Course Outline

Day 1:

Basic Python and Data Analysis Skills Review

Introduction to NumPy

  • Creating NumPy arrays
  • Common operations on matrices
  • Using ufuncs
  • Views and broadcasting on NumPy arrays
  • Optimizing performance by avoiding loops
  • Optimizing performance with cProfile

Data Analysis with Pandas

  • Using vectorized data in pandas
  • Data wrangling
  • Sorting and filtering data
  • Aggregate operations
  • Analyzing time series

Data Visualization with Matplotlib

  • Plotting diagrams with Matplotlib
  • Using Matplotlib from within pandas
  • Creating quality diagrams
  • Visualizing data in Jupyter notebooks
  • Other visualization libraries in Python

Day 2: 

Other Python Libraries for Data Analysis

  • scikit-learn
  • Scipy
  • statsmodel
  • RPy2

Summary and Next Steps

Requirements

  • Basic Python and data analysis skills

Audience

  • Python developer
  • Data analysts
 14 Hours

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