FOOD HUB DATA ANALYSIS
EDA
PYTHON
Matplotlib, NUMPY, Seaborn
Actionable Insights
FoodHub, a food aggregator company, facilitates online food delivery from various restaurants through a single app. The company aims to enhance customer experience by analyzing data on customer orders. As a Data Scientist at FoodHub, the task is to perform data analysis to address key business questions and improve operations.
Through this Project, I have developed skills at :
- Data Collection: Utilized Python to collect and manage data on customer orders from FoodHub’s online portal
- Exploratory Data Analysis (EDA): Employed Python libraries such as Pandas, NumPy, and Matplotlib to conduct EDA on the dataset.
- Data Visualization: Created visualizations using Matplotlib and Seaborn to gain insights into restaurant demand trends, customer preferences, and delivery patterns.
- Statistical Analysis: Conducted statistical analysis using Python to identify significant trends and patterns in the data.
- Business Recommendations: Leveraged findings from EDA to provide actionable recommendations for enhancing customer experience, optimizing delivery routes, and improving operational efficiency.