Use when "scientific computing", "astronomy", "astropy", "bioinformatics", "biopython", "symbolic math", "sympy", "statistics", "statsmodels", "scientific Python"
Domain-specific Python libraries for scientific applications.
| Library | Domain | Purpose |
|---|---|---|
| AstroPy | Astronomy | Coordinates, units, FITS files |
| BioPython | Bioinformatics | Sequences, BLAST, PDB |
| SymPy | Mathematics | Symbolic computation |
| Statsmodels | Statistics | Statistical modeling, tests |
Astronomy and astrophysics computations.
Key capabilities:
Key concept: Unit-aware calculations prevent errors from unit mismatches.
Bioinformatics - sequences, structures, databases.
Key capabilities:
Key concept: SeqIO for reading any sequence format, Seq for sequence operations.
Symbolic mathematics - algebra, calculus, equation solving.
Key capabilities:
Key concept: Work with symbols, not numbers. Get exact answers, not approximations.
Statistical modeling with R-like formula interface.
Key capabilities:
y ~ x1 + x2)Key concept: model.summary() gives comprehensive statistical output like R.
| Domain | Library |
|---|---|
| Astronomy/astrophysics | AstroPy |
| Biology/genetics | BioPython |
| Symbolic math | SymPy |
| Statistical analysis | Statsmodels |
| Numerical computing | NumPy, SciPy |
| Data manipulation | Pandas |