Salary Data Analysis
This project demonstrates skills in using the Pandas library by analyzing salary data of IT specialists. The project aims to analyze various aspects of the data, such as salary distribution across roles, experience levels, cities, and other factors.
Project Overview
This project involves:
Collecting, processing, and cleaning the data. Analyzing and visualizing salary data using Pandas. Examining salary trends based on various factors, including experience, job level, and geography.
Data Structure
Data Science Job Salaries Dataset contains 11 columns, each are:
work_year: The year the salary was paid. experience_level: The experience level in the job during the year employment_type: The type of employment for the role job_title: The role worked in during the year. salary: The total gross salary amount paid. salary_currency: The currency of the salary paid as an ISO 4217 currency code. salaryinusd: The salary in USD employee_residence: Employee's primary country of residence in during the work year as an ISO 3166 country code. remote_ratio: The overall amount of work done remotely company_location: The country of the employer's main office or contracting branch company_size: The median number of people that worked for the company during the year
Methods Used
The project utilizes the following Pandas techniques:
Data loading and cleaning: Handling missing values, addressing outliers. Grouping and aggregation: Salary analysis across different categories. Filtering and sorting: Selecting data for specific groups. Statistical analysis: Calculating metrics like mean, median, and standard deviation.
Analysis Results
Average salaries were calculated for different roles and experience levels. Salaries for various contrys were compared. The relationship between salary and other factors was examined.
Conclusions
Significant salary differences are observed based on experience level and role. Location also impacts salary levels, which can be useful information for IT professionals when considering job location.