I have a CSV text file encoded in UTF-16 (so as to preserve Unicode characters when others use Excel) but when doing a read_csv with Pandas 0.9.0, I get this cryptic error:
df = pd.read_csv('data.txt',encoding='utf-16',sep='\t',header=0)
df.head()
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
<ipython-input-18-85da1383cd9e> in <module>()
----> 1 df = pd.read_csv('candidates-spanish.txt',encoding='utf-16',sep='\t',header=0)
2 df.head()
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/io/parsers.pyc in read_csv(filepath_or_buffer, sep, dialect, header, index_col, names, skiprows, na_values, keep_default_na, thousands, comment, parse_dates, keep_date_col, dayfirst, date_parser, nrows, iterator, chunksize, skip_footer, converters, verbose, delimiter, encoding, squeeze, **kwds)
248 kdict['delimiter'] = sep
249
--> 250 return _read(TextParser, filepath_or_buffer, kdict)
251
252 @Appender(_read_table_doc)
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/io/parsers.pyc in _read(cls, filepath_or_buffer, kwds)
198 return parser
199
--> 200 return parser.get_chunk()
201
202 @Appender(_read_csv_doc)
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/io/parsers.pyc in get_chunk(self, rows)
853 elif not self._has_complex_date_col:
854 index = self._get_simple_index(alldata, columns)
--> 855 index = self._agg_index(index)
856
857 elif self._has_complex_date_col:
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/io/parsers.pyc in _agg_index(self, index, try_parse_dates)
980 arr, _ = _convert_types(arr, col_na_values)
981 arrays.append(arr)
--> 982 index = MultiIndex.from_arrays(arrays, names=self.index_name)
983 return index
984
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/index.pyc in from_arrays(cls, arrays, sortorder, names)
1570
1571 return MultiIndex(levels=levels, labels=labels,
-> 1572 sortorder=sortorder, names=names)
1573
1574 @classmethod
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/index.pyc in __new__(cls, levels, labels, sortorder, names)
1254 assert(len(levels) == len(labels))
1255 if len(levels) == 0:
-> 1256 raise Exception('Must pass non-zero number of levels/labels')
1257
1258 if len(levels) == 1:
Exception: Must pass non-zero number of levels/labels
Reading the data in line-by-line with csv.reader based on this example implies that my data is not incorrectly formatted:
from io import BytesIO
import csv
with open('data.txt','rb') as f:
r = f.read().decode('utf-16').encode('utf-8')
for l in csv.reader(BytesIO(r),delimiter='\t'):
print l
['Country', 'State/City', 'Title', 'Date', 'Catalogue', 'Wikipedia Election Page', 'Wikipedia Individual Page', 'Electoral Institution in Country', 'Twitter', 'CANDIDATE NAME 1', 'CANDIDATE NAME 2']
['Venezuela', 'N/A', 'President', '10/7/12', 'Hugo Rafael Chavez Frias', 'Hugo Ch\xc3\xa1vez', 'Hugo Ch\xc3\xa1vez', 'Hugo Chavez', 'Hugo Ch\xc3\xa1vez Fr\xc3\xadas', 'Hugo Chavez', 'Hugo Ch\xc3\xa1vez']
['Venezuela', 'N/A', 'President', '10/7/12', 'Henrique Capriles Radonski', 'Henrique Capriles Radonski', 'Henrique Capriles Radonski', 'Henrique Capriles Radonski', 'Henrique Capriles R.', 'Henrique Capriles', '']
Is there some pre-processing, an addition option in read_csv, or something else that needs to be done before pandas.read_csv can read a utf-16 file? Thanks!
Python loads CSV files 100 times faster than Excel files. Use CSVs. Con: csv files are nearly always bigger than . xlsx files.
The difference between read_csv() and read_table() is almost nothing. In fact, the same function is called by the source: read_csv() delimiter is a comma character. read_table() is a delimiter of tab \t .
In this case, the Pandas read_csv() function returns a new DataFrame with the data and labels from the file data. csv , which you specified with the first argument. This string can be any valid path, including URLs.
The Pandas read_csv() function has an argument call encoding that allows you to specify an encoding to use when reading a file. Let's take a look at an example below: First, we create a DataFrame with some Chinese characters and save it with encoding='gb2312' .
This is a bug, I think because csv reader was passing back an extra empty line in the beginning. It worked for me on Python 2.7.3 and pandas 0.9.1 if I do:
In [36]: pd.read_csv(BytesIO(fh.read().decode('UTF-16').encode('UTF-8')), sep='\t', header=0)
Out[36]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 50 entries, 0 to 49
Data columns:
Country 43 non-null values
State/City 43 non-null values
Title 43 non-null values
Date 43 non-null values
Catalogue 43 non-null values
Wikipedia Election Page 43 non-null values
Wikipedia Individual Page 43 non-null values
Electoral Institution in Country 43 non-null values
Twitter 43 non-null values
CANDIDATE NAME 1 43 non-null values
CANDIDATE NAME 2 16 non-null values
dtypes: object(11)
I reported the bug here: https://github.com/pydata/pandas/issues/2418 On github master it unfortunately causes a segfault in the c-parser. We'll fix it.
Now, interestingly: https://softwareengineering.stackexchange.com/questions/102205/should-utf-16-be-considered-harmful ;)
Python3:
with open('data.txt',encoding='UTF-16') as f:
df = pd.read_csv(f)
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