Embark on a gastronomic odyssey with our meticulously crafted Zomato Analysis project, where we delve into the realm of data-driven dining trends and epicurean patterns. Our endeavor encapsulates the essence of culinary exploration, offering aficionados and analysts alike a curated selection of insights extracted from Zomato's extensive repository.
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Unveiling Trends: Our code meticulously analyzes Zomato's voluminous data, unveiling nuanced trends and shifts in the culinary landscape. From upsurges in plant-based cuisine to the resurgence of age-old gastronomic traditions, we dissect the data to present a comprehensive view.
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Restaurant Prodigy: Discover the celebrated eateries that grace the Zomato platform. We dissect the hidden metrics that define culinary excellence, providing a panoramic view of what makes a restaurant truly exceptional.
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Cuisine Chronicles: Delve into the world of trending cuisines and gastronomic adventures. Our code examines the popularity of various culinary styles, shedding light on evolving preferences and cultural crossovers.
This project harnesses the power of Python and an array of cutting-edge libraries:
- Pandas: Seamlessly handling and manipulating data for insightful analysis.
- Matplotlib: Crafting stunning visualizations that narrate the culinary story.
- Scikit-learn: Extrapolating predictive trends to amplify our understanding of the data.
# Analyzing Zomato Data with Pandas and Matplotlib
import pandas as pd
import matplotlib.pyplot as plt
# Load data
data = pd.read_csv('zomato_data.csv')
# Data preprocessing and exploration
...
# Visualizing trends
...
# Machine learning insights
...
plt.show()```
### Get Started🫕🥫
1. Clone this repository.
2. Download Zomato data and place it in the project folder.
3. Install required libraries: pip install pandas matplotlib scikit-learn.
4. Run the provided Jupyter Notebook or explore the Python scripts.