Python project of ABC company
Here I used a dataset of ABC company which includes the columns:
- Name: Employee name
- Team: Team or department of the employee
- Number: A numerical identifier (possibly for teams)
- Position: Position within the team or company
- Age: Employee age
- Height: A timestamp which seems to be incorrectly stored (this should be the height data)
- Weight: Employee weight
- College: College attended
- Salary: Employee salary
#Steps : First we read the excel data from the system and then check that the data is proper. After checking clean the data by handling missing values, remove repeated values etc and some mistake for the height column. So Correct the data in the "height" column by replacing it with random numbers between 150 and 180.Now let's start the analysis
Task 1: Distribution of Employees Across Each Team Insight: By analyzing the distribution of employees across each team, you can identify which teams are the largest and which are the smallest. For example: Teams with higher numbers of employees could be essential to the company’s operations or could require more workforce due to their functions. Smaller teams may suggest specialized roles or less emphasis in that area, or perhaps they could benefit from additional staffing if these teams are critical to company goals. Additionally, knowing the percentage split between teams can highlight how resources are distributed across the organization. Graph: Bar graph to show the proportion of employees across each team.
Task 2: Segregation of Employees Based on Positions Insight: This analysis shows how different job roles or positions are distributed within the company. Key points include: If certain positions, such as “Senior Engineer” or “Project Manager,” have a high representation, it could indicate a hierarchy structure where more senior roles are common. If there’s an abundance of entry-level positions, it could indicate a focus on hiring fresh talent or perhaps a growth-oriented strategy where they train employees up. Uncovering this information can help with career development planning and identifying which positions may need better support or additional hires. Graph : Horizontal Bar Chart to clearly represent the count of employees by position.
Task 3: Predominant Age Group Among Employees Insight: Understanding the predominant age group in the company provides valuable demographic information: A younger workforce might suggest that the company attracts fresh graduates or is technology-oriented. An older workforce might indicate that the company values experience or that employees tend to have long tenures, pointing to high job satisfaction or stability. Recognizing the age distribution also helps in designing targeted employee engagement programs, benefits, and training based on employee demographics. Graph : Histogram for to show the age distribution among employees.
Task 4: Team and Position with the Highest Salary Expenditure Insight: Knowing which team and position have the highest salary expenditure can guide budget allocation and HR planning: If a particular team (e.g., "Engineering" or "Sales") has the highest salary expenditure, it might reflect that this team is critical for the company's revenue generation or operations. A specific high-expenditure position (e.g., “Product Manager” or “Sales Director”) can indicate the company’s investment in leadership or specialized roles, as well as the importance placed on these roles. This insight helps with future budget forecasts, identifying where most payroll costs go, and whether this aligns with business priorities. Graph : Stacked Bar Chart for to visualize salary expenditure by both team and position in one chart.
Task 5: Correlation Between Age and Salary Insight: Analyzing the correlation between age and salary can reveal the company’s approach to compensation: A positive correlation might indicate that older employees, potentially with more experience, earn higher salaries. A weak or no correlation could mean that salary depends more on factors like job role, performance, or skills rather than age. A visual representation (e.g., scatter plot) can help see any patterns, outliers, or deviations, offering insights into how compensation policies align with career progression and experience. Graph : Scatter Plot for to reveal any correlation between age and salary visually.
Data Story Overall Insights and Trends: The culmination of the above tasks helps provide a comprehensive view of the workforce and organizational structure at ABC Company: Employee Distribution tells where workforce resources are concentrated, hinting at areas of focus. Position Segregation gives insight into the hierarchy and role structure within the company, indicating possible growth areas. Age Group Analysis shows demographic trends, aiding in understanding workforce needs. Salary Expenditure reveals the company’s financial priorities and the strategic importance of certain teams or roles. Age-Salary Correlation provides insight into career growth trajectories and compensation strategies.