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<h4>Introduction:</h4>
<p>In this blog we will talk about some really useful functions which will easily do some processes in your code for you. Functions are as follows:</p>
<ul>
<li>Map</li>
<li>Filter</li>
<li>Reduce</li>
</ul>
<p><strong>Note:&nbsp;</strong>All these three functions return an object so we have to type cast it to list with the help of list() function.</p>
<h4>Map:</h4>
<p>Map function takes <strong>two arguments</strong>. It takes a <strong>function name and a list</strong> and it automatically applies that function on all the list items and returns an object. We don&rsquo;t have to make a for loop and pass those list items through it one by one. Also with the help of this function, code becomes extremely small. Here is an example:</p>
<h5>Without map function:</h5>
<pre class="language-python"><code>def square(n):
    return n**2

h1 = [1,2,4,5,7]
sq =[]
for item in h1:
    sq.append(item**2)
print(sq)</code></pre>
<p>&lt;|AD|&gt;</p>
<h5>With map function:</h5>
<pre class="language-python"><code>def square(n):
    return n**2

h1 = [1,2,4,5,7]
sq = list(map(square, h1))
print(sq)</code></pre>
<p>You can also pass list through <strong>multiple functions</strong> with the help of map function.</p>
<h4>Filter:</h4>
<p>It does what it is named, it filters. It filters a list for you according to the function you gave it. It takes two arguments, <strong>function name and list name</strong>. Function should <strong>return true or false</strong>. It takes the list and for whatever list item the function <strong>returns true</strong>, it filters all those items and shows you. Here is an example:</p>
<pre class="language-python"><code>def greater_than_2(n):
    if n&gt;2:
        return True
    else:
        return False

h1 = [1,2,3,4,5,6,7,-2,-5]
greater_th_2 = list(filter(greater_than_2, h1))
print(greater_th_2)</code></pre>
<h4>Reduce:</h4>
<p>We can&rsquo;t directly use reduce like map or filter function. We have to <strong>import it first</strong>. To import it write:</p>
<pre class="language-python"><code>from functools import reduce</code></pre>
<p>It also takes a function and a list and applies that function on each list item but the difference is, other two functions separately applied the given function on every list item but this function applies it like a chain on every list item. Here is an example for you to understand better:</p>
<pre class="language-python"><code>from functools import reduce

def string_sum(a, b):
    return a+b

newstring = reduce(string_sum, ["You", " are", " on", " codewithharry"])
print(newstring)</code></pre>
<p>&lt;|AD|&gt;</p>
<p>Output:</p>
<pre class="language-python"><code>You are on codewithharry</code></pre>
<p>It could be used like this too:</p>
<pre class="language-python"><code>from functools import reduce

def sum_num(a, b):
    return a+b

li = reduce(sum_num, [1,2,3,4])
print(li)</code></pre>
<p>Output:</p>
<pre class="language-python"><code>10</code></pre>
<p>Like this it links the next list element with the previous output.</p>
<h4>#tut6a.py file as described in the video</h4>
<pre class="language-python"><code>#Map function

# map(function_to_apply, list of inputs)

def square(n):
    return n**2

h1 = [1,2,4,5,7]
# sq =[]
# for item in h1:
#     sq.append(item**2)

sq = list(map(square, h1))
print(sq)

</code></pre>
<h4>#tut6b.py file as described in the video</h4>
<pre class="language-python"><code>def greater_than_2(n):
    if n&gt;2:
        return True
    else:
        return False

h1 = [1,2,3,4,5,6,7,-2,-5]
greater_th_2 = list(filter(greater_than_2, h1))
print(greater_th_2)
</code></pre>
<h4>#tut6c.py file as described in the video</h4>
<pre class="language-python"><code>from functools import reduce

def sum_num(a, b):
    return a+b


li1 = reduce(sum_num, [1,2,3,4])
print(li1)
</code></pre>