Pie chart – Python(matplot)

A pie chart is a circular graph that represents data as parts of a whole. It treats the whole as 100% and divides the circle into slices, with each slice showing the proportion of an item.

Pros

• Intuitive: You can quickly grasp the composition of the data at a glance, making it easy to understand.
• Easy comparison: The relative sizes of each slice make comparisons straightforward.

Cons

• Hard to compare similar sizes: It’s challenging to accurately compare slices of similar size.
• Limited for complex data: Pie charts become difficult to read when dealing with many items or complex datasets.

Pie Chart – Code

import matplotlib.pyplot as plt

labels = ['Aisa', 'Africa', 'Europe', 'Central and South America','North America','Oceania']
sizes = [59.5, 17.2, 9.6, 8.4, 4.7, 0.5]
colors = ['yellow', 'gray', 'lightskyblue', 'blue', 'red', 'green']
explode = (0.1, 0, 0, 0, 0 ,0)  # 두 번째 조각을 강조

plt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True, startangle=140, explode=explode)

plt.title('Population Pie Chart')

plt.show()

Pie charts are great for showing the relationship between parts of data and the whole. For example, they work well for visualizing the share of sales by product or the distribution of budgets.

However, they become problematic when there are too many items, making analysis more difficult. While pie charts excel at showing the distribution of a few simple items, they fall short in certain scenarios.

One major issue I’ve faced with pie charts in real-world analysis is their reliance on a 100% total. In periodic reports, where the overall total changes over time, pie charts struggle to capture trends, making them unsuitable for analyzing data over time. They work better as a snapshot of a fixed total with a small number of items.

If there are too many items, aggregating them can lead to misrepresentation. In such cases, it’s better to avoid pie charts altogether. After all, if consolidation isn’t an option, pie charts may not be the right choice!