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Python for Quantitative Finance / Scientific Python Bridge

Overview

Every result produced across this unit's seven earlier topics has been read as a printed number, a True/False, or a short trace of print statements. This closing topic adds one more way to read a result: a plot. docs/programme-profiles/library/introduction-to-python.md names this Stage 8, "hand-off to numerics and ML" — deliberately the unit's shortest and lightest-touch topic, whose entire job is to make a reader comfortable producing a correctly labelled chart and to point forward, explicitly, to the numpy-array-based vectorisation and pandas DataFrame machinery that learn/library/programming/ds-a/ and the vault's future learn/library/programming/ml/ notes develop properly. This topic does not attempt to teach vectorisation, broadcasting, or DataFrames — following the reconciliation between Guttag's actual chapter coverage (plotting only, in section 11.1–11.2) and the vault's grounding-over-coverage rule, those topics are deferred rather than authored from web knowledge.

In this lesson

  1. Learning objectives
  2. Contents
  3. The big picture

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