This project analyzes gas price trends across different countries over time. It provides various visualizations to illustrate how gas prices have evolved, allowing for better understanding and comparison between countries.
Make sure you have the following prerequisites installed:
- Python 3.x
- Jupyter Notebook
- Matplotlib
- Pandas
- Seaborn
To run the code and generate the visualizations:
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Ensure you have Python installed on your system: Download Python
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Clone this repository to your local machine, run the following command in your terminal:
git clone https://github.com/keasamani/Data-Visualisation-project.gitcd gas-price-visualization- Install the required dependencies using pip in your jupyter notebook:
pip install pandas matplotlib seaborn- Run each provided in script (Gas_Price_Visualisation.ipynb) in your preferred Python environment.
Once executed, visualizations will be generated and saved in the project directory.
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Modify the 'gas_df DataFrame' in each 'code' with your own gas price data if necessary. Ensure that the DataFrame structure remains consistent with the provided example.
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Customize the plot attributes such as colors, labels, and titles according to your preferences.
Box Plot This box plot represents the distribution of gas prices across countries. [ Bar Plot This bar plot visualizes the average gas prices across different countries.
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Stacked Area Plot This plot illustrates the contribution of each country to total gas prices over time.
Heatmap This heatmap visualizes gas prices across different countries over time.
Scatter Plot This plot visualizes the correlation between gas prices across different countries over time.
This project is licensed under the MIT License - see the LICENSE file for details.