Basic Statistics on Numpy Arrays
Dive into the basic statistics on Numpy arrays and their functions.
We'll cover the following
Basic statistics
np.mean
It computes the arithmetic mean along the specified axis of the numpy array. It takes in an axis
parameter.

If the axis is not specified, it returns the mean of the flattened version of the array.

If the axis is specified as zero, it returns the mean across each column.

If the axis is specified as one, it returns the mean across each row.
np.std
It computes the standard deviation along the specified axis of the numpy array. It takes in an axis
parameter.

If the axis is not specified, it returns the standard deviation of the array’s flattened version.

If the axis is specified as zero, it returns the standard deviation across each column.

If the axis is specified as one, it returns the standard deviation across each row.
np.var
It computes the variance along the specified axis of the Numpy array. It takes in an axis
parameter.

If the axis is not specified, it returns the variance of the flattened version of the array.

If the axis is specified as zero, it returns variance across each column.

If the axis is specified as one, it returns variance across each row.
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