1 Programming Foundations for Data Science

Variables and values

A variable is a name bound to a value. Assign a value with =, and choose descriptive names such as temperature or row_count to make code easier to understand. Python determines an object’s data type at runtime, so the same name can later refer to a value of a different type.

Common built-in types include:

• int for whole numbers, such as 12.

• float for numbers with a decimal part, such as 3.5.

• bool for True or False, often used in tests.

• str for text, such as "sample A".

• NoneType for the type of None, which is commonly used to represent an absent value.

Text that looks numeric is still a string: "12" is a str, not an int. Convert values explicitly when needed, for example with int("12") or float("3.5"). Conversion can fail if the text is not a valid number, so check data from external sources before relying on it.

Collections

Collections group related values. Choose a collection according to how its data will be accessed or changed.

• A list (list) is an ordered, changeable sequence. Use it for values you may add, remove, or update, such as scores = [82, 91, 76].

• A tuple (tuple) is an ordered sequence that cannot be changed after creation, such as location = (40.7, -74.0).

• A dictionary (dict) is a changeable mapping from keys to values, useful for records with named fields, such as record = {"site": "north", "count": 18}.

• A set (set) contains distinct values and is useful for membership checks or removing duplicates, such as sites = {"north", "south"}.

Lists and tuples use positions starting at index 0; for example, scores[0] accesses the first list item. Dictionaries are accessed by key, as in record["count"]. Use len(collection) to get a collection’s size and value in collection to test membership. Lists and dictionaries can be changed, while tuples cannot; sets do not provide positional indexing.

Conditions

A conditional chooses which instructions to run. if evaluates a condition; elif checks another condition if earlier tests were false; and else handles the remaining case. Comparisons such as ==, !=, <, and >= produce Boolean values. Combine tests with and, or, and not.

Use is None to check specifically for the missing-value marker None. Empty collections and zero are also treated as false in conditions, so distinguish these cases when they have different meanings in your data.

Loops

A loop repeats instructions. A for loop visits each item in an iterable, such as a list or dictionary, and is useful when the items themselves define what to process. A while loop repeats as long as a condition remains true; ensure its condition can eventually become false to avoid an endless loop.

Use range(n) when a fixed number of iterations is needed. break exits the innermost loop, while continue skips to the next iteration.

Functions for reusable operations

A function names a reusable operation. Define one with def, give it parameters for its inputs, and use return to send a result back to the caller. If a function reaches its end without a return statement, it returns None.

The following function collects available scores from records, skips missing scores, and returns None if no scores are available. That check avoids dividing by zero.

In this example, a list holds records, each dictionary represents a record, a loop examines each score, and a conditional skips missing values. Functions make repeated operations easier to test and reuse; descriptive names and a short docstring clarify their purpose.