NumPy advanced array manipulation

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·reshape()

In many cases, you can convert an array from one shape to another without copying any data. To do this, pass a tuple indicating the new shape to the reshape array instance method.

 

A multidimensional array can also be reshaped:

 

One of the passed shape dimensions can be -1, in which case the value used for that dimension will be inferred from the data:

 

The opposite operation of reshape from one-dimensional to a higher dimension is typically known as flattening or raveling

·ravel()

The ravel method does not produce a copy of the underlying values if the values in the result were contiguous in the original array

 

·flatten()

The flatten method behaves like ravel except it always returns a copy of the data

·transpose()

For higher dimensional arrays, transpose will accept a tuple of axis numbers to permute the axes:

 

np.concatenate

numpy.concatenate takes a sequence (tuple, list, etc.) of arrays and joins them together in order along the input axis

 

np.split

split slices apart an array into multiple arrays along an axis

 

2 equal division where axis = 1

 

Reference

Python for Data Analysis Second Edition