Help loading data into pandas
I have a large (~400mb) csv file I am trying to open in Pandas. When I don't specify the dtype and open it with the following command It appears to work.
df = pd.io.parsers.read_csv(CSVFILECLEAN2013, quotechar='"', low_memory=False, na_values='')
If I try to specify the dtype for each field I get an error but no hint as to where I should look. I have "cleaned" the csv by checking that all values that should be an int for a float are either blank or can be cast as a float or a int. I guess my question is, can I get a more useful error message or is there a hint as to where the problem is that I am not seeing.
Exception Traceback (most recent call last) <ipython-input-2-8715d8cbaa54> in <module>() 3 import load_data 4 import numpy as np ----> 5 df2 = load_data.load('jeffco_2013')
/Users/vmd/GitHub/Jeffco-Properties/tools/load_data.py in load(data) 47 def load(data): 48 files = dict(jeffco_2013 = '/Users/vmd/GitHub/Jeffco-Properties/Data/JeffersonCo/Datasets/2013_clean_Jeffco_ATSDTA_ATSP600.csv') ---> 49 return pd.io.parsers.read_csv(files[data], quotechar='"', low_memory=False, na_values='', dtype=DATASHAPE)
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in parser_f(filepath_or_buffer, sep, dialect, compression, doublequote, escapechar, quotechar, quoting, skipinitialspace, lineterminator, header, index_col, names, prefix, skiprows, skipfooter, skip_footer, na_values, na_fvalues, true_values, false_values, delimiter, converters, dtype, usecols, engine, delim_whitespace, as_recarray, na_filter, compact_ints, use_unsigned, low_memory, buffer_lines, warn_bad_lines, error_bad_lines, keep_default_na, thousands, comment, decimal, parse_dates, keep_date_col, dayfirst, date_parser, memory_map, float_precision, nrows, iterator, chunksize, verbose, encoding, squeeze, mangle_dupe_cols, tupleize_cols, infer_datetime_format, skip_blank_lines) 468 skip_blank_lines=skip_blank_lines) 469 --> 470 return _read(filepath_or_buffer, kwds) 471 472 parser_f.__name__ = name
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds) 254 return parser 255 --> 256 return parser.read() 257 258 _parser_defaults = {
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in read(self, nrows) 713 raise ValueError('skip_footer not supported for iteration') 714 --> 715 ret = self._engine.read(nrows) 716 717 if self.options.get('as_recarray'):
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in read(self, nrows) 1162 1163 try: -> 1164 data = self._reader.read(nrows) 1165 except StopIteration: 1166 if nrows is None:
pandas/parser.pyx in pandas.parser.TextReader.read (pandas/parser.c:7426)()
pandas/parser.pyx in pandas.parser.TextReader._read_rows (pandas/parser.c:8484)()
pandas/parser.pyx in pandas.parser.TextReader._convert_column_data (pandas/parser.c:9795)()
pandas/parser.pyx in pandas.parser.TextReader._convert_tokens (pandas/parser.c:10403)()
pandas/parser.pyx in pandas.parser.TextReader._convert_with_dtype (pandas/parser.c:11257)()
Exception: Integer column has NA values
Vincent Davis 720-301-3003
I don't think pandas allows blank values in integer columns? You might get better results asking on the pandas list, though -- see http://pandas.pydata.org/community.html
-n On May 13, 2015 2:17 PM, "Vincent Davis" vincent@vincentdavis.net wrote:
I have a large (~400mb) csv file I am trying to open in Pandas. When I don't specify the dtype and open it with the following command It appears to work.
df = pd.io.parsers.read_csv(CSVFILECLEAN2013, quotechar='"', low_memory=False, na_values='')
If I try to specify the dtype for each field I get an error but no hint as to where I should look. I have "cleaned" the csv by checking that all values that should be an int for a float are either blank or can be cast as a float or a int. I guess my question is, can I get a more useful error message or is there a hint as to where the problem is that I am not seeing.
Exception Traceback (most recent call last) <ipython-input-2-8715d8cbaa54> in <module>() 3 import load_data 4 import numpy as np ----> 5 df2 = load_data.load('jeffco_2013')
/Users/vmd/GitHub/Jeffco-Properties/tools/load_data.py in load(data) 47 def load(data): 48 files = dict(jeffco_2013 = '/Users/vmd/GitHub/Jeffco-Properties/Data/JeffersonCo/Datasets/2013_clean_Jeffco_ATSDTA_ATSP600.csv') ---> 49 return pd.io.parsers.read_csv(files[data], quotechar='"', low_memory=False, na_values='', dtype=DATASHAPE)
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in parser_f(filepath_or_buffer, sep, dialect, compression, doublequote, escapechar, quotechar, quoting, skipinitialspace, lineterminator, header, index_col, names, prefix, skiprows, skipfooter, skip_footer, na_values, na_fvalues, true_values, false_values, delimiter, converters, dtype, usecols, engine, delim_whitespace, as_recarray, na_filter, compact_ints, use_unsigned, low_memory, buffer_lines, warn_bad_lines, error_bad_lines, keep_default_na, thousands, comment, decimal, parse_dates, keep_date_col, dayfirst, date_parser, memory_map, float_precision, nrows, iterator, chunksize, verbose, encoding, squeeze, mangle_dupe_cols, tupleize_cols, infer_datetime_format, skip_blank_lines) 468 skip_blank_lines=skip_blank_lines) 469 --> 470 return _read(filepath_or_buffer, kwds) 471 472 parser_f.__name__ = name
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds) 254 return parser 255 --> 256 return parser.read() 257 258 _parser_defaults = {
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in read(self, nrows) 713 raise ValueError('skip_footer not supported for iteration') 714 --> 715 ret = self._engine.read(nrows) 716 717 if self.options.get('as_recarray'):
/Users/vmd/anaconda/envs/py34/lib/python3.4/site-packages/pandas/io/parsers.py in read(self, nrows) 1162 1163 try: -> 1164 data = self._reader.read(nrows) 1165 except StopIteration: 1166 if nrows is None:
pandas/parser.pyx in pandas.parser.TextReader.read (pandas/parser.c:7426)()
pandas/parser.pyx in pandas.parser.TextReader._read_rows (pandas/parser.c:8484)()
pandas/parser.pyx in pandas.parser.TextReader._convert_column_data (pandas/parser.c:9795)()
pandas/parser.pyx in pandas.parser.TextReader._convert_tokens (pandas/parser.c:10403)()
pandas/parser.pyx in pandas.parser.TextReader._convert_with_dtype (pandas/parser.c:11257)()
Exception: Integer column has NA values
Vincent Davis 720-301-3003
NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
On Wed, May 13, 2015 at 3:27 PM, Nathaniel Smith njs@pobox.com wrote:
I don't think pandas allows blank values in integer columns? You might get better results asking on the pandas list, though -- see http://pandas.pydata.org/community.html
"integer columns" seems to be the key. they have to be float. Thanks
Vincent Davis
participants (2)
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Nathaniel Smith -
Vincent Davis