我使用pandas read_csv函数来读取我的csv文件。
feature_file_df_5=pd.read_csv('/home/jayashree/Documents/Nokia/DataSet/SMT Data Analytics/SPI (Solder Paste Inspection)/086990A-108-FHFB-TRX-985676H-BOTTOM-N_0608_2001_2500.csv',header=501)
我正面临解析器错误
/home/jayashree/anaconda2/lib/python2.7/site-packages/pandas/io/parsers.pyc in read(self, nrows)
1717 def read(self, nrows=None):
1718 try:
-> 1719 data = self._reader.read(nrows)
1720 except StopIteration:
1721 if self._first_chunk:
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader.read (pandas/_libs/parsers.c:10862)()
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_low_memory (pandas/_libs/parsers.c:11138)()
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_rows (pandas/_libs/parsers.c:11884)()
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._tokenize_rows (pandas/_libs/parsers.c:11755)()
pandas/_libs/parsers.pyx in pandas._libs.parsers.raise_parser_error (pandas/_libs/parsers.c:28765)()
ParserError: Error tokenizing data. C error: Expected 2503 fields in line 2624, saw 52523
根据thread的建议,我尝试将sep选项添加为
feature_file_df_5=pd.read_csv('/home/jayashree/Documents/Nokia/DataSet/SMT Data Analytics/SPI (Solder Paste Inspection)/086990A-108-FHFB-TRX-985676H-BOTTOM-N_0608_2001_2500.csv', sep=',',header=501)
得到同样的错误 当我使用sep = None
时`feature_file_df_5=pd.read_csv('/home/jayashree/Documents/Nokia/DataSet/SMT Data Analytics/SPI (Solder Paste Inspection)/086990A-108-FHFB-TRX-985676H-BOTTOM-N_0608_2001_2500.csv', sep=None,header=`501)
我收到此错误
/home/jayashree/anaconda2/lib/python2.7/site-packages/pandas/io/parsers.pyc in _rows_to_cols(self, content)
2782 msg = ('Expected %d fields in line %d, saw %d' %
2783 (col_len, row_num + 1, actual_len))
-> 2784 if len(self.delimiter) > 1 and self.quoting != csv.QUOTE_NONE:
2785 # see gh-13374
2786 reason = ('Error could possibly be due to quotes being '
TypeError: object of type 'NoneType' has no len()
[1]: https://stackoverflow.com/questions/18039057/python-pandas-error-tokenizing-data
在电子表格中打开时,我发现所有行都存在任何问题。 如何解决错误。
答案 0 :(得分:0)
您应该尝试参数quoting
和quotechar
,它们可以帮助进行文件字段结构化。
更多细节在这里:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html
或者如果只有一个(或几个)可以省略的断行,请使用error_bad_lines=False
。