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In this lecture we will learn:
Filter Map and Reduce in Python
Use of filter(), map() and reduce() functions
How lambda function can be used with filter map and reduce
Syntax of Filter, Map and reduce function
Difference between filter(), map() and reduce() functions
#1
Lambda function can be used with these three functions:
1. filter()
2. map()
3. reduce()
#2
filter() function will take a list and do filtering and give values.
filter() takes a sequence and also returns a sequence.
filter() function takes two arguments: function and iterable.
filter(func, iterable)
We have to give the definition of a function that we have passed as a condition in an argument.
The defined function should return a value of either True or False based on the condition.
Then, filter() will take the value that is returned by the defined function and does perform filtering based on this value.
In the defined function, we need only two things i.e, a variable and an expression. So, we can also use the lambda function instead of using the normal function to define the condition for a filter.
-Lambda reduces the number of lines of code and makes it more precise.
Filter() simply returns the iterable passed to it.
#3
map() function is used when we want to change the value of every element of a list.
map() function also takes two arguments i.e., a function and an iterable.
map(func, *iterables)
To get the result as a list, the built-in list() function can be called on the map object.
We have to define a function that we have passed as a condition in an argument.
The defined function should return any value.
The lambda function can also be used in an argument as a function instead of defining the normal function for the logic.
map() function returns a list. The function returns a map object which is a generator object.
#4
reduce() function is used to reduce the number of values from a list.
reduce() function belongs to a module known as functools.
We have to import the module functools from the library to use the reduce function.
reduce() also take two arguments i.e., a function and a sequence.
reduce(func, iterable[, initial])
We have to give the definition of a function that we have passed as a condition in an argument.
The lambda function can also be used in an argument as a function instead of defining the normal function for the logic.
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