Key Points

Getting Started

  • You can launch JupyterLab from the command line or from Anaconda Navigator.
  • You can use a JupyterLab notebook to edit and run Python.
  • Notebooks can include both code and markdown (text) cells.

Variables and Data Types

  • Use print() to display values.
  • Use # to add comments that explain why the code does what it does.
  • Use = to assign a value to a variable.
  • Basic data types are strings (str), integers (int), floating point numbers (float), and booleans (bool).
  • Use type() to find out the type of a value.
  • Jupyter displays the value of the last line of a cell.

Operators, Functions and Methods

  • The type of a value determines what an operator does with it.
  • Read error messages from the bottom up: the last line names the error.
  • Use int(), float() and str() to convert between types.
  • Functions are called with function(arguments), methods with object.method(arguments).
  • String methods return a new value and do not change the original string.

Lists and Dictionaries

  • A list stores many values in order: [value1, value2, ...].
  • Use list[index] to access an element; indexing starts at 0.
  • Use list[start:stop] to select a slice; stop is not included.
  • A dictionary stores key-value pairs: {key: value, ...}.
  • Use dictionary[key] to look up a value.

Loops and Conditionals

  • A for loop runs its indented body once for each element of a collection.
  • Use if, elif and else to choose which code to run.
  • Conditions are tested in order; the first one that is True wins.
  • Indentation defines which lines belong to a loop or an if statement.

Introduction to pandas

  • Use import library as alias to load a library.
  • pd.read_csv() reads a CSV file into a DataFrame.
  • Use .head(), .shape and .columns to get an overview of a DataFrame.
  • df["column"] selects a column, df[["col1", "col2"]] several columns.
  • df[condition] keeps only the rows where the condition is True.
  • Series have methods for statistics (.mean(), .median(), …) and plotting (.hist(), .plot.bar(), …).

Retrieving Metadata from an API

  • A web API lets programs request data from a web service via a URL.
  • urllib.request.urlopen(url).read() downloads the response of a URL.
  • json.loads() converts JSON text into Python dictionaries and lists.
  • Navigate nested data step by step: data["titles"][0]["title"].
  • DataCite registers DOIs for data and software, Crossref for most articles.