- Write clean and efficient Python code to support data handling and analysis tasks
- Understand key programming concepts such as data types, loops, and functions for structured workflows
- Use scripting to support repetitive analysis and improve preparation processes
- Load, clean, and reshape data using pandas DataFrames and Series
- Filter, group, and aggregate data to explore patterns and draw conclusions
- Work effectively with missing values, date formats, and combined data tables
- Create various chart types—including histograms, scatter plots, bar charts, and boxplots—with matplotlib and pandas
- Customize visuals to match analytical objectives and presentation contexts
- Combine pandas and matplotlib to build complete visual reports in Python
- Construct full analysis workflows, from data import and preparation to visualization and interpretation
- Apply tools and methods in practical projects such as taxi trip and churn analysis
- Gain confidence through hands-on experience with real datasets and structured analytical processes