パンダでタイムスタンプを別々の列に分割するにはどうすればよいですか？

Question

年ごとにデータを並べ替えたいので、タイムスタンプを別の列に分けたいと思います。データの

12/08/2011 11:04:13 AM 

サンプル：私のタイムスタンプは次のようになります

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')) 

しかし、私は以下の表示されるエラーを受け付けております：

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 

私はこれを使用してみました

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' 

Answer 1

pandas.read_csv()関数のキーワード引数はparse_datesです。あなたがここにそれについての詳細を読むことができ

：手始めにdatetime dtypes in pandas read_csv

Answer 2

を、あなたがのstrptimeし渡しているフォーマットは、「％Yの％mは％dは％H」は、あなたのように与えた日付/時刻文字列と一致していません例。また、datetimeは1つの列にしかないので、なぜparse_dates引数に[1,2,3,4]を渡していますか？

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 

以下は動作するはずです：：

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')) 

あなただけ保持したい場合は、あなたのCSVの内容はfoo.csv（ヘッダーなし）と呼ばれるファイルであると仮定すると、含まれてい

年：

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'))