https://github.com/priyapuranik/data-analytics-using_python
Analyzed data of Hotels and find out meaningful insights from it including booking patterns and seasonal trends and many more.
https://github.com/priyapuranik/data-analytics-using_python
data pandas python sql visualization
Last synced: 3 months ago
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Analyzed data of Hotels and find out meaningful insights from it including booking patterns and seasonal trends and many more.
- Host: GitHub
- URL: https://github.com/priyapuranik/data-analytics-using_python
- Owner: priyapuranik
- Created: 2024-08-01T17:01:49.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-11-18T16:45:20.000Z (over 1 year ago)
- Last Synced: 2026-01-03T22:43:37.291Z (6 months ago)
- Topics: data, pandas, python, sql, visualization
- Language: Jupyter Notebook
- Homepage:
- Size: 3.79 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Hotel Booking Data Analysis
**This project involves analyzing hotel booking data using Python and Jupyter. The primary goals are to understand cancellation rates across different countries and to perform a comprehensive analysis of the dataset using data visualization techniques.**
## Data Analysis
--Examined cancellation rates by state.
--Analyzed various aspects of hotel booking data, including booking patterns, guest demographics, and seasonal trends.
## Analysis and Visualizations
The following visualizations were created to better understand hotel cancellation trends:
- **Bar Plots**: To find reservation status count (cancellation or not cancellation)
- **Count Plots**: Displays counts of resort hotel and city hotel.
- **Pie Charts**: Illustrates countries that cancelled the reservation.
And many more charts.
**Run the analysis**:
Follow the steps in the notebook or script to load the data, perform the analysis, and visualize the results.
**MySQL Connection**:
Make sure to configure MySQL credentials to connect and save data permanently.