Blank column in Pandas Dataframe

Question

How do I ignore last whitespace in a line when converting to Pandas DataFrame?

I have a CSV file in the following format:

Column #1   : Type
Column #2   : Total Length
Column #3   : Found
Column #4   : Grand Total

1;2;1;7.00;
2;32;2;0.76;
3;4;6;6.00;
4;1;5;4.00;

I loop through the 'Column #' lines to create my column names first (so 4 columns), then I parse the following lines to create my DataFrame using ';' as the separator. However some of my files contain a trailing ';' on the end of each line as shown above, so my Pandas DataFrame thinks there is a 5th column containing whitespace, and consequently throws an error to say there aren't enough column names specified

Is there a mechanism in Pandas to remove/ignore the trailing ';', or whitespace when creating a DataFrame? I am using read_csv to create the DataFrame.

Thanks.

EdChum · Accepted Answer · 2015-07-07 11:20:38Z

1

Just pass param for usecols:

In [160]:
t="""1;2;1;7.00;
2;32;2;0.76;
3;4;6;6.00;
4;1;5;4.00;"""
import pandas as pd
import io
df = pd.read_csv(io.StringIO(t), sep=';', header=None, usecols=range(4))
df

Out[160]:
   0   1  2     3
0  1   2  1  7.00
1  2  32  2  0.76
2  3   4  6  6.00
3  4   1  5  4.00

Here I generate the list [0,1,2,3] to indicate which columns I'm interested in.

answered Jul 7, 2015 at 11:20

EdChum

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