我想将我的时间戳分成不同的列，因为我想按年对数据进行排序。我的时间戳看起来像这样：
12/08/2011 11:04:13 AM
数据样本：
BusinessName DBAName LegalOwner NameLast NameFirst ISSDTTM
NEW GARDEN RESTAURANT ZHENG JIA XIANG 12/8/11 11:04
Estragon CITY OF BOSTON De Haro Julio 1/18/12 17:01
TAIWAN CAFE Yan-Fang Zhang Pres. 8/3/12 14:54
Earl of Sandwich Earl of Sandwich (Boston) L L C 1/7/13 9:08
TAIWAN CAFE Yan-Fang Zhang Pres. 8/3/12 14:54
我试过用这个：
df = pd.read_csv("Food_Establishment_Inspections.csv", low_memory=False, index_col='datetime',
parse_dates={'year':[0]},
date_parser=lambda x:pd.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p').strftime('%Y'))
但是我收到一个错误，我在下面显示：
TypeError Traceback (most recent call last)
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in converter(*date_cols)
2661 result = tools.to_datetime(
-> 2662 date_parser(*date_cols), errors='ignore')
2663 if isinstance(result, datetime.datetime):
<ipython-input-60-4bd0710aff18> in <lambda>(x)
2 parse_dates={'year':[0]},
----> 3 date_parser=lambda x:pd.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p').strftime('%Y'))
TypeError: strptime() argument 1 must be str, not numpy.ndarray
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in converter(*date_cols)
2670 parser=date_parser,
-> 2671 dayfirst=dayfirst),
2672 errors='ignore')
pandas/src/inference.pyx in pandas.lib.try_parse_dates (pandas/lib.c:61053)()
pandas/src/inference.pyx in pandas.lib.try_parse_dates (pandas/lib.c:60951)()
<ipython-input-60-4bd0710aff18> in <lambda>(x)
2 parse_dates={'year':[0]},
----> 3 date_parser=lambda x:pd.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p').strftime('%Y'))
//anaconda/lib/python3.6/_strptime.py in _strptime_datetime(cls, data_string, format)
564 format string."""
--> 565 tt, fraction = _strptime(data_string, format)
566 tzname, gmtoff = tt[-2:]
//anaconda/lib/python3.6/_strptime.py in _strptime(data_string, format)
361 raise ValueError("time data %r does not match format %r" %
--> 362 (data_string, format))
363 if len(data_string) != found.end():
ValueError: time data 'NEW GARDEN RESTAURANT' does not match format '%m/%d/%Y %I:%M:%S %p'
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-60-4bd0710aff18> in <module>()
1 df = pd.read_csv("Food_Establishment_Inspections.csv", low_memory=False, index_col='datetime',
2 parse_dates={'year':[0]},
----> 3 date_parser=lambda x:pd.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p').strftime('%Y'))
//anaconda/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, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)
644 skip_blank_lines=skip_blank_lines)
645
--> 646 return _read(filepath_or_buffer, kwds)
647
648 parser_f.__name__ = name
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds)
399 return parser
400
--> 401 data = parser.read()
402 parser.close()
403 return data
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in read(self, nrows)
937 raise ValueError('skipfooter not supported for iteration')
938
--> 939 ret = self._engine.read(nrows)
940
941 if self.options.get('as_recarray'):
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in read(self, nrows)
1583 data = dict((k, v) for k, (i, v) in zip(names, data))
1584
-> 1585 names, data = self._do_date_conversions(names, data)
1586 index, names = self._make_index(data, alldata, names)
1587
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in _do_date_conversions(self, names, data)
1362 data, names = _process_date_conversion(
1363 data, self._date_conv, self.parse_dates, self.index_col,
-> 1364 self.index_names, names, keep_date_col=self.keep_date_col)
1365
1366 return names, data
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in _process_date_conversion(data_dict, converter, parse_spec, index_col, index_names, columns, keep_date_col)
2724
2725 _, col, old_names = _try_convert_dates(converter, colspec,
-> 2726 data_dict, orig_names)
2727
2728 new_data[new_name] = col
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in _try_convert_dates(parser, colspec, data_dict, columns)
2756 to_parse = [data_dict[c] for c in colnames if c in data_dict]
2757
-> 2758 new_col = parser(*to_parse)
2759 return new_name, new_col, colnames
2760
//anaconda/lib/python3.6/site-packages/pandas/io/parsers.py in converter(*date_cols)
2672 errors='ignore')
2673 except Exception:
-> 2674 return generic_parser(date_parser, *date_cols)
2675
2676 return converter
//anaconda/lib/python3.6/site-packages/pandas/io/date_converters.py 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-60-4bd0710aff18> in <lambda>(x)
1 df = pd.read_csv("Food_Establishment_Inspections.csv", low_memory=False, index_col='datetime',
2 parse_dates={'year':[0]},
----> 3 date_parser=lambda x:pd.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p').strftime('%Y'))
//anaconda/lib/python3.6/_strptime.py in _strptime_datetime(cls, data_string, format)
563 """Return a class cls instance based on the input string and the
564 format string."""
--> 565 tt, fraction = _strptime(data_string, format)
566 tzname, gmtoff = tt[-2:]
567 args = tt[:6] + (fraction,)
//anaconda/lib/python3.6/_strptime.py in _strptime(data_string, format)
360 if not found:
361 raise ValueError("time data %r does not match format %r" %
--> 362 (data_string, format))
363 if len(data_string) != found.end():
364 raise ValueError("unconverted data remains: %s" %
ValueError: time data 'NEW GARDEN RESTAURANT' does not match format '%m/%d/%Y %I:%M:%S %p'
答案 0 :(得分：0)
pandas.read_csv()函数有一个名为parse_dates的关键字参数。
您可以在此处详细了解：datetime dtypes in pandas read_csv
答案 1 :(得分：0)
首先，你要传递给strptime的格式，％Y％m％d％H＆＃39;并不匹配您提供的日期/时间字符串作为示例。另外，你的日期时间只在一列，为什么你在parse_dates参数中传递[1,2,3,4]？
假设您的CSV内容位于名为foo.csv（无标题）的文件中并包含：
12/08/2011 11:04:13 AM,35
12/08/2011 11:04:13 AM,82
12/08/2011 11:04:13 AM,11
12/08/2011 11:04:13 AM,21
12/08/2011 11:04:13 AM,91
12/08/2011 11:04:13 AM,44
以下内容应该有效：
df = pd.read_csv('foo.csv', parse_dates={'datetime':[0]}, date_parser=lambda x:pd.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p'))
如果您只想保留年份：
df = pd.read_csv('foo.csv', parse_dates={'year':[0]}, date_parser=lambda x:pd.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p').strftime('%Y'))