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

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'.

Answer 2

If you are using Linux/OS X/Windows Cygwin, you should be able to prepare the file as follows:

cat your_file |  cut -d' ' -f1,2,3,4,5,6,7 > out.file

Then in Python:

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

Example:

Input:

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

Output:

foo - bar - 10 2e-5 0.0
quz - baz - 4 1e-2 1

You can run this command manually on the command-line, or simply call it from within Python using the subprocess module.