README.md

metadata

title: Plotly-Graph-Objects-Treemap-101
emoji: 🌳📊Graph
colorFrom: green
colorTo: indigo
sdk: streamlit
sdk_version: 1.17.0
app_file: app.py
pinned: false
license: mit

📊 Randomized Treemap Graphs for Demonstrating Data Variation 📈

🔍 Overview

• Introduction - Purpose - Data Visualization

🧮 Methodology

• Statistical Analysis - Random Sampling - Treemap Graphs

🚀 Implementation - Rendering Charts with Streamlit - Example Code

👋 Conclusion - Summary - Use Cases - Fun Facts

🔍 Overview 👋 Hello! In this article, we will learn about Randomized Treemap Graphs for Demonstrating Data Variation! 📊📈

🧮 Methodology:

1. 📈 Statistical Analysis: We'll use statistical analysis to demonstrate variation in data.
2. 🎲 Random Sampling: We'll generate random data to create our treemap graphs.
3. 🌳 Treemap Graphs: We'll use treemap graphs to display our data in a visually engaging way.

🚀 Implementation

1. 📊 Rendering Charts with Streamlit: We'll use Streamlit to render our treemap graphs.
2. 👀 Example Code: Here's an example code snippet to get you started!

import plotly.express as px
import streamlit as st

# Generate random data
data = px.data.tips()
fig = px.treemap(data, path=['day', 'time', 'value'], values='total_count')

# Render chart with Streamlit
st.plotly_chart(fig)