Lambda functions and map filter reduce functions in Python

Python Lambda functions and map filter reduce functions

Lambda expressions:-
function_name = lambda input_parameters  :  output_parameters
str_to_list = lambda x: x.split()
large = lambda x, y : x if x >y else y
proper = lambda x, y: x[0].upper()+x[1:] +' '+ y[0].upper()+y[1:]


Built-in functions:-

map function
map(function_to_apply, list_of_inputs) # function will be applied to all elements of list
' '.join(map(str.capitalize, str9.split(' ')))
a = list(map(int, input().rstrip().split()))
newcode = map(ord, co.co_code)
squares = list(map(lambda x: x**2, range(10))) # output is not list in Python 3, so convert it manually
print(list(map(lambda x, y : x+y, sums_list, sums_list2)))
for i in map(function, list): print(i)
df['Diabetes'] = df['Diabetes'].map({'Yes': 1, 'No': 0})

filter function
filter(function_to_apply, list_of_inputs) # filter out all the elements of a list
filter(iseven, range(100))
map(lambda e: e**2, filter(lambda e: type(e) == types.IntType, a_list))
less_than_zero = list(filter(lambda x: x < 0, number_list))
sa = list(filter(lambda x: x.startswith('s') and x.endswith('a'), input_list))

reduce function
reduce(function_to_apply, list_of_inputs) # aggregate operation
from functools import reduce
product = reduce((lambda x, y: x * y), [1, 2, 3, 4])
>>> reduce(lambda x, y: x+y, range(1,101))
print(reduce(lambda a, b: a+' '+ b, input_list))


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