Python/Pandas - Sum dataframe items if indexes have the same month
<p>I have this two DataFrames:</p>

<h1>Seasonal_Component:</h1>

<pre><code># DataFrame that has the seasonal component of a time series

Date
2014-12   -1.08
2015-01   -0.28
2015-02    0.15
2015-03    0.46
2015-04    0.48
2015-05    0.37
2015-06    0.20
2015-07    0.15
2015-08    0.12
2015-09   -0.02
2015-10   -0.17
2015-11   -0.39
</code></pre>

<h1>Prediction_df:</h1>

<pre><code># DataFrame with the prediction of the trend of that same time series
            Prediction  MAPE  Score
2015-11-01        7.93  1.83      1
2015-12-01        7.93  1.67      1
2016-01-01        7.92  1.71      1
2016-02-01        7.95  1.84      1
2016-03-01        7.94  1.53      1
2016-04-01        7.87  1.45      1
2016-05-01        7.91  1.53      1
2016-06-01        7.87  1.40      1
2016-07-01        7.84  1.40      1
2016-08-01        7.89  1.77      1
2016-09-01        7.87  1.99      1
</code></pre>

<p>What I need to do:
Check which Prediction_df index have the same months as the Seasonal_Component index and sum the correspondent seasonal component with the prediction, so the Prediction_df looks like this:</p>

<pre><code>            Prediction  MAPE  Score
2015-11-01        7,54  1.83      1
2015-12-01        6.85  1.67      1
2016-01-01        7.64  1.71      1
2016-02-01        8.10  1.84      1
2016-03-01        8.40  1.53      1
2016-04-01        8.35  1.45      1
2016-05-01        8.28  1.53      1
2016-06-01        8.07  1.40      1
2016-07-01        7.99  1.40      1
2016-08-01        8.01  1.77      1
2016-09-01        7.85  1.99      1
</code></pre>

<p>Anyone available to enlight my journey?
I'm already on the "almost mad" stage trying to solve this.</p>

<h1>EDIT</h1>

<p>Important note to make it clearer: I need to disconsider the year and consider only the month to make the sum. Something like "everytime that an April appears (doesn't matter if it is 2006 or 2025) I need to sum with the April value of the Seasonal_Component frame.</p>