python pandas overflow error dataFrame

Question

I am rather new to python and I am using the pandas library to work with data frames. I created a function "elevate_power" that reads in a data frame with one column of floating point values (example x) , and a degree (example lambda), and outputs a dataframe where each column contains a power of the original column (example: output is x,x^2,x^3)

The problem is when I have a degree that is above 30, I get overflow error. Is there a way around this problem ?

I am not particularly worried about the precision, so I would not mind loosing some precision.

However, (and this is important), I need the output to be type float because I then call some numpy subroutines that give me errors if I change the type.

I have tried several tricks: for example I tried using decimal inside the function but then I cannot get the format back to floats, which is a problem because then I get errors when I call dot product and linear algebra solvers from numpy.

Any suggestion will be greatly appreciated,

This is the test code (which I ran with a low degree value so it won't crash):

def elevate_power(column, degree):
    df = pd.DataFrame(column)
    dfbase=df
    if degree > 0:
        for power in range(2, degree+1): 
            # first we'll give the column a name:
            name = 'power_' + str(power)
            df[name]= 0           
            df[name] = dfbase.apply(lambda x: x**power , axis=1)
    return(df)

   import pandas as pd
   import numpy as np
   test= pd.Series([1., 2., 3.])
   test2=pd.DataFrame(test)
   degree=5
   print elevate_power(test2, degree )
   np.dot(test2['power_2'],test2['power_3'])

The printout is :

   0  power_2  power_3  power_4  power_5
0  1        1        1        1        1
1  2        4        8       16       32
2  3        9       27       81      243

276.0

python pandas overflow error dataFrame

1 Answers