Embark on a Data Odyssey: Elevating Hospitality with Python-Powered Hotel Analytics. This project seamlessly integrates cutting-edge Python libraries to analyze user-generated queries and input data, crafting a sophisticated narrative of hotel performance. Through the lens of predictive modeling, delve into future projections, unraveling the insights that guide strategic decisions for an unparalleled guest experience and operational excellence.
1. df_agg_bookings.head()
2. df_agg_bookings.groupby('room_category')['occ_pct'].mean()
3. df_rooms.head()
4. df = pd.merge(df_agg_bookings,df_rooms,left_on='room_category',right_on='room_id')
df.head()
5. df.groupby('room_class')['occ_pct'].mean().plot(kind='bar')
6. df.groupby('day_type')['occ_pct'].mean().round(2).plot(kind='pie')
7. df_updated_bookings.groupby('booking_platform')['revenue_realized'].sum().sort_values(ascending=False).plot(kind='pie')
Looking Forward
to sharing this journey with you! Excited
