python - Prevent pandas from automatically inferring type in read_csv

Question

I have a #-separated file with three columns: the first is integer, the second looks like a float, but isn't, and the third is a string. I attempt to load this directly into python with pandas.read_csv

In [149]: d = pandas.read_csv('resources/names/fos_names.csv',  sep='#', header=None, names=['int_field', 'floatlike_field', 'str_field'])

In [150]: d
Out[150]: 
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1673 entries, 0 to 1672
Data columns:
int_field          1673  non-null values
floatlike_field    1673  non-null values
str_field          1673  non-null values
dtypes: float64(1), int64(1), object(1)

pandas tries to be smart and automatically convert fields to a useful type. The issue is that I don't actually want it to do so (if I did, I'd used the converters argument). How can I prevent pandas from converting types automatically?

Answer 1

I'm planning to add explicit column dtypes in the upcoming file parser engine overhaul in pandas 0.10. Can't commit myself 100% to it but it should be pretty simple with the new infrastructure coming together (http://wesmckinney.com/blog/?p=543).