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Installation
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============
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- The easiest way for the majority of users to install pandas is to install it
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+ The easiest way to install pandas is to install it
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as part of the `Anaconda <http://docs.continuum.io/anaconda/ >`__ distribution, a
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cross platform distribution for data analysis and scientific computing.
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This is the recommended installation method for most users.
@@ -40,7 +40,7 @@ packages that make up the `SciPy <http://www.scipy.org/>`__ stack
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(Linux, Mac OS X, Windows) Python distribution for data analytics and
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scientific computing.
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- After running a simple installer, the user will have access to pandas and the
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+ After running the installer, the user will have access to pandas and the
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rest of the `SciPy <http://www.scipy.org/ >`__ stack without needing to install
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anything else, and without needing to wait for any software to be compiled.
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@@ -51,9 +51,9 @@ A full list of the packages available as part of the
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`Anaconda <http://docs.continuum.io/anaconda/ >`__ distribution
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`can be found here <http://docs.continuum.io/anaconda/pkg-docs.html >`__.
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- An additional advantage of installing with Anaconda is that you don't require
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- admin rights to install it, it will install in the user's home directory, and
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- this also makes it trivial to delete Anaconda at a later date (just delete
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+ Another advantage to installing Anaconda is that you don't need
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+ admin rights to install it. Anaconda can install in the user's home directory,
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+ which makes it trivial to delete Anaconda if you decide (just delete
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that folder).
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.. _install.miniconda :
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will do this for you. The installer
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`can be found here <http://conda.pydata.org/miniconda.html >`__
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- The next step is to create a new conda environment (these are analogous to a
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- virtualenv but they also allow you to specify precisely which Python version
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- to install also). Run the following commands from a terminal window::
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+ The next step is to create a new conda environment. A conda environment is like a
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+ virtualenv that allows you to specify a specific version of Python and set of libraries.
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+ Run the following commands from a terminal window::
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conda create -n name_of_my_env python
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@@ -118,8 +118,8 @@ distribution::
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conda install anaconda
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- If you require any packages that are available to pip but not conda, simply
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- install pip, and use pip to install these packages::
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+ If you need packages that are available to pip but not conda, then
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+ install pip, and then use pip to install those packages::
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conda install pip
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pip install django
@@ -134,15 +134,12 @@ pandas can be installed via pip from
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pip install pandas
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- This will likely require the installation of a number of dependencies,
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- including NumPy, will require a compiler to compile required bits of code,
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- and can take a few minutes to complete.
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Installing using your Linux distribution's package manager.
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The commands in this table will install pandas for Python 3 from your distribution.
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- To install pandas for Python 2 you may need to use the package ``python-pandas ``.
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+ To install pandas for Python 2, you may need to use the ``python-pandas `` package .
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.. csv-table ::
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:header: "Distribution", "Status", "Download / Repository Link", "Install method"
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Running the test suite
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~~~~~~~~~~~~~~~~~~~~~~
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- pandas is equipped with an exhaustive set of unit tests covering about 97% of
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+ pandas is equipped with an exhaustive set of unit tests, covering about 97% of
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the codebase as of this writing. To run it on your machine to verify that
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- everything is working (and you have all of the dependencies, soft and hard,
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+ everything is working (and that you have all of the dependencies, soft and hard,
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installed), make sure you have `pytest
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<http://doc.pytest.org/en/latest/> `__ and run:
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@@ -214,8 +211,8 @@ Recommended Dependencies
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.. note ::
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- You are highly encouraged to install these libraries, as they provide large speedups , especially
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- if working with large data sets.
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+ You are highly encouraged to install these libraries, as they provide speed improvements , especially
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+ when working with large data sets.
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.. _install.optional_dependencies :
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