FoodHub

FoodHub is a data analytics project designed to analyze customer orders and restaurant performance on a food delivery platform. I developed the analysis using Python, exploratory data analysis, and data visualization techniques.

First, I processed the FoodHub order dataset to clean and structure the data. Then, I explored customer behavior, restaurant performance, and delivery trends to identify key patterns in the platform.

Next, I analyzed order frequency, popular cuisines, delivery times, and customer preferences.

As a result, the FoodHub analysis provides insights that can help improve restaurant operations, optimize delivery performance, and enhance customer experience on the platform.

FoodHub is a data analytics project designed to analyze customer behavior and operational performance on a food delivery platform. I developed the analysis using Python and modern data analysis techniques.

First, I explored and cleaned the FoodHub dataset containing customer orders, restaurant information, and delivery details. Then, I performed exploratory data analysis and engineered insights that highlight ordering patterns, popular cuisines, and customer preferences.

Next, I used data visualization and statistical analysis to evaluate restaurant performance, order trends, and delivery efficiency.

In addition, I identified key factors that influence customer ordering behavior and platform activity.

Overall, the FoodHub project demonstrates how data analysis can transform raw transactional data into actionable insights that support better decision making in food delivery platforms.

Stack:

Python, Pandas, Seaborn, Matplotlib, Exploratory Data Analysis (EDA)

  • Executed rigorous Exploratory Data Analysis (EDA) to uncover demand patterns across cuisines and restaurants, performing deep univariate and multivariate analysis on transactional datasets.
  • Translated complex data patterns into actionable business strategies for revenue growth, generating high-fidelity visual reports to communicate findings and trends to non-technical stakeholders.

“Clear data insights turn raw transactions into strategic decisions.”

Randley Morales, Ph.D.Ph.D. Mathematician & Machine Learning Specialist | Generative AI, Computer Vision & Predictive Modeling

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