Running and Quitting

  • Python scripts are plain text files.
  • Use the Jupyter Notebook for editing and running Python.
  • The Notebook has Command and Edit modes.
  • Use the keyboard and mouse to select and edit cells.
  • The Notebook will turn Markdown into pretty-printed documentation.
  • Markdown does most of what HTML does.

Variables and Assignment

  • Use variables to store values.
  • Use print to display values.
  • Variables persist between cells.
  • Variables must be created before they are used.
  • Variables can be used in calculations.
  • Use an index to get a single character from a string.
  • Use a slice to get a substring.
  • Use the built-in function len to find the length of a string.
  • Python is case-sensitive.
  • Use meaningful variable names.

Data Types and Type Conversion

  • Every value has a type.
  • Use the built-in function type to find the type of a value.
  • Types control what operations can be done on values.
  • Strings can be added and multiplied.
  • Strings have a length (but numbers don’t).
  • Must convert numbers to strings or vice versa when operating on them.
  • Can mix integers and floats freely in operations.
  • Variables only change value when something is assigned to them.

Built-in Functions and Help

  • Use comments to add documentation to programs.
  • A function may take zero or more arguments.
  • Commonly-used built-in functions include max, min, and round.
  • Functions may only work for certain (combinations of) arguments.
  • Functions may have default values for some arguments.
  • Use the built-in function help to get help for a function.
  • The Jupyter Notebook has two ways to get help.
  • Every function returns something.
  • Python reports a syntax error when it can’t understand the source of a program.
  • Python reports a runtime error when something goes wrong while a program is executing.
  • Fix syntax errors by reading the source code, and runtime errors by tracing the program’s execution.

Morning Coffee

Libraries

  • Most of the power of a programming language is in its libraries.
  • A program must import a library module in order to use it.
  • Use help to learn about the contents of a library module.
  • Import specific items from a library to shorten programs.
  • Create an alias for a library when importing it to shorten programs.

Reading Tabular Data into DataFrames

  • Use the Pandas library to get basic statistics out of tabular data.
  • Use index_col to specify that a column’s values should be used as row headings.
  • Use DataFrame.info to find out more about a dataframe.
  • The DataFrame.columns variable stores information about the dataframe’s columns.
  • Use DataFrame.T to transpose a dataframe.
  • Use DataFrame.describe to get summary statistics about data.

Pandas DataFrames

  • Use DataFrame.iloc[..., ...] to select values by integer location.
  • Use : on its own to mean all columns or all rows.
  • Select multiple columns or rows using DataFrame.loc and a named slice.
  • Result of slicing can be used in further operations.
  • Use comparisons to select data based on value.
  • Select values or NaN using a Boolean mask.

Plotting

  • matplotlib is the most widely used scientific plotting library in Python.
  • Plot data directly from a Pandas dataframe.
  • Select and transform data, then plot it.
  • Many styles of plot are available: see the Python Graph Gallery for more options.
  • Can plot many sets of data together.

Lunch

Lists

  • A list stores many values in a single structure.
  • Use an item’s index to fetch it from a list.
  • Lists’ values can be replaced by assigning to them.
  • Appending items to a list lengthens it.
  • Use del to remove items from a list entirely.
  • The empty list contains no values.
  • Lists may contain values of different types.
  • Character strings can be indexed like lists.
  • Character strings are immutable.
  • Indexing beyond the end of the collection is an error.

For Loops

  • A for loop executes commands once for each value in a collection.
  • A for loop is made up of a collection, a loop variable, and a body.
  • The first line of the for loop must end with a colon, and the body must be indented.
  • Indentation is always meaningful in Python.
  • Loop variables can be called anything (but it is strongly advised to have a meaningful name to the looping variable).
  • The body of a loop can contain many statements.
  • Use range to iterate over a sequence of numbers.
  • The Accumulator pattern turns many values into one.

Conditionals

  • Use if statements to control whether or not a block of code is executed.
  • Conditionals are often used inside loops.
  • Use else to execute a block of code when an if condition is not true.
  • Use elif to specify additional tests.
  • Conditions are tested once, in order.
  • Create a table showing variables’ values to trace a program’s execution.

Looping Over Data Sets

  • Use a for loop to process files given a list of their names.
  • Use glob.glob to find sets of files whose names match a pattern.
  • Use glob and for to process batches of files.

Afternoon Coffee

Writing Functions

  • Break programs down into functions to make them easier to understand.
  • Define a function using def with a name, parameters, and a block of code.
  • Defining a function does not run it.
  • Arguments in a function call are matched to its defined parameters.
  • Functions may return a result to their caller using return.

Variable Scope

  • The scope of a variable is the part of a program that can ‘see’ that variable.

Programming Style

  • Follow standard Python style in your code.
  • Use docstrings to provide builtin help.

Wrap-Up

  • Python supports a large and diverse community across academia and industry.

Feedback

  • We are constantly seeking to improve this course.