Resample Pandas Dataframe With "bin Size"/"frequency"

9I have a multi-indexed dataframe which I would like to resample to reduce the frequency of datapoints by a factor of 3 (meaning that every 3 rows become one). This:

Solution 1:

I think the idea for you could be - divide records inside each ID into bins by 3 records each (like ntile(3) in SQL) group by it and calculate mean. To create this numbers we can use the fact that you already have sequential numbers for each row - measurement level of index. So we can just divide this number by 3 to get numbers we need:

>>>df
                   time  value  ntile
ID    measurement                  
ET001 0            0.00      2      0
      1            0.15      3      0
      2            0.30      4      0
      3            0.45      3      1
      4            0.60      3      1
      5            0.75      2      1
      6            0.90      3      2
ET002 0            0.00      2      0
      1            0.16      5      0
      2            0.32      4      0
      3            0.45      3      1
      4            0.60      3      1
      5            0.75      2      1

So we can use helper function like this and apply it to each group to get desired results.

>>>defhelper(x):...    x = x.reset_index()...    x = x.groupby(x['measurement'].div(3)).mean()...del x['measurement']...return x...>>>df.groupby(level=0).apply(helper)
                   time     value
ID    measurement                
ET001 0            0.15  3.000000
      1            0.60  2.666667
      2            0.90  3.000000
ET002 0            0.16  3.666667
      1            0.60  2.666667

Hope it helps.