Metadata-Version: 1.1
Name: monthly-returns-heatmap
Version: 0.0.7
Summary: Utility to create a monthly returns heatmap from Pandas series
Home-page: https://github.com/ranaroussi/monthly-returns-heatmap
Author: Ran Aroussi
Author-email: ran@aroussi.com
License: LGPL
Description-Content-Type: UNKNOWN
Description: Python Monthly Returns Heatmap
        ==============================
        
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        \
        
        **monthly-returns-heatmap** is a simple Python library for creating
        Monthly Returns Heatmap from Pandas series with ease.
        
        `Changelog » <./CHANGELOG.rst>`__
        
        -----
        
        Quick Start
        -----------
        
        Let's create a returns heatmap for `SPY <https://finance.yahoo.com/quote/SPY>`_
        (S&P 500 Spider ETF).
        
        First, let's download SPY's daily close prices from Google finance.
        
        .. code:: python
        
            from pandas_datareader import data
            prices = data.get_data_google("SPY")['Close']
            returns = prices.pct_change()
        
        Next, we'll import ``monthly_returns_heatmap`` and plot the monthly return heatmap:
        
        .. code:: python
        
            import monthly_returns_heatmap as mrh
        
            returns.plot_monthly_returns_heatmap()
            # mrh.plot(returns) # <== or using direct call
        
        
        .. image:: https://raw.githubusercontent.com/ranaroussi/monthly-returns-heatmap/master/demo.png?
            :width: 720
            :height: 318
            :alt: demo
        
        
        **Getting heatmap data only (no plotting)**
        
        .. code:: python
        
            heatmap = prices.get_monthly_returns_heatmap()
            # heatmap = mrh.get(returns) # <== or using direct call
        
            print(heatmap)
        
            # prints:
        
            Month       Jan        Feb        Mar        Apr  ...        Dec
            Year
            2010   0.000000   0.031195   0.056529   0.015470  ...   0.061271
            2011   0.023300   0.034737  -0.004807   0.030413  ...   0.003117
            2012   0.045498   0.043137   0.028129  -0.006751  ...   0.001759
            2013   0.051190   0.012759   0.033375   0.019212  ...   0.020387
            2014  -0.035248   0.045516   0.003865   0.006951  ...  -0.008012
            2015  -0.029629   0.056205  -0.020080   0.009834  ...  -0.023096
            2016  -0.049787  -0.001910   0.062943   0.003941  ...   0.014293
            2017   0.017895   0.039292  -0.003087   0.009926  ...   0.000000
        
        
        Get Parameters (optional)
        --------------------------
        - ``is_prices`` - set to ``True`` if the data used is price data instead of returns data
        - ``eoy`` - set to ``True`` to add a **End Of Year** column with total yearly returns
        
        Plot Parameters (optional)
        --------------------------
        - ``title`` - Heatmap title (defaults to ``"Monthly Returns (%)"``)
        - ``title_color`` - Heatmap title color (defaults to ``"black"``)
        - ``title_size`` - Heatmap title font size (defaults to ``12``)
        - ``annot_size`` - Returns boxes font size (defaults to ``10``)
        - ``figsize`` - Heatmap figure size (defaults to ``None``)
        - ``cmap`` - Color map (defaults to ``"RdYlGn"``)
        - ``cbar`` - Show color bar? (defaults to ``True``)
        - ``square`` - Force squere returns boxes? (defaults to ``False``)
        - ``is_prices`` - set to ``True`` if the data used is price data instead of returns data
        - ``eoy`` - set to ``True`` to add a **End Of Year** column with total yearly returns
        
        Installation
        ------------
        
        Install ``monthly_returns_heatmap`` using ``pip``:
        
        .. code:: bash
        
            $ pip install monthly_returns_heatmap --upgrade --no-cache-dir
        
        Requirements
        ------------
        
        * `Python <https://www.python.org>`_ >=3.4
        * `Pandas <https://github.com/pydata/pandas>`_ (tested to work with >=0.18.1)
        * `Matplotlib <https://matplotlib.org>`_ (tested to work with >=1.5.3)
        * `Seaborn <https://seaborn.pydata.org/>`_ (tested to work with >=0.7)
        
        
        Legal Stuff
        ------------
        
        **monthly-returns-heatmap** is distributed under the **GNU Lesser General Public License v3.0**. See the `LICENSE.txt <./LICENSE.txt>`_ file in the release for details.
        
        
        P.S.
        ------------
        
        Please drop me an note with any feedback you have.
        
        **Ran Aroussi**
        
Keywords: plot,heatmap,returns grid
Platform: any
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Development Status :: 5 - Production/Stable
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Topic :: Scientific/Engineering :: Interface Engine/Protocol Translator
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
