Pandas for Everyone: Python Data Analysis, First Edition

N. Comprehensions

A typical task in Python is to iterate over a list, run some function on each value, and save the results into a new list.

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# create a list l = [1, 2, 3, 4, 5] # list of newly calculated results r = [] # iterate over the list for i in l:     # square each number and add the new value to a new list     r.append(i ** 2) print(r)

[1, 4, 9, 16, 25]

Unfortunately, this approach requires a few lines of code to do a relatively simple task. One way to rewrite this loop more compactly is by using a Python list-comprehension. This shortcut offers a concise way of performing the same action.

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# note the square brackets around on the right-hand side # this saves the final results ...