In this project, I followed the CRISP-DM process to analyze Málaga Airbnb homes data and answer the following questions:
- What is the perfect time of year to visit Málaga city?
- which neighborhood is more affordable and less crowded?
- Which features are more involved in predicting price?
These directories hold the files used in this project:
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Data:
Contains downloaded files from the insideairbnb data source for Malaga, Spain in Feb 2020 -
Airbnb_Malaga_Analytics.ipynb
These files have the insights, process steps and answers for this project goal. -
requirements.txt
It contains the used libraries in this project.
The main findings are:
- March is the perfect month of the year to visit Malaga because it's cheap and less crowded.
- Prices increase in the Winter season, mostly in December, January, and February.
- Prices decrease in the Spring season mostly in March, April and May.
- The expensive neighborhoods have a medium crowding (not extreme crowded or of the most fewer neighborhoods)
- Ciudad Jardin and Cruz De Humilladero are the cheapest but they are crowded so you have to sacrifice by adapting with crowding if you want to save some money.
- The property type, the host and property history, visitors’ reviews and the cost of cleaning service is the most important factor in determining property price.
You can find all required libraries that used in this project in requirements.txt .
The below sites were very useful for the projects:
Mahmoud Ahmed