Convert data frame column to float and perform operation in Pandas - python-2.7

Question

I have a data frame that contains the following that are imported as strings
df3 = pd.DataFrame(data = {
'Column1':['10/1','9/5','7/4','12/3','18/7','14/2']})
I am tried to convert to float and do the division. The following did work well.
for i, v in enumerate(df3.Column1):
df3['Column2'] = float(v[:-2]) / float(v[-1])
print df3.Column2
This is the output that I am trying to achieve
df3 = pd.DataFrame(data = {
'Column1':['10/1','9/5','7/4','12/3','18/7','14/2'],
'Column2':['10.0','1.8','1.75','4.0','2.57142857143','7.0']})
df3

Answer 1

The following would work, define a function to perform the casting to float and return this, the result of which should be assigned to your new column:
In [10]:
df3 = pd.DataFrame(data = {
'Column1':['10/1','9/5','7/4','12/3','18/7','14/2']})
def func(x):
return float(x[:-2]) / float(x[-1])
df3['Column2'] = df3['Column1'].apply(func)
df3
Out[10]:
Column1 Column2
0 10/1 10.000000
1 9/5 1.800000
2 7/4 1.750000
3 12/3 4.000000
4 18/7 2.571429
5 14/2 7.000000

Answer 2

if, and ONLY IF, you do not have input/data from an untrusted source, here's a shortcut:
In [46]: df3
Out[46]:
Column1
0 10/1
1 9/5
2 7/4
3 12/3
4 18/7
5 14/2
In [47]: df3.Column1.map(eval)
Out[47]:
0 10.000000
1 1.800000
2 1.750000
3 4.000000
4 2.571429
5 7.000000
Name: Column1, dtype: float64
But seriously...be careful with eval.