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Creating Interactive Dashboards with Streamlit or Dash

 Creating Interactive Dashboards with Streamlit or Dash


Interactive dashboards allow users to explore data visually using filters, charts, and controls. Streamlit and Dash are two popular Python frameworks for building data dashboards quickly and effectively.


1. What Is an Interactive Dashboard?


An interactive dashboard:


Displays data using charts, tables, and metrics


Allows user interaction (dropdowns, sliders, buttons)


Updates visuals dynamically based on user input


2. Streamlit Overview


Streamlit is designed for simplicity and speed. It is ideal for beginners and data scientists who want to turn scripts into web apps.


Key Features


Very easy to learn


Minimal code required


Automatic app updates


Built-in widgets


When to Use Streamlit


Rapid prototyping


Data science projects


Machine learning demos


Internal dashboards


Basic Streamlit Example

import streamlit as st

import pandas as pd


st.title("Sales Dashboard")


data = pd.read_csv("sales.csv")

region = st.selectbox("Select Region", data["Region"].unique())


filtered_data = data[data["Region"] == region]

st.line_chart(filtered_data["Sales"])


Common Streamlit Widgets


st.selectbox()


st.slider()


st.button()


st.checkbox()


st.text_input()


3. Dash Overview


Dash (by Plotly) is more powerful and flexible, suitable for production-grade dashboards.


Key Features


Built on Flask, React, and Plotly


Highly customizable layouts


Interactive callbacks


Enterprise-ready


When to Use Dash


Complex dashboards


Production web applications


Multi-page apps


Advanced interactivity


Basic Dash Example

from dash import Dash, html, dcc

import plotly.express as px

import pandas as pd


app = Dash(__name__)


df = pd.read_csv("sales.csv")

fig = px.bar(df, x="Region", y="Sales")


app.layout = html.Div([

    html.H1("Sales Dashboard"),

    dcc.Graph(figure=fig)

])


if __name__ == "__main__":

    app.run_server(debug=True)


4. Streamlit vs Dash Comparison

Feature Streamlit Dash

Ease of Use Very Easy Moderate

Customization Limited High

Performance Good Excellent

Learning Curve Low Higher

Best For Prototypes Production Apps

5. Key Dashboard Components

Charts


Line charts


Bar charts


Pie charts


Scatter plots


Filters & Controls


Dropdown menus


Sliders


Radio buttons


Date pickers


Layout


Columns and rows


Tabs


Sidebars


6. Best Practices


Keep dashboards simple and focused


Use clear labels and titles


Avoid cluttered visuals


Use consistent color schemes


Optimize for performance


7. Deployment Options

Streamlit


Streamlit Cloud


Docker


AWS / Azure


Dash


Dash Enterprise


Heroku


AWS / GCP


Conclusion


Choose Streamlit if you want fast, simple, and beginner-friendly dashboards.


Choose Dash if you need advanced interactivity and production-level control.


Both tools are powerful for turning data into interactive insights.

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