I am trying to upload a huge csv file using this script below but getting error
header = ["SKU","STORAGE_AREA","MOVE_TYPE","ORDER_NO","ORDER_ITEM","PICK_VOL","M_UNIT","DATE"]
d_type = {"SKU":"str","STORAGE_AREA":"str","MOVE_TYPE":"str","ORDER_NO":"category","ORDER_ITEM":"str","PICK_VOL":"int","M_UNIT":"str","DATE":"datetime"}
product = pd.read_csv('pick_data.csv', encoding='latin-1', sep=',', index_col=False, header=None, names=header, dtype=d_type)
error:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Input In [68], in <cell line: 3>()
1 header = ["SKU","STORAGE_AREA","MOVE_TYPE","ORDER_NO","ORDER_ITEM","PICK_VOL","M_UNIT","DATE"]
2 d_type = {"SKU":"str","STORAGE_AREA":"str","MOVE_TYPE":"str","ORDER_NO":"category","ORDER_ITEM":"str","PICK_VOL":"int","M_UNIT":"str","DATE":"datetime"}
----> 3 product = pd.read_csv('pick_data.csv', encoding='latin-1', sep=',', index_col=False, header=None, names=header, dtype=d_type)
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\util\_decorators.py:311, in deprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper(*args, **kwargs)
305 if len(args) > num_allow_args:
306 warnings.warn(
307 msg.format(arguments=arguments),
308 FutureWarning,
309 stacklevel=stacklevel,
310 )
--> 311 return func(*args, **kwargs)
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parsers\readers.py:680, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, error_bad_lines, warn_bad_lines, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)
665 kwds_defaults = _refine_defaults_read(
666 dialect,
667 delimiter,
(...)
676 defaults={"delimiter": ","},
677 )
678 kwds.update(kwds_defaults)
--> 680 return _read(filepath_or_buffer, kwds)
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parsers\readers.py:575, in _read(filepath_or_buffer, kwds)
572 _validate_names(kwds.get("names", None))
574 # Create the parser.
--> 575 parser = TextFileReader(filepath_or_buffer, **kwds)
577 if chunksize or iterator:
578 return parser
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parsers\readers.py:933, in TextFileReader.__init__(self, f, engine, **kwds)
930 self.options["has_index_names"] = kwds["has_index_names"]
932 self.handles: IOHandles | None = None
--> 933 self._engine = self._make_engine(f, self.engine)
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parsers\readers.py:1235, in TextFileReader._make_engine(self, f, engine)
1232 raise ValueError(msg)
1234 try:
-> 1235 return mapping[engine](f, **self.options)
1236 except Exception:
1237 if self.handles is not None:
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parsers\c_parser_wrapper.py:74, in CParserWrapper.__init__(self, src, **kwds)
64 for key in (
65 "storage_options",
66 "encoding",
(...)
70 "warn_bad_lines",
71 ):
72 kwds.pop(key, None)
---> 74 kwds["dtype"] = ensure_dtype_objs(kwds.get("dtype", None))
75 self._reader = parsers.TextReader(src, **kwds)
77 self.unnamed_cols = self._reader.unnamed_cols
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parsers\c_parser_wrapper.py:416, in ensure_dtype_objs(dtype)
411 """
412 Ensure we have either None, a dtype object, or a dictionary mapping to
413 dtype objects.
414 """
415 if isinstance(dtype, dict):
--> 416 return {k: pandas_dtype(dtype[k]) for k in dtype}
417 elif dtype is not None:
418 return pandas_dtype(dtype)
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parsers\c_parser_wrapper.py:416, in <dictcomp>(.0)
411 """
412 Ensure we have either None, a dtype object, or a dictionary mapping to
413 dtype objects.
414 """
415 if isinstance(dtype, dict):
--> 416 return {k: pandas_dtype(dtype[k]) for k in dtype}
417 elif dtype is not None:
418 return pandas_dtype(dtype)
File C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\dtypes\common.py:1777, in pandas_dtype(dtype)
1774 # try a numpy dtype
1775 # raise a consistent TypeError if failed
1776 try:
-> 1777 npdtype = np.dtype(dtype)
1778 except SyntaxError as err:
1779 # np.dtype uses `eval` which can raise SyntaxError
1780 raise TypeError(f"data type '{dtype}' not understood") from err
TypeError: data type 'datetime' not understood
tried to change data types several times but still error