Python can also be used with functional programming with functions such as map<\/strong>, filter<\/strong>, and reduce<\/strong> which helps in efficient transformations, filtering, and aggregations on data collections.<\/p>\n\n\n\n These functions enable efficient data manipulation and make code more concise. They\u2019re helpful in tasks like applying adjustments to a list of barangay donations or selecting donations above a certain amount. By using map, filter, and reduce<\/strong> you can perform these actions in one line, improving readability and functionality.<\/p>\n\n\n\n <\/p>\n\n\n\n Let’s say we want to filter, increase, and calculate the donations into a barangay we can do it using map, filter, and reduce.<\/p>\n\n\n\n <\/p>\n\n\n\n\n
Why use map, filter, and reduce?<\/h2>\n\n\n\n
Syntax<\/h2>\n\n\n\n
map(function, iterable)\nfilter(function, iterable)\nreduce(function, iterable)<\/pre><\/div>\n\n\n\n
Example<\/h2>\n\n\n\n
# Import reduce from functools\nfrom functools import reduce\n\ndonatios = [1000, 1500, 500, 2000, 2500]\n\n# Increase each donation by 10% using map\nupdated_donatios = list(map(lambda x: x*1.1,donations))\n\n# Filter donations abouve Php 2000\nlarge_donations = list(filter(lambda x : x > 2000, updated_donations))\n\n# Calculate the total donation using reduce\ntotal_donation = reduce(lambda x, y: x + y, updated_donations)\n\nprint("Updated Donations:", updated_donations) # Updated amounts\nprint("Large Donations:", large_donations) # Donations above 2000\nprint("Total Donation:", total_donation) # Sum of all donations<\/pre><\/div>\n\n\n\n