Data Analysis in Python with 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 provides fundamental support for numerical computing through array operations. Together, they create a robust ecosystem for efficient data work and analysis in Python.
Who is this course for?
- Python developers looking to expand their data analysis skills
- Data analysts eager to process and analyze tabular data efficiently
- Professionals wishing to integrate Python tools into their analytical workflows
Book the course
- Format: Remote
- Language: English
- Type: Open, guaranteed course
- Date: December 15-16, 2025
- Duration: 2 days (7h/day)
Net price per participant. Guaranteed courses require at least one participant.
Benefits of attending the course
- Setting up a professional development 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
- Performance optimization and code debugging
- Using additional Python libraries for data analysis (scikit-learn, SciPy, statsmodels, RPy2)
Course Agenda at a Glance
- 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.
Course Program
Day 1
- Review of Python and data analysis basics
- 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 a guaranteed course?
- Guaranteed execution. The course will take place regardless of the number of participants.
- Exchange of knowledge and experience with specialists from other industries.
- Interactive, live-led sessions. Not just theory, but also practical exercises and discussions.
- Flexible remote format. Join from anywhere.
Need Help?
Reach out to learn more about our team and the kinds of tailored solutions we can offer your organization.
Get in Touchwroclaw@nobleprog.pl or +48 (22) 103 3718