• Learn to set up data analysis pipelines with pandas and Jupyter notebooks
• Effective techniques for data selection, manipulation, and...

• Get a hands-on, fast-paced introduction to the Python data science stack
• Explore ways to create useful metrics and statistics from...

• Grasp all aspects of numerical computing and understand NumPy
• Explore examples to learn exploratory data analysis (EDA), regression, and clustering
• Access...

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute...

• Master Matplotlib for data visualization
• Customize basic plots to make and deploy figures in cloud environments
• Explore recipes to design various...

• Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values
• From Simple Linear Regression...

• Get up and running with the Jupyter ecosystem and some example datasets
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Examine and solve the common misconceptions and fallacies that non-statisticians bring to their interpretation of statistical results. Explore the many pitfalls that non-statisticians―and also statisticians who present statistical reports to non-statisticians―must avoid if statistical results are to be correctly used for...

• Cover all fundamental libraries for operation and manipulation of Python for data analysis
• Implement real-world datasets to perform predictive analytics with Python
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• Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance
• Get familiar with complex concepts such as monads,...