Project 2 - Supply and Demand Gap Analysis
SUPPLY AND DEMAND GAP ANALYSIS FOR CAB SERVICE
I. AIM: The aim of this project is to collect and analyze the data for supply and demand gap analysis for a cab company uber
II. INTRODUCTION: This data here provides us with the request id , driver id, pickup location, status, drop and request timestamp by taking up the above data we will find out the availability of driver for the request made in the two pick up location Airport and city. Uber provides 2016 data. Through the analysis of data, we can find out some important insights. The data has been downloaded from kaggle
III. PROBLEM STATEMENT: In This project, we will find out number of request id at pick up point. How many Drivers are available. How many trips are completed, how many trips are cancelled etc
IV. METHODOLOGY:
Ø Step 1: Data cleaning and Data Interpretation
Ø Firstly, I loaded data by name Uber request data then loaded data by using power bi transform data option
Ø The dataset was almost clear and completed. I replaced the null values with 0.
Ø There are total of 6547 rows and 6 columns
Ø I also created extra column of month to do month-based analysis
Step 2: VISUALIZATION
In visualization, I took the help of Power Bi desktop software to make graphs and charts here some relevant graphs and charts here some relevant graphs and charts are attached
V. ANALYSIS:
Ø In analysis I found some insights through the following graphs and visualization
Ø Cards for total request id, card for total driver id, card for max number of request id, max nuber of driver
Ø We have found the number of request id as per pick up point and driver id as per pick up point
Ø Most request id per date
Ø Comparison graph for availability of driver as per request made in pick up location
Ø Status of driver as well as requester as per trip completed or cancelled or cars not available
Ø Created a slicer based of pickup location
Ø Created 2 quick measures for max number of request id per request timestamp, max number of driver per request timestamp
VI. INSIGHTS:
Ø Some interesting information like
Ø Number of trips completed, cancelled by drivers
Ø Number of trips completed, cancelled or cars not available as per request made
Ø Total Number of requests depending upon pick up location and Total number of Drivers also
VII. RECOMMENDATIONS:
We can collect some more accurate dataset for analysis
We can work on larger dataset and analyze them with the proper format of charts