Anaconda Navigator Installation Tutorial

This tutorial explains how to install Anaconda Navigator, set up a new environment with Python, and install commonly used libraries such as pandas, numpy, seaborn, and scikit-learn to use in Jupyter Notebook.

1. Download and Install Anaconda

Step 1.1: Download Anaconda

Visit the Anaconda Individual Edition page and download the installer for your operating system (Windows, macOS, or Linux).

Step 1.2: Install Anaconda

• Windows:
  1. Double-click the downloaded .exe installer.
  2. Follow the installation prompts. You can usually accept the default settings.
  3. (Optional) Choose to add Anaconda to your PATH, though it’s recommended to use the Anaconda Prompt.
• macOS/Linux:
  1. Open a terminal.
  2. Navigate to the directory containing the downloaded installer.
  3. Run the installer using a command like:

     bash Anaconda3-202X.XX-MacOSX-x86_64.sh

  4. Follow the prompts in the terminal to complete the installation.

2. Launch Anaconda Navigator

Once installed, open Anaconda Navigator:

• Windows: Open the Start Menu and search for “Anaconda Navigator.”
• macOS/Linux: Open your Applications folder or use the terminal command anaconda-navigator.

Anaconda Navigator provides a user-friendly interface to manage environments and launch applications like Jupyter Notebook.

3. Create a New Conda Environment (Optional but Recommended)

Step 3.1: Open the Terminal or Anaconda Prompt

• Windows: Open the Anaconda Prompt from the Start Menu.
• macOS/Linux: Open your Terminal.

Step 3.2: Create a New Environment

Run the following command to create a new environment (for example, named datasci_env) with a specific Python version:

conda create -n datasci_env python=3.9

Press y when prompted to proceed.

Step 3.3: Activate the Environment

Activate the new environment using:

conda activate datasci_env

Your prompt should change to indicate that you’re now working within datasci_env.

4. Install the Required Libraries

With your environment activated, install the libraries along with Jupyter Notebook using the following command:

conda install pandas numpy seaborn scikit-learn jupyter

This command will install all the specified libraries. Follow the prompts to complete the installation.

Note: Anaconda often comes with these libraries pre-installed in the base environment. Creating a separate environment ensures your project dependencies are controlled.

5. Launch Jupyter Notebook

Step 5.1: Start Jupyter Notebook

In your terminal (with the environment activated), launch Jupyter Notebook by running:

jupyter notebook

A new browser tab should open showing the Jupyter Notebook dashboard.

Step 5.2: Create a New Notebook

Click on the New button (usually on the right side) and select Python 3. A new notebook will open in a new tab.

6. Test Your Setup

In your new Jupyter Notebook, run the following code cells one at a time to ensure all libraries are correctly installed:

# Import libraries
import pandas as pd
import numpy as np
import seaborn as sns
from sklearn import datasets, model_selection, metrics

# Display versions
print("Pandas version:", pd.__version__)
print("NumPy version:", np.__version__)
print("Seaborn version:", sns.__version__)

If these commands run without errors and print out the version numbers, your setup is complete.

Additional Tips

• Updating Packages: You can update any package using:

  conda update package-name

  For example, to update scikit-learn:

  conda update scikit-learn

• Managing Environments: Use Anaconda Navigator or the command line to create, list, and remove environments. For example, list environments with:

  conda env list

• Installing Additional Libraries: If you need more libraries later, simply activate your environment and install them using conda install or pip install if they’re not available via conda.

This guide covers the entire process from downloading and installing Anaconda to setting up an environment with the necessary libraries and launching Jupyter Notebook. Enjoy your data science journey with Python!