Python Pandas : How to skip columns when reading a file?

Question

I have table formatted as follow :

foo - bar - 10 2e-5 0.0 some information quz - baz - 4 1e-2 1 some other description in here 

When I open it with pandas doing :

a = pd.read_table("file", header=None, sep=" ") 

It tells me :

CParserError: Error tokenizing data. C error: Expected 9 fields in line 2, saw 12 

What I'd basically like to have is something similar to the skiprows option which would allow me to do something like :

a = pd.read_table("file", header=None, sep=" ", skipcolumns=[8:]) 

I'm aware that I could re-format this table with awk, but I'd like to known whether a Pandas solution exists or not.

Thanks.

Answer 1

The usecols parameter allows you to select which columns to use:

a = pd.read_table("file", header=None, sep=" ", usecols=range(8)) 

However, to accept irregular column counts you need to also use engine='python'.