Python Pandas : How To Skip Columns When Reading A File?
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_tabl
Solution 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'
.
Solution 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 -102e-50.0some information
quz - baz -41e-21some 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.
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