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Chart elements

Streamlit supports several different charting libraries, and our goal is to continually add support for more. Right now, the most basic library in our arsenal is Matplotlib. Then there are also interactive charting libraries like Vega Lite (2D charts) and deck.gl (maps and 3D charts). And finally we also provide a few chart types that are "native" to Streamlit, like st.line_chart and st.area_chart.

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Simple area charts

Display an area chart.

st.area_chart(my_data_frame)
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Simple bar charts

Display a bar chart.

st.bar_chart(my_data_frame)
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Simple line charts

Display a line chart.

st.line_chart(my_data_frame)
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Simple scatter charts

Display a line chart.

st.scatter_chart(my_data_frame)
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Scatterplots on maps

Display a map with points on it.

st.map(my_data_frame)
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Matplotlib

Display a matplotlib.pyplot figure.

st.pyplot(my_mpl_figure)
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Altair

Display a chart using the Altair library.

st.altair_chart(my_altair_chart)
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Vega-Lite

Display a chart using the Vega-Lite library.

st.vega_lite_chart(my_vega_lite_chart)
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Plotly

Display an interactive Plotly chart.

st.plotly_chart(my_plotly_chart)
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Bokeh

Display an interactive Bokeh chart.

st.bokeh_chart(my_bokeh_chart)
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PyDeck

Display a chart using the PyDeck library.

st.pydeck_chart(my_pydeck_chart)
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GraphViz

Display a graph using the dagre-d3 library.

st.graphviz_chart(my_graphviz_spec)

Third-party components

These are featured components created by our lovely community. For more examples and inspiration, check out our Components Gallery and Streamlit Extras!

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Streamlit Folium

Streamlit Component for rendering Folium maps. Created by @randyzwitch.

m = folium.Map(location=[39.949610, -75.150282], zoom_start=16) st_data = st_folium(m, width=725)
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Spacy-Streamlit

spaCy building blocks and visualizers for Streamlit apps. Created by @explosion.

models = ["en_core_web_sm", "en_core_web_md"] spacy_streamlit.visualize(models, "Sundar Pichai is the CEO of Google.")
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Streamlit Agraph

A Streamlit Graph Vis, based on react-grah-vis. Created by @ChrisDelClea.

from streamlit_agraph import agraph, Node, Edge, Config agraph(nodes=nodes, edges=edges, config=config)
forum

Still have questions?

Our forums are full of helpful information and Streamlit experts.