Data Visualization, Python
A ready-to-run tutorial in Python Altair to build charts to represent a percentage
Representing a percentage visually may engage the audience more and help them better understand the data. There are different ways to represent a percentage visually. The most straightforward strategy is a Big Number (BAN), as shown in the figure below.
In addition to BAN, there are other ways to represent a percentage visually. In this article, we will focus on three strategies:
- Donut Chart
- 100% Stacked Chart
- Waffle Chart.
We will use Python Altair to show how to build each strategy. The Vega-Altair library (Altair, for short) is a declarative Python library for statistical visualization based on the Vega and Vega-Lite visualization grammars. For more details on how to get started with Altair, you can read the official Python Altair documentation.
To show how each type of chart works, we will represent the following percentage: 70%. To represent this value, you must use the following Pandas DataFrame:
data = {
'percentage': [0.7,0.3],
'label' : ['70%','30%'],
'color' : ['#81c01e','lightgray']
}df = pd.DataFrame(data)
The DataFrame must contain two values: the percentage (70%) and its complementary value (30%). In addition, we set the colors associated with each slice: #81c01e (a type of green) for our value, and light gray for the other.
Let’s start representing this DataFrame through a donut chart.
A donut chart is a circular chart displaying data in a ring shape. It is similar to the pie chart but with a hole in the center, creating a visual representation of percentages of different categories.
This post originally appeared on TechToday.