Project 2 - Supply and Demand Gap Analysis

Project 2 – Supply and Demand Gap Analysis

Aim – The aim of this project is to collect and analysis the data in detail of the Pickup point of the Airport and City request id in Uber Request Data.

Introduction- Uber provides the 2016 year data ,by using this data we will find out the demand and supply analysis gap of the cab.

The main objective of this project is to analysis the data on Uber Request data, through the analysis of the data ,we can find some important insights.

Problem Statement- In this project ,we find out how many request id is placed from pickup point of the Airport and City, how many trips are cancelled also find out how many trips the car is not available for the trips.

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 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 driver are present each driver assigns a separate driver ID.
• Another column is Status in this Status column three status are present completed , cancelled and No car available.
• The last two column are the request timestamp and drop timestamp in this column the request time and drop time are present.
• The data is almost clean and completed
• Replace the Null value with 0
• There is total of 6746 rows and 4 column 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

From the above Visualization find some interesting points that are mentioned below.

• In the first chart almost 1327 trips are completed for Airport and 1504 trips are completed for City.
• A total of 198 trips are cancelled for airport and 1066 trips are cancelled for city trips .
• In second chart 15 july 2016,almost 20.67% of request IDs are placed .
• The total request id is placed for airports is 50.99% and the total request id are placed for city is 49.01%.
• 1327 trips are completed for Airport and 1504 trips are completed in City where as 198 and 1066 are cancelled for airport and city.

Insights

In Conclusion we can take a look at the final Dashboard for further analysis ,where as the data is according to the request Id .

Recommendation

We understood the data of the overall Trips in the City.

Like this dataset, we can analysis the data according to the different cities area it takes more clarity to how to fill the supply and demand gap.

We can analysis the data with proper format.

We can collect good datasets for more effective analysis by using charts.

Conclusion

We can take a look at the dashboard for further analysis.

According to analysis ,almost we understood the completion of trips for airport and city trips are done .