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https://pypi.python.org/pypi/pandas_log\n\n.. image:: https://img.shields.io/travis/eyaltrabelsi/pandas-log.svg\n        :target: https://travis-ci.org/eyaltrabelsi/pandas-log\n\n.. image:: https://readthedocs.org/projects/pandas-log/badge/?version=latest\n        :target: https://pandas-log.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n\n.. image:: https://pyup.io/repos/github/eyaltrabelsi/pandas-log/shield.svg\n     :target: https://pyup.io/repos/github/eyaltrabelsi/pandas-log/\n     :alt: Updates\n\nThe 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.\n\nWhy pandas-log?\n---------------\n``Pandas-log`` is a Python implementation of the R package ``tidylog``, and provides a feedback about basic pandas operations.\n\nThe 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.\nThese 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.\n\n\n\nLets look at an example, first we need to load ``pandas-log`` after ``pandas`` and create a dataframe:\n\n.. code-block:: python\n\n    import pandas\n    import pandas_log\n\n    with pandas_log.enable():\n        df = pd.DataFrame({\"name\": ['Alfred', 'Batman', 'Catwoman'],\n                       \"toy\": [np.nan, 'Batmobile', 'Bullwhip'],\n                       \"born\": [pd.NaT, pd.Timestamp(\"1940-04-25\"), pd.NaT]})\n\n\n``pandas-log`` will give you feedback, for instance when filtering a data frame or adding a new variable:\n\n.. code-block:: python\n\n    df.assign(toy=lambda x: x.toy.map(str.lower))\n      .query(\"name != 'Batman'\")\n\n``pandas-log`` can be especially helpful in longer pipes:\n\n.. code-block:: python\n\n    df.assign(toy=lambda x: x.toy.map(str.lower))\n      .query(\"name != 'Batman'\")\n      .dropna()\\\n      .assign(lower_name=lambda x: x.name.map(str.lower))\n      .reset_index()\n\nFor medium article `go here\n\u003chttps://towardsdatascience.com/introducing-pandas-log-3240a5e57e21\u003e`_\n\nFor a full walkthrough `go here\n\u003chttps://github.com/eyaltrabelsi/pandas-log/blob/master/examples/pandas_log_intro.ipynb\u003e`_\n\n\nInstallation\n------------\n``pandas-log`` is currently installable from PyPI:\n\n.. code-block:: bash\n\n    pip install pandas-log\n\n\nContributing\n------------\nFollow `contribution docs\n\u003chttps://pandas-log.readthedocs.io/en/latest/contributing.html\u003e`_ for a full description of the process of contributing to ``pandas-log``.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feyaltrabelsi%2Fpandas-log","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feyaltrabelsi%2Fpandas-log","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feyaltrabelsi%2Fpandas-log/lists"}