How to install pandas on linux

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 3.9, 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 using your Linux distribution’s package manager.#

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

Download / Repository Link

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

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.

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

Источник