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I am reading many different data files into various pandas dataframes. The columns in these datafiles are separated by spaces. However, for each file, the number of spaces is different (for some of them, there is only one space, for others, there are two spaces and so on). Thus, every time I import the file, I have to manually go to that file and see the number of spaces that have been used and give those many number of spaces in sep:

import pandas as pd
df = pd.read_csv('myfile.dat', sep = '    ')

Is there any way I can tell pandas to assume "any number of spaces" as the separator? Also, is there any way I can tell pandas to use either tab (\t) or spaces as the separator?

4 Answers 4

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Yes, you can use a simple regular expression like sep='\s+' to denote one or more spaces.

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2 Comments

That worked! Thanks. Is there any way I can tell pandas to use either space or tab as the separator?
The whitespace might match tab as well but I believe you can just add an or condition to the regular expression: sep=\s+|\t+
5

You can directly use delim_whitespace:

import pandas as pd
df = pd.read_csv('myfile.dat', delim_whitespace=True )

The argument delim_whitespace controls whether or not whitespace (e.g. ' ' or ' ') will be used as separator. See pandas.read_csv for details.

Comments

4

You can also use the parameter skipinitialspace=True which skips the leading spaces after any delimiter.

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2

One thing I found is if you use a unsupported separator. Pandas/Dask will have to use the Python engine instead of the C engine. This is a good deal slower.

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