- Different ways to perform aggregation in MongoDB
7
- Creating a new database
8
- Operations in the aggregation pipeline
9
- Stages in the aggregation pipeline
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- match operation
11
- group operation
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- sort operation
13
- Creating JSON file
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- pymongoarrow
15
- Final Note
Description:
Learn how to perform data analysis on house pricing data using MongoDB aggregation pipelines in Python. Create a free Atlas cluster and explore different aggregation techniques including match, group, and sort operations. Discover how to create JSON files and utilize pymongoarrow for efficient data handling. Follow along with code examples and gain practical insights into leveraging MongoDB's powerful data analysis capabilities for real estate market analysis.
Data Analysis on House Pricing Data Using MongoDB Aggregation Pipelines