/taxi_cabs

Data Analytics using PowerBI and Python

Primary LanguageJupyter Notebook

TAXI CABS ANALYSIS

  • This project begins with loading the csv files from the data folder and converting them into a single Excel file for easy visualisation and analysis on Microsot PowerBI(Tableau can also be used); kindly check eda.ipyb file

  • The exported Excel file is named full_data.xlsx

  • Images of visualisations performed can be seen in the img folder

  • The Microsoft PowerBI file is taxi_cabs_visualisation.pbix

  • Further analysis was done using Python; kindly check eda_notebook.ipynb & plots folder.

  • Based on the analysis the following can be drawn;

    Conclusion

    After analysis and observations made, Yellow Cab company has come out as the preferred choice for investment based on the following;

    • Yellow Cab company has a greater reach in genders compared to that of Pink Cab company.
    • Yellow Cab company has a greater profit margin compared to the Pink Cab company.
    • Yellow Cab company has a lower loss margin compared to that of Pink Cab company.
    • Yellow Cab company has profit increases considerably more than Pink Cab company as price charged increases.
    • Yellow Cab has a higher transaction margin for each year and month more than that of Pink Cab company
    • The mean profit for each year and month for Yellow Cab company is more than that of Pink Cab company

    Recommendations

    • Although Yellow Cab has three cities that are in the top six cities namely; New York NY, Chicago IL, Los Angeles CA and the remaining in cities with population below 1 million. It needs to increase its reach in the following remaining top six cities namely; Miami FL, Silicon Valley and Orange County, in order to fully maximise its profit.