python - Pandas ParserError EOF character when reading multiple csv files to HDF5

Question

Using Python3, Pandas 0.12

I'm trying to write multiple csv files (total size is 7.9 GB) to a HDF5 store to process later onwards. The csv files contain around a million of rows each, 15 columns and data types are mostly strings, but some floats. However when I'm trying to read the csv files I get the following error:

Traceback (most recent call last):
  File "filter-1.py", line 38, in <module>
    to_hdf()
  File "filter-1.py", line 31, in to_hdf
    for chunk in reader:
  File "C:Python33libsite-packagespandasioparsers.py", line 578, in __iter__
    yield self.read(self.chunksize)
  File "C:Python33libsite-packagespandasioparsers.py", line 608, in read
    ret = self._engine.read(nrows)
  File "C:Python33libsite-packagespandasioparsers.py", line 1028, in read
    data = self._reader.read(nrows)
  File "parser.pyx", line 706, in pandas.parser.TextReader.read (pandasparser.c:6745)
  File "parser.pyx", line 740, in pandas.parser.TextReader._read_low_memory (pandasparser.c:7146)
  File "parser.pyx", line 781, in pandas.parser.TextReader._read_rows (pandasparser.c:7568)
  File "parser.pyx", line 768, in pandas.parser.TextReader._tokenize_rows (pandasparser.c:7451)
  File "parser.pyx", line 1661, in pandas.parser.raise_parser_error (pandasparser.c:18744)
pandas.parser.CParserError: Error tokenizing data. C error: EOF inside string starting at line 754991
Closing remaining open files: ta_store.h5... done 

Edit:

I managed to find a file that produced this problem. I think it's reading an EOF character. However I have no clue to overcome this problem. Given the large size of the combined files I think it's too cumbersome to check each single character in each string. (Even then I would still not be sure what to do.) As far as I checked, there are no strange characters in the csv files that could raise the error. I also tried passing error_bad_lines=False to pd.read_csv(), but the error persists.

My code is the following:

# -*- coding: utf-8 -*-

import pandas as pd
import os
from glob import glob


def list_files(path=os.getcwd()):
    ''' List all files in specified path '''
    list_of_files = [f for f in glob('2013-06*.csv')]
    return list_of_files


def to_hdf():
    """ Function that reads multiple csv files to HDF5 Store """
    # Defining path name
    path = 'ta_store.h5'
    # If path exists delete it such that a new instance can be created
    if os.path.exists(path):
        os.remove(path)
    # Creating HDF5 Store
    store = pd.HDFStore(path)

    # Reading csv files from list_files function
    for f in list_files():
        # Creating reader in chunks -- reduces memory load
        reader = pd.read_csv(f, chunksize=50000)
        # Looping over chunks and storing them in store file, node name 'ta_data'
        for chunk in reader:
            chunk.to_hdf(store, 'ta_data', mode='w', table=True)

    # Return store
    return store.select('ta_data')
    return 'Finished reading to HDF5 Store, continuing processing data.'

to_hdf()

Edit

If I go into the CSV file that raises the CParserError EOF... and manually delete all rows after the line that is causing the problem, the csv file is read properly. However all I'm deleting are blank rows anyway. The weird thing is that when I manually correct the erroneous csv files, they are loaded fine into the store individually. But when I again use a list of multiple files the 'false' files still return me errors.

Answer 1

I had a similar problem. The line listed with the 'EOF inside string' had a string that contained within it a single quote mark. When I added the option quoting=csv.QUOTE_NONE it fixed my problem.

For example:

import csv
df = pd.read_csv(csvfile, header = None, delimiter="", quoting=csv.QUOTE_NONE, encoding='utf-8')