Installation¶
You have the option to install an official release or to build the development version. If you choose to install from source and are running Windows, you will have to ensure that you have a compatible C compiler (MinGW or Visual Studio) installed. How-to install MinGW on Windows
Python version support¶
Officially Python 2.6, 2.7, 3.2, 3.3, and 3.4.
Binary installers¶
All platforms¶
Stable installers available on PyPI
Preliminary builds and installers on the pandas download page .
Overview¶
| Platform | Distribution | Status | Download / Repository Link | Install method |
|---|---|---|---|---|
| Windows | all | stable | All platforms | pip install pandas |
| Mac | all | stable | All platforms | pip install pandas |
| Linux | Debian | stable | official Debian repository | sudo apt-get install python-pandas |
| Linux | Debian & Ubuntu | unstable (latest packages) | NeuroDebian | sudo apt-get install python-pandas |
| Linux | Ubuntu | stable | official Ubuntu repository | sudo apt-get install python-pandas |
| Linux | Ubuntu | unstable (daily builds) | PythonXY PPA; activate by: sudo add-apt-repository ppa:pythonxy/pythonxy-devel && sudo apt-get update | sudo apt-get install python-pandas |
| Linux | OpenSuse & Fedora | stable | OpenSuse Repository | zypper in python-pandas |
Dependencies¶
NumPy: 1.6.1 or higher
python-dateutil 1.5
- pytz
- Needed for time zone support
Recommended Dependencies¶
- numexpr: for accelerating certain numerical operations. numexpr uses multiple cores as well as smart chunking and caching to achieve large speedups.
- bottleneck: for accelerating certain types of nan evaluations. bottleneck uses specialized cython routines to achieve large speedups.
Note
You are highly encouraged to install these libraries, as they provide large speedups, especially if working with large data sets.
Optional Dependencies¶
Cython: Only necessary to build development version. Version 0.17.1 or higher.
SciPy: miscellaneous statistical functions
PyTables: necessary for HDF5-based storage
SQLAlchemy: for SQL database support. Version 0.8.1 or higher recommended.
matplotlib: for plotting
- statsmodels
- Needed for parts of pandas.stats
- XlsxWriter
- Alternative Excel writer.
boto: necessary for Amazon S3 access.
One of PyQt4, PySide, pygtk, xsel, or xclip: necessary to use read_clipboard(). Most package managers on Linux distributions will have xclip and/or xsel immediately available for installation.
Google’s python-gflags and google-api-python-client * Needed for gbq
httplib2 * Needed for gbq
One of the following combinations of libraries is needed to use the top-level read_html() function:
- BeautifulSoup4 and html5lib (Any recent version of html5lib is okay.)
- BeautifulSoup4 and lxml
- BeautifulSoup4 and html5lib and lxml
- Only lxml, although see HTML reading gotchas for reasons as to why you should probably not take this approach.
Warning
if you install BeautifulSoup4 you must install either lxml or html5lib or both. read_html() will not work with only BeautifulSoup4 installed.
You are highly encouraged to read HTML reading gotchas. It explains issues surrounding the installation and usage of the above three libraries
- You may need to install an older version of BeautifulSoup4:
- Versions 4.2.1, 4.1.3 and 4.0.2 have been confirmed for 64 and 32-bit Ubuntu/Debian
Additionally, if you’re using Anaconda you should definitely read the gotchas about HTML parsing libraries
Note
if you’re on a system with apt-get you can do
sudo apt-get build-dep python-lxmlto get the necessary dependencies for installation of lxml. This will prevent further headaches down the line.
Note
Without the optional dependencies, many useful features will not work. Hence, it is highly recommended that you install these. A packaged distribution like Enthought Canopy may be worth considering.
Installing from source¶
Note
Installing from the git repository requires a recent installation of Cython as the cythonized C sources are no longer checked into source control. Released source distributions will contain the built C files. I recommend installing the latest Cython via easy_install -U Cython
The source code is hosted at http://github.com/pydata/pandas, it can be checked out using git and compiled / installed like so:
git clone git://github.com/pydata/pandas.git
cd pandas
python setup.py install
Make sure you have Cython installed when installing from the repository, rather then a tarball or pypi.
On Windows, I suggest installing the MinGW compiler suite following the directions linked to above. Once configured property, run the following on the command line:
python setup.py build --compiler=mingw32
python setup.py install
Note that you will not be able to import pandas if you open an interpreter in the source directory unless you build the C extensions in place:
python setup.py build_ext --inplace
The most recent version of MinGW (any installer dated after 2011-08-03) has removed the ‘-mno-cygwin’ option but Distutils has not yet been updated to reflect that. Thus, you may run into an error like “unrecognized command line option ‘-mno-cygwin’”. Until the bug is fixed in Distutils, you may need to install a slightly older version of MinGW (2011-08-02 installer).
Running the test suite¶
pandas is equipped with an exhaustive set of unit tests covering about 97% of the codebase as of this writing. To run it on your machine to verify that everything is working (and you have all of the dependencies, soft and hard, installed), make sure you have nose and run:
$ nosetests pandas
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Ran 818 tests in 21.631s
OK (SKIP=2)