i have multiple dataframes have same number of columns not have same number of rows. need able iterations through them @ same time cannot if different lengths. therefore figured best interpolate data given number of rows. possible? have tried using:
testdf1 = df1.reindex(df1.index.union(numpy.linspace(0.00, 4304.92, 860.984))) testdf1.interpolate('index')
only issue returns data frame load of nan's , on number of rows needed puts original data in.
these data frames on 50 columns long , ~600 rows down.
edit pressed post before completion
a standard dataframe so:
b c d z 0.00 7.2 100.22 12.1 y 7.06 3.4 150.21 12.1 x 12.56 1.2 176.32 12.1 w 20.98 1.2 190.23 12.1 ...
and on.
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