OTHER USEFUL NUMPY METHODS

In addition to the NumPy methods that you saw in the code samples prior to this section, the following NumPy methods are also useful.

• The method np.zeros() initializes an array with 0 values.
• The method np.ones() initializes an array with 1 value.
• The method np.empty() initializes an array with 0 values.
• The method np.arange() provides a range of numbers.
• The method np.shape() displays the shape of an object.
• The method np.reshape() <= very useful!
• The method np.linspace() <= useful in regression
• The method np.mean() computes the mean of a set of numbers.
• The method np.std() computes the standard deviation of a set of numbers.

Although the np.zeros() and np.empty() both initialize a 2D array with 0, np.zeros() requires less execution time. You could also use np.full(size, 0), but this method is the slowest of all three methods.

The reshape() method and the linspace() method are very useful for changing the dimensions of an array and generating a list...