Summary  
This chapter explains how to use matplotlib.pyplot to implement code that creates and customizes bar and pie charts—adding axis labels, titles, colors, and then displaying the visualizations.  

General domain of usage  
Human resources analytics

Data visualization is a vital tool for **HR specialists** because it transforms complex data into clear, actionable insights. In HR reporting, visualizations such as charts and graphs make it easier to spot trends, compare groups, and communicate findings to stakeholders who may not be familiar with raw data. By presenting employee information visually, you can quickly highlight key metrics like department sizes, gender distribution, and turnover rates. This approach not only streamlines decision-making but also helps ensure that important patterns in workforce data are not overlooked.

import matplotlib.pyplot as plt

# Sample data: number of employees by department
departments = ['Sales', 'Engineering', 'HR', 'Marketing']
employee_counts = [40, 55, 15, 20]

plt.bar(departments, employee_counts, color='skyblue')
plt.xlabel('Department')
plt.ylabel('Number of Employees')
plt.title('Employee Counts by Department')
plt.show()

In the code above, you start by importing the `matplotlib.pyplot` module, which provides functions for creating charts. Next, you define two lists: `departments` contains the department names, and `employee_counts` holds the number of employees in each department. The `plt.bar` function creates a bar chart using these lists, with the department names on the x-axis and the employee counts on the y-axis. You then add labels to the axes with `plt.xlabel` and `plt.ylabel`, and set a title for the chart using `plt.title`. Finally, calling `plt.show()` displays the chart in a new window.

import matplotlib.pyplot as plt

# Sample data: gender distribution
genders = ['Male', 'Female', 'Non-binary']
counts = [60, 50, 5]

plt.pie(counts, labels=genders, autopct='%1.1f%%', startangle=140, colors=['lightblue', 'pink', 'lightgreen'])
plt.title('Gender Distribution Among Employees')
plt.axis('equal')  # Ensures pie is drawn as a circle
plt.show()

Which library is commonly used for plotting in Python?

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Visualizing HR Data with Matplotlib

1. Why is data visualization useful in HR?

2. Which library is commonly used for plotting in Python?

3. Fill in the blank: To display a chart in matplotlib, use the _______ function.