Data-Science-Udacity-Projects-

This repository contains my data science projects as a part of Udacity nanodegree program.

Motivation of the project.

The motivation for doing this project was primarily an interest in undertaking a challenging project in an interesting area of research.

Libraries used

1. pandas : pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
2. Numpy : NumPy is a Python library used for working with arrays.
3. Matplotlib : Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
4. seaborn : Seaborn is a Python data visualization library based on matplotlib.
5. statistics : Python's statistics is a built-in Python library for descriptive statistics.

Files present in the dataset

1. listings.csv : This file contains almost all the data that we require. Host names, house location, number of reviews, room and property type, number of beds, bedrooms and bathrooms, rent of the house. These we some main features, rest are named in the listings_column file.
2. review .csv : This file contains the id, date, reviewer name and the reviews of the guests.
3. calendar.csv : This file contains the id, date, availability, and price of the listed houses.

Contribute

If you find any bugs in my code, you can fork the repository. If you feel that the code can be executed in a much better way, please let me know.

Credits

I have completed this project under the guidance of Udacity, as a part of Udacity Nanodegree program. Link to their website: https://www.udacity.com/

License

https://github.com/vidyuth12/Data-Science-Udacity-Projects-/blob/2eba00e77eb38ac0dbabd430418bde128b11e6c7/LICENSE

I have written a blog for the same, you can find in the link below:

https://sridharvidyuth-18-ce.medium.com/what-influences-the-price-and-number-of-guests-in-your-destined-holiday-houses-2d6a81f86241