Project 2 - Supply and Demand Gap Analysis

Aim

The aim of this project is collecting a raw data of ola or uber and anaylize a data properly

I)Introduction

Uber provides the 2016 data. By using this data find out the demand and supply Analysis gap of the cab.

The main objective of this project is to anaylize the data on of uber and find the conclusion for demand and supply

II)Problem Statement.

In this project, we find out how many request id is placed from the pickup point of the Airport and city, How many Drivers are present, How many trips are completed, and how many trips are cancelled also find out how many trips the car is not available for the trips.

III)Methodology

• In Uber, the Request Data set the first column is Request id in this column the request-id is present the placed by the customer.
• In the second column, the pickup point is present in this data only two Airport and City pickup point is present.
• The next column is Driver Id in this column so many drivers are present each driver assigns a separate driver ID.
• Another column is Status in this Status column three statuses are present completed, cancelled and No car available.
• The last two columns are the Request timestamp and Drop Timestamp in this column the request time and drop time are present.
• The first step is cleaning the data. In data cleaning I cleaned the data with the transform data option present in Power BI because the dataset was not cleaned and included some missing values, so with the help of the duplicates function in Power BI, I cleaned the data and replace the null values with 0 and then started working on it.
• After Data cleaning performs the Data interpretation step. In Data interpretation found some important information.
• The data set was almost clean and completed.
• Replace the Null values with 0
• There is a total of 6746 rows and 4 columns are present.

Visualization

In visualization, I took the help of Power BI Desktop software to make graphs and charts here some relevant graphs and charts are attached.

Analysis

in Visualization find some interesting points that are mentioned below

• In the first chart, total request id and status,18,20% request was cancelled and 41.97% requested trip completed and 39.28% car not available for that request
• In the Second chart we coclude that in a day between 11 to 15 in 1264 request was cancelled and 2831 requested trip completed and for 2650 request no car available for that
• The Total of Requested id is 6745 and total No id driver id is 4095
• In the third Chart, the Total driver id is 4095 and in that id total No of 2570 passenger are pick from city and total 1525 passenger pick from airport.
• in the last chart there is 1066 passenger pick up location is city but that cancelled and 198 passenger pick up location is airport that also cancelled and 1504 passenger pick up location is city that complete a trip of that passenger and 1327 passenger pick up location is airport that complete a trip of passenger

Insights

• In conclusion, we can take a look at the final Dashboard for further Analysis.
• We analyzed the data according to the request ID and driver Id

Recommendations

• We can analyze the data of the overall Trips in the City and airport
• Like this dataset, we can Analyze the Data according to the Different Cities-Area it takes more clarity to how to fill the supply and demand gap
• We can analyze the data with the proper format
• We can collect good datasets for more effective analysis by using charts.

Conclusion

In Conclusion, we can take look at the Dashboard for further Analysis.

• According to analysis, almost 1066 trips are cancelled for Airport trips. In airports, trips need to increase the drivers that help to increase the Business.
• The second points are that almost 198 trips are cancelled by the customer in the city area and need to improve some features.
• A total of 1327 Drivers successfully completed the Airport trips and 1504 Drivers successfully completed the City trips.