monthly-returns-heatmap

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>__

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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

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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
• compounded - set to False if the you don't want the calculation to use compounded returns
• 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
• compounded - set to False if the you don't want the calculation to use compounded returns
• 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