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DOC: Link to new PyPI instead legacy PyPI (#20872)
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README.md

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<tr>
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<td>Latest Release</td>
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<td>
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<a href="https://pypi.python.org/pypi/pandas/">
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<a href="https://pypi.org/project/pandas/">
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<img src="https://img.shields.io/pypi/v/pandas.svg" alt="latest release" />
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</a>
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</td>
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<tr>
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<td>Package Status</td>
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<td>
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<a href="https://pypi.python.org/pypi/pandas/">
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<a href="https://pypi.org/project/pandas/">
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<img src="https://img.shields.io/pypi/status/pandas.svg" alt="status" /></td>
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</a>
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</tr>
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https://github.com/pandas-dev/pandas
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Binary installers for the latest released version are available at the [Python
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package index](https://pypi.python.org/pypi/pandas) and on conda.
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package index](https://pypi.org/project/pandas) and on conda.
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```sh
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# conda

doc/source/contributing.rst

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- every header file must include a header guard to avoid name collisions if re-included
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:ref:`Continuous Integration <contributing.ci>` will run the
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`cpplint <https://pypi.python.org/pypi/cpplint>`_ tool
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`cpplint <https://pypi.org/project/cpplint>`_ tool
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and report any stylistic errors in your code. Therefore, it is helpful before
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submitting code to run the check yourself::
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- passing arguments should have spaces after commas, e.g. ``foo(arg1, arg2, kw1='bar')``
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:ref:`Continuous Integration <contributing.ci>` will run
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the `flake8 <http://pypi.python.org/pypi/flake8>`_ tool
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the `flake8 <https://pypi.org/project/flake8>`_ tool
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and report any stylistic errors in your code. Therefore, it is helpful before
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submitting code to run the check yourself on the diff::
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pytest pandas/tests/[test-module].py::[TestClass]
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pytest pandas/tests/[test-module].py::[TestClass]::[test_method]
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Using `pytest-xdist <https://pypi.python.org/pypi/pytest-xdist>`_, one can
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Using `pytest-xdist <https://pypi.org/project/pytest-xdist>`_, one can
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speed up local testing on multicore machines. To use this feature, you will
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need to install `pytest-xdist` via::
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doc/source/index.rst.template

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**Date**: |today| **Version**: |version|
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**Binary Installers:** http://pypi.python.org/pypi/pandas
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**Binary Installers:** https://pypi.org/project/pandas
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**Source Repository:** http://github.com/pandas-dev/pandas
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doc/source/install.rst

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This is the recommended installation method for most users.
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Instructions for installing from source,
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`PyPI <http://pypi.python.org/pypi/pandas>`__, `ActivePython <https://www.activestate.com/activepython/downloads>`__, various Linux distributions, or a
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`PyPI <https://pypi.org/project/pandas>`__, `ActivePython <https://www.activestate.com/activepython/downloads>`__, various Linux distributions, or a
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`development version <http://github.com/pandas-dev/pandas>`__ are also provided.
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.. _install.dropping-27:
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~~~~~~~~~~~~~~~~~~~~
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pandas can be installed via pip from
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`PyPI <http://pypi.python.org/pypi/pandas>`__.
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`PyPI <https://pypi.org/project/pandas>`__.
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::
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* `xarray <http://xarray.pydata.org>`__: pandas like handling for > 2 dims, needed for converting Panels to xarray objects. Version 0.7.0 or higher is recommended.
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* `PyTables <http://www.pytables.org>`__: necessary for HDF5-based storage. Version 3.0.0 or higher required, Version 3.2.1 or higher highly recommended.
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* `Feather Format <https://github.com/wesm/feather>`__: necessary for feather-based storage, version 0.3.1 or higher.
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* `Apache Parquet <https://parquet.apache.org/>`__, either `pyarrow <http://arrow.apache.org/docs/python/>`__ (>= 0.4.1) or `fastparquet <https://fastparquet.readthedocs.io/en/latest>`__ (>= 0.0.6) for parquet-based storage. The `snappy <https://pypi.python.org/pypi/python-snappy>`__ and `brotli <https://pypi.python.org/pypi/brotlipy>`__ are available for compression support.
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* `Apache Parquet <https://parquet.apache.org/>`__, either `pyarrow <http://arrow.apache.org/docs/python/>`__ (>= 0.4.1) or `fastparquet <https://fastparquet.readthedocs.io/en/latest>`__ (>= 0.0.6) for parquet-based storage. The `snappy <https://pypi.org/project/python-snappy>`__ and `brotli <https://pypi.org/project/brotlipy>`__ are available for compression support.
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* `SQLAlchemy <http://www.sqlalchemy.org>`__: for SQL database support. Version 0.8.1 or higher recommended. Besides SQLAlchemy, you also need a database specific driver. You can find an overview of supported drivers for each SQL dialect in the `SQLAlchemy docs <http://docs.sqlalchemy.org/en/latest/dialects/index.html>`__. Some common drivers are:
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* `psycopg2 <http://initd.org/psycopg/>`__: for PostgreSQL
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* `xlrd/xlwt <http://www.python-excel.org/>`__: Excel reading (xlrd) and writing (xlwt)
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* `openpyxl <http://https://openpyxl.readthedocs.io/en/default/>`__: openpyxl version 2.4.0
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for writing .xlsx files (xlrd >= 0.9.0)
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* `XlsxWriter <https://pypi.python.org/pypi/XlsxWriter>`__: Alternative Excel writer
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* `XlsxWriter <https://pypi.org/project/XlsxWriter>`__: Alternative Excel writer
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* `Jinja2 <http://jinja.pocoo.org/>`__: Template engine for conditional HTML formatting.
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* `s3fs <http://s3fs.readthedocs.io/>`__: necessary for Amazon S3 access (s3fs >= 0.0.7).
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* `blosc <https://pypi.python.org/pypi/blosc>`__: for msgpack compression using ``blosc``
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* `blosc <https://pypi.org/project/blosc>`__: for msgpack compression using ``blosc``
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* One of
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`qtpy <https://github.com/spyder-ide/qtpy>`__ (requires PyQt or PySide),
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`PyQt5 <https://www.riverbankcomputing.com/software/pyqt/download5>`__,
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* `pandas-gbq <https://pandas-gbq.readthedocs.io/en/latest/install.html#dependencies>`__: for Google BigQuery I/O.
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* `Backports.lzma <https://pypi.python.org/pypi/backports.lzma/>`__: Only for Python 2, for writing to and/or reading from an xz compressed DataFrame in CSV; Python 3 support is built into the standard library.
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* `Backports.lzma <https://pypi.org/project/backports.lzma/>`__: Only for Python 2, for writing to and/or reading from an xz compressed DataFrame in CSV; Python 3 support is built into the standard library.
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* One of the following combinations of libraries is needed to use the
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top-level :func:`~pandas.read_html` function:
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doc/source/release.rst

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**Where to get it**
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* Source code: http://github.com/pandas-dev/pandas
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* Binary installers on PyPI: http://pypi.python.org/pypi/pandas
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* Binary installers on PyPI: https://pypi.org/project/pandas
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* Documentation: http://pandas.pydata.org
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pandas 0.22.0

pandas/core/frame.py

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Notes
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-----
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This function requires either the `fastparquet
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<https://pypi.python.org/pypi/fastparquet>`_ or `pyarrow
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<https://pypi.org/project/fastparquet>`_ or `pyarrow
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<https://arrow.apache.org/docs/python/>`_ library.
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Examples

pandas/io/clipboard/__init__.py

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try:
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# qtpy is a small abstraction layer that lets you write
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# applications using a single api call to either PyQt or PySide
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# https://pypi.python.org/pypi/QtPy
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# https://pypi.org/project/QtPy
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import qtpy # noqa
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except ImportError:
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# If qtpy isn't installed, fall back on importing PyQt5, or PyQt5

versioneer.py

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* Compatible With: python2.6, 2.7, 3.2, 3.3, 3.4, and pypy
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* [![Latest Version]
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(https://pypip.in/version/versioneer/badge.svg?style=flat)
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](https://pypi.python.org/pypi/versioneer/)
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](https://pypi.org/project/versioneer/)
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* [![Build Status]
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(https://travis-ci.org/warner/python-versioneer.png?branch=master)
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](https://travis-ci.org/warner/python-versioneer)

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