A curious problem-solver well versed in Excel, SQL, Tableau, and Power BI.
And still upskills in Pyhton, R and moreover...
I've been delivering food with my car via UBER EATs for additional income since March 2022. I've made numerous deliviries and my earnings per ride varied despite the similar variables. So I've analysed my delivery data to unveil patterns among different variables.
I've scrunitised the suburb, order and earning relations in geo data. Then conducted quadrant analysis on distance and time I drove for each delivery to see the effect on earnings. Finally, demonstrated earning distribution by days.
This platform has layered dashboards. Delivery data can be examined under monthly, weekly and daily breakdowns.
Linear and multiple linear regression analysis on some variables. Histogram and normal distribution analysis. Heatmap analysis for order quantity breakdown by hours.
Queries for how many orders picked up from and delivered to each suburb; average waiting time for new order in dinner time regarding the days.
I've transformed structured delivery data to unstructured data for creating graphical database. This file includes the cypher code for creating database.
Two main variables, distance and delivery time, are compared with earnings to show correlation level among them by using scatter plot analysis.
Independent t test and ANOVA application on delivery days, meal times and UBER pro levels on IBM's SPSS.
Coming soon...