on disk can then be loaded using np loadin [ ]np load('some_array npy'out[ ]array([ ]you save multiple arrays in zip archive using np savez and passing the arrays as keyword argumentsin [ ]np savez('array_archive npz' =arrb=arrwhen loading an npz fileyou get back dict-like object which loads the individual arrays lazilyin [ ]arch np load('array_archive npz'in [ ]arch[' 'out[ ]array([ ]saving and loading text files loading text from files is fairly standard task the landscape of file reading and writing functions in python can be bit confusing for newcomerso will focus mainly on the read_csv and read_table functions in pandas it will at times be useful to load data into vanilla numpy arrays using np loadtxt or the more specialized np genfromtxt these functions have many options allowing you to specify different delimitersconverter functions for certain columnsskipping rowsand other things take simple case of comma-separated file (csvlike thisin [ ]!cat array_ex txt , , , ,- ,- , - , ,- , - , ,- , , , ,- - , , , this can be loaded into array like soin [ ]arr np loadtxt('array_ex txt'delimiter=','in [ ]arr out[ ]array([ ] - - ][- - ][- - ] - ][- ]]np savetxt performs the inverse operationwriting an array to delimited text file genfromtxt is similar to loadtxt but is geared for structured arrays and missing data handlingsee for more on structured arrays numpy basicsarrays and vectorized computation www it-ebooks info