Good explanation of slicing notation Python

The slicing notation is commonly used for matrix or array operation, and in order to understand how the slicing notation for python works, here is the good note I took from Stackflow:

>>> seq[:]                # [seq[0], seq[1],   ..., seq[-1] ]
>>> seq[low:]             # [seq[low], seq[low+1], ..., seq[-1]]
>>> seq[:high]            # [seq[0],   seq[1], ..., seq[high-1]]
>>> seq[low:high]         # [seq[low], seq[low+1],..., seq[high-1]]
>>> seq[::stride]         # [seq[0],   seq[stride],..., seq[-1]]
>>> seq[low::stride]      # [seq[low], seq[low+stride],..., seq[-1]]
>>> seq[:high:stride]     # [seq[0],  seq[stride] ,...,seq[high-1]]
>>> seq[low:high:stride]  # [seq[low],seq[low+stride],.,seq[high-1]]

Of course, if (high-low)%stride != 0, then the end point will be a little lower than high-1.

If stride is negative, the ordering is changed a bit since we're counting down:

>>> seq[::-stride]        # [seq[-1],   seq[-1-stride],   ..., seq[0]    ]
>>> seq[high::-stride]    # [seq[high], seq[high-stride], ..., seq[0]    ]
>>> seq[:low:-stride]     # [seq[-1],   seq[-1-stride],   ..., seq[low+1]]
>>> seq[high:low:-stride] # [seq[high], seq[high-stride], ..., seq[low+1]]

The slicing notation is related to the ‘slice()’ function

a[start:end:step] is equivalent to a[slice(start, end, step)]

For example:

a[-1]    # last item in the array
a[-2:]   # last two items in the array
a[:-2]   # everything except the last two items

Source: https://stackoverflow.com/questions/509211/understanding-slice-notation