how to NOT read_csv if csv is empty

Question

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))

score 40 · Answer 1 · edited Feb 01 '23 at 11:01

40

I would just catch the appropriate exception, as a catch all is not recommended in python:

import pandas.io.common

for i in range(0,len(file_paths)):
   try:
      pd.read_csv(file_paths[i])
   except pandas.errors.EmptyDataError:
      print file_paths[i], " is empty"

edited Feb 01 '23 at 11:01

iD_Sgh

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answered Feb 09 '17 at 17:38

Zeugma

31,231
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7

This seems to have changed since this solution was posted. Now need to use pandas.errors instead of pandas.io.common – NandaKishore.Rao Nov 12 '21 at 15:33

score 29 · Answer 2 · answered Jul 08 '18 at 09:43

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 like import pandas as pd, then use pd instead of pandas.

If your csv filenames are in an array manyfiles, then

import pandas as pd
for filename in manyfiles:
    try:
        df = pd.read_csv(filename)

    except pd.errors.EmptyDataError:
        print('Note: filename.csv was empty. Skipping.')
        continue # will skip the rest of the block and move to next file

    # operations on df

I'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-all except: as you won't be able to know if it's something else causing the issue.

Pandas version 1.0 moved error handling to `pandas.errors.EmptyDataError`. — Geoff D, May 17 '21 at 16:46

score 7 · Accepted Answer · edited May 23 '17 at 12:09

7

You can use the in built try and except syntax to skip over files that return you an error, as follows:

Described here: Try/Except in Python: How do you properly ignore Exceptions?

for i in range(0,len(file_paths)):
   try:
       pd.read_csv(file_paths[i])
       ### Do Some Stuff
   except:
       continue
       # or pass

This will attempt to read each file, and if unsuccessful continue to the next file.

edited May 23 '17 at 12:09

Community

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answered Feb 09 '17 at 17:35

Chuck

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You are welcome: I am glad this solved your problem. In the interests of the dissemination of proper standards: @Boud is right though - his answer is less general. – Chuck Feb 09 '17 at 17:51
7

I think such a broad except is not a best practice, the answer by @Boud is more appropriate. – kuanb Jul 28 '17 at 18:57

how to NOT read_csv if csv is empty

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