NumPy: Set the precision value to 6 and print the array of scientific notation numbers

Last update on August 29 2025 12:45:23 (UTC/GMT +8 hours)

Represent values in scientific notation with precision.

Write a NumPy program to create an array using scientific notation numbers. Set the precision value to 6 and print the array.

Sample Solution:

Python Code:

# Importing NumPy library
import numpy as np

# Creating an array with scientific notation values
nums = np.array([1.2e-7, 1.5e-6, 1.7e-5])

# Displaying the original array
print("Original arrays:")
print(nums)

# Setting the precision value to 10 and suppressing the scientific notation
np.set_printoptions(suppress=True, precision=10)

# Displaying the array with updated precision and suppressed scientific notation
print("Set the precision value to 10:")
print(nums)

Sample Output:

Original arrays:
[1.2e-07 1.5e-06 1.7e-05]
Set the precision value to 10:
[0.00000012 0.0000015  0.000017  ]

Explanation:

In the above exercise -

nums = np.array([1.2e-7, 1.5e-6, 1.7e-5]) creates a NumPy array with three small floating-point numbers in scientific notation.

np.set_printoptions(suppress=True, precision=10) sets the global print options for NumPy. The suppress=True option disables the use of scientific notation when printing NumPy arrays, and the precision=10 option sets the number of decimal places displayed to 10.

print(nums): Finally print() function prints the generated array.

For more Practice: Solve these Related Problems:

Write a NumPy program to create an array using scientific notation and adjust the print precision using np.set_printoptions with suppress=False.
Create a function that converts an array of numbers into scientific notation strings with a specified precision.
Implement a solution that displays both the raw scientific notation and a formatted version with controlled decimal places.
Test the notation conversion on an array with very small numbers to verify that the output uses scientific notation with the desired precision.

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