Map Function
Map takes a function and a collection of items.
It makes a new, empty collection, runs the function on each item in the original collection and inserts each return value into the new collection. It returns the new collection.
This is a simple map that takes a list of names and returns a list of the lengths of those names:
name_lengths = map(len, ["Mary", "Isla", "Sam"])
print(name_lengths) =>[4, 4, 3]
map(fun, iter)
fun : It is a function to which map passes each element of given iterable.
iter : It is a iterable which is to be mapped.
Reduce Function
Reduce takes a function and a collection of items. It returns a value that is created by combining the items.
This is a simple reduce. It returns the sum of all the items in the collection.
total = reduce(lambda a, x: a + x, [0, 1, 2, 3, 4])
print(total) =>10
Syntax:
filter(function, iterable)
function: A Function to be run for each item in the iterable
iterable: The iterable to be filtered
Example:
def my_func3(x,y):
return x+y
from functools import reduce
reduce(my_func3,[1,2,3,4,5])
Filter Function
Filter takes a function and a collection. It returns a collection of every item for which the function returned True.
arr=[1,2,3,4,5,6]
[i for i in filter(lambda x:x>4,arr)]
# outputs[5,6]
Syntax:
reduce(function, iterable)
function: A Function to be run for each item in the iterable
iterable: The iterable to be reduced
Example:
ages = [5, 12, 17, 18, 24, 32]
def myFunc(x):
if x < 18:
return False
else:
return True
adults = filter(myFunc, ages)
for x in adults:
print(x)
>> 18
24
32
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