# Numpy recarray.flatten() function | Python

• Last Updated : 29 Nov, 2022

In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is [(a, int), (b, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr[‘a’] and arr[‘b’]. Record arrays allow the fields to be accessed as members of the array, using arr.a and arr.b. numpy.recarray.flatten() function returns record arrays in one dimension.

Syntax : numpy.recarray.flatten(order=’C’) Parameters: order : [[‘C’, ‘F’, ‘A’, ‘K’], optional] ‘C’ means to flatten in row-major (C-style) order. ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten in the order the elements occur in memory. The default is ‘C’. Return : A copy of the input array, flattened to one dimension. Code #1 :

## Python3

 `# Python program explaining``# numpy.recarray.flatten() method`` ` `# importing numpy as geek``import` `numpy as geek`` ` `# creating input array with 2 different field``in_arr ``=` `geek.array([[(``5.0``, ``2``), (``3.0``, ``-``4``), (``6.0``, ``9``)],``                     ``[(``9.0``, ``1``), (``5.0``, ``4``), (``-``12.0``, ``-``7``)]],``                     ``dtype ``=``[(``'a'``, ``float``), (``'b'``, ``int``)])` `print` `("``Input` `array : ", in_arr)`` ` `# convert it to a record array,``# using arr.view(np.recarray)``rec_arr ``=` `in_arr.view(geek.recarray)``print``("Record array of ``float``: ", rec_arr.a)``print``("Record array of ``int``: ", rec_arr.b)`` ` `# applying recarray.flatten methods``# to float record in Fortran order``out_arr1 ``=` `rec_arr.a.flatten(order ``=``'F'``)``print` `("Output ``float` `flattened array ``in` `Fortran order: ", out_arr1)`` ` `# applying recarray.flatten methods``# to float record array in default order``out_arr2 ``=` `rec_arr.a.flatten()``print` `("Output ``float` `flattenedarray ``in` `default order : ", out_arr2)` `# applying recarray.flatten methods``# to int record in 'A' order``out_arr3 ``=` `rec_arr.b.flatten(order ``=``'A'``)``print` `("Output ``int` `flattened array ``in` `A order: ", out_arr3)`` ` `# applying recarray.flatten methods``# to float record array in 'K' order``out_arr4 ``=` `rec_arr.b.flatten(order ``=``'K'``)``print` `("Output intt flattened array ``in` `K order : ", out_arr4)`

Output:

```Input array :  [[(  5.,  2) (  3., -4) (  6.,  9)]
[(  9.,  1) (  5.,  4) (-12., -7)]]
Record array of float:  [[  5.   3.   6.]
[  9.   5. -12.]]
Record array of int:  [[ 2 -4  9]
[ 1  4 -7]]
Output float flattened array in Fortan order:  [  5.   9.   3.   5.   6. -12.]
Output float flattenedarray in default order :  [  5.   3.   6.   9.   5. -12.]
Output int flattened array in A order:  [ 2 -4  9  1  4 -7]
Output intt flattened array in K order :  [ 2 -4  9  1  4 -7]```

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