3 3 Area Chart Explained

Key Concepts

• Area Chart: A type of chart that represents data as a filled area between a line and the axis.
• Data Series: The set of data points that the area chart represents.
• Stacked Area Chart: An area chart where multiple data series are stacked on top of each other.
• Customization: Options to customize the appearance of the area chart.

Explanation

1. Area Chart

An area chart is a graphical representation of data that uses a filled area between a line and the axis. It is useful for showing the cumulative total over time or across categories. The area under the line is filled, making it easy to visualize the magnitude of the data.

2. Data Series

A data series in an area chart is a set of data points that are plotted on the chart. Each data series corresponds to a different category or time period. Multiple data series can be plotted on the same chart to compare different categories or trends.

3. Stacked Area Chart

A stacked area chart is a variation of the area chart where multiple data series are stacked on top of each other. This type of chart is useful for showing the composition of a total over time or across categories. Each data series is stacked on top of the previous one, making it easy to see the contribution of each category to the total.

4. Customization

Customization options for area charts include changing the color of the area, adjusting the transparency, and adding labels and titles. These options allow you to tailor the chart to your specific needs and make it more visually appealing.

Examples

Example 1: Basic Area Chart

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt

data = pd.DataFrame({
    'Year': [2010, 2011, 2012, 2013, 2014],
    'Sales': [100, 150, 200, 250, 300]
})

plt.fill_between(data['Year'], data['Sales'], color='skyblue', alpha=0.4)
plt.plot(data['Year'], data['Sales'], color='skyblue', alpha=0.6)
st.pyplot()
    

Example 2: Stacked Area Chart

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt

data = pd.DataFrame({
    'Year': [2010, 2011, 2012, 2013, 2014],
    'Product A': [100, 150, 200, 250, 300],
    'Product B': [50, 75, 100, 125, 150]
})

plt.stackplot(data['Year'], data['Product A'], data['Product B'], labels=['Product A', 'Product B'])
plt.legend(loc='upper left')
st.pyplot()
    

Analogies

Think of an area chart as a mountain range where the height of each peak represents the value of the data. A stacked area chart is like multiple mountain ranges stacked on top of each other, showing the total height and the contribution of each range.

By mastering area charts in Streamlit, you can create powerful visualizations that help you understand and communicate complex data trends and compositions.