3 Chart Elements Explained

Key Concepts

• st.line_chart: Creates a line chart from data.
• st.bar_chart: Creates a bar chart from data.
• st.area_chart: Creates an area chart from data.

st.line_chart

st.line_chart is used to create a line chart in Streamlit. This chart is ideal for visualizing trends over time or across categories. The data provided to this function should be in a format that can be easily plotted, such as a Pandas DataFrame.

Example:

import streamlit as st
import pandas as pd

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

st.line_chart(data.set_index('year'))
    

st.bar_chart

st.bar_chart is used to create a bar chart in Streamlit. This chart is suitable for comparing categorical data. The data provided should be in a format that can be easily plotted, such as a Pandas DataFrame.

Example:

import streamlit as st
import pandas as pd

data = pd.DataFrame({
    'category': ['A', 'B', 'C', 'D'],
    'value': [10, 24, 36, 40]
})

st.bar_chart(data.set_index('category'))
    

st.area_chart

st.area_chart is used to create an area chart in Streamlit. This chart is useful for visualizing cumulative data or trends over time. The data provided should be in a format that can be easily plotted, such as a Pandas DataFrame.

Example:

import streamlit as st
import pandas as pd

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

st.area_chart(data.set_index('year'))
    

Analogies

Think of st.line_chart as a line graph in a stock market report, showing how a value changes over time. The st.bar_chart is like a bar graph in a survey report, comparing different categories. The st.area_chart is akin to a shaded area under a line graph, representing cumulative values over time.

By mastering these chart elements, you can create powerful visualizations in your Streamlit applications, making data more accessible and understandable to your users.