You are given a path to a file of comma-separated values (CSV), jobs.csv, which contains people's...

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You are given a path to a file of comma-separated values (CSV), jobs.csv, which contains people's names and job titles, such as Dancer, Nurse, Pilot, etc. The dataset has two columns: 'name' (a string data type) and 'job' (also a string data type). name job Tony Sullivan Office manager Mary Henry Film editor Tiffany Young Dancer Implement a group_sort(input_path) method that reads data from the jobs.csv file and returns a dictionary in which the keys are jobs and the values are counts of how many times each job appears within the dataset. The dictionary should be ordered by count (in ascending order), then job (in ascending order from A to Z). The group_sort (input_path) method takes one argument: input_path - a path to the CSV file containing the data. Available packages/libraries Python 3.8 and all of its built-in packages • Spark version 3.1.1 You are given a path to a file of comma-separated values (CSV), jobs.csv, which contains people's names and job titles, such as Dancer, Nurse, Pilot, etc. The dataset has two columns: 'name' (a string data type) and 'job' (also a string data type). name job Tony Sullivan Office manager Mary Henry Film editor Tiffany Young Dancer Implement a group_sort(input_path) method that reads data from the jobs.csv file and returns a dictionary in which the keys are jobs and the values are counts of how many times each job appears within the dataset. The dictionary should be ordered by count (in ascending order), then job (in ascending order from A to Z). The group_sort (input_path) method takes one argument: input_path - a path to the CSV file containing the data. Available packages/libraries Python 3.8 and all of its built-in packages • Spark version 3.1.1

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import csv from collections import defaultdict def groupsortinputpath Read the data from the C... View the full answer