn More About Pandas By Building and Using a Weighted Average Function

2015

Wed 30 December 2015: Getting to the “Plateau of Productivity” with Python
Mon 07 December 2015: Creating Advanced Excel Workbooks with Python
Mon 26 October 2015: Pandas 0.17 Release and Other Notes
Mon 14 September 2015: Adding a Simple GUI to Your Pandas Script
Mon 17 August 2015: Creating Powerpoint Presentations with Python
Mon 13 July 2015: Best Practices for Managing Your Code Library
Thu 02 July 2015: Visualizing Google Forms Data with Seaborn
Tue 09 June 2015: Collecting Data with Google Forms and Pandas
Sun 17 May 2015: Notebooks Now on Github and Other Updates
Mon 04 May 2015: Tips for Customizing Your IPython and Pandas Display
Wed 08 April 2015: Improving Pandas Excel Output
Mon 23 March 2015: Generating fake data with barnum
Mon 16 February 2015: Creating PDF Reports with Pandas, Jinja and WeasyPrint
Mon 02 February 2015: Generating Excel Reports from a Pandas Pivot Table
Tue 20 January 2015: Overview of Python Visualization Tools
Tue 06 January 2015: Web Scraping - It’s Your Civic Duty

2014

Mon 29 December 2014: Pandas Pivot Table Explained
Wed 17 December 2014: Combining Data From Multiple Excel Files
Mon 08 December 2014: Common Excel Tasks Demonstrated in Pandas - Part 2
Sun 30 November 2014: Common Excel Tasks Demonstrated in Pandas
Tue 18 November 2014: Creating a Waterfall Chart in Python
Sun 09 November 2014: Using Pandas To Create an Excel Diff
Sun 26 October 2014: Simple Graphing with IPython and Pandas
Tue 14 October 2014: Simple Interactive Data Analysis with Python
Sun 05 October 2014: Using Sets for Data Analysis
Sat 27 September 2014: Configuring Pelican Static Blog
Wed 24 September 2014: The Technology Behind PB Python

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