Analyse following 10 cities in USA: North Carolina, Texas,New Jersey, California, New York, Oregon, Washington,Massachusetts,Nevada,Colorado AirBnB Exploratory data analysis and visualization Using power BI and R
Budget: ₹600 – ₹1,500 INR
Dataset:http://insideairbnb.com/get-the-data/
1. Take airbnb data
2. Merge required datasets
3. Store it in Datalake format using Amazon S3
4. perform exploratory data analysis
5. Display results visually using various graphs and plots
EDA:
1. preprocess the dataset(clean for missing,duplicate,outliers and similar data and any other preprocess steps)
2. First visualize the dataset using some plots
3. Find patterns for property listings vs avg prices
4. List property vs maximum reviews & avg prices
5. find top neighborhood and prices based on reviews & roomtype
6. Visualize price from the launch of airbnb
7. Visualize availability vs review count
8. Analyze prices over weekdays vs weekends
9. Analyze price variations over months and years
10. how prices of listings vary by location
11. correlate the demand and prices of rentals
12. which locations in USA are highly rated
13. plot showing avg location score by area
14. plot number of reviews across month and year
15. occupancy rate by month
16. identify superhost?? average rating by response rate
superhost(hosts having higher bookings) avg rating by host response rate plot to tell if the host is superhost or normal host
Performance metrics:
1. Time taken to generate these plots
2. Time taken for analysis
3. Time taken to connect to datalake
4. dax queries,power query
1. Take airbnb data
2. Merge required datasets
3. Store it in Datalake format using Amazon S3
4. perform exploratory data analysis
5. Display results visually using various graphs and plots
EDA:
1. preprocess the dataset(clean for missing,duplicate,outliers and similar data and any other preprocess steps)
2. First visualize the dataset using some plots
3. Find patterns for property listings vs avg prices
4. List property vs maximum reviews & avg prices
5. find top neighborhood and prices based on reviews & roomtype
6. Visualize price from the launch of airbnb
7. Visualize availability vs review count
8. Analyze prices over weekdays vs weekends
9. Analyze price variations over months and years
10. how prices of listings vary by location
11. correlate the demand and prices of rentals
12. which locations in USA are highly rated
13. plot showing avg location score by area
14. plot number of reviews across month and year
15. occupancy rate by month
16. identify superhost?? average rating by response rate
superhost(hosts having higher bookings) avg rating by host response rate plot to tell if the host is superhost or normal host
Performance metrics:
1. Time taken to generate these plots
2. Time taken for analysis
3. Time taken to connect to datalake
4. dax queries,power query