Project 2 - Supply and Demand Gap Analysis
Trip Pricing with Taxi Mobility Analytics
Aim:· This Project aim is to collect and analyses the data of Trip Pricing and With Taxi Mobility Analytics site data and going to analyses by each Gender, Destination Type, Customer rating, Trip Destinations etc.…,
Introduction:
· The Main Objective of this Project is to analyses on Trip Pricing with Taxi Mobility, here the data that we can get it on from Kaggle.com and We can Through the Analysis of data and we can work for get some important insights.
Problem Statement:
· We can find out how many Males and Females are on how many Ratings and long destinations.
· We can find total pricing by gender and then by type of cab, in this analysis, we can see the number of cancellations in the last month and the Lifestyle index etc.…,
Methodology:
v Step 1:
Ø Data Cleaning:
§ Here I cleaned the data with transform data option present in power BI because here the data sets were not cleaned and have some missing values, so here we get done data cleaned with the help of duplicates functions in power BI. I cleaned the date and replaced the null value with.
v Step 2:
§ Data Interpretation:
¨ In this Data Interpretation steps I have done some important information about the data sets and its almost clear and completed.
¨ I replaced the null values with 0.
¨ There is 131662 rows and 14 columns.
Ø Step3:
· Data Visualizations:
Ø In this data visualizations that I use the help of Power BI Desktop software to make Graphs and Charts
Ø Cancellation Last month By Gender
Ø Trip distance and since month of cancellation by gender
Ø Cancellation in last month or customer Rating by the confidence life style
Ø Confident life style or trip distance by gender,
Ø Trip Distance By type of cab Male and Female
Ø Surge Price by type of cab Then Male and Female
Ø Cancellation, Rating, Surge price By Gender
Ø Cancellation, Rating, Surge price By Gender
Ø Type of confidence life style index
Ø Area Chart of Cab type and distance
Ø Duplicates of Customer Rating in Confidence Lifestyle
v Analysis (Data sheets pertaining to it)
§ Here, we found some valuable insights and points that are mentioned below
§ Sum of Last Month Cancellation was for male 73651 and Female 29419.
§ Sum of total distance covered is 5819580.2 and last month cancellation is 103070.
§ Highest customer Rating is 100K and the 35K cancelation last month by confidence life style index.
§ Maximum Trip distance travelled by female on life style index B and they travelled 0.62 M and Male in Life style index B is 1.54M.
§ The Maximum customer rating is 110K in confidence lifestyle A and the maximum cancellation in the last month is 35K in confidence lifestyle A..
Here the viz hat shows we can understand total distance by cabs with gender.
This visualization that can Prove the identity of surge price with the gender differences and compared to above one with is High surge pricing by cabs.
Insights:
§ In conclusion we can take a look at the Dashboard for the further analysis.
§ Like we can see the values according to gender.
Recommendations:
§ We are collected a Good and most eligible datasets for analysis.
§ We can analysis the data of the Trip Destinations.
§ Like this dataset are perform various categories, Like gender , Life style index and destinations.
· We can work on large datasets and analyse them with the proper format of the chart.
Conclusions:
In the conclusion we can take a look at the dashboard for further analysis. And over all data collection on dashboard.
Thank You
By
Rameshkumar R