Decimal Places in Python: Beginner to Advanced

1. Introduction

2. Basic methods for specifying decimal places in Python

2.1 Using the round() function

Syntax

round(number, digits)

• Number: The number to be rounded.
• Digits: The number of digits after the decimal point (if omitted, it rounds to an integer).

Example

# Round to 2 decimal places
result = round(3.14159, 2)
print(result)  # Output: 3.14

Notes

• Because round() works with floating-point numbers, rounding errors may occur.
• If the specified number of digits is negative, digits to the left of the decimal point are rounded.

Example

# Round to the tens place
result = round(123.456, -1)
print(result)  # Output: 120

2.2 Using the format() function and f-strings

Syntax of the format() function

"{:.digitsf}".format(number)

Example

# Format to 2 decimal places
result = "{:.2f}".format(3.14159)
print(result)  # Output: '3.14'

f-string syntax

f"{number:.digitsf}"

Example

# Use an f-string
pi = 3.14159
result = f"{pi:.2f}"
print(result)  # Output: '3.14'

Tips for choosing between them

• round() is suitable for obtaining calculation results, while format() and f-strings are convenient for displaying data.

3. How to perform advanced decimal operations

3.1 High-precision calculations using the Decimal module

Basic usage

from decimal import Decimal, getcontext

# Set precision to 3 decimal places
getcontext().prec = 3
result = Decimal('1.2345') + Decimal('2.3456')
print(result)  # Output: 3.58

Differences from round()

• Decimal prevents floating-point errors.
• You can change the precision dynamically, allowing control tailored to specific use cases.

4. Practical examples of specifying decimal places

4.1 Using for currency displays

Example

price = 123.456
formatted_price = f"${price:.2f}"
print(formatted_price)  # Output: '$123.46'

4.2 Precision control in scientific computing

Example

result = "{:.4e}".format(0.00012345)
print(result)  # Output: '1.2345e-04'

4.3 Display formatting in data analysis

Example

import pandas as pd

data = {'A': [1.123456, 2.345678], 'B': [3.567890, 4.789012]}
df = pd.DataFrame(data)

# Specify the number of decimal places to display
pd.options.display.float_format = '{:.2f}'.format
print(df)

Output

      A     B
0  1.12  3.57
1  2.35  4.79

5. Precautions for Decimal Operations and How to Choose the Best Method

Floating-point Errors

Performance

Recommendations

• Use the Decimal module for financial calculations.
• Use format() or f-strings for formatting output.
• Choose the appropriate method based on your practical needs.

6. Conclusion