Python Study Note: NumPy array - 2

There are more about the ndarray --- its operations.

1. Array conversion

    ndarray.tolist()   ---   Return the array as a (possibly nested) list.

    ndarray.astype(dtype[, order, casting, ...])   ---   Copy of the array, cast to a specified type.
    ndarray.copy([order])   ---   Return a copy of the array.
    ndarray.fill(value)   ---   Fill the array with a scalar value.

2. Shape manipulation

    ndarray.reshape(shape[, order])   ---   Returns an array containing the same data with a new shape.

    ndarray.resize(new_shape[, refcheck])   ---   Change shape and size of array in-place.

    ndarray.flatten([order])   ---   Return a copy of the array collapsed into one dimension.

    ndarray.ravel([order])   ---   Return a flattened array.

   Difference between reshape and resize is: reshape does not affect the raw array; resize directly change the raw array

   Difference between flatten and ravel is: the ravel array's entries are affected by the raw array's value change; the flatten array is a totally different new array.

3. Item selection

    ndarray.sort([axis, kind, order])   ---   Sort an array, in-place.

    ndarray.argsort([axis, kind, order])   ---   Returns the indices that would sort this array.

    ndarray.repeat(repeats[, axis])   ---   Repeat elements of an array.

4. Calculation

    The calculation functions are quite straightforward: ndarray.func([axis, out]), however, remember that there are one major parameters: axis. 

    If axis is None (the default), the array is treated as a 1-D array and the operation is performed over the entire array.

    If axis is an integer, then the operation is done over the given axis (for each 1-D subarray that can be created along the given axis).