pip install in jupyter notebook with code examples

Pip is one of the most widely used package management systems in the Python community. It allows users to install and manage third-party packages and libraries that are not included in the standard Python library. The Jupyter Notebook is a popular interactive computing environment that is used for data analysis, scientific computing, and education. In this article, we will explore how to install and manage third-party packages using pip in Jupyter Notebook.

Installation of Pip

Before we dive into pip installation, it is important to note that pip is not included in the standard Python installation package. Therefore, we must first install pip before we can use it to install other packages. Installing pip on your system is easy and can be done in two ways – using a package manager or via the command line.

Using a Package Manager

Most modern OSes come with package managers pre-installed. If you’re on a Unix-like system such as Ubuntu, you can use the apt package manager to install pip. Similarly, if you’re on a Mac system, you can use Homebrew.

To install pip via the command line on Unix-like systems, follow the steps below:

1. Open the terminal
2. Run the command: sudo apt-get install python-pip

Using the Command Line

If you’re using the Windows OS or do not have a package manager installed, you can use the command line to install pip. Follow the steps below:

1. Download the get-pip script from https://bootstrap.pypa.io/get-pip.py
2. Open the command prompt or terminal
3. Navigate to the directory in which the get-pip.py script was saved
4. Run the command: python get-pip.py

Note: If you’re using a virtual environment, make sure to activate it before installing pip.

Once pip has been successfully installed, you can verify its installation by running the ‘pip –version’ command in the terminal.

Using Pip in Jupyter Notebook

To use pip in Jupyter Notebook, we must first ensure that the notebook is running in the same environment as the pip installation. This can be done by activating the environment before launching the notebook or installing pip in the base environment. Here are two quick methods to ensure you access pip in your notebook.

Method 1: Activating an Environment

If you are running your Jupyter Notebook within a virtual environment, you will need to activate the environment before launching Jupyter Notebook.

To activate the environment, follow these steps:

1. Open your terminal or command prompt
2. Navigate to the directory where your environment is stored
3. Run the command: source activate environment-name

Note: Replace ‘environment-name’ with the name of your virtual environment.

4. Once the environment is active, launch Jupyter Notebook by running the command: jupyter notebook

Method 2: Installing Pip in the Base Environment

Alternatively, you can install pip in the base environment. This will make it accessible to all Jupyter Notebooks. To install pip in the base environment, follow these steps:

1. Open your terminal or command prompt
2. Run the command: python -m pip install ipykernel
3. Next, run the command: python -m ipykernel install –user

The above command will install pip and the IPython kernel, which is required for Jupyter Notebook. After installation, see the list of kernels that are available in Jupyter by running ‘jupyter kernelspec list.’

Therefore, if you don’t want to use the default base environment, you can create a new environment in which to install your packages, activate it and install the desired packages using the usual ‘!pip install package-name’ command.

Installing Packages using Pip in Jupyter Notebook

Once pip has been installed in the desired environment, you can proceed to install packages in Jupyter Notebook. Similar to installing in your local machine, you can use pip install command to install a package in Jupyter Notebook via the terminal or using the !pip command in the Notebook.

For example, to install pandas, a popular data analysis library, you can simply run the following command:

!pip install pandas

To install multiple packages, you can use a comma-separated list of package names like so:

!pip install pandas numpy matplotlib

Note: If you’re using a virtual environment in Jupyter Notebook, you must ensure that you activate that environment before executing the pip install command.

Upgrading a Package

To upgrade a package using pip, simply use the –upgrade flag as shown below:

!pip install –upgrade package-name

Uninstalling a Package

To uninstall a package using pip in Jupyter Notebook, you can use the command below:

!pip uninstall package-name

Conclusion

Pip is a powerful package management system that provides an easy way to install and manage third-party packages on Python. Jupyter Notebook, on the other hand, is an excellent environment for data analysis, coding, and education. By following the steps outlined in this article, you can install and use pip in Jupyter Notebook. Additionally, you can install and manage packages within the Notebook via pip install command or the terminal.

Installing pip on Windows

In addition to the methods mentioned above, pip can also be installed on Windows using the executable installer. To install pip on Windows via the installer, follow these steps:

1. Download the get-pip.py script from https://bootstrap.pypa.io/get-pip.py
2. Open the command prompt
3. Navigate to the directory in which the get-pip.py script was saved
4. Run the command: python get-pip.py

Once pip has been successfully installed, you can verify its installation by running the ‘pip –version’ command in the command prompt.

Creating and Activating Virtual Environments

Virtual environments allow users to create isolated Python environments, each with their own set of packages and dependencies. This helps prevent conflicts between different projects and keeps dependencies organized.

To create a virtual environment using Python’s built-in modules, follow these steps:

1. Open the command prompt or terminal
2. Navigate to the directory in which you want to create the virtual environment
3. Run the command: python -m venv environment-name

Note: Replace ‘environment-name’ with the desired name of your virtual environment.

4. To activate the environment, run the command: source environment-name/bin/activate

Note: On Windows, the command to activate the environment is ‘environment-name\Scripts\activate.bat’

Once activated, you can install packages within the virtual environment using the pip install command. To exit or deactivate the virtual environment, simply run the command ‘deactivate’.

Using Conda Instead of Pip

Conda is another popular package management system commonly used in data science. It is commonly used to install and manage scientific computing packages such as NumPy, SciPy, and pandas. Conda is particularly useful when working with complex dependencies or different versions of a package.

To install packages using Conda, follow these steps:

1. Open the command prompt or terminal
2. Navigate to the directory in which Conda is installed
3. Run the command: conda install package-name

Note: To create a new environment with Conda, use the command ‘conda create –name environment-name’.

Conclusion

In summary, pip is an essential tool for managing Python packages and libraries. By understanding how to install pip, create and activate virtual environments, and install packages using pip or Conda, users can effectively manage their Python dependencies and build powerful projects. These concepts apply to Jupyter Notebook as well, providing users with the ability to easily access and use pip within their notebooks.

Popular questions

Q1. What is pip and why is it important for Python?
A1. Pip is a package management system for Python that enables users to install and manage third-party packages and libraries that are not part of the standard Python library. Pip is important for Python because it allows developers to efficiently and effectively manage their project dependencies and build more powerful and complex projects.

Q2. How can pip be installed on Windows?
A2. Pip can be installed on Windows using a number of methods, including via the executable installer, via the command line, or through a package manager like Chocolatey or Scoop.

Q3. How can virtual environments be created and activated using Python’s built-in modules?
A3. Virtual environments can be created and activated using Python’s built-in ‘venv’ module. To create a virtual environment, navigate to the desired directory in the command prompt or terminal and run the command ‘python -m venv environment-name’. To activate the environment, run the command ‘source environment-name/bin/activate’ on Linux and Mac machines, and ‘environment-name\Scripts\activate’ on Windows.

Q4. How can packages be installed using Conda?
A4. Packages can be installed using Conda by navigating to the desired directory in the command prompt or terminal and running the command ‘conda install package-name’. To create a new environment with Conda, use the command ‘conda create –name environment-name’.

Q5. How can packages be installed using pip in Jupyter Notebook?
A5. Packages can be installed using pip in Jupyter Notebook by ensuring that pip is installed in the desired environment, either by activating the environment before launching Jupyter Notebook or by installing pip in the base environment. Once pip is installed, packages can be installed by running the command ‘!pip install package-name’ in a code cell within the notebook.

Tag

Installation