Series Indexes

Question:

Start Quiz:

import pandas as pd

countries = [
    'Afghanistan', 'Albania', 'Algeria', 'Angola',
    'Argentina', 'Armenia', 'Australia', 'Austria',
    'Azerbaijan', 'Bahamas', 'Bahrain', 'Bangladesh',
    'Barbados', 'Belarus', 'Belgium', 'Belize',
    'Benin', 'Bhutan', 'Bolivia', 'Bosnia and Herzegovina',
]


employment_values = [
    55.70000076,  51.40000153,  50.5       ,  75.69999695,
    58.40000153,  40.09999847,  61.5       ,  57.09999847,
    60.90000153,  66.59999847,  60.40000153,  68.09999847,
    66.90000153,  53.40000153,  48.59999847,  56.79999924,
    71.59999847,  58.40000153,  70.40000153,  41.20000076,
]

# Employment data in 2007 for 20 countries
employment = pd.Series(employment_values, index=countries)

def max_employment(employment):
    '''
    Fill in this function to return the name of the country
    with the highest employment in the given employment
    data, and the employment in that country.
    
    The input will be a Pandas series where the values
    are employment and the index is country names.
    
    Try using the Pandas idxmax() function. Documention can
    be found here:
    http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.idxmax.html
    '''
    max_country = None      # Replace this with your code
    max_value = None   # Replace this with your code

    return (max_country, max_value)

Solution:

INSTRUCTOR NOTE:

Pandas idxmax()

Note: The argmax() function mentioned in the videos has been realiased to idxmax(), and returns the index of the first maximally-valued element. You can find documentation for the idxmax() function in Pandas here.