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#1
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
#2
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
#3
Python Data Science Handbook: Essential Tools for Working with Data
#4
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#5
Power Query Beyond The User Interface: Solving Advanced Data Cleaning Problems Using M
#1
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
#2
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
#3
Python Data Science Handbook: Essential Tools for Working with Data
#4
Data Science from Scratch: First Principles with Python
#5
Power Query Beyond The User Interface: Solving Advanced Data Cleaning Problems Using M
#1
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
#2
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
#3
Python Data Science Handbook: Essential Tools for Working with Data
#4
Data Science from Scratch: First Principles with Python
#5
Power Query Beyond The User Interface: Solving Advanced Data Cleaning Problems Using M
#1
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
#2
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
#3
Python Data Science Handbook: Essential Tools for Working with Data
#4
Data Science from Scratch: First Principles with Python
#5
Power Query Beyond The User Interface: Solving Advanced Data Cleaning Problems Using M
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