This repository contains various data visualization projects and interactive dashboards built using **Tableau, Matplotlib, Seaborn, Plotly, Dash, and Folium. The visualizations span multiple domains, including COVID-19 analytics, wildfire trends, automobile sales, immigration data, and Olympic statistics.
This repository focuses on exploratory data analysis (EDA) and interactive data visualization techniques. The notebooks contain data wrangling, statistical analysis, and visual storytelling using Python.
- Matplotlib & Seaborn Visualizations (Line Plots, Bar Charts, Histograms, Scatter Plots, etc.)
- Plotly Dash Dashboards (Interactive web-based visualizations)
- Geospatial Analytics with Folium (Mapping datasets with spatial insights)
- Exploratory Data Analysis (EDA) (Summarizing and understanding data)
- Case Studies in Real-World Data (Olympics, COVID-19, Wildfire trends, and more)
| 🔹 File Name | 📂 Description |
|---|---|
| ** Tableau | |
| 4.3_Plotly_Visualization.ipynb | Interactive visualizations using Plotly. |
| Activity_Explore descriptive statistics.ipynb | Statistical summaries and EDA. |
| Analyzing wildfire activities in Australia.ipynb | Wildfire trend analysis. |
| Create visualizations using Matplotlib, Seaborn and Folium.ipynb | Various visualization techniques. |
| dash_dashboard.py.ipynb | Interactive dashboards using Dash. |
| EDA with Data Visualization.ipynb | Exploratory data analysis using visualization. |
| Exploring and Pre-processing a Dataset using Pandas.ipynb | Data cleaning and preparation. |
| Geospatial Visual Analytics with Folium.ipynb | Mapping data using Folium. |
| Olympics Exploratory Data analysis.ipynb | Visualizing Olympic datasets. |
| Pie-Charts-Box-Plots-Scatter-Plots-and-Bubble-Plots.ipynb | Plotting different chart types. |
| Scatter, Line, Bar, Bubble, Histogram, Pie, Sunburst.ipynb | Multiple visualization techniques. |
| plotly Dash visualization.ipynb | Dashboarding with Plotly Dash. |
| Waffle-Charts-Word-Clouds-and-Regression-Plots.ipynb | Advanced data storytelling techniques. |
| Tool/Technology | Purpose |
|---|---|
| Matplotlib | Static data visualization |
| Seaborn | Statistical visualization |
| Plotly | Interactive graphs |
| Dash | Web-based dashboards |
| Folium | Geospatial visualization |
| Pandas | Data manipulation |
| Jupyter Notebook | Interactive development |
- Clone the Repository:
git clone https://github.com/Tolumie/Dashboards-visualisation.git
- Navigate into the Folder:
cd Dashboards-visualisation - Install Required Dependencies:
pip install -r requirements.txt
- Run the Notebooks/Dashboard:
jupyter notebook
- OR for Dash apps:
python dash_dashboard.py
- OR for Dash apps:
- Feel free to fork the repository and submit pull requests.
- If you encounter any issues, report them via GitHub Issues.
For any inquiries, reach out via GitHub. 🚀
🔹 Happy Visualizing! 📊💡