How Does Nested List Comprehension Work in Python?

Understanding Nested List Comprehension

Nested list comprehension is a powerful feature in Python that allows you to create complex data structures effortlessly. To understand how it works, let's examine a simplified version:

<code class="python">[(min([row[i] for row in rows]), 
max([row[i] for row in rows])) 
for i in range(len(rows[0]))]</code>

This expression is equivalent to the following for loop:

<code class="python">result=[]
for i in range(len(rows[0])):
  innerResult=[]
  for row in rows:
    innerResult.append(row[i])
  innerResult2=[]
  for row in rows:
    innerResult2.append(row[i])
  tuple=(min(innerResult), max(innerResult2))
  result.append(tuple)</code>

The key to understanding nested list comprehension is the nesting of the for loops. The outer loop iterates over the elements of rows[0], while the inner loop iterates over the rows in rows.

In the expression above, the first for loop is responsible for creating the outer structure of the list. For each iteration, it creates a new tuple. Meanwhile, the second for loop creates the inner structure of the tuple. For each row in rows, it extracts the element at index i and adds it to the inner result list.

To generalize this concept, any nested list comprehension of the form

<code class="python">[exp2([exp1 for x in xSet]) for y in ySet]</code>

Can be translated to the for loop structure:

<code class="python">result=[]
for y in ySet:
  innerResult =[]
  for x in xSet:
    innerResult.append(exp1)
  exp2Result = exp2(innerResult)
  result.append(exp2Result)</code>

For simpler cases, the equivalence is straightforward:

• [exp1 for x in xSet for y in ySet]: Equivalent to for x in xSet: for y in ySet: result.append(exp1)
• [[exp1 for x in xSet] for y in ySet]: Equivalent to for y in ySet: innerResult=[]; for x in xSet: innerResult.append(exp1); result.append(innerResult)

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