MongoDB Tutorial with Python: Exploring MongoDB Functions and Data Analysis with Matplotlib and Pandas 🐍🍃

Overview

This Jupyter Notebook provides a comprehensive tutorial for working with MongoDB using Python. The tutorial covers MongoDB basics, demonstrates interactions with MongoDB databases using pymongo, and showcases data analysis with matplotlib and pandas.

Prerequisites

Before you begin, ensure you have the following:

• Python 3.x 🐍
• Jupyter Notebook 📓
• MongoDB installed and running 🍃

Install required Python libraries: pip install pymongo matplotlib pandas

Contents

1. Introduction to MongoDB
   • Brief overview of MongoDB
2. Installation and setup
3. Connecting to MongoDB with pymongo
   • Establishing a connection
   • Creating and selecting a database
   • Creating collections and documents
4. CRUD Operations
   • Inserting documents
   • querying documents
   • updating documents
   • deleting documents
5. Indexes
   • Creating single and compound indexes
   • Using indexes for query optimization
6. Views
   • Creating views based on aggregation pipelines
   • Working with virtual collections
7. Aggregations
   • Using aggregation pipelines for data transformations
   • Visualizing aggregation results with Matplotlib

Usage

1. Clone the repository:

   git clone https://github.com/your-username/mongodb-tutorial.git
   cd mongodb-tutorial
   

2. Open the Jupyter Notebook:

   jupyter notebook MongoDB_Tutorial.ipynb
   

3. Follow the step-by-step guide in the notebook to learn about MongoDB and explore its functions with Python.

Notes

• Ensure your MongoDB server is running before executing the notebook.
• Modify the connection details in the notebook based on your MongoDB setup.

Feedback

If you encounter any issues or have suggestions for improvement, please open an issue or submit a pull request.

Happy coding!" 🚀