Discover unique accommodations and unforgettable experiences around the world.
ABOUT DATASET:
Data contains 50 Columns, 7581 Rows.
Data Source GitHub repository
Data Contains Travelers Details, Host Details, Accommodation details, Review.
Data Transformation, Data Cleaning in SQL
Data Visualization Power BI
Data Cleaning are removed unwanted Columns, Change Column name, Change Date format, Remove duplicate details.
DATA ANALYSING:
Total Availability in 30, 60, 90, 365 days.
Analyze which Room type most of visitors use.
Find Price list, Most Verification methods are use.
Calculate Accommodation details like Bedrooms types.
Calculate Review ratings about Property.
Calculate dirty ratings.
SCREEN SHOT:
DATA MODELING:
QUESTIONS: 1.Total Availibility in 30 days, 60 days, 90 days, 365 days?
2.Find dirty Reviews are short listed by Host side
3.Which Neighbourhood group there is a maximum number of properties?
4.Which host has maximum number of properties listed?
5.What is the average price in different listed properties listed?
6.What is the most prefered having room type in the every neighbourhooAd groups?
7.Total availiability of properties having different room Type?
SUMMARY FINDINGS:
Entire Home/apt had highest Room type at 5741 followed by Private, Shared, Hotel room.
Entire Home/apt accounted for 78.88% Room Type.
All metrics remained relatively constant on 24-May-2023.