Data Analysis in Python using Pandas and NumPy
Course Description
Python is a versatile programming language valued for its simplicity and readability. Pandas is a Python library that provides data structures for working with tabular, multidimensional, and time-series data. NumPy offers fundamental support for numerical computations through array operations. Together, they create a robust ecosystem for efficient data work and analysis in Python.
Who is it for?
- Python programmers looking to expand their data analysis skills
- Data analysts aiming to efficiently process and analyze tabular data
- Specialists looking to integrate Python tools into their analytical processes
Book the Training
- Format: Remote
- Language: Polish
- Type: Open, guaranteed training
- Date: 15-16.12.2025
- Duration: 2 days (7h/day)
Net price per participant. Guaranteed trainings require at least one participant.
Benefits of Attending the Training
- Configuring a professional working environment for Python, Pandas, and NumPy
- Creating data analysis applications
- Advanced data transformation, sorting, filtering, and aggregation
- Working with time-series data
- Data visualization using Matplotlib and Jupyter Notebook
- Optimizing performance and debugging code
- Utilizing additional Python libraries for data analysis (scikit-learn, SciPy, statsmodels, RPy2)
Agenda Overview
- Day 1: NumPy basics, Pandas in data analysis, Data visualization with Matplotlib
- Day 2: Advanced Python libraries for data analysis, Summary and next steps
Prerequisites
Basic knowledge of Python and fundamental data analysis concepts.
Training Program
Day 1
- Review of basic Python and data analysis concepts
- Introduction to NumPy: creating arrays, matrix operations, ufuncs, views and broadcasting, performance optimization with cProfile
- Data analysis with Pandas: vectorized data, transformation, sorting, filtering, aggregation, time-series analysis
- Data visualization with Matplotlib: creating plots, integration with Pandas, visualization in Jupyter Notebook, other visualization libraries
Day 2
- Other Python libraries for data analysis: scikit-learn, SciPy, statsmodels, RPy2
- Summary and next steps
Why Guaranteed Training?
- Guaranteed execution. The training will take place regardless of the number of participants.
- Exchange of knowledge and experiences with specialists from other industries.
- Interactive, live-led sessions. Not just theory, but also practical exercises and discussions.
- Flexible remote format. Join from anywhere.
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