that if you have two-dimensional array of datathe items in each row of the array are stored in adjacent memory locations the alternative to row major ordering is column major orderwhich means that (you guessed itvalues within each column of data are stored in adjacent memory locations for historical reasonsrow and column major order are also know as and fortran orderrespectively in fortran the language of our forebearsmatrices were all column major functions like reshape and ravelaccept an order argument indicating the order to use the data in the array this can be 'cor 'fin most cases (there are also less commonlyused options 'aand ' 'see the numpy documentationthese are illustrated in figure - in [ ]arr np arange( reshape(( )in [ ]arr out[ ]array([ ] ] ]]in [ ]arr ravel(out[ ]array( ]in [ ]arr ravel(' 'out[ ]array( ]reshaping arrays with more than two dimensions can be bit mind-bending the key difference between and fortran order is the order in which the dimensions are walkedc row major ordertraverse higher dimensions first ( axis before advancing on axis fortran column major ordertraverse higher dimensions last ( axis before advancing on axis concatenating and splitting arrays numpy concatenate takes sequence (tuplelistetc of arrays and joins them together in order along the input axis in [ ]arr np array([[ ][ ]]in [ ]arr np array([[ ][ ]]in [ ]np concatenate([arr arr ]axis= out[ ]array([ ] ]advanced array manipulation www it-ebooks info