Matplotlib is a Python library for drawing plots that make numerical and geometric ideas easier to inspect. It becomes useful when formulas or approximations need a visual explanation. section 6.2.3
Matplotlib supports practical mathematical communication by:
- Turning application data into plots, such as workout times measured across rowing sessions. section 6.2.3
- Showing how a linear approximation follows a trend and how polynomial approximation generalizes that idea. section 6.2.3
- Working alongside SymPy for formulas and NumPy for numerical computations in application-focused examples. section 1.5
Plotting a trend in rowing times
Represent five workout sessions and their 2000-meter times, then plot the measurements with an approximating line. The resulting figure makes the trend visible and gives the approximation a concrete geometric interpretation. section 6.2.3
Table 6.1 2000-meter rowing times per workout session (view table figure)
Inspect the session-by-session rowing measurements used as the concrete plotting data. section 6.2.3
