Combine two Pandas dataframes, resample on one time column, interpolate

Question

This is my first question on stackoverflow. Go easy on me!

I have two data sets acquired simultaneously by different acquisition systems with different sampling rate

Answer 1

If you construct a single DataFrame from Series, using time values as index, like this:

>>> t1 = np.array([0, 0.5, 1.0, 1.5, 2.0])
>>> y1 = pd.Series(t1, index=t1)

>>> t2 = np.array([0, 0.34, 1.01, 1.4, 1.6, 1.7, 2.01])
>>> y2 = pd.Series(3*t2, index=t2)

>>> df = pd.DataFrame({'y1': y1, 'y2': y2})
>>> df
       y1    y2
0.00  0.0  0.00
0.34  NaN  1.02
0.50  0.5   NaN
1.00  1.0   NaN
1.01  NaN  3.03
1.40  NaN  4.20
1.50  1.5   NaN
1.60  NaN  4.80
1.70  NaN  5.10
2.00  2.0   NaN
2.01  NaN  6.03

You can simply interpolate it, and select only the part where y1 is defined:

>>> df.interpolate('index').reindex(y1)
      y1   y2
0.0  0.0  0.0
0.5  0.5  1.5
1.0  1.0  3.0
1.5  1.5  4.5
2.0  2.0  6.0