Metadata-Version: 2.1
Name: pandas-log
Version: 0.1.2
Summary: pandas-log provides feedback about basic pandas operations. It provides simple wrapper functions for the most common functions, such as apply, map, query and more.
Home-page: https://github.com/eyaltrabelsi/pandas-log
Author: Eyal Trabelsi
Author-email: eyaltrabelsi@gmail.com
License: MIT license
Description: ==========
        pandas-log
        ==========
        
        
        .. image:: https://img.shields.io/pypi/v/pandas_log.svg
                :target: https://pypi.python.org/pypi/pandas_log
        
        .. image:: https://img.shields.io/travis/eyaltrabelsi/pandas-log.svg
                :target: https://travis-ci.org/eyaltrabelsi/pandas-log
        
        .. image:: https://readthedocs.org/projects/pandas-log/badge/?version=latest
                :target: https://pandas-log.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        .. image:: https://pyup.io/repos/github/eyaltrabelsi/pandas-log/shield.svg
             :target: https://pyup.io/repos/github/eyaltrabelsi/pandas-log/
             :alt: Updates
        
        The goal of pandas-log is to provide feedback about basic pandas operations. It provides simple wrapper functions for the most common functions, such as ``.query``, ``.apply``, ``.merge``, ``.group_by`` and more.
        
        Why pandas-log?
        ---------------
        ``Pandas-log`` is a Python implementation of the R package ``tidylog``, and provides a feedback about basic pandas operations.
        
        The pandas has been invaluable for the data science ecosystem and usually consists of a series of steps that involve transforming raw data into an understandable/usable format.
        These series of steps need to be run in a certain sequence and if the result is unexpected it's hard to understand what happened. ``Pandas-log`` log metadata on each operation which will allow to pinpoint the issues.
        
        
        
        Lets look at an example, first we need to load ``pandas-log`` after ``pandas`` and create a dataframe:
        
        .. code-block:: python
        
            import pandas
            import pandas_logs
        
            with pandas_logs.enable():
                df = pd.DataFrame({"name": ['Alfred', 'Batman', 'Catwoman'],
                               "toy": [np.nan, 'Batmobile', 'Bullwhip'],
                               "born": [pd.NaT, pd.Timestamp("1940-04-25"), pd.NaT]})
        
        
        ``pandas-log`` will give you feedback, for instance when filtering a data frame or adding a new variable:
        
        .. code-block:: python
        
            df.assign(toy=lambda x: x.toy.map(str.lower))
              .query("name != 'Batman'")
        
        ``pandas-log`` can be especially helpful in longer pipes:
        
        .. code-block:: python
        
            df.assign(toy=lambda x: x.toy.map(str.lower))
              .query("name != 'Batman'")
              .dropna()\
              .assign(lower_name=lambda x: x.name.map(str.lower))
              .reset_index()
        
        For a full walkthrough `go here
        <https://github.com/eyaltrabelsi/pandas-log/blob/master/examples/pandas_log_intro.ipynb>`_
        
        
        Installation
        ------------
        ``pandas-log`` is currently installable from PyPI:
        
        .. code-block:: bash
        
            pip install pandas-log
        
        
        Contributing
        ------------
        Follow `contribution docs
        <https://pandas-log.readthedocs.io/en/latest/contributing.html>`_ for a full description of the process of contributing to ``pandas-log``.
        
Platform: UNKNOWN
Requires-Python: >=3.4
Description-Content-Type: text/x-rst
