NumPy on Ubuntu: From Zero to First Arrays

August 27, 2025

This content originally appeared on DEV Community and was authored by Anas Hussain

Why this post?

Today I set up a clean Python workspace on Ubuntu and ran my first NumPy code. I wrote down every step so you (or future‑me) can repeat it in minutes.

Prerequisites

Ubuntu (works on 20.04/22.04/24.04+)
Terminal access
Basic comfort running shell commands

Tip: Commands with $ go in your terminal. Don’t copy the $ itself.

Install Python and pip

Ubuntu ships with Python 3, but let’s make sure the essentials are installed and up‑to‑date.

$ sudo apt update && sudo apt install -y python3 python3-pip python3-venv
$ python3 --version
$ pip3 --version

Create a Virtual Environment

Make a dedicated folder for your NumPy learning so packages don’t leak into system Python.

$ mkdir -p ~/numpy-learning && cd ~/numpy-learning
$ python3 -m venv numpy-venv
$ source numpy-venv/bin/activate
(numpy-venv) $ which python

You should see something like /home/you/numpy-learning/numpy-venv/bin/python. The (numpy-venv) prefix means the environment is active.

Why venv? Each project gets its own clean set of packages. No conflicts.

Install NumPy and Jupyter

First, bring pip up to date, then install the tools we need:

(numpy-venv) $ python -m pip install --upgrade pip
(numpy-venv) $ pip install numpy jupyter

Optional but handy for data work:

(numpy-venv) $ pip install matplotlib pandas

Verify installs:

(numpy-venv) $ python -c "import numpy as np; print(np.__version__)"
(numpy-venv) $ jupyter --version

Launch Jupyter Notebook

Start the notebook server. Your browser will open automatically (or you’ll get a URL with a token to paste into your browser):

(numpy-venv) $ jupyter notebook

In the Jupyter UI:

Click New → Python 3 (ipykernel).
Rename it to numpy_basics.ipynb (click the title at the top).

Take a look into my Jupyter UI

Your First NumPy Operations

Create a few cells and run the following. (Click a cell and press Shift+Enter to run.)

Cell 1 — Import & version

import numpy as np
print("NumPy version:", np.__version__)

Cell 2 — Create arrays

# 1D and 2D arrays
a = np.array([1, 2, 3, 4, 5])
b = np.array([[1, 2, 3],
              [4, 5, 6]])
print("a:", a)
print("b:\n", b)

Cell 3 — Properties

print("a.shape:", a.shape, "a.dtype:", a.dtype)
print("b.shape:", b.shape, "b.ndim:", b.ndim, "b.size:", b.size)

Cell 4 — Indexing & slicing

print("First of a:", a[0])
print("Last two of a:", a[-2:])
print("b second column:", b[:, 1])

Cell 5 — Vectorized operations

print("a * 2:", a * 2)
print("a + 10:", a + 10)
print("a ** 2:", a ** 2)

Cell 6 — Broadcasting

row = np.array([10, 20, 30])
print("b + row:\n", b + row)

Cell 7 — Aggregations

arr = np.array([10, 20, 30, 40, 50])
print("sum:", np.sum(arr))
print("mean:", np.mean(arr))
print("std:", np.std(arr))
print("min:", np.min(arr), "max:", np.max(arr))

Cell 8 — Reshape

reshaped = b.reshape(3, 2)
print("reshaped b (3x2):\n", reshaped)

That’s it — your first NumPy session is done!

Shut Down & Deactivate

When you’re finished for the day:

In the Jupyter tab: File → Save and Checkpoint.
In the terminal where Jupyter is running: press Ctrl + C and confirm to stop the server.
Deactivate your virtual environment:

(numpy-venv) $ deactivate

Next time, come back with:

$ cd ~/numpy-learning
$ source numpy-venv/bin/activate
(numpy-venv) $ jupyter notebook

Common Pitfalls & Fixes

pip installs to the wrong place

Always use python -m pip ... inside your venv to be explicit.

(numpy-venv) $ python -m pip install numpy jupyter

jupyter: command not found after install

Make sure your venv is active (look for (numpy-venv)), then reinstall:

$ source numpy-venv/bin/activate
(numpy-venv) $ python -m pip install --upgrade pip jupyter

Mixing system Python and venv Python

Check which Python is running:

(numpy-venv) $ which python

It should point to your project’s numpy-venv folder.

Permission errors

Avoid sudo pip. Use a venv. If needed, upgrade pip:

(numpy-venv) $ python -m pip install --upgrade pip

What’s Next

Try JupyterLab for a modern UI:

  (numpy-venv) $ pip install jupyterlab
  (numpy-venv) $ jupyter lab

Explore: np.arange, np.linspace, np.random.rand, np.vstack, np.hstack.
Add matplotlib and plot your arrays.
Day 2 topics: boolean masking, fancy indexing, broadcasting tricks, and small exercises.

If this helped, drop a comment or share what you built with NumPy today!