This project involves analyzing a dataset of employees working in an ABC company. The dataset contains 458 rows and 9 columns, and the goal is to provide a detailed report and explanation of the employees in each team while addressing several key questions:
Team Distribution: The project begins by counting how many employees belong to each team and calculating the percentage of employees in each team relative to the total number of employees.
Position Segregation: Employees are segregated based on their different positions within the company.
Age Group Analysis: The project identifies the age group to which most of the employees belong.
High Salary Spending: It determines the team and position in which the company is spending the most in terms of salary.
Age-Salary Correlation: The project visually analyzes the correlation between age and salary using a scatter plot.
Before addressing these questions, the dataset undergoes preprocessing, which includes:
Checking for missing data. Identifying and handling duplicate data. Correcting the 'Height' column by replacing incorrect data with random values between 150 and 180. Ensuring the correct data types for the 'Age' and 'Salary' columns. The exploration and analysis phase of the project involve several steps:
Counting employees in each team and calculating the percentage distribution. Segregating employees based on their positions and calculating average salaries for each position. Finding the age group with the most employees. Identifying the team and position with the highest salary spending. Visualizing the correlation between age and salary using a scatter plot. In summary, this project aims to provide valuable insights into the company's employee data, including team distribution, position segregation, age group demographics, salary spending analysis, and the visual representation of age-salary correlation. These insights can assist the company in making informed decisions regarding its workforce and compensation strategies.