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Course Outline
Day 1:
Review of Basic Python and Data Analysis Skills for Government
Introduction to NumPy for Government
- Creating NumPy arrays for data management tasks
- Performing common operations on matrices for efficient computation
- Utilizing universal functions (ufuncs) for vectorized operations
- Understanding views and broadcasting in NumPy arrays for optimized memory usage
- Enhancing performance by avoiding loops in data processing
- Optimizing code performance with cProfile for government applications
Data Analysis with Pandas for Government
- Leveraging vectorized data operations in pandas for efficient data handling
- Conducting data wrangling tasks to prepare datasets for analysis
- Sorting and filtering data to extract meaningful insights
- Performing aggregate operations to summarize data effectively
- Analyzing time series data for trend identification and forecasting
Data Visualization with Matplotlib for Government
- Creating diagrams using Matplotlib for clear data representation
- Integrating Matplotlib within pandas for streamlined visualization workflows
- Producing high-quality diagrams to support decision-making processes
- Visualizing data in Jupyter notebooks for interactive exploration
- Exploring other visualization libraries in Python for enhanced graphical capabilities
Day 2:
Additional Python Libraries for Data Analysis for Government
- scikit-learn for machine learning and predictive analytics
- Scipy for scientific computing and advanced mathematical operations
- statsmodels for statistical modeling and hypothesis testing
- RPy2 for integrating R statistical functions within Python scripts
Summary and Next Steps for Government Applications
Requirements
- Foundational Python programming and data analysis capabilities
Audience
- Python developers for government
- Data analysts
14 Hours
Testimonials (1)
Trainer develops training based on participant's pace
