Apply all guidelines shared in the announcement titled “Grading Guidelines”
computer science
Description
Instructions:
Apply all guidelines shared in the announcement titled “Grading Guidelines”
Import all_data_master.csv, and replace all \N values with NaN. Name this data frame as “all_data”
For problems 1 to 6 use all_data, so do not change this data frame at any point
For problems that ask to order by a variable always use ascending order unless stated otherwise
For problem 7 and 8 import csv files core_data and salary_grid into data frames employee and salary respectively. From employee, drop rows where all fields are null (Carries credit)
For problem 9 import credit_default_dataset.csv. Also see attached data dictionary if you want to know more about the customer features
In‐line comments are preferred for this assignment but not mandatory
No explanations are expected at the end of answers, unless requested
Problems:
1. Display total number of job postings in each year. Print the year that had most jobs. Plot a simple line graph to see if jobs rise with each passing year.
2. Display mean salary per year for the company Wells Fargo in a single data frame (company, year, mean_salary). Plot a graph to determine whether Wells Fargo mean salaries are on the rise with every passing year.
3.Display standard deviation in salaries for the states AZ, TX and DC in descending order. Now visualize this data in a bar chart.
4. Display all_data without those states that have less than 1000 job postings. Final data frame must include all columns as the original data frame.
5. For each state, find the company that posted the job with highest salary (among all job postings in that state alone). Final data frame must have columns job_id, company, salary. There will be only one record per state.
6. Display all_data without those companies whose highest salary was lower than the overall median (median of all salaries in all_data). Final data frame must include all columns of the original data frame.
7. Get salary information for all employees. Display the employee name, state, age, position and Hourly_Max salary offered.
8. Who are the top 20 highest paid employees based on the Hourly_Max salary column? Print the
percentage of top 20 employees that fully meet their performance score.
