This repository contains a Jupyter Notebook file for performing Exploratory Data Analysis (EDA) on the Zomato dataset. The EDA is conducted step by step, covering various aspects of the dataset including data import, data cleaning, analysis of numerical and categorical variables, visualization of relationships between variables, and more.
- Project Title: Zomato Dataset - EDA Python Notebook
- Date: February 25, 2024
The project consists of a single Jupyter Notebook file:
- Zomato Dataset - EDA Python Notebook: This notebook contains the code and explanations for each step of the Exploratory Data Analysis process.
The notebook is structured into different sections:
-
Step 0: Importing Libraries
- Imports necessary libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data analysis and visualization.
-
Step 1: Import Data and Preview
- Reads the Zomato dataset from a CSV file and displays the first few rows to get an overview of the data.
-
Step 2: Data Analysis Part
- Conducts various analyses on the dataset, including:
- Checking for missing values.
- Exploring numerical variables using descriptive statistics.
- Exploring categorical variables.
- Finding relationships between variables.
- Conducts various analyses on the dataset, including:
-
Observations
- Summarizes key observations and insights obtained from the data analysis.
To run the notebook:
- Clone this repository to your local machine.
- Install Jupyter Notebook and the required dependencies (Pandas, NumPy, Matplotlib, Seaborn).
- Open the Jupyter Notebook file in your Jupyter Notebook environment.
- Execute each cell in the notebook sequentially to perform the analysis steps.
The Zomato dataset used in this project is available on GitHub: Dataset Link
- Pandas
- NumPy
- Matplotlib
- Seaborn
This EDA project was conducted by Sofia Rajan.
This project is licensed under the [GNU General Public License] - see the LICENSE file for details.