========== 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_log with pandas_log.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 medium article `go here `_ For a full walkthrough `go here `_ Installation ------------ ``pandas-log`` is currently installable from PyPI: .. code-block:: bash pip install pandas-log Contributing ------------ Follow `contribution docs `_ for a full description of the process of contributing to ``pandas-log``.