in [ ]int_array astype(calibers dtypeout[ ]array( ]there are shorthand type code strings you can also use to refer to dtypein [ ]empty_uint np empty( dtype=' 'in [ ]empty_uint out[ ]array( ]dtype=uint calling astype always creates new array ( copy of the data)even if the new dtype is the same as the old dtype it' worth keeping in mind that floating point numberssuch as those in float and float arraysare only capable of approximating fractional quantities in complex computationsyou may accrue some floating point errormaking comparisons only valid up to certain number of decimal places operations between arrays and scalars arrays are important because they enable you to express batch operations on data without writing any for loops this is usually called vectorization any arithmetic operations between equal-size arrays applies the operation elementwisein [ ]arr np array([[ ][ ]]in [ ]arr out[ ]array([ ] ]]in [ ]arr arr out[ ]array([ ] ]]in [ ]arr arr out[ ]array([ ] ]]arithmetic operations with scalars are as you would expectpropagating the value to each elementin [ ] arr out[ ]array([ ] ]]in [ ]arr * out[ ]array([ ] ]]the numpy ndarraya multidimensional array object www it-ebooks info