Displaying DataFrames

Streamlit works seamlessly with pandas. Just pass a DataFrame to st.dataframe().

import streamlit as st
import pandas as pd

df = pd.DataFrame({
    "Name": ["Alice", "Bob", "Charlie"],
    "Score": [85, 92, 78]
})

st.dataframe(df)

The interactive table lets users sort columns and scroll through large datasets.

For static display, use st.table():

st.table(df)

For editable data:

edited_df = st.data_editor(df)

Users can modify cells directly, and you get the updated DataFrame.

Display metrics prominently:

st.metric("Total Users", 1234, delta="+12%")

Streamlit makes data presentation effortless.

I cover data display in my Streamlit course.