Analyzing Airbnb Stays in NYC (2019)

Data Acquisition:

Downloads the Airbnb NYC 2019 open-dataset from Kaggle.com to local PC.


Imports Data to Google Spreadsheets

Explores and familiarizes the dataset.

Insights and Meta-data: 

- It appears that the dataset contains information about Airbnb listings in New York, with each row representing a different listing. 
- The columns name and rows reveal details like the listing name, host information, location (neighbourhood_group, neighbourhood, latitude, longitude), room type, pricing, minimum nights stay, number of reviews, last review date, reviews per month, host listings count, and availability throughout the year.
- The data types in the dataset consist of integers, floats, and strings.
- Inlcudes data sizes, host information, pricing, geographical information, and other unique identifiers.

Data Cleaning:

Identify and handle missing values. Create new sheet for clean data and input in cell 'A1' function '=ARRAYFORMULA(IF(AB_NYC_2019!A1:P48896="", "N/A", AB_NYC_2019!A1:P48896))' to replace missing data with 'N/A'.

Remove duplicates if necessary. Data > Data Cleanup > Remove Duplicates. None.
Remove spaces with 'ARRAYFORMULA(TRIM(A1:P48896))' or Data > Data Cleanup > Trim Whitespaces.
Correct data types as needed.


Data Analysis:

Organizes and creates new table. Labels table as "Clean_Dataset". 
This analysis provides a snapshot of Airbnb listings in New York City, covering key details like host information, geographical coordinates, review statistics, pricing, and availability. 
The findings offer a concise overview, valuable for understanding trends in short-term rentals within the city.

Data Visualization:

Use Tableau
Create charts, graphs, and maps to present findings.