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:\Python33\lib\site-packages\pandas\io\parsers.py", line 578, in __iter__ yield self.read(self.chunksize) File "C:\Python33\lib\site-packages\pandas\io\parsers.py", line 608, in read ret = self._engine.read(nrows) File "C:\Python33\lib\site-packages\pandas\io\parsers.py", line 1028, in read data = self._reader.read(nrows) File "parser.pyx", line 706, in pandas.parser.TextReader.read (pandas\parser.c:6745) File "parser.pyx", line 740, in pandas.parser.TextReader._read_low_memory (pandas\parser.c:7146) File "parser.pyx", line 781, in pandas.parser.TextReader._read_rows (pandas\parser.c:7568) File "parser.pyx", line 768, in pandas.parser.TextReader._tokenize_rows (pandas\parser.c:7451) File "parser.pyx", line 1661, in pandas.parser.raise_parser_error (pandas\parser.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.
I have the same problem, and after adding these two params to my code, the problem is gone.
read_csv (...
quoting=3
,error_bad_lines=False
)
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="\t", quoting=csv.QUOTE_NONE, encoding='utf-8')
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