The aim of the project is to collect and analyze the data in detail of the pickup point of the Airport and City Request id in Uber Request Data.

I have attached also those files and the files are given below

Uber Supply and Demand Gap Analysis

Subtitle

aim

introduction

problem statement

methodology

analysis

insights

recommendations

conclusion

Aim:

The aim of the project is to collect and analyze the data in detail of the pickup point of the Airport and City Request id in Uber Request Data.

Introduction:

Uber provides the year of 2016th dataset. By using this data to find the demand and supply analysis gap of the cab.

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

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.

Methodology:

Step 1: Data Cleaning

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.

Step 2: Data Interpretation

In this interpretation step, I found out some important information about the dataset.

• The dataset was almost clear and completed.
• I replaced the null values with 0.
• There is total of 6746 rows and 6 columns.

Step 3: 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 (Data sheets pertaining to it):

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.
• For a total of 1713 trips, there is no Car Available for Airport trips and 937 trips with no car available for city trips.
• A total of 198 trips are cancelled for Airport and 1066 trips are cancelled for city trips.
• In the second chart 13^th July 2016 has almost 36.88 % of request id are placed.
• The Total of 301 Drivers are available in 2016.
• The total Request id is placed for Airports is 51.99 % and total Request id is placed for City is 48.01 %.
• Finally, 297 Drivers are completed the Airport trips and 299 Drivers are completed the City trips.
• The total of 145 Drivers cancelled the Airport trips and 291 Drivers cancelled the City trips.

Insights:

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

Recommendations:

• We can collect good datasets for more effective analysis by using charts.
• We can analyze the data with the proper format.
• We can analyze the data of the overall Trips in Airports and City.
• 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

Conclusion:

In conclusion, we can take look at the Dashboard for further Analysis. According to analysis, total of 1327 Drivers successfully completed the Airports trips and 1504 Drivers successfully completed the City trips. Where almost 1713 trips cancelled for Airport trips and 1066 trips cancelled in City, So increase the drivers to increase the business.