从csv读取datetime会引发“未转换的数据保留：0”类型错误

我试图索引一个datetime，它由代表year、dayofyear和2400hr时间的3列组成

2014,323,1203,47.77,320.9
2014,323,1204,48.46,402.6
2014,323,1205,49.2,422.7
2014,323,1206,49.82,432.4
2014,323,1207,50.03,438.6
2014,323,1208,50.15,445.4
2014,323,1209,50.85,449.7
2014,323,1210,50.85,454.4
2014,323,1211,50.85,458.1
2014,323,1212,50.91,460.2

我正在使用以下代码：

In [1]:

import numpy as np
import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt
In [2]:

def parse(yr, yearday, hrmn):
          date_string = ' '.join([yr, yearday, hrmn])
          print(date_string)
          return datetime.strptime(date_string,"%Y %j %H%M")
In [3]:


df = pd.read_csv('home_prepped.dat', parse_dates={'datetime':[0,1,2]},
                  date_parser=parse, index_col='datetime', header=None)

当数据有缺陷时，我成功地将其引入，在DST更改期间有额外的数据，现在它已被修复、删除并缝合在一起，我的整个错误如下：

2014 92 2355
2014 92 2356
2014 92 2357
2014 92 2358
2014 92 2359
2014 92 2400
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-5-9c710834ee23> in <module>()
      1 
----> 2 df = pd.read_csv('home_prepped.dat', parse_dates={'datetime':[0,1,2]}, date_parser=parse, index_col='datetime', header=None)

/Volumes/anaconda/anaconda/lib/python2.7/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)
    463                     skip_blank_lines=skip_blank_lines)
    464 
--> 465         return _read(filepath_or_buffer, kwds)
    466 
    467     parser_f.__name__ = name

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/parsers.pyc in _read(filepath_or_buffer, kwds)
    249         return parser
    250 
--> 251     return parser.read()
    252 
    253 _parser_defaults = {

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/parsers.pyc in read(self, nrows)
    708                 raise ValueError('skip_footer not supported for iteration')
    709 
--> 710         ret = self._engine.read(nrows)
    711 
    712         if self.options.get('as_recarray'):

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/parsers.pyc in read(self, nrows)
   1209             data = dict((k, v) for k, (i, v) in zip(names, data))
   1210 
-> 1211             names, data = self._do_date_conversions(names, data)
   1212             index, names = self._make_index(data, alldata, names)
   1213 

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/parsers.pyc in _do_date_conversions(self, names, data)
   1033             data, names = _process_date_conversion(
   1034                 data, self._date_conv, self.parse_dates, self.index_col,
-> 1035                 self.index_names, names, keep_date_col=self.keep_date_col)
   1036 
   1037         return names, data

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/parsers.pyc in _process_date_conversion(data_dict, converter, parse_spec, index_col, index_names, columns, keep_date_col)
   2100 
   2101             _, col, old_names = _try_convert_dates(converter, colspec,
-> 2102                                                    data_dict, orig_names)
   2103 
   2104             new_data[new_name] = col

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/parsers.pyc in _try_convert_dates(parser, colspec, data_dict, columns)
   2132     to_parse = [data_dict[c] for c in colnames if c in data_dict]
   2133 
-> 2134     new_col = parser(*to_parse)
   2135     return new_name, new_col, colnames
   2136 

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/parsers.pyc in converter(*date_cols)
   2048                                                dayfirst=dayfirst)
   2049                 except Exception:
-> 2050                     return generic_parser(date_parser, *date_cols)
   2051 
   2052     return converter

/Volumes/anaconda/anaconda/lib/python2.7/site-packages/pandas/io/date_converters.pyc in generic_parser(parse_func, *cols)
     36     for i in range(N):
     37         args = [c[i] for c in cols]
---> 38         results[i] = parse_func(*args)
     39 
     40     return results

<ipython-input-2-57e18ddd7deb> in parse(yr, yearday, hrmn)
      1 def parse(yr, yearday, hrmn):
      2           date_string = ' '.join([yr, yearday, hrmn])
----> 3           return datetime.strptime(date_string,"%Y %j %H%M")

/Volumes/anaconda/anaconda/python.app/Contents/lib/python2.7/_strptime.pyc in _strptime(data_string, format)
    326     if len(data_string) != found.end():
    327         raise ValueError("unconverted data remains: %s" %
--> 328                           data_string[found.end():])
    329 
    330     year = None

ValueError: unconverted data remains: 0

我正在寻找关于如何调试或解决此问题的建议。我已经浏览了这些数据，根据我在类似帖子中读到的内容，我应该寻找一些无关的时间数据，而这些数据并不存在

---

谢谢。

在返回之前，将printdate\u字符串添加到解析器函数中。然后重新运行代码，看看这个麻烦的字符串是什么样子的；我被难住了！它返回值的前几天值。。。2014 92 1931 2014 92 1932 2014 92 1933 2014 92 1934 2014 92 1935.. 那么你是说现在没有错误了？哈哈，如果我不清楚的话，对不起。仍然有一个错误，我仍然不明白为什么，因为我没有注意到日期字符串中有任何缺陷。我将更新问题以反映更新的函数和结果。有没有办法像你昨天建议的那样，将csv上传给你？我不能使用那个网站，也许数据太大了？它只有8mb，但要粘贴到您给我的链接中需要花费很长时间…24对于%H来说是不可接受的输入-正如文档所解释的，它只接受00-23。