Programming and Plotting in Python

Python programs 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.

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.

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.

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.

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.

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.

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.

Can plot many sets of data together.

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.

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 call are matched to parameters in definition.

Functions may return a result to their caller using return.

Python supports a large community within and outwith research.