Using Python 2.7 and Pandas
I have to parse through my directory and plot a bunch of CSVs. If the CSV is empty, the script breaks and produces the error message:
pandas.io.common.EmptyDataError: No columns to parse from file
If I have my file paths stored in
file_paths=[]
how do I read through each one and only plot the non empty CSVs? If I have an empty dataframe defined as df=[] I attempt the following code
for i in range(0,len(file_paths)):
if pd.read_csv(file_paths[i] == ""):
print "empty"
else df.append(pd.read_csv(file_paths[i],header=None))
Note, as of pandas 0.22.0 (that I can be sure of) , the exception raised for empty csv is
pandas.errors.EmptyDataError
. And if you're importing pandas likeimport pandas as pd
, then usepd
instead ofpandas
.If your csv filenames are in an array
manyfiles
, thenI'm not sure if
pandas.io.common.EmptyDataError
is still valid or not. Can't find it in reference docs. And I also would advise against the catch-allexcept:
as you won't be able to know if it's something else causing the issue.You can use the in built
try
andexcept
syntax to skip over files that return you an error, as follows:Described here: Try/Except in Python: How do you properly ignore Exceptions?
This will attempt to read each file, and if unsuccessful continue to the next file.
I would just catch the appropriate exception, as a catch all is not recommended in python: