所以我试着从一个文件夹中读取所有的csv文件,然后将它们连接起来创建一个大csv(所有文件的结构都是相同的),保存并再次读取。所有这些都是用熊猫做的。读取时出错。我附上代码和下面的错误。
import pandas as pd
import numpy as np
import glob
path =r'somePath' # use your path
allFiles = glob.glob(path + "/*.csv")
frame = pd.DataFrame()
list_ = []
for file_ in allFiles:
df = pd.read_csv(file_,index_col=None, header=0)
list_.append(df)
store = pd.concat(list_)
store.to_csv("C:\work\DATA\Raw_data\\store.csv", sep=',', index= False)
store1 = pd.read_csv("C:\work\DATA\Raw_data\\store.csv", sep=',')
错误:
CParserError Traceback (most recent call last)
<ipython-input-48-2983d97ccca6> in <module>()
----> 1 store1 = pd.read_csv("C:\work\DATA\Raw_data\\store.csv", sep=',')
C:\Users\armsharm\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.pyc 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)
472 skip_blank_lines=skip_blank_lines)
473
--> 474 return _read(filepath_or_buffer, kwds)
475
476 parser_f.__name__ = name
C:\Users\armsharm\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.pyc in _read(filepath_or_buffer, kwds)
258 return parser
259
--> 260 return parser.read()
261
262 _parser_defaults = {
C:\Users\armsharm\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.pyc in read(self, nrows)
719 raise ValueError('skip_footer not supported for iteration')
720
--> 721 ret = self._engine.read(nrows)
722
723 if self.options.get('as_recarray'):
C:\Users\armsharm\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.pyc in read(self, nrows)
1168
1169 try:
-> 1170 data = self._reader.read(nrows)
1171 except StopIteration:
1172 if nrows is None:
pandas\parser.pyx in pandas.parser.TextReader.read (pandas\parser.c:7544)()
pandas\parser.pyx in pandas.parser.TextReader._read_low_memory (pandas\parser.c:7784)()
pandas\parser.pyx in pandas.parser.TextReader._read_rows (pandas\parser.c:8401)()
pandas\parser.pyx in pandas.parser.TextReader._tokenize_rows (pandas\parser.c:8275)()
pandas\parser.pyx in pandas.parser.raise_parser_error (pandas\parser.c:20691)()
CParserError: Error tokenizing data. C error: Buffer overflow caught - possible malformed input file.
我也试过使用csv阅读器:
import csv
with open("C:\work\DATA\Raw_data\\store.csv", 'rb') as f:
reader = csv.reader(f)
l = list(reader)
错误:
Error Traceback (most recent call last)
<ipython-input-36-9249469f31a6> in <module>()
1 with open('C:\work\DATA\Raw_data\\store.csv', 'rb') as f:
2 reader = csv.reader(f)
----> 3 l = list(reader)
Error: new-line character seen in unquoted field - do you need to open the file in universal-newline mode?
不是一个答案,但是对于注释来说太长了(不是说代码格式)
当您在csv模块中读取它时,它断开,您至少可以找到发生错误的行:
然后在store.csv中查看该行发生了什么。
如果您使用的是python及其大文件,则可以使用
engine='python'
如下,应该可以工作。df = pd.read_csv( file_, index_col=None, header=0, engine='python' )
我发现这个错误,原因是pandas用作行结束符的数据中有一些回车符“\r”,就好像它是“\n”。我想我应该在这里发帖,因为这可能是出现这个错误的常见原因。
我找到的解决方案是将lineterminator='\n'添加到read-csv函数中,如下所示:
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