Count of elements matching particular condition in Python

In this article, we will see how to count elements in a Python list that match a particular condition. We'll explore different approaches to filter and count elements based on specific criteria.

Using Generator Expression with sum()

This approach uses a generator expression with an if condition inside the sum() function. The expression generates 1 for each element that matches the condition ?

Example

days = ['Mon', 'Wed', 'Mon', 'Tue', 'Thu']

# Given list
print("Given list:")
print(days)

# Count elements that are 'Mon' or 'Wed'
count = sum(1 for day in days if day in ('Mon', 'Wed'))
print("Number of times the condition is satisfied:")
print(count)

Given list:
['Mon', 'Wed', 'Mon', 'Tue', 'Thu']
Number of times the condition is satisfied:
3

Using map() with lambda

Here we use map() with a lambda function to apply the condition to each element. The lambda returns True (1) or False (0), and sum() counts the True values ?

Example

days = ['Mon', 'Wed', 'Mon', 'Tue', 'Thu']

# Given list
print("Given list:")
print(days)

# Count using map and lambda
count = sum(map(lambda day: day in ('Mon', 'Wed'), days))
print("Number of times the condition is satisfied:")
print(count)

Given list:
['Mon', 'Wed', 'Mon', 'Tue', 'Thu']
Number of times the condition is satisfied:
3

Using reduce()

The reduce() function applies a function cumulatively to all elements in the list. We use it with a lambda function that accumulates the count of matching elements ?

Example

from functools import reduce

days = ['Mon', 'Wed', 'Mon', 'Tue', 'Thu']

# Given list
print("Given list:")
print(days)

# Count using reduce
count = reduce(lambda total, day: total + (day in ('Mon', 'Wed')), days, 0)
print("Number of times the condition is satisfied:")
print(count)

Given list:
['Mon', 'Wed', 'Mon', 'Tue', 'Thu']
Number of times the condition is satisfied:
3

Comparison of Methods

Conclusion

The generator expression with sum() is the most readable and efficient approach for counting elements. Use map() for functional programming style, and reduce() for complex accumulation patterns.