Python vs. R: apply a function to each element in a vector

Question

I want to apply a function (len) over each element in a vector. In R I can easily do this with sapply(cities,char). Is there an alternative like this in Python WITHOUT writing a loop?

Answer 1

The syntax is map(function, list).

Example:

map(len, [ [ 1,2,3], [4,5,6] ])

Output:

[ 3, 3 ]

Answer 2

The R sapply() could be replaced with a list comprehension, but fair enough a list comprehension doesn't strictly avoid the writing of a loop.

In addition to map() you should take a look at Pandas, which provides Python alternatives to several of the functionality that people use in R.

import pandas as pd

vector = [1,2,3,4,5]
square_vector = pd.Series(vector).apply(lambda x: x**2)  
print square_vector.tolist()

The above code results in a new list with the square values of the imput:

[1, 4, 9, 16, 25]

Here, I passed the vector to a series constructor pd.Series(vector) and apply an anonymus function apply(lambda x: x**2). The output is a pandas series which can be converted back to a list if desired tolist(). Pandas series have a lot of functionalities and are ideal for many data manipulation and analysis tasks.