title: interp1d for pandas time series
body: <p>I want to interpolate between times in a pandas time series. I would like to use scipy.interpolate.interp1d (or similar). The <code>pandas.interpolate</code> function is undesirable, as it would require inserting <code>nan</code> values and then replace them using interpolation (and thus modifying the dataset). What I tried to do:</p>
  
  <pre><code>from datetime import datetime
  import scipy.interpolate as si
  import pandas as pd
  d1 = datetime(2019, 1, 1)
  d2 = datetime(2019, 1, 5)
  d3 = datetime(2019, 1, 10)
  df = pd.DataFrame([1, 4, 2], index=[d1, d2, d3], columns=['conc'])
  import scipy.interpolate as si
  f = si.interp1d(df.index, df.conc)
  f(datetime(2019, 1, 3))
  </code></pre>
  
  <p>All is good until the last line, where I get an <code>ValueError: object arrays are not supported</code>. Strangely enough <code>f.x</code> nicely shows the dates as <code>dtype='datetime64[ns]</code>, so I was hoping it would work. Anybody know how to get this to work?</p>