How to install jupiter notebook on windows 10

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. Uses include data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

Jupyter has support for over 40 different programming languages and Python is one of them. Python is a requirement (Python 3.3 or greater, or Python 2.7) for installing the Jupyter Notebook itself.

Jupyter Notebook can be installed by using either of the two ways described below:

• Using Anaconda:
  Install Python and Jupyter using the Anaconda Distribution, which includes Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science. To install Anaconda, go through How to install Anaconda on windows? and follow the instructions provided.

• Using PIP:
  Install Jupyter using the PIP package manager used to install and manage software packages/libraries written in Python. To install pip, go through How to install PIP on Windows? and follow the instructions provided.

Installing Jupyter Notebook using Anaconda:

Anaconda is an open-source software that contains Jupyter, spyder, etc that are used for large data processing, data analytics, heavy scientific computing. Anaconda works for R and python programming language. Spyder(sub-application of Anaconda) is used for python. Opencv for python will work in spyder. Package versions are managed by the package management system called conda.

To install Jupyter using Anaconda, just go through the following instructions:

Launching Jupyter:

Installing Jupyter Notebook using pip:

PIP is a package management system used to install and manage software packages/libraries written in Python. These files are stored in a large “on-line repository” termed as Python Package Index (PyPI).
pip uses PyPI as the default source for packages and their dependencies.

To install Jupyter using pip, we need to first check if pip is updated in our system. Use the following command to update pip:

python -m pip install --upgrade pip

After updating the pip version, follow the instructions provided below to install Jupyter:

• Command to install Jupyter:

  python -m pip install jupyter
  

• Beginning Installation:
  
• Downloading Files and Data:
  
• Installing Packages:
  
• Finished Installation:
  

Launching Jupyter:
Use the following command to launch Jupyter using command-line:

jupyter notebook

Being Pythonists it is very important to work with the best text editor/notebook so that the visibility of codes and various other diagrams are clear and understood by the people. The Python programming language contains an inbuilt text editor called IDLE and is highly preferred by developers because it provides numerous features for the users to play with starting from model creation to deployment.

There are many other alternative text editors to IDLE as well that provide high-end features to Python developers to carry out their tasks like Atom, Sublime, Notepad++, Spyder, Visual Studio, etc.

From so many text editors present for this programming language the most preferred one for the Data Science community is Jupyter. This special kind of Python notebook comes with an extension of .ipynb which stands for I Python Notebook.

The Python work that we usually do with normal editors gets saved with the extension of .py. Still, with this notebook, in hand, the extension is changed because this notebook provides a high-end command terminal where scientific computing can be performed with much ease. This I Python notebook can integrate with many existing web libraries for data visualization.

Now, as we know that Python is easily downloadable either through the official website or through Anaconda installation the question arises is Jupyter downloadable in the normal installation of Python, or do we need Anaconda to run Jupyter??

Also, as we know that Python is independent of the operating system we are working with so how to download the same in Windows 10? The answers to these questions are given below along with the working steps i.e. how to download Jupyter using plain Python:

Installing Jupyter on Windows 10 or 7

Please follow the following steps to install Jupyter NoteBook on Windows 10 or 7 without having an Anaconda setup.

Download Python

• The first and foremost thing to download is Python from the official website which is python.org (Downloads section).
• Here you will find various versions of executable files for Windows, Mac, and Linux.
• Just click on the version you want to work with for Windows and processor 64-bit or 32-bit and start the installation.

Install Python 3.8.x 64-bit

• Once the installation is finished click on the .exe file and it starts the setup for installation.
• The first page that opens in setup is the Install Python page where it will ask you to install python, customize your installation, install launchers for all users, and add Python to the path.
• Just make sure that you check the option of adding Python to the path and then click on customize the installation and check all the options getting displayed.
• Once you are finished with this just click on the install now option and wait for Python to get installed into your system.

Open Command Prompt and run Python

• Now after the installation finishes, to make sure that everything is properly installed just go to your command prompt and type python.
• If it is throwing no error and showing “Python 3.7.6 (tags/v3.7.6:43364a7ae0, Dec 19, 2019, 00:42:30) [MSC v.1916 64 bit (AMD64)] on win32 Type “help”, “copyright”, “credits” or “license” for more information” then congratulations you have successfully downloaded Python to your system and are ready to proceed to the next step that is, installing Jupyter.

Check whether PIP is Installed on Windows 10 or not

Again go to the command prompt and then make sure that pip is installed with Python and check that type pip in the command prompt. If it throws no error then there is a pip installed in your system. But don’t after Python setup it will be there.

Install Jupyter Notebook on Windows 10/7 using PIP

• Once you have made sure that everything is fine just type pip install jupyter and wait for the installation to finish.
• If everything goes right then Jupyter will get installed within the Python environment and to make sure that it is properly installed just type jupyter notebook in the command prompt.
• This will take you to the local host of your system where the Jupyter notebook will get integrated allowing the users to access its features and work on the same.

Start using Jupyter I Python notebook

• Within the Jupyter environment just click on New and start working with your very first I Python notebook.
• There is also a provision to upload existing notebooks within the environment and people can access this feature as and when required.

So this is how we can install Jupyter in your system (Windows 10) without downloading Anaconda.

FAQ

Can I run Jupyter without Anaconda?

Yes, we can run Jupyter notebook without Anaconds by installing directly on Windows 11 /10 or Linux. Here in this tutorial we already have discussed that.

Is Jupyter a Python IDE?

Ofcourse, Jupyter is an IDE – interactive development environment for Python programming. We can use a browser to access Jupyter, as it is web-based. Further, it is an open-source IDE that allows users to create and share documents of live code. Not only Python but also supports R and Julia programming languages.

Is Anaconda and Jupyter same?

Anaconda and Jupyter are not the same things, however, they are related. Both are open source, however, Anacona is a distribution of Python and R for data science and machine learning. Whereas, Jupyter Notebook is used to share Live code in a document form.

Jupyter is included in Anaconda, so when you install Anaconda, Jupyter will come automatically.  Furthermore, Anaconda includes a package manager called CONDA to install various packages such as NumPy, pandas, and more. Also, unlike Anaconda, Jupyter can be used with multiple programming languages, including Python, R, and Julia,

This information explains how to install the Jupyter Notebook and the IPython
kernel.

pip3 install --upgrade pip

In this article, We will cover how to install Jupyter Notebook without Anaconda on Windows. Before the installation procedure let us try to understand what is Jupyter Notebook?

Jupyter Notebook

Jupyter Notebook is a free, open-source, and interactive web application that allows us to create and share documents containing live code, equations, visualizations, and narrative text. Some of the most important uses of Jupyter Notebook are data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more interesting.

Jupyter Notebook provides support for over 40 different programming languages. And the interesting thing is Python is one of them. To install the Jupyter Notebook in order to work with python needs the version of Python as follows: (Python 3.3 or greater, or Python 2.7).

Now as we are not installing Jupyter Notebook through Anaconda, but we install it with the help of PIP. Now there must be a question in your mind what is PIP?

So let us direct our discussion to PIP

What is PIP?

In Python, the package installer is known as PIP. PIP is basically a package management system that is mainly used to install and manage software packages/libraries that are written in Python.

• And all the files are mainly stored in a large «on-line repository» which is termed as Python Package Index that is PyPI.

• Thus the pip uses PyPI as its default source for the packages and their dependencies.

To install the Jupyter Notebook in your system, first of all, you need to check if PIP is already installed or not. You will need to write the command in your command prompt.The command to update the pip is as given below:

python -m pip install --upgrade pip

Then you will see this on your screen:

After the updation of pip, the steps to install Jupyter Notebook are as follows:

1. To Install the Jupyter, the command is as given below:

python -m pip install jupyter

2. After the installation begins you will see this:

3. Installation of Packages and finish of Installation

Launching the Jupyter in command prompt

To launch the Jupyter you need to write the following command

jupyter notebook

After writing the above command in your cmd, you will see this:

And then it will open this:

Now To create a Notebook where you will store and run your code you just need to make a click on «New» on the top on the right side; there you have four options: Python 3(notebook), Text File, Folder, and Terminal. Just click on Python 3 and start your coding.

The notebook is always saved with (.ipynb) extension.

Now we will show you what exactly you will see on your screen:

Hopefully, you guys understood the installation of Jupyter without the help of Anaconda. For any doubts or queries, please comment below.

You may also like:

• Matplotlib in Jupyter Notebook

• Beginners Guide to Jupyter Notebook

• How to Install Burp Suite on Windows 10?

• What is Homebrew and How to Install it on Mac OSX

Three Ways to Run Jupyter In Windows

The «Pure Python» Way

Make your way over to python.org, download and install the latest version (3.5.1 as of this writing) and make sure that wherever you install it, the directory containing python.exe is in your system PATH environment variable. I like to install it in the root of my C: drive, e.g. C:Python35, so my PATH contains that directory.

Once that’s installed, you’ll want to create a virtual environment, a lightweight, disposable, isolated python installation where you can experiment and install 3rd party libraries without affecting your «main» installation. To do this, open up a Powershell window, and enter the following commands (where «myenv» is the name of the virtualenv we’re going to create, you can use any name you like for this):

PS C:> python -m venv myenv
PS C:> myenvScriptsactivate

Then, let’s install jupyter and start up a notebook:

PS C:> pip install jupyter
PS C:> jupyter notebook

Incidentally, if you get a warning about upgrading pip, make sure to use the following incantation to upgrade (to prevent an issue on windows where pip is unable to upgrade its own executable in-place):

PS C:> python -m pip install --upgrade pip

Advantages: Uses «pure» python, official tools, and no external dependencies. Well supported, with plenty of online documentation and support communities.

Disadvantages: While many popular data analysis or scientific python libraries can be installed by pip on windows (including Pandas and Matplotlib), some (for example SciPy) require a C compiler and the presence of 3rd party C libraries on the system which are difficult to install on Windows.

Who is it for? Python users comfortable with the command line and the tools that ship with Python itself.

The Python Distributions

Because of the difficulty mentioned above in getting packages like SciPy installed on Windows, a few commercial entities have put together pre-packaged Python «distributions» that contain most, if not all, of the commonly used libraries for data analysis and/or scientific computing.

Anaconda is an excellent option for this. Download their Python 3.5 installer for Windows, run it, and in your Start menu you’ll have a bunch of neat new tools, including an entry for Jupyter Notebook. Click to start it up and it’ll launch in the background and open up your browser to the notebook console. It doesn’t get any easier than that.

Advantages: Simplest, fastest way to get started and it comes with probably everything you need for your scientific computing projects. And anything it doesn’t ship with you can still instalAl via its built in conda package manager.

Disadvantages: No virtualenv support, although the conda package manager provides very similar functionality with the conda create command. Relies on a commercial 3rd party for support.

Who is it for? People who want the quickest, easiest way to get Jupyter notebook up and running (IE, most people).

Docker

Docker is a platform for running software in «containers«, or self-contained, isolated processes. While it may sound similar in concept to python virtual environments, Docker containers are an entirely different kind of technology offering vast flexibility and power. Don’t let the flexibility and power and confusing terminology put you off though — Docker can be easy to get up and running on your PC and has some advantages of its own with respect to Python and Jupyter.

To get started on Windows, download the Docker Toolbox, which contains the tools you need to get up and running. Run the installer and make sure the checkbox to install Virtualbox is checked if you don’t already have Virtualbox or another virtualization platform (like VMWare Workstation) installed.

Once installed, you’ll have a «Docker Quickstart Terminal» shortcut in your Start Menu. Double click that shortcut and it will create your first Docker engine for you and set up everything you need automatically. Once you see a prompt in the terminal, you can use the docker run command to run Docker «images», which you can think of as pre-packaged bundles of software that will be automatically downloaded from the Docker Hub when you run them. There are many images on Docker Hub that offer Jupyter, including the official Jupyter Notebook image, and Anaconda itself if you want the full SciPy stack.

To run just the official Jupyter Notebook image in your Docker engine, type the following into the Docker Quickstart Terminal:

$ docker run --rm -it -p 8888:8888 -v "$(pwd):/notebooks" jupyter/notebook

After all the image’s «layers» are downloaded, it will start up. Make a note of the IP address listed in the terminal (for example, 192.168.99.100), and point your browser at that IP address, port 8888 (e.g. http://192.168.99.100:8888) and you’ll see the familiar Jupyter console, with both Python 2 and Python 3 kernels available.

Advantages: Use the flexibility and power of Docker! Honestly one of my favorite things about Docker is thinking of it as an open software distribution platform for things like the SciPy stack that are hard to install.

Disadvantages: Grapple with the flexibility and power of Docker! There are quite a few «gotchas» to be aware of when dealing with Docker, such as immutable containers, data volumes, arcane commands, and rapidly developing, occasionally buggy tooling.