Project 2 - Supply and Demand Gap Analysis
SUPPLY & DEMAND GAP ANALYSIS
AIM
To aim of this project is to collect & analyze the data in detail of pickup the point of the airport & city uber request data.
Introduction
The object of project is supply and demand gap analysis.I find some important data.
Problem statement
To find the how many people can travel in airport and city.
Methodology
Step 1: Data exploration
I take the data from kaggle website (Uber Request Data.csv). I download the file and change into excel.
Step2: Data importing
To import the data into power bi. Let’s I drop down the file in excel file.
Step 3: Data cleaning
I used the power bi tool to clean and transform the data as per my understanding and I stared to work.
Step 4: visualization
I used the power bi tool visualize to tool make the line graph, bar graph & all available tools.
Analysis
· I observed some important data I give the point wise mentioned below.
· According to data supply and demand gap.
· The data FY-2016.
· They have only two data airport & city.
· The Total pickup point based on sum of request id 2282943
|
Year |
Quarter |
Pickup point |
Status |
Sum of Request id |
|
2016 |
Qtr 3 |
City |
Cancelled |
3297630 |
|
2016 |
Qtr 3 |
City |
No Cars Available |
3281702 |
|
2016 |
Qtr 3 |
City |
Trip Completed |
5061348 |
|
2016 |
Qtr 3 |
Airport |
Cancelled |
651439 |
|
2016 |
Qtr 3 |
Airport |
No Cars Available |
6219812 |
|
2016 |
Qtr 3 |
Airport |
Trip Completed |
4317499 |
|
|
Total |
22829430 |
· The Total pickup based on status
|
Total cancelled 3949069 Total trip completed 9378847 Total no cars available 9501514 |
· Most of them no cars available 41.37%
· I compered the both airport and city cancelled is more in city 14.44%.
· Total count of driver id is 301
· Pick up point high in city 12M
Insights
ü In conclusion, we can take a look the final report.
ü We can see the top 10 source.
Recommendations
· We can analyse the data of the trip in city
· We can analyse the proper data.
· We can collect good datasets more effective analysis by using charts.
Conclusion
In conclusion, we can give well analyse the data in case future analyse. The datasets good quality and analyse well in supply and demand project.