st.dataframe() in Streamlit

st.dataframe() is used to display a pandas DataFrame (or any tabular data) in an interactive, scrollable table inside your Streamlit app.

It supports:

Column sorting
Horizontal & vertical scrolling
Resizing columns
Expanding large datasets

Syntax

st.dataframe(
    data=None,
    width="stretch",
    height="auto",
    *,
    use_container_width=None,
    hide_index=None,
    column_order=None,
    column_config=None,
    key=None,
    on_select="ignore",
    selection_mode="multi-row",
    row_height=None,
    placeholder=None
)

The function has the following parameters:

data: The data to display (usually a pandas DataFrame or NumPy array)
width: Optional. Width of the table in pixels
height: Optional. Height of the table in pixels
use_container_width: If True, the table expands to fit the app’s width

Example: Basic usage.

Python

import streamlit as st
import pandas as pd

# Create sample data
data = {
    'Name': ['Alice', 'Bob', 'Charlie', 'David'],
    'Age': [25, 30, 35, 40],
    'City': ['New York', 'London', 'Paris', 'Berlin']
}

df = pd.DataFrame(data)

# Display dataframe
st.dataframe(df)  # Interactive table

Output: An interactive table where you can:

Scroll through rows
Sort columns
Adjust column width

Example: Combine with File Uploader

Python

import streamlit as st
import pandas as pd

uploaded_file = st.file_uploader("Upload a CSV file", type="csv")

if uploaded_file:
    df = pd.read_csv(uploaded_file)
    st.success("✅ File uploaded successfully!")
    st.dataframe(df, use_container_width=True)

The uploaded CSV file is displayed as an interactive table.
The table automatically adjusts to the container width.

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