In today’s world, data analysis and visualization play a crucial role in various industries, including fashion. Pie charts are a popular method for representing data in a visually appealing and easy-to-understand manner. One common use case is to display the percentage of each category in a dataset. In this article, we will discuss how to create an auto percentage pie chart using Python, as well as delve into related libraries and functions that help solve the problem.

While creating an auto percentage pie chart might seem like a daunting task, Python’s vast range of libraries and functionalities makes this process quite efficient. Our solution will make use of the Python programming language and libraries such as Matplotlib and NumPy, which are commonly used for data visualization and numerical operations.

**Step-by-Step Explanation of the Code**

To solve this problem, we will follow the steps outlined below:

1. Import the necessary Python libraries (Matplotlib and NumPy)

2. Prepare the data for the pie chart

3. Define the chart’s settings and create the pie chart with auto percentage values

4. Display the pie chart

import matplotlib.pyplot as plt import numpy as np # Data preparation categories = ['Trendy', 'Classic', 'Casual', 'Formal', 'Athletic'] values = [25, 35, 15, 10, 15] # Chart settings and creation fig, ax = plt.subplots() ax.pie(values, labels=categories, autopct='%1.1f%%', startangle=90) # Equal aspect ratio ensures the pie chart is circular ax.axis('equal') # Display the pie chart plt.show()

We begin by importing the required Python libraries, Matplotlib and NumPy. Then, we prepare the data for our pie chart, defining the different categories and their corresponding values. In our example, these categories represent different fashion styles with their associated percentages.

## Matplotlib Library

**Matplotlib** is one of the most popular Python libraries for data visualization. It allows for the creation of a wide range of figures, such as line plots, scatter plots, and bar plots, in addition to pie charts. What makes Matplotlib stand out is its ability to customize plots to a high degree, modify their appearance, and even create interactive visualizations.

In our code, we use Matplotlib’s “pie()” function to create the pie chart from the input data. The “autopct” parameter is utilized for displaying the auto percentage values, while the “startangle” parameter rotates the chart to a desired orientation.

## NumPy Library

**NumPy** (Numerical Python) is another essential Python library, particularly for numerical computing. It offers support for arrays, matrices, and various mathematical operations, such as linear algebra, random number generation, and statistical operations. NumPy integrates seamlessly with other Python libraries like Matplotlib, and its powerful capabilities make it an indispensable tool for data analysis and processing.

In our example, we do not use any specific NumPy functions, but its presence is crucial for other advanced applications that might deal with more complex data processing before creating the pie chart.

In conclusion, Python offers a straightforward and efficient method to create an auto percentage pie chart using libraries like Matplotlib and NumPy. Understanding this process will not only help in data visualization tasks but also improve your skills in Python programming and data analysis as a whole.