- Machine Learning
- Machine Learning Tutorial
- Getting Started
- Mean Median Mode
- Standard Deviation
- Percentile
- Data Distribution
- Normal Data Distribution
- Scatter Plot
- Linear Regression
- Polynomial Regression
- Multiple Regression
- Scale
- Train-Test
- Decision Tree
- Confusion Matrix
- Hierarchical Clustering
- Logistic Regression
- Grid Search
- Categorical Data
- K-means
- Bootstrap Aggregation
- Cross Validation
- AUC - ROC Curve
- K-nearest neighbors
- Python MySQL
- Python - MySQL
- MySQL Get Started
- MySQL Create Database
- MySQL Create Table
- MySQL Insert
- MySQL Select
- MySQL Where
- MySQL Order By
- MySQL Delete
- MySQL Drop Table
- MySQL Update
- MySQL Limit
- MySQL Join
- Python MongoDB
- Python - MongoDB
- MongoDB Get Started
- MongoDB Create DB
- MongoDB Collection
- MongoDB Insert
- MongoDB Find
- MongoDB Query
- MongoDB Sort
- MongoDB Delete
- MongoDB Drop Collection
- MongoDB Update
- MongoDB Limit
- Selected Reading
- Q&A
Python MongoDB:
Python can be used in database applications.
One of the most popular NoSQL database is MongoDB.
MongoDB
MongoDB stores data in JSON-like documents, which makes the database very flexible and scalable.
To be able to experiment with the code examples in this tutorial, you will need access to a MongoDB database.
You can download a free MongoDB database at https://www.mongodb.com.
Or get started right away with a MongoDB cloud service at https://www.mongodb.com/cloud/atlas.
PyMongo
Python needs a MongoDB driver to access the MongoDB database.
In this tutorial we will use the MongoDB driver "PyMongo".
We recommend that you use PIP to install "PyMongo".
PIP is most likely already installed in your Python environment.
Navigate your command line to the location of PIP, and type the following:
Download and install "PyMongo":
C:\Users\Your Name\AppData\Local\Programs\Python\Python36-32\Scripts>python -m pip install pymongo
Now you have downloaded and installed a mongoDB driver.
Test PyMongo
To test if the installation was successful, or if you already have "pymongo" installed, create a Python page with the following content:
If the above code was executed with no errors, "pymongo" is installed and ready to be used.