When Python Writing is Triggered
Ana automatically switches to Python analysis when your requests involve:- Any calculations (even simple math)
- Statistical analysis and summaries
- Pattern identification in data
- Data aggregation or grouping
- Data filtering or transformation
- Data preparation for visualization
What You’ll See During Python Writing
When Ana uses Python for analysis, you’ll observe:- Python code execution results
- Data analysis outputs
- Statistical summaries
- Memory usage indicators
- Computation progress updates
Supported Python Libraries
Ana comes pre-configured with a comprehensive set of data science libraries:| Category | Library | Description |
|---|---|---|
| Data Processing | pandas | Data manipulation and analysis |
| numpy | Numerical computing with arrays | |
| scipy | Scientific and technical computing | |
| pyarrow | High-performance data serialization and transport | |
| tabulate | Pretty-print tabular data | |
| Statistical Analysis | statsmodels | Statistical modeling and testing |
| scikit-learn | Machine learning and statistical tools | |
| sympy | Symbolic mathematics | |
| Visualization | matplotlib | Plotting and data visualization |
| seaborn | Statistical data visualization | |
| cartopy | Geospatial plotting | |
| folium | Interactive maps | |
| Optimization | ortools | Operations research and combinatorial optimization |
| pulp | Linear programming and optimization | |
| Geospatial | shapely | Geometric objects and operations |
| pygeos | Geometric operations with speed | |
| Process Mining | pm4py | Process mining and workflow analysis |
| Utilities | grpcio-tools | gRPC tools for protocol buffers |
| protobuf | Protocol buffers serialization | |
| Pillow | Image processing |