resampling pandas series with numeric index

Question

suppose I have a pandas.Series with index with numeric value type e.g.

pd.Series( [10,20], [1.1, 2.3] )

How do we resample above series with 0.1 interval? look like the .resample func only work on datetime interval?

Answer 1

That goes by the name of interpolation. You can think for resampling as a special case of interpolation.

In [24]: new_idx = s.index + pd.Index(np.arange(1.1, 2.3, .01))

In [25]: s.reindex(new_idx).interpolate().head()
Out[25]: 
1.10    10.000000
1.11    10.083333
1.12    10.166667
1.13    10.250000
1.14    10.333333
dtype: float64

In [26]: s.reindex(new_idx).interpolate().tail()
Out[26]: 
2.26    19.666667
2.27    19.750000
2.28    19.833333
2.29    19.916667
2.30    20.000000
dtype: float64

We need new_idx to be a union of the original index and the values we want to interpolate, so that the original index isn't dropped.

Have a look at the interpolation methods: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.interpolate.html