Question

我想使用逗号作为小数点分隔符来打开一个csv文件。我通过了decimal=","。但是，我总是收到错误的csv文件的最后一行的float值未成功解析（我尝试删除csv文件的某些行，并且该错误总是在最后一行...）。浮点值在csv中也被引用，因此我通过了quoting=csv.QUOTE_ALL。

有人知道这里会发生什么吗？如果我删除了dtype选项，它会起作用，但是列amount是一个字符串...

这是我使用的代码（为了便于阅读而重新格式化）：

import pandas as pd
import numpy as np
dateparse = lambda x: pd.datetime.strptime(x, '%d/%m/%Y')
expenses = pd.read_csv("/home/jovyan/work/expenses.csv",
 quoting=csv.QUOTE_ALL, decimal=",", header=None, na_values=[""],
 names=['date','category','amount','currency','note','tags'],
 parse_dates=["date"], date_parser=dateparse,  
 dtype={"date": str,"category": str, "amount":float, "currency": str,
 "note": str, "tags": str})

Answer 1

我认为这是我不了解的熊猫行为问题，但看来问题出在读取的数据中。浮柱也使用了千位分隔符，例如'1.345,50'。这些线路造成了麻烦。解决方案是使用read_csv选项thousands='.'。

错误消息令人困惑，因为报告为不可转换为浮点的值取自csv文件的最后一行，而不是引起麻烦的行。...

作为参考，以下是错误消息：

    ---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()

TypeError: Cannot cast array from dtype('O') to dtype('float64') according to the rule 'safe'

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-109-e77d6530ab30> in <module>()
      3 import csv
      4 dateparse = lambda x: pd.datetime.strptime(x, '%d/%m/%Y')
----> 5 expenses = pd.read_csv("/home/jovyan/work/test.csv", quoting=csv.QUOTE_ALL, decimal=",", header=None, na_values=[""],names=['date','category','amount','currency','note','tags'],parse_dates=["date"], date_parser=dateparse,  dtype={"date": str,"category": str, "amount":float, "currency": str, "note": str, "tags": str})
      6 expenses['tags']=expenses['tags'].str.split(",")
      7 #,  dtype={"date": str,"category": str, "amount":float, "currency": str, "note": str, "tags": str}

/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, doublequote, delim_whitespace, low_memory, memory_map, float_precision)
    676                     skip_blank_lines=skip_blank_lines)
    677 
--> 678         return _read(filepath_or_buffer, kwds)
    679 
    680     parser_f.__name__ = name

/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds)
    444 
    445     try:
--> 446         data = parser.read(nrows)
    447     finally:
    448         parser.close()

/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in read(self, nrows)
   1034                 raise ValueError('skipfooter not supported for iteration')
   1035 
-> 1036         ret = self._engine.read(nrows)
   1037 
   1038         # May alter columns / col_dict

/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in read(self, nrows)
   1846     def read(self, nrows=None):
   1847         try:
-> 1848             data = self._reader.read(nrows)
   1849         except StopIteration:
   1850             if self._first_chunk:

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader.read()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_low_memory()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_rows()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_column_data()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()

ValueError: could not convert string to float: '0,99'

使用dtype时，pandas read_csv无法解析逗号十进制分隔符吗？

1 个答案: