Streamlit 101 - A faster way to build and share data apps

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  • Опубліковано 3 жов 2024

КОМЕНТАРІ • 17

  • @DmitryPonomareF
    @DmitryPonomareF 4 місяці тому +2

    I like DataProfessor. I would like more videos from him:) Like this video)

    • @DataProfessor
      @DataProfessor 4 місяці тому +1

      Thanks Dmitry for the support :)

  • @fabianacampanari4786
    @fabianacampanari4786 2 місяці тому

    Streamlit ois indeed a powerfull tool !

  • @Lucifer._.658
    @Lucifer._.658 День тому

    i created a dashboard using streamlit, pandas, and plotly. when i run the code in vs code, it displays the full dashboard with all the data. however, when i deploy it on streamlit share, the dashboard or some charts are not fully visible.

  • @thejaatsahabvlogs
    @thejaatsahabvlogs 4 місяці тому

    while plotting the line chart, is it default setting in streamlit that it takes the browser timezone information, even if the dataframe is in to different timezone.

  • @oktjona
    @oktjona 3 місяці тому

    what about how to use database to save data and retrieve

  • @MRT122YT
    @MRT122YT 4 місяці тому

    Does this support VPython? if so can you make a video about that

  • @saimanohar3363
    @saimanohar3363 4 місяці тому

    Good video on streamlit. Is it possible to drill down and drill across on a chart in streamlit? Grt if there is any document. Thanks

    • @VKjkd
      @VKjkd 3 місяці тому +1

      I suppose you could use the highcharts library?

  • @MohamedjihedJenayah
    @MohamedjihedJenayah 4 місяці тому

    Thanks a lot for this video. Could you please show how to deploy a Streamlit app that connects to a PostgreSQL database?

    • @streamlitofficial
      @streamlitofficial  4 місяці тому

      Happy to help! Try this documentation: docs.streamlit.io/develop/tutorials/databases/postgresql
      If you still run into questions, please let us know on the forum! discuss.streamlit.io/

    • @majukanumi9639
      @majukanumi9639 4 місяці тому

      athane le code pour postgresql:
      import streamlit as st
      import psycopg2
      import pandas as pd
      import matplotlib.pyplot as plt
      # Connect to the PostgreSQL database
      conn = psycopg2.connect(dbname="dbname", user="youruser", password="yourpassword", host="localhost")
      # Allow user to select data to visualize
      table = st.selectbox("Select table", ["billions", "countries"])
      # Write a function to query data from the table
      @st.cache_resource
      def load_data(table):
      cur = conn.cursor()
      cur.execute(f"SELECT * FROM {table}")
      rows = cur.fetchall()
      cur.close()
      return rows
      # Load data into a pandas DataFrame
      rows = load_data(table)
      df = pd.DataFrame(rows, columns=["country_id", "country"]) # Replace with actual column names
      # Create a bar chart
      plt.figure(figsize=(8, 6))
      plt.bar(df["country_id"], df["country"])
      plt.xlabel("X-axis label")
      plt.ylabel("Y-axis label")
      plt.title("Bar Chart")
      st.pyplot(plt)
      # Close the database connection
      conn.close()

  • @ReginaldCarey
    @ReginaldCarey 2 місяці тому

    Considering recent events. It might be better to distance Streamlit from Snowflake.