displaying-streamlit-data

Display data visuals in Streamlit apps with native charts and Altair.

Updated Aug 29, 2025
One-click install
npx skills add https://github.com/DDTully/dotfiles --skill displaying-streamlit-data-ddtully
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: displaying-streamlit-data
Source: https://github.com/DDTully/dotfiles/tree/main/skills/.agent_skills/developing-with-streamlit/skills/displaying-streamlit-data
Command: npx skills add https://github.com/DDTully/dotfiles --skill displaying-streamlit-data-ddtully

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Streamlit users often struggle to quickly visualize data within apps and customize displays for readers.

Core Features & Use Cases

  • st.dataframe for interactive tables
  • st.data_editor for editable data
  • st.table for static displays
  • st.metric for KPIs
  • st.json for structured data
  • st.line_chart, st.bar_chart, st.area_chart for charts
  • st.altair_chart for advanced visuals
  • st.column_config to tailor dataframe columns

Quick Start

Create a Streamlit app, load your dataframe, and render visuals with st.line_chart(df, x='date', y='revenue').

Frequently Asked Questions about displaying-streamlit-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I display a dataframe in Streamlit with customized columns?▼

You can display a dataframe in Streamlit using st.dataframe and tailor individual columns with st.column_config to define data types, edit behavior, and visual formatting for interactive tables.

What is the best way to create KPI metrics in a Streamlit dashboard?▼

The best way to create KPI metrics in a Streamlit dashboard is using st.metric, which renders key performance indicators with values and optional deltas for straightforward data reporting.

How do I integrate Altair charts into a Streamlit app?▼

You integrate Altair charts into a Streamlit app by passing an Altair chart object to st.altair_chart, enabling advanced data visuals and layered charting beyond native Streamlit charts.

Can I make a Streamlit dataframe editable for users?▼

Yes, you can make a Streamlit dataframe editable by using st.data_editor instead of st.dataframe, allowing users to interactively edit data directly within the table display.

When should I use st.table instead of st.dataframe in Streamlit?▼

You should use st.table in Streamlit when you need a static display of data, whereas st.dataframe is better suited for interactive tables with sorting, scrolling, and column configuration.

Does Streamlit support native line charts and bar charts without external libraries?▼

Yes, Streamlit supports native line charts and bar charts through st.line_chart, st.bar_chart, and st.area_chart, allowing basic data visualization directly from dataframes without external libraries.