Common Python Problems - [3] Float Data Types
By JoeVu, at: 2023年1月12日14:30
1. Floating Point Arithmetic Inaccuracies
Example 1
x = 1/10
y = 1/5
z = x + y
print(z) # expected output is 0.3Output
0.30000000000000004Solution: Using the decimal module in Python, we can accurately represent decimal values and avoid floating point inaccuracies.
from decimal import Decimal
x = Decimal("1") / Decimal("10")
y = Decimal("1") / Decimal("5")
z = x + y
print(z) # expected output is 0.3Output
0.3
2. Overflow Errors
Example 1
An example of a float overflow error in Python can be seen below:
num1 = 9e309
num2 = 2
result = num1 * num2
print(result)Output
infSolution: Python will raise an OverflowError when the value of a float is too large. To avoid this error, you can use the Decimal module to handle large numbers and prevent float overflow errors. For example:
num1 = Decimal("9e309")
num2 = Decimal(2)
result = num1 * num2
print(result)Output
1.8E+3103. Rounding Errors
Example 1
# We are trying to calculate 0.1 + 0.2
x = 1/10
y = 1/5
z = x + y
print(z)Output
0.30000000000000004Solution:We can use the round() function to round off the result
x = 1/10
y = 1/5
z = x + y
rounded_z = round(z, 2)
print(rounded_z)Output
0.3
