st.bar_chart() in Streamlit

In Streamlit, the st.bar_chart() method is a quick way to visualize data as a bar chart without writing complex plotting code. It is ideal for dashboards, analytics apps, and quick data exploration.

What is st.bar_chart()?

st.bar_chart() creates a bar chart directly from:

Pandas DataFrame
Pandas Series
NumPy array
Python lists

It automatically handles axes, labels, and rendering.

Basic Syntax

st.bar_chart(
    data=None,
    *,
    x=None,
    y=None,
    x_label=None,
    y_label=None,
    color=None,
    horizontal=False,
    sort=True,
    stack=None,
    width="stretch",
    height="content",
    use_container_width=None
)

The function has the following parameters:

data: Data to visualize
x: Column for X-axis
y: Column(s) for Y-axis
width: Chart width
height: Chart height
use_container_width: Makes chart responsive

Example 1: Simple Bar Chart

Python

import streamlit as st
import pandas as pd

# Sample data
data = pd.DataFrame({
    "Fruits": ["Apple", "Banana", "Mango", "Orange"],
    "Sales": [35, 50, 25, 40]
})

st.title("Fruit Sales Bar Chart")

# Set Fruits as index for chart
data = data.set_index("Fruits")

# Display bar chart
st.bar_chart(data)

✔ What happens?

X-axis → Fruits
Y-axis → Sales
Streamlit automatically renders the chart

The output of the above code is shown below:

Example 2: Multiple Columns (Grouped Bars)

Python

import streamlit as st
import pandas as pd

data = pd.DataFrame({
    "Month": ["Jan", "Feb", "Mar", "Apr"],
    "Product A": [100, 120, 90, 140],
    "Product B": [80, 95, 70, 110]
})

data = data.set_index("Month")

st.bar_chart(data)

Output: Each month shows grouped bars for Product A and Product B.

The output of the above code is shown below:

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