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# Averaging over every N elements of a Numpy Array

• Difficulty Level : Expert
• Last Updated : 16 May, 2021

In this article, we will learn how to find the average over every n element of a NumPy array. For doing our task, we will some inbuilt methods provided by NumPy module which are as follows:

• numpy.average() to calculate the average i.e the sum of all the numbers divided by the number of elements
• numpy.reshape() to reshape the array taking n elements at a time without changing the original data
• numpy.mean() to calculate the average as mean is nothing but the sum of elements divided by the number of elements

Example 1: Average over a 1-D array

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## Python3

 `import` `numpy as np`` ` `# converting list to numpy array``givenArray ``=` `np.array([``6``, ``5``, ``4``, ``3``, ``2``, ``1``, ``9``,``                       ``8``, ``7``, ``12``, ``11``, ``10``, ``15``, ``                       ``14``, ``13``])`` ` `# here we took 3 as our input``n ``=` `3`` ` `# calculates the average``avgResult ``=` `np.average(givenArray.reshape(``-``1``, n), axis``=``1``)`` ` `print``(``"Given array:"``)``print``(givenArray)`` ` `print``(``"Averaging over every "``, n, ``" elements of a numpy array:"``)``print``(avgResult)`

Output: Note: N should be an integer multiple of the size of 1d array.

Example 2: Average over a 1-D array(Row-wise)

Here we have taken an array of dimensions (5,3) i.e it has 5 rows and 3 columns. Since the axis=1, it will reshape the elements in groups of n and then calculate the average row-wise using axis=1.

## Python3

 `import` `numpy as np`` ` `# converting list to numpy array``givenArray ``=` `np.array([[``60``, ``50``, ``40``], [``30``, ``20``, ``10``], [``90``, ``80``,``70``],``                       ``[``120``, ``110``, ``100``], [``150``, ``140``, ``130``]])`` ` `# here we took 5 as our input``n ``=` `5`` ` `# calculates the average``avgResult ``=` `np.average(givenArray.reshape(``-``1``, n), axis``=``1``)`` ` `print``(``"Given array:"``)``print``(givenArray, ``"\n"``)`` ` `print``(``"Dimensions of given array:"``, givenArray.shape, ``"\n"``)`` ` `print``(``"Averaging over every "``, n, ``" elements of a numpy array:"``)``print``(avgResult)`

Output: Example 3: Average over a 1-D array(Column-wise)

Remember we need to give the axis=1 only then it can group elements row-wise starting from the 0th index. Now if we change the axis value to 0, then after reshaping in groups of n, it will perform the average operation column-wise as given below which will not give us the desired result. It is best if we want to calculate the average column-wise.

## Python3

 `import` `numpy as np`` ` `# converting list to numpy array``givenArray ``=` `np.array([[``60``, ``50``, ``40``], [``30``, ``20``, ``10``], [``90``, ``80``, ``70``],``                       ``[``120``, ``110``, ``100``], [``150``, ``140``, ``130``]])`` ` `# here we will calculate average``# over every 5 elements``n ``=` `5`` ` `# calculates the average``avgResult ``=` `np.average(givenArray.reshape(``-``1``, n), axis``=``0``)`` ` `print``(``"Given array:"``)``print``(givenArray, ``"\n"``)`` ` `print``(``"Dimensions of given array:"``, givenArray.shape, ``"\n"``)`` ` `print``(``"Averaging over every "``, n, ``" elements of a numpy array:"``)``print``(avgResult)`

After reshaping the 2D array it looks like below: Then performing the average column wise we get the answer.

Output: Example 4: Average over a 1-D array(Column-wise without reshaping)

Note here that taking axis=0 we cannot perform the average row-wise over every n element. It will just calculate the average of each column separately. The below code will calculate the average over every column element.

## Python3

 `import` `numpy as np``# converting list to numpy array``givenArray ``=` `np.array([[``60``, ``50``, ``40``], [``30``, ``20``, ``10``], [``90``, ``80``,``70``],``                       ``[``120``, ``110``, ``100``], [``150``, ``140``, ``130``]])`` ` `# here we will calculate average over``# every 5 elements``n ``=` `5`` ` `# calculates the average``avgResult1 ``=` `givenArray.mean(axis``=``0``)`` ` `print``(``"Given array:"``)``print``(givenArray, ``"\n"``)`` ` `print``(``"Dimensions of given array:"``, givenArray.shape, ``"\n"``)`` ` `print``(``"Averaging over every "``, n, ``" elements of a numpy array:"``)``print``(avgResult1)`

Output: My Personal Notes arrow_drop_up