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Python map() with Lambda Function
By IncludeHelp Last updated : December 08, 2024
Python map() with Lambda Function
The map() function is used to apply the function to all items of an iterable collection like list, tuple etc and it returns the list of the result after performing the functionality defined in the applied function.
The lambda function is an anonymous function - that means the function which does not have any name.
Implementing map() with lambda function
Given a list of temperatures and we have to convert 1) all the values in Celsius and 2) all the values in Fahrenheit - using map() with lambda.
Approach 1: Using normal way
# function definition to convert temp. from c to f
def ctof(c):
f = 9 / 5 * c + 32
return f
# function definition to convert temp. from f to c
def ftoc(f):
c = 5 / 9 * (f - 32)
return c
# list of the values
temp = [12, 45, 6, 78, 5, 26, 67]
print("Orignal Data : ", temp)
# list declration to store temp. in C
cel = []
for t in temp:
x = ftoc(t)
cel.append(x)
print("Celcuis Data : ", cel)
# list declration to store temp. in F
far = []
for t in temp:
x = ctof(t)
far.append(x)
print("Farenhiet Data : ", far)
Output
Orignal Data : [12, 45, 6, 78, 5, 26, 67]
Celcuis Data : [-11.11111111111111, 7.222222222222222, -14.444444444444445,
25.555555555555557, -15.0, -3.3333333333333335, 19.444444444444446]
Farenhiet Data : [53.6, 113.0, 42.8, 172.4, 41.0,
78.80000000000001, 152.60000000000002]
Approach 2: Using map() with lambda
# list of the values
temp = [12, 45, 6, 78, 5, 26, 67]
print("Orignal Data : ", temp)
# converting values to cel using map and lambda
cel = list(map(lambda f: 5 / 9 * (f - 32), temp))
print("Celcuis Data : ", cel)
# converting values to far using map and lambda
far = list(map(lambda c: 9 / 5 * c + 32, temp))
print("Farenhiet Data : ", far)
Output
Orignal Data : [12, 45, 6, 78, 5, 26, 67]
Celcuis Data : [-11.11111111111111, 7.222222222222222, -14.444444444444445,
25.555555555555557, -15.0, -3.3333333333333335, 19.444444444444446]
Farenhiet Data : [53.6, 113.0, 42.8, 172.4, 41.0,
78.80000000000001, 152.60000000000002]