final review/overview

all topics

• simple variable types
• arithmetic and logical operators
• repr() (print representation)
• logical expressions
• indexing and slicing (strings, lists, arrays, data frames …)
• string methods (.lower(), .upper(), .replace(), .isalpha()
• lists, list operators (+=), list methods
• mutability
• conditionals and flow control
  • if, for, while (break)
  • nested loops
• functions
• modules
• tuples, tuple methods
• files
  • opening and closing, .closed
  • .read(), .readlines(), next, StopIteration
  • .strip(), .split(), type conversion
• sets (non-ordered, unique): .add, .remove, …
• dictionaries
  • indexing (not by number unless keys are numeric)
  • .keys(), .values(), .items(), for
  • inversion
• random numbers (random or numpy.random)
  • random.seed()
  • .choice, .uniform, .randrange
  • Monte Carlo methods/simulations
  • use np.mean or np.sum on a bool array to count fraction or total
• numpy
  • arrays
    • defining with dtype
    • .shape
    • zeros(), ones(), eye(), identity, reshape(), flatten(), arange(), linspace(), copy(), fill()
    • operators, indexing, slicing, selections by logical
    • vectorized and non-vectorized operators (np.sin vs math.sin)
    • operations over axes: sum, mean, min, max, newaxis
    • np.logical.[and,not,or]
• numerics
  • underflow (too close to zero)
  • overflow (integer and float)
  • loss of precision (small number + large number)
  • nan
• matplotlib
  • .plot (uses index as x-variable if no x provided: draws lines by default)
  • fig, ax = plt.subplots()
  • .scatter (draws points by default)
  • .hist (histogram)
  • .bar (barplot)
  • set_xlabel, set_xticklabels, suptitle (recognize)
  • label, legend
  • imshow (image)
• error handling
  • raise
  • try/except (pass)
  • ValueError (inappropriate value), NameError (undefined symbol), IndexError (incorrect indexing), TypeError (inappropriate type)
• pandas
  • DataFrame and Series
  • indexing: .loc and .iloc; indexing columns d[["key1","key2"]]; extracting columns as d.key1
  • read_csv(), .to_csv()
  • operations across rows/columns
  • .groupby, .aggregate (collapse by group: MC only)