For example, user can pass a dataframe to that component, by default it displays the data in dataframe.
It also provides several tabs to switch between the chart type(line, bar, scatter, etc) that you want to visualize the dataframe, and you can choose the x, y column for the chart.
This is pretty much similar with using z.show(dataframe) in Zeppelin notebook.
If you’re looking into building an app to do exploratory data analysis, you can look into using components such as Mito (Data analysis with Mito: A powerful spreadsheet in Streamlit) or pandas-profiling (https://okld-gallery.streamlit.app/). Or you can also build your own by combining a data filters and data viz (Drill-downs and filtering with Streamlit and Altair).
Hi, thanks for your reply.
Actually I am looking for something more lightweight which can be integrated into the chat stream of chatbot app.
Feels like Mito or pandas profiling are too heavy for it.
Maybe I can try building one by combining basic components as suggested.
Yes I agree, perhaps a custom solution that leverages in-built chart display would be more light weight to show a simple line plot (st.line_chart - Streamlit Docs) for example.