How to find the longest list in a list?

Question

Given a list of lists, the length of the longest list can be found with the following code.

values = [[\'a\',\'a\'], [\         


        

Answer 1

This will return the length of the longest list:

max(map(len, values))

Answer 2

This will return the longest list in the list values:

max(values, key=len)

Answer 3

• The answer from blhsing is great for finding the first, longest sub-list, and it's fast.
  • For a list of 1M lists, varying in length from 1-15, it takes 29.6 ms to return the first list with the maximum length.

values = [['a','a'], ['a','b','b'], ['a','b','b','a'], ['a','b','c','a']]

max(values, key=len)

[out]:
['a', 'b', 'b', 'a']

• This pandas solution isn't a competitor with the accepted answer for speed in returning the first, longest list.
• There are a lot of people using pandas for analysis, so this is a valid question, from that perspecive.
• This solution is for returning all sub-lists for the max list length, or a specified length.
  • df.len.max() can be substituted with an int, to return lists of a specified length.
• This solution takes advantage of pandas: Boolean Indexing.
• This solution is slower, but it's returning a different result
  • The lists have to be loaded in pandas
  • The 'len' column is created
  • The Boolean mask is used to return all the matching lists
  • For a list of 1M lists, varying in length from 1-15, it takes 682 ms to return all the lists with the maximum (or specified) length.
• It should be noted, max(df.lists, key=len) can be used on a pandas.Series to find the first, longest list.

import pandas as pd

# convert the list of lists to a dataframe
df = pd.DataFrame({'lists': values})

# display(df)
          lists
0        [a, a]
1     [a, b, b]
2  [a, b, b, a]
3  [a, b, c, a]

# create column for the length of each list
df['len'] = df.lists.map(len)

          lists  len
0        [a, a]    2
1     [a, b, b]    3
2  [a, b, b, a]    4
3  [a, b, c, a]    4

# select lists with max(len)
max_len = df[df.len == df.len.max()]  # or [df.len == some int] for a specific length

# display(max_len)
          lists  len
2  [a, b, b, a]    4
3  [a, b, c, a]    4

%timeit

import pandas as pd
import random
import string

# 1M sub-list of 1-15 characters
l = [random.sample(string.ascii_letters, random.randint(1, 15)) for _ in range(10**6)]

%timeit max(l, key=len)
29.6 ms ± 1.74 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

# function to do all the pandas stuff for testing
def get_max_len(l):
    df = pd.DataFrame({'lists': l})
    df['len'] = df.lists.map(len)
    return df[df.len == df.len.max()]


%timeit get_max_len(l)
682 ms ± 14.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)