Regarding datatype: dtype('<M8[ns]')

Is this dtype(<M8[ns]) same as timestamp.
Iam using " to_datetime" function to convert dates to " timestamp" dtype but im getting this dtype. Is this same.?

I would like to add one thing, when I have perform “rolling” function on top of it. It is working fine

datetime64[ns] is a general dtype, while <M8[ns] is a specific dtype. General dtypes map to specific dtypes, but may be different from one installation of NumPy to the next.

On a machine whose byte order is little endian, there is no difference between np.dtype('datetime64[ns]') and np.dtype('<M8[ns]') :

In [6]: np.dtype('datetime64[ns]') == np.dtype('<M8[ns]')
Out[6]: True

However, on a big endian machine, np.dtype('datetime64[ns]') would equal np.dtype('>M8[ns]') .

So datetime64[ns] maps to either <M8[ns] or >M8[ns] depending on the endian-ness of the machine.

There are many other similar examples of general dtypes mapping to specific dtypes: int64 maps to <i8 or >i8 , and int maps to either int32 or int64 depending on the bit architecture of the OS and how NumPy was compiled.

Source :

Difference between data type ‘datetime64[ns]’ and ‘<M8[ns]’? - Stack Overflow