{ "info": { "author": "Shay Palachy", "author_email": "shay.palachy@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Software Development :: Libraries", "Topic :: Software Development :: Libraries :: Python Modules" ], "description": "pdutil\n######\n|PyPI-Status| |PyPI-Versions| |Build-Status| |Codecov| |LICENCE| |Black|\n\nUtilities for pandas.\n\n.. code-block:: python\n\n import pdutil\n for subdf in pdutil.iter.sub_dfs_by_size(df, 2):\n print(subdf)\n\n.. contents::\n\n.. section-numbering::\n\n\nInstallation\n============\n\n.. code-block:: bash\n\n pip install pdutil\n\n\nBasic Use\n=========\n\n``pdutil`` is divided into several sub-modules by functionality:\n\ndisplay\n-------\n\nFunctions related to displaying ``pandas`` DataFrames:\n\n* ``df_string`` - Returns a nicely formatted string for the given dataframe.\n* ``pandas_big_frame_setup`` - Sets pandas to display really big data frames.\n* ``df_to_html`` - Return a nicely formatted HTML code string for the given dataframe.\n\niter\n----\n\nFunctions related to iterating over ``pandas`` dataframes:\n\n* ``sub_dfs_by_size`` - Get a generator yielding consecutive sub-dataframes of the given size.\n* ``sub_dfs_by_num`` - Get a generator yielding num consecutive sub-dataframes of the given df. \n\ntransform\n---------\n\n* ``x_y_by_col_lbl`` - Returns an X dataframe and a y series by the given column name.\n* ``or_by_masks`` - Returns a sub-dataframe by the logical or over the given masks. \n\nserial\n------\n\n* ``SerializationFormat`` - A mutli-singleton representing different serialization formats of dataframes.\n\n\nContributing\n============\n\nPackage author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help. 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