Name: pandas
Owner: Makina Corpus
Description: Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Created: 2014-10-22 10:50:56.0
Updated: 2016-10-12 23:01:51.0
Pushed: 2014-10-22 10:52:53.0
Homepage: http://pandas.pydata.org
Size: 40032
Language: null
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pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal.
Here are just a few of the things that pandas does well:
NaN
) in floating point as well as non-floating point dataSeries
, DataFrame
, etc. automatically
align the data for you in computationsThe source code is currently hosted on GitHub at: http://github.com/pydata/pandas
Binary installers for the latest released version are available at the Python package index
http://pypi.python.org/pypi/pandas/
And via easy_install
:
_install pandas
or pip
:
install pandas
pandas.date_range
pandas.stats
pandas.io.gbq
pandas.read_html
function:If you install BeautifulSoup4 you must install
either lxml or html5lib or both.
pandas.read_html
will not work with only BeautifulSoup4
installed.
You are strongly 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:
Additionally, if you're using Anaconda you should definitely read the gotchas about HTML parsing libraries
If you're on a system with apt-get
you can do
apt-get build-dep python-lxml
to get the necessary dependencies for installation of lxml. This will prevent further headaches down the line.
To install pandas from source you need Cython in addition to the normal dependencies above. Cython can be installed from pypi:
install cython
In the pandas
directory (same one where you found this file after
cloning the git repo), execute:
on setup.py install
or for installing in development mode:
on setup.py develop
Alternatively, you can use pip
if you want all the dependencies pulled
in automatically (the -e
option is for installing it in development mode):
install -e .
On Windows, you will need to install MinGW and execute:
on setup.py build --compiler=mingw32
on setup.py install
See http://pandas.pydata.org/ for more information.
BSD
The official documentation is hosted on PyData.org: http://pandas.pydata.org/
The Sphinx documentation should provide a good starting point for learning how to use the library. Expect the docs to continue to expand as time goes on.
Work on pandas
started at AQR (a quantitative hedge fund) in 2008 and
has been under active development since then.
Since pandas development is related to a number of other scientific Python projects, questions are welcome on the scipy-user mailing list. Specialized discussions or design issues should take place on the PyData mailing list / Google group:
https://groups.google.com/forum/#!forum/pydata