Game Sales Analysis

Project Summary

This project was about an analysis of 2 Hotels: Resort Hotel and City Hotel. The aim was to do analysis and answer some business questions. Dataset was taken from Kaggle.

The tools:

  • Python (Pandas, SQLite3) for cleaning and exploring data
  • Python (Matplotlib, Seaborn) for visualization

The steps:

  • Data cleaning
  • Perform Exploratory Data Analysis (EDA) for examining following research questions:
    1. How many bookings were canceled?
    2. Where are guests mostly coming from?
    3. What months are mostly busy?
    4. Which month have the highest number of cancelations?
    5. Bookings by market segment?
    6. How long do guests stay at the hotels?
    7. How much do guests pay a room per night?
    8. How does the price vary per night over the year?
  • Create graphs

Project Files

For more comprehensive analysis and visualization, please open these files

  • Jupiter notebook - Analysis

    • Data Cleaning

    1. First, I replaced all null values and categorized them into '0' or 'Unknown'.
    2. Replaced 'Undefined' from meal column into 'SC', as they have same meaning.
    3. Dropped some rows that have zero guest on adults column, including children and babies.

    Data Analysis

    How many bookings were canceled?

    Interpretation:

    Where are guests mostly coming from?

    Interpretation:

    What months are mostly busy?

    Interpretation:

    Which month have the highest number of cancelations?

    Interpretation:

    Bookings by market segment?

    Interpretation:

    How long do guests stay at the hotels?

    Interpretation:

    How much do guests pay a room per night?

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    How does the price vary per night over the year?

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    Conclusion

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