Python: Convert string (in scientific notation) to float

Question

I\'m trying to import a large .csv file containing text and numbers using genfromtxt in numpy. I\'m only interested in two columns. I have most of the import sorted out wit

Answer 1

MAybe that will be helpful for anybody, I had similar problem and I've found on stackoverflow about applying pandas to_numeric to DataFrame columns including replacing commas with dots

import re
import pandas as pd
atw[cc] = pd.to_numeric(atw[cc].apply(lambda x: re.sub(',', '.', str(x))))

Answer 2

 with open( datafile,'r' ) as inData:
     for line in inData:
          j = list( map( float,   filter( None  , [ x for x in line.strip().split(',') ] )) )

Just mentioned generally, as it solves a similar problem that brought me to this page.

Answer 3

Having such list of scientific notations, you can also do this:

1. a = [9.0181446e-01, 1.3179450e-02, 4.3021311e-04, 2.3546994e-03, 3.6531375e-03, 7.8567989e-02]
2. max(a)

Output will be: 0.90181446

Answer 4

The float function can do this:

>>> float('1.31E+01')
13.1

or for a list:

>>> map(float, ['3.76E+00', '1.31E+01', '1.14E+01'])
[3.76, 13.1, 11.4]