Streamlit app with sample data

 import streamlit as st

# Use st.cache_data for caching to avoid deprecation warning
import pandas as pd
import numpy as np
import pydeck as pdk
import plotly.express as px

def load_data():
    # Sample data generation
    np.random.seed(0)
    dates = pd.date_range('20230101', periods=6)
    df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
    return df

def main():
    st.title("Dashboard with Cool Graphs and Maps")

    df = load_data()

    st.write("### Sample Data")
    st.write(df)

    st.write("### Line Chart")

About this template

A basic streamlit web app starting point

Introduction to the Streamlit Dashboard Template

Welcome to the step-by-step guide on how to use the Streamlit Dashboard Template on the Lazy platform. This template is designed to help you create a web application that showcases cool graphs and maps using sample data. It's perfect for builders who want to visualize data without worrying about the complexities of setting up and deploying an application.

Getting Started with the Template

To begin using this template, simply click on "Start with this Template" on the Lazy platform. This will pre-populate the code in the Lazy Builder interface, so you won't need to copy, paste, or delete any code manually.

Test: Deploying the App

Once you have the template loaded, the next step is to deploy your app. Press the "Test" button on the Lazy platform. This will initiate the deployment process and launch the Lazy CLI. There is no need for user input at this stage, as the template does not require it.

Using the Streamlit Dashboard

After pressing the "Test" button, Lazy will handle the deployment of your Streamlit app. Once the deployment is complete, Lazy will provide you with a dedicated server link. Use this link to access your Streamlit dashboard and interact with the visualizations.

The dashboard includes the following features:

  • A title displaying "Dashboard with Cool Graphs and Maps".
  • A section showcasing sample data in a table format.
  • A line chart visualization of the sample data.
  • A 3D map with sample hexagon layers representing data points.
  • A regular map showing the distribution of data points.

Explore these features by navigating through the dashboard using the Streamlit interface. You can interact with the graphs and maps to gain insights from the sample data provided.

Integrating the App

If you wish to integrate this Streamlit dashboard into an external service or frontend, you may need to take additional steps, such as adding the app's server link provided by Lazy to your external tool. However, since this template is self-contained and does not require such integration, you can use the dashboard as is.

Should you need to customize the dashboard or integrate it with other tools, refer to the Streamlit documentation for guidance:

https://docs.streamlit.io/

Remember, all the necessary libraries and dependencies are already included in the requirements.txt file, and Lazy handles all the deployment details, so you can focus on building and customizing your application.

Enjoy creating and sharing your data visualizations with the Streamlit Dashboard Template on Lazy!

Category
Technology
Last published
July 20, 2024

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Streamlit app with sample data