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My educational blog which contains anayses based on results achieved in iroject1.ipynb

Acknowledgment

I would like to express my gratitude to Airbnb for providing the publicly available Seattle Airbnb Open Data and to Kaggle for hosting and facilitating access to the dataset.

The dataset can be found at Seattle Airbnb Open Data on Kaggle:https://www.kaggle.com/datasets/airbnb/seattle/data

File description

• Listings: data including full descriptions and average review score.
• Reviews: data including unique id for each reviewer and detailed comments.
• Calendar: data including listing id and the price and availability for that day.

Purpose of that project is to analyse thee topics:

1. How do prices influence amount of bookings?

2. In which areas are the most accomodations located? (neighbourhood)

3. Which accomodations have the best review_scores and how do they go together with bookings?

Libraries used

List of all libraries used in this project can be found in the attached file 'requirements.txt'

Findings

The findings of the project analyzes can be viewed in this blog:https://igross2022.github.io/UDACITY_DS_Project1_Blog/