TypeError: float() argument must be a string or a number, not 'Period' : <p>I have a pandas dataframe with columns like this:</p>

<pre><code>df.columns = pd.to_datetime(list(df)) #list(df) = ["2017-01", "2016-01", ...]
</code></pre>

<p>Then I performed an interpolation in each row of the dataset because I have some NaNs that I want to get rid off. Here is the result printed:</p>

<pre><code>ORIGINAL  
2007-12-01     NaN 
2008-12-01     NaN 
2009-12-01     NaN 
2010-12-01   -0.35 
2011-12-01    0.67 
2012-12-01     NaN 
2013-12-01     NaN 
2014-12-01    1.03 
2015-12-01    0.37 
2016-12-01     NaN 
2017-12-01     NaN 
Name: row1, dtype: float64 

INTERPOLATION  
2007-12-01   -0.350000 
2008-12-01   -0.350000 
2009-12-01   -0.350000 
2010-12-01   -0.350000 
2011-12-01    0.670000 
2012-12-01    0.790219 
2013-12-01    0.910109 
2014-12-01    1.030000 
2015-12-01    0.370000 
2016-12-01    0.370000 
2017-12-01    0.370000 
Name: row1, dtype: float64
</code></pre>

<p>Then I try to plot the interpolated row and get:</p>

<pre><code>TypeError: float() argument must be a string or a number, not 'Period' 
</code></pre>

<p>The whole code:</p>

<pre><code>print("ORIGINAL\n", series)
interpolation = series.interpolate(method=func, limit=10, limit_direction='both')
interpolation.plot()
print("INTERPOLATION\n",interpolation)
</code></pre>

<p>It seems to me that the error is in the time values in the series, but I think matplotlib should be hable to handle it, so I'm doing something wrong for sure. Thanks in advance.</p>
