Examples & Utilities

Explore practical Python for Excel examples, data transformation utilities, custom functions, and interactive workbook workflows.

These showcase templates illustrate the core capabilities of the Boardflare Python for Excel platform: data manipulation, cleaning, custom worksheet functions, and interactive task-pane workflows.

Each workbook opens fully populated with example data and working Python code. Run them as-is to see the output, paste your own data, or ask Copilot/ChatGPT to adapt them to your routine spreadsheet tasks.

Categories of Examples

Data Cleaning & Matching: Fuzzy text matching, deduplication, combining multiple files, and diffing spreadsheets.
Data Transformation: Reshaping tables (pivot/melt), table filtering, and text manipulation.
Worksheet Custom Functions: Create reusable Excel formulas backed by Python packages (BF.FUNCTION).
Interactive Models & Simulation: Workforce forecasting, inventory planning, epidemic models, and scenario analysis.

Available Templates

Cash Flow Forecast & Liquidity Outlook

Forecast weekly cash receipts, payments, and liquidity in Excel with trend models, scenario assumptions, uncertainty bands, and threshold diagnostics.

Clean Data

Standardize messy customer or transaction exports with automated whitespace, casing, date, number, and mapping rules in Excel.

Combine Files

Stack several monthly exports into one table, with a report of which columns matched, which did not, and which values need a look.

Compare Sheets

Find added, removed and changed rows between two versions of a list, matched by a key column, with the old and new value for each changed cell.

Custom Functions

Write custom business logic in Python and call it directly from worksheet cells with BF.FUNCTION formulas.

Customer Details

Click a customer in your Excel table and see their orders, invoices, tickets and revenue in one place.

Demand & Inventory Planner

Optimize case-pack replenishment orders in Excel with safety stock, demand forecasts, and a shared purchasing budget using SciPy MILP.

Forecast

Forecast the next months from a monthly history, test the method on past months, and draw a range around each forecast from how far those tests were off.

Fuzzy Match

Match messy customer or vendor records against a master reference list with text similarity scoring, review bands, and threshold controls in Excel, plus `fuzzy_match` and `fuzzy_lookup` functions for worksheet formulas.

Intermittent Demand Forecast for Spare Parts

Forecast sparse spare-parts demand in Excel with Croston-style methods, event-aware backtests, empirical lead-time safety stock, and planner model overrides.

Product Classification

Classify products by annual revenue (ABC) and weekly demand variability (XYZ) in Excel, with a Pareto view and a review frequency for each combined class.

Product Details

Click a product to see its stock, demand, open purchase orders and a suggested reorder quantity in Python for Excel.

Regression

Identify store sales drivers and quantify unit effects with multiple linear regression in Python for Excel.

Remove Duplicates

Group rows that name the same company after normalising the name, keep one row per group by a rule you choose, and list the rest for removal.

Reshape Data

Unpivot wide month columns, pivot long rows into a grid, or split delimited lists into columns or rows, and report every row that could not be reshaped cleanly.

Sales Scenario Analysis

Compare baseline and discounted revenue in Excel with pandas using worksheet inputs with a Python for Excel notebook.

Segments

Sort customers into natural groups with k-means clustering in Python for Excel, with segment profiles and a fit-by-number chart.

Text Functions

Pull invoice references, email addresses, phone numbers, numbers and names out of messy free text with one worksheet function per call, using Python regular expressions.