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The tools you'll meet in this course

Module 01 · Introduction to Python8 min readBeginner

What you'll learn

  • Recognise the names of the core tools and libraries
  • Understand the role each one plays
  • Stop being intimidated by the jargon

A field guide to the names

When you read Python tutorials online, you'll see the same dozen words over and over. Here's what each one is and why you'll meet it in this course.

Python

The language itself. When someone says "I wrote it in Python," they mean they wrote code in this language and ran it with the Python interpreter.

Anaconda

A free bundled installer that gives you Python plus the most-used libraries (pandas, NumPy, Jupyter, matplotlib) in one click. The friendliest way to get set up. We use it in Module 2.

pip

Python's package installer. To add a new library to your Python: pip install thelibrary. Anaconda gives you the common ones already, but pip is how you get anything else.

Library / package

A bundle of pre-written Python code that adds capabilities. Excel calls these "add-ins"; Python calls them libraries. There are hundreds of thousands of them for free.

pandas

The library that turns Python into a souped-up spreadsheet. You will use this constantly. It introduces the DataFrame — that "Python sheet" we just met. Full crash course in Module 9.

NumPy

A library for fast number-crunching. Pandas is built on top of NumPy. You'll touch it occasionally.

openpyxl

The library that reads and writes .xlsx Excel files at a low level — sheets, cells, formatting, formulas, charts. We use it in Modules 7 and 12 for things pandas can't do.

matplotlib & seaborn

The two most common libraries for making charts in Python. We use them in Module 11.

Jupyter notebook

The "code + notes + charts in one document" format we mentioned earlier. File extension .ipynb. Comes free with Anaconda.

VS Code (Visual Studio Code)

A free, modern code editor from Microsoft. It's what we'll use to write Python scripts. There are others (PyCharm, Sublime, etc.) but VS Code is the easiest starting point and works on Mac, Windows, and Linux.

Terminal / command line / PowerShell

The text-based way to talk to your computer. Macs call it Terminal; Windows calls it PowerShell or Command Prompt. You'll need it occasionally — mainly to install things with pip. We hand-hold you through it in Module 2.

=PY() in Excel

The formula that runs Python inside an Excel cell. Microsoft 365 only, as of 2026. Full module on this in Module 8.

Microsoft 365 / Excel for the web

You need the modern subscription version of Excel to use =PY(). The classic boxed Excel 2019 / 2021 does not include it.

How they fit together

A typical day in this course looks like:

  1. You open VS Code.
  2. You write a Python script that imports pandas.
  3. Pandas reads an Excel file (under the hood it uses openpyxl).
  4. You clean and reshape the data.
  5. You save the result back to Excel, or you build a chart with matplotlib.
  6. Optionally: you switch to Excel, type =PY(), and re-run a small piece of the analysis live in a cell.
💡 You don't need to memorise this
This page is a glossary, not a quiz. Bookmark it. As we use each tool you'll learn what it actually feels like.

Key takeaways

  • The names you'll hear most: Python, Anaconda, pip, pandas, openpyxl, Jupyter, VS Code, =PY().
  • Each one has one job — they fit together like Lego.
  • You don't need to memorise them now; you'll meet each in context.

Spot the tool

For each of these jobs, name the tool from this lesson that does it:

  1. "Open and edit an .xlsx file at the cell level."
  2. "Write a chart with code."
  3. "Run a piece of Python inside an Excel cell."
  4. "Install a new library."
  5. "Work on data with code, output, and notes mixed in one document."
Show answers
  1. openpyxl
  2. matplotlib (or seaborn)
  3. =PY()
  4. pip
  5. A Jupyter notebook
📹 Video walkthrough
A video walkthrough of this lesson will be embedded here. Until then, the written walkthrough above mirrors what the video will cover step-for-step.