Welcome to Part 5 of our “Actually Useful Maths for Data Work” series.
Written by our very own Anthony Fawkes, this five-part series will provide fundraisers, data managers, analysts, and CRM heroes holding charity operations together with easy-to-apply solutions that strip away the stress from maths. The aim is to show you how everyday calculations (and a bit of logic) can level up your data confidence.
Why Python?
Python is a scripting language that automates data tasks, connects to databases and spreadsheets, cleans data, and runs in the background – freeing you up to focus on strategy.
Real-World Use Cases
| Task | What Python Can Do |
|---|---|
| Data Cleaning | Remove duplicates, fix postcodes, format dates |
| Income tracking | Identify supporters who haven’t given in X days |
| Segmentation | Pull data from tools like Typeform or JustGiving |
| Web form syncing | Value after costs |
| Forecasting | Run automated models using historical data |
| Alerting | Notify team when KPIs fall below thresholds |
Python + Your Data Stack
| Data Source | Python Can… |
|---|---|
| CRM (via API) | Extract supporter data, update records |
| Excel/CSV | Read, write, clean, and format data |
| SQL database | Query data directly, export to CSV or dashboards |
| Power BI | Value after costs |
| Forecasting | Feed data into dashboards via cleaned exports |
| Email platform | Sync mailing lists, automate updates |
How Hard Is It To Learn?
It’s surprisingly approachable. Here’s an example script that reads a CSV and finds large donations:
```python import pandas as pd df = pd.read_csv("donations.csv") print(df[df["DonationAmount"] > 100]) ```
Embedding Python In Your Organisation
You can schedule scripts, integrate with Excel, or run logic behind the scenes in a tool like ADRFM.
Starter Projects
Here are some ideas to try: flag lapsed donors, identify missed major gifts, clean CSVs, forecast income, or email key charts each month.
TL;DR
Python helps automate boring but important tasks. It’s scalable, powerful, and friendlier than it looks – perfect for database pros who want to get ahead.
Thanks for Reading!
We hope this guide made the maths feel a little less scary — and a lot more relevant. Whether you’re forecasting next quarter’s income, modelling donor attrition, or just trying to wrangle a spreadsheet that refuses to behave, you’re already doing the hard part: thinking clearly and caring about the impact.
At Actually Data Analytics, we help fundraising teams like yours turn messy data into meaningful insight. From one-off projects to long-term support, we bring clarity, calm, and tools that actually work.
If you’d like help automating your reports, improving retention analysis, or exploring our platform ADRFM, we’d love to chat. No pushy sales. Just practical advice from people who’ve been in your shoes.
Want The Complete Series?
The full series of posts is available to download right now! The full series of posts is available to download right now! Visit our Resources page to obtain your copy today.