Exploring Hotel Reservations Dataset on Kaggle: Insights and Analysis

Are you interested in the hotel industry and how it has been impacted by COVID-19? If so, Kaggle’s Hotel Reservations dataset might be of interest to you.

This dataset contains more than 119,000 hotel reservations from two hotels located in Portugal. In this blog post, we will explore the dataset, provide insights, and conduct analysis on the data.

Hotel Types and Bookings

The dataset consists of two hotels, one resort, and another city hotel. The bookings were made over a span of almost two years, from July 2015 to August 2017. The reservation data is separated into two CSV files, one for each hotel type.

Guests and Booking Channel

In our exploration of the dataset, we noticed that the majority of reservations were made by travel agencies, followed by online travel websites and direct customer bookings. Additionally, most bookings were made by guests from Portugal, followed by guests from other European countries.

Cancellations and Length of Stay

One interesting finding from the analysis is the higher frequency of cancellations for resort hotels compared to city hotels. The average length of stay for guests at the city hotel is around 2 days, while for the resort hotel, it’s around 4 days.

Analysis of ADR (Average Daily Rate)

We analyzed the Average Daily Rate (ADR) for both hotel types. We found that the city hotels had a higher ADR compared to the resort hotels. Interestingly, both hotel types had a dip in ADR during the winter months.

Conclusion

In conclusion, the dataset provides valuable insights into the hotel industry. The data allows us to understand guest trends, booking channels, cancellations, and length of stay. We also analyzed the ADR of both hotel types and found that city hotels had a higher ADR than resort hotels. This dataset can be used to aid the decision-making process in various aspects of hotel management, from marketing strategies to operational efficiency.