-
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.
-
Notifications
You must be signed in to change notification settings - Fork 1
daniau23/taxi_cabs
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
Data Analytics using PowerBI and Python
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published