Visualization Tool Activity 📊

Data Resources

• Kaggle Datasets

Project Overview

This project consists of three parts, focusing on data visualization using various libraries and tools. We explore datasets from Kaggle to analyze and represent data effectively.

Part 1: Course 8 Week 1 & 2 Activity

In this section, we selected a dataset and created visualizations using different libraries, including Matplotlib, Seaborn, and Plotly.

Approach:

• Dataset Selection: Describe the dataset you chose.
• Libraries Used: List the libraries you implemented and why you selected them.
• Visualizations Created: Briefly explain the types of visualizations created and the insights gathered from them.

Evaluation:

Discuss whether the chosen tools were appropriate for representing and analyzing your selected dataset.

Part 2: Course 8 Week 3 Activity

Building upon the previous work, we focused on advanced visualizations to uncover deeper insights.

Selected Visualizations:

• Waffle Charts
• Word Clouds
• Seaborn & Regression Plots
• Geospatial Data Visualization (using Folium, maps with markers, and Choropleth maps)

Resources:

• Word Clouds with Python
• Generating Word Cloud
• Waffle Charts with Matplotlib
• Creating Waffle Charts

Part 3: Course 8 Week 4 Activity

In the final part, we implemented a simple dashboard to showcase our visualizations.

Dashboard Implementation:

• Describe the dashboard's layout and functionality.
• Highlight any interactivity or features you added.

Resources:

• Introducing Dash
• Dashboards in Python: Advanced Examples
• Awesome Dash GitHub Repository
• Dash Documentation

Output

Data.Visualization.Summer.Olympic.medals.mov