Pandas python install windows

How to Install Python and Pandas on Windows

In this tutorial, we’ll learn how to install Pandas and Python on Windows. We will cover the most popular ways of installation.

The instructions described below have been tested on Windows 7 and 20.

2. Install Python on Windows 10

Python is a widely-used easy to learn, user friendly, concise and high-level programming language. It is very easy to start coding on it and has a huge community.

Python is one of the most liked and wanted languages according to: stackoverflow — Python is the most wanted language for its fifth-year

2.1. Download and Install Python on Windows

Unlike Linux, Windows doesn’t come with a pre-installed Python version.

So if we want to use the latest version of Python then manual installation is the way to go. The steps to install Python on Windows are:

1. Go to Python Releases for Windows
2. Select the Python version you like — I prefer to go with the Stable Releases. For example — Python 3.9.10 — Jan. 14, 2022
3. Select the type of the installation — I prefer Download Windows installer (64-bit) — python-3.9.10-amd64.exe
4. Download the desired version
5. Run the Python Installer
6. During installation
   6.1. Select Install launcher for all users — if you like to have it for all users
   6.2. Check Add Python 3.9 to PATH in order Python to be visible for other programs
7. Press Install Now
8. Finally you can verify the installation by checking the version — Python -V — expected output — Python 3.9.10

2.2. Create a virtual environment (optional)

Python offers a powerful package system venv which helps separate different Python packages. In simple words, you can create several virtual environments in multiple Pandas versions:

To create new virtual environment called pandas1 :

• create folder for your virtual environments ( or select existing one)
• Run command: python -m venv pandas1
• activate the environment by:

cd pandas1 source bin/activate 

Once environment is activated you will see change in the terminal:

The command above deactivates the environment.

To learn more please check:

2.3. Install PIP (optional)

PIP is one of the most popular package managers for Python. If it’s not installed:

will return message that the command is not recognized — then you can install it by:

To learn more please check:

3. Install Pandas on Windows

3.1. Install Pandas by Pypi

Next step is to install Pandas on Windows. The most easiest way of installing Pandas is by running:

You can find more information for Pandas on: pandas — pypi.org.

3.2. Install Anaconda and Pandas on Windows

If you like to use alternative installation methods you can check the official docs: Installing Anaconda on Windows.

For example Pandas is part of Anaconda — so if you install Anaconda on your system you will get Pandas:

• download the Anaconda installer for Windows
• Verify data integrity with SHA-256. (optional but highly RECOMMENDED step)
• Install Anaconda by double click on the installer
• Press Next
• «I Agree» on — licensing terms
• Select «Just Me» — if you are going to use it for yourself only
• Select a destination folder
• Click the Next button
• Add «Anaconda to your PATH environment variable» — highly recommended
• Continue the rest depending on your personal preferences or refer to the official installation guide

3.3. Verify Pandas installation

Finally you can test Pandas installation by running next commands:

4. Conclusion

To summarize, in this article, we’ve seen examples of installing Python and Pandas on Windows in several ways. We’ve briefly explained these installation methods and how to verify the installation.

And finally, we’ve seen how to manage multiple Python/Pandas installations on Windows like systems with different package versions.

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Installation#

The easiest way to install pandas is to install it as part of the Anaconda distribution, a cross platform distribution for data analysis and scientific computing. The Conda package manager is the recommended installation method for most users.

Instructions for installing from source , PyPI , or a development version are also provided.

Python version support#

Officially Python 3.9, 3.10 and 3.11.

Installing pandas#

Installing with Anaconda#

For users that are new to Python, the easiest way to install Python, pandas, and the packages that make up the PyData stack (SciPy, NumPy, Matplotlib, and more) is with Anaconda, a cross-platform (Linux, macOS, Windows) Python distribution for data analytics and scientific computing. Installation instructions for Anaconda can be found here.

Installing with Miniconda#

For users experienced with Python, the recommended way to install pandas with Miniconda. Miniconda allows you to create a minimal, self-contained Python installation compared to Anaconda and use the Conda package manager to install additional packages and create a virtual environment for your installation. Installation instructions for Miniconda can be found here.

The next step is to create a new conda environment. A conda environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window.

conda create -c conda-forge -n name_of_my_env python pandas

This will create a minimal environment with only Python and pandas installed. To put your self inside this environment run.

source activate name_of_my_env # On Windows activate name_of_my_env

Installing from PyPI#

pandas can be installed via pip from PyPI.

You must have pip>=19.3 to install from PyPI.

It is recommended to install and run pandas from a virtual environment, for example, using the Python standard library’s venv

pandas can also be installed with sets of optional dependencies to enable certain functionality. For example, to install pandas with the optional dependencies to read Excel files.

The full list of extras that can be installed can be found in the dependency section.

Handling ImportErrors#

If you encounter an ImportError , it usually means that Python couldn’t find pandas in the list of available libraries. Python internally has a list of directories it searches through, to find packages. You can obtain these directories with.

One way you could be encountering this error is if you have multiple Python installations on your system and you don’t have pandas installed in the Python installation you’re currently using. In Linux/Mac you can run which python on your terminal and it will tell you which Python installation you’re using. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended.

It is highly recommended to use conda , for quick installation and for package and dependency updates. You can find simple installation instructions for pandas in this document .

Installing from source#

See the contributing guide for complete instructions on building from the git source tree. Further, see creating a development environment if you wish to create a pandas development environment.

Installing the development version of pandas#

Installing the development version is the quickest way to:

• Try a new feature that will be shipped in the next release (that is, a feature from a pull-request that was recently merged to the main branch).
• Check whether a bug you encountered has been fixed since the last release.

The development version is usually uploaded daily to the scientific-python-nightly-wheels index from the PyPI registry of anaconda.org. You can install it by running.

pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas

Note that you might be required to uninstall an existing version of pandas to install the development version.

Running the test suite#

pandas is equipped with an exhaustive set of unit tests. The packages required to run the tests can be installed with pip install «pandas[test]» . To run the tests from a Python terminal.

>>> import pandas as pd >>> pd.test() running: pytest -m "not slow and not network and not db" /home/user/anaconda3/lib/python3.9/site-packages/pandas ============================= test session starts ============================== platform linux -- Python 3.9.7, pytest-6.2.5, py-1.11.0, pluggy-1.0.0 rootdir: /home/user plugins: dash-1.19.0, anyio-3.5.0, hypothesis-6.29.3 collected 154975 items / 4 skipped / 154971 selected . [ 0%] . [ 99%] . [100%] ==================================== ERRORS ==================================== =================================== FAILURES =================================== =============================== warnings summary =============================== =========================== short test summary info ============================ = 1 failed, 146194 passed, 7402 skipped, 1367 xfailed, 5 xpassed, 197 warnings, 10 errors in 1090.16s (0:18:10) = 

This is just an example of what information is shown. Test failures are not necessarily indicative of a broken pandas installation.

Dependencies#

Required dependencies#

pandas requires the following dependencies.

Minimum supported version

Источник

Installation#

The easiest way to install pandas is to install it as part of the Anaconda distribution, a cross platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.

Instructions for installing from source, PyPI, ActivePython, various Linux distributions, or a development version are also provided.

Python version support#

Officially Python 3.8, 3.9, 3.10 and 3.11.

Installing pandas#

Installing with Anaconda#

Installing pandas and the rest of the NumPy and SciPy stack can be a little difficult for inexperienced users.

The simplest way to install not only pandas, but Python and the most popular packages that make up the SciPy stack (IPython, NumPy, Matplotlib, …) is with Anaconda, a cross-platform (Linux, macOS, Windows) Python distribution for data analytics and scientific computing.

After running the installer, the user will have access to pandas and the rest of the SciPy stack without needing to install anything else, and without needing to wait for any software to be compiled.

Installation instructions for Anaconda can be found here.

A full list of the packages available as part of the Anaconda distribution can be found here.

Another advantage to installing Anaconda is that you don’t need admin rights to install it. Anaconda can install in the user’s home directory, which makes it trivial to delete Anaconda if you decide (just delete that folder).

Installing with Miniconda#

The previous section outlined how to get pandas installed as part of the Anaconda distribution. However this approach means you will install well over one hundred packages and involves downloading the installer which is a few hundred megabytes in size.

If you want to have more control on which packages, or have a limited internet bandwidth, then installing pandas with Miniconda may be a better solution.

Conda is the package manager that the Anaconda distribution is built upon. It is a package manager that is both cross-platform and language agnostic (it can play a similar role to a pip and virtualenv combination).

Miniconda allows you to create a minimal self contained Python installation, and then use the Conda command to install additional packages.

First you will need Conda to be installed and downloading and running the Miniconda will do this for you. The installer can be found here

The next step is to create a new conda environment. A conda environment is like a virtualenv that allows you to specify a specific version of Python and set of libraries. Run the following commands from a terminal window:

conda create -n name_of_my_env python 

This will create a minimal environment with only Python installed in it. To put your self inside this environment run:

source activate name_of_my_env 

On Windows the command is:

The final step required is to install pandas. This can be done with the following command:

To install a specific pandas version:

To install other packages, IPython for example:

To install the full Anaconda distribution:

If you need packages that are available to pip but not conda, then install pip, and then use pip to install those packages:

conda install pip pip install django 

Installing from PyPI#

pandas can be installed via pip from PyPI.

You must have pip>=19.3 to install from PyPI.

pandas can also be installed with sets of optional dependencies to enable certain functionality. For example, to install pandas with the optional dependencies to read Excel files.

The full list of extras that can be installed can be found in the dependency section.

Installing with ActivePython#

Installation instructions for ActivePython can be found here. Versions 2.7, 3.5 and 3.6 include pandas.

Installing using your Linux distribution’s package manager.#

The commands in this table will install pandas for Python 3 from your distribution.

Download / Repository Link

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