Hotel Bookings Data Analysis

This repository contains an analysis of hotel bookings data using R. The analysis includes visualizations created using various R libraries to explore different trends, patterns, and distributions related to hotel bookings.

Dataset

The dataset used in this analysis is hotel_bookings.csv, which contains information about hotel bookings, such as hotel type, booking cancellation status, lead time, and average daily rates (ADR). The dataset is loaded directly in the R script and cleaned to handle missing values.

Libraries Used

The following R libraries are required to run the analysis:

• ggplot2: For creating elegant data visualizations.
• dplyr: For data manipulation.
• treemap: For creating treemap visualizations.
• plotly: For adding interactivity to the plots.

Data Cleaning

Before starting the analysis, we perform some basic data cleaning:

• Missing values in the agent and company columns are replaced with 0.

Visualizations

Below is a list of the visualizations included in this analysis:

1. Cancellation Rate by Hotel Type

• A bar plot that shows the number of canceled and non-canceled bookings for each hotel type (City Hotel or Resort Hotel).
• Plot type: Bar Plot (Grouped)
• Libraries used: ggplot2, dplyr

2. Distribution of Market Segments

• A treemap that visualizes the distribution of bookings across different market segments.
• Plot type: Treemap
• Libraries used: treemap, dplyr

3. Average ADR by Customer Type

• A bar plot that shows the average ADR (Average Daily Rate) for different customer types.
• Plot type: Bar Plot
• Libraries used: ggplot2, dplyr

4. Lead Time Distribution

• A histogram that displays the distribution of lead times (number of days between booking and arrival).
• Plot type: Histogram
• Libraries used: ggplot2

5. Booking Changes Distribution

• A bar plot that shows the distribution of booking changes.
• Plot type: Bar Plot
• Libraries used: ggplot2

6. Proportion of Cancellations by Market Segment

• A stacked bar plot that displays the proportion of cancellations for each market segment.
• Plot type: Stacked Bar Plot (Proportion)
• Libraries used: ggplot2, dplyr

7. Average Lead Time by Customer Type

• A bar plot showing the average lead time for each customer type.
• Plot type: Bar Plot
• Libraries used: ggplot2, dplyr

8. ADR Trend Over Time

• A line plot showing the trend of ADR (Average Daily Rate) over time.
• Plot type: Line Plot with Points
• Libraries used: ggplot2, dplyr

How to Run

1. Ensure you have the required libraries installed. You can install the necessary packages by running:

   install.packages(c("ggplot2", "dplyr", "treemap", "plotly"))

2. Load the dataset (hotel_bookings.csv) into your working directory.

3. Run the R script (hotel_bookings_analysis.R) to generate the visualizations. The script will load the data, clean it, and generate the above-mentioned plots.

Requirements

• R (version 3.6 or higher)
• ggplot2
• dplyr
• treemap
• plotly

Author

This analysis was created by [Mohamed El-Baz]. Feel free to reach out with any questions or suggestions.