Ravindra BagaleCourses & study guides Track your progress

Guides

Install Python 3, a venv and Jupyter for Data Science

By , Data Science & Data Analytics trainer LinkedIn Published: Last updated:

Read this guide in: English · मराठी · हिंदी

Install Python 3, create a venv, pip install Jupyter and pandas (not sklearn), then launch a notebook. That is the setup lap for this Data Science course.

Chala mitrano! Broken installs waste weekends. Today we do a clean path: Python → venv → packages → Jupyter. Simple vertical steps. Samajla ka? Check at the end.

Quick answer

Vertical install path:

  1. Install Python 3 and confirm python3 --version.
  2. Make a folder such as ds-practice.
  3. Create venv: python3 -m venv ds-env.
  4. Activate the venv.
  5. pip install jupyter pandas openpyxl matplotlib seaborn.
  6. jupyter notebook or jupyter lab → new notebook → print(1+1).
Python3 → venv → pip install → Jupyter → first cell

Language: English · मराठी · हिंदी

What do I need before this guide?

  • A computer you can install software on (Windows, macOS or Linux).
  • Permission to use a terminal / command prompt.
  • Course: Install Python 3.

Before and after (look at the tables first)

Before install No venv and no Jupyter.

Before — no venv, Jupyter not found.

After install venv and Jupyter are ready.

After — ds-env venv and Jupyter running.

Before: no venv, Jupyter missing. After: ds-env active and Jupyter running.

Why a virtual environment?

What it is

  1. A folder that holds packages for one project.
  2. Keeps class work from fighting system Python.

Why you care

  1. “It works on my machine” often means “wrong global packages”.
  2. You can delete ds-env and rebuild without reinstalling the OS.

What you see

  1. After activate, the prompt often shows (ds-env).
  2. which python / where python points inside the venv.

Step 1 — Install Python 3

Vertical steps:

  1. Prefer the official python.org installer or your OS package manager.
  2. On Windows, enable “Add Python to PATH” if the installer offers it.
  3. Open a new terminal.
  4. Run python3 --version (or python --version on some Windows setups).

What you want to see: a 3.x version string, not an error.

Course: Install Python 3.

Step 2 — Project folder + venv

mkdir ds-practice
cd ds-practice
python3 -m venv ds-env

Activate (conceptual — exact line depends on OS):

  1. Linux/macOS: source ds-env/bin/activate
  2. Windows cmd: ds-env\Scripts\activate
  3. Windows PowerShell: ds-env\Scripts\Activate.ps1 (execution policy may apply)

Course: Project folder and venv.

Step 3 — Install packages (no sklearn)

python -m pip install --upgrade pip
pip install jupyter pandas openpyxl matplotlib seaborn

Why these:

  1. jupyter — notebooks.
  2. pandas — DataFrames.
  3. openpyxl — Excel.
  4. matplotlib / seaborn — charts.

Why not sklearn here: this course excludes ML model training. See Install packages (no sklearn).

Step 4 — Launch Jupyter

jupyter notebook

or:

jupyter lab

Vertical checks:

  1. Browser opens the Jupyter UI.
  2. New → Notebook → Python 3.
  3. Cell: print(1+1) → 2.
  4. Cell: import pandas as pd; print(pd.__version__).

Course: Launch Jupyter.

Common problems (and calm fixes)

Problem Likely cause Fix
python3: command not found Not installed / PATH Reinstall; open a new terminal
jupyter: command not found venv not active Activate, or python -​m jupyter notebook
pip installs to the wrong place Forgot activate Activate; confirm which python
Excel read fails later openpyxl missing pip install openpyxl inside venv
Port busy Old Jupyter still running Close old session or pick another port

Tiny first notebook idea

  1. Create shop_sales.csv with Mumbai 120, Pune 70.
  2. df = pd.read_csv("shop_sales.csv")
  3. df["sales"].sum() → 190
  4. You have proven install + pandas in one sitting.

Ravindra Bagale's Tip

Screenshot your python --version and a notebook cell showing 190. That pair proves setup more than a long story. Samajla ka?

Practice task

  1. Create a venv named ds-env.
  2. Install the package list from Quick answer (no sklearn).
  3. Launch Jupyter and run import pandas as pd.
  4. Write one Markdown cell: “Setup done — next DataFrame”.

Learn it properly

Course lessons:

Related guides: Python for data science beginners · pandas DataFrame beginners

Samajla ka? Python 3, venv, pip packages without sklearn, Jupyter open, first cell green. Then load a CSV. Aata pudhe jaauya.

Frequently asked questions

What is a venv?

A virtual environment: an isolated folder of Python packages so class projects do not break your system Python.

Do I need Anaconda?

Optional. A plain Python + venv + pip path is enough for this course.

Why not install sklearn?

This Data Science course explicitly excludes machine learning model training. Stay with pandas, cleaning, EDA and charts.

jupyter: command not found?

Activate the venv first, or call python -m jupyter notebook.

Windows vs Linux/macOS?

Commands differ for activation paths; Python and pip ideas stay the same. Follow the course setup chapter for screenshots.

Next after install?

Learn Series vs DataFrame, then read_csv.