# How to suppress the use of scientific notations for small numbers using NumPy?

• Last Updated : 24 Oct, 2020

Sometimes we have elements that are in scientific notations, and we have to suppress the scientific notation for simplicity. For this purpose, we call a function named as numpy.set_printoptions(). This function will help to suppress the scientific notation and display number to a certain precision.

Syntax: numpy.set_printoptions(precision=None, threshold=None, edgeitems=None, linewidth=None, suppress=None, nanstr=None, infstr=None, formatter=None, sign=None, floatmode=None, *, legacy=None)

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Parameters:

• precision: Number of digits of precision for floating point output (default 8)
• suppress: If True, always print floating point numbers using fixed point notation, if False, then scientific notation is used when absolute value of the smallest number is < 1e-4

Rest of the parameters are optional.

Example 1:

## Python3

 `# Importing Numpy library ``import` `numpy as np`` ` `# Creating a 1-D Numpy array``num ``=` `np.array([``1.8e``-``10``, ``1.586``, ``150.45``, ``0.2855``]) `` ` `# Suppressing 1-D numpy array with precision 2 ``# using numpy.set_printoptions()``print``(``"Numpy array values with precision 2:\n"``)``np.set_printoptions(precision ``=` `2``, suppress ``=` `True``)``print``(num)`

Output: In the above example, we suppress the scientific notations for the elements of 1-D NumPy array with precision 2.

Example 2:

## Python3

 `# Importing Numpy library ``import` `numpy as np`` ` `# Creating a 2-D Numpy array``num ``=` `np.array([[``3.1415``, ``2.7182``],``                 ``[``6.6260e``-``34``, ``6.6743e``-``11``]]) `` ` `# Suppressing 2-D numpy array with precision 3 ``# using numpy.set_printoptions()``print``(``"Numpy array values with precision 3:\n"``)``np.set_printoptions(precision ``=` `3``, suppress ``=` `True``)``print``(num)`

Output: In the above example, we suppress the scientific notations for the elements of 2-D NumPy array with precision 3.

Example 3:

## Python3

 `# Importing Numpy library ``import` `numpy as np`` ` `# Creating a 3-D Numpy array``num ``=` `np.array([[[``3.141527``, ``2.718283``],``                 ``[``6.6268574``, ``6.6743e``-``11``]],``                ``[[``34.8454``, ``8.6260e``-``34``],``                 ``[``7``, ``8``]]]) `` ` `# Suppressing 3-D numpy array with precision 4``# using numpy.set_printoptions()``print``(``"Numpy array values with precision 4:\n"``)``np.set_printoptions(precision ``=` `4``, suppress ``=` `True``)``print``(num)`

Output: In the above example, we suppress the scientific notations for the elements of 3-D NumPy array with precision 4.

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