Python Collections: Lists, Strings, Dictionaries, and Basic Statistics

Python Collections

Introduction to Python Collections

Python provides several built-in data structures for storing and organizing data. Collections are fundamental for managing data in programs, enabling efficient access, modification, and analysis. The main types of collections in Python are sequential collections (such as lists and strings) and non-sequential collections (such as dictionaries).

• Lists are used to store ordered, heterogeneous data.

• Dictionaries store associative data as key-value pairs.

• Strings are sequences of characters.

Sequential Collections: Lists and Strings

Lists

A list in Python is a mutable, ordered collection of items, which can be of different types. Lists are defined using square brackets [ ] and can be indexed and sliced.

• Definition: A list is a sequence of Python objects, delimited inside square brackets.

• Example: myList = [3, "cat", 6.5, 2]

• Lists are mutable, meaning their contents can be changed after creation.

Figure 4.2: Sequential storage of the elements in a list with indices:

Index	0	1	2	3
Value	3	'cat'	6.5	2

Strings

A string is a sequence of characters. Unlike lists, strings are immutable, meaning their contents cannot be changed after creation.

• Strings are defined using single or double quotes.

• Individual characters can be accessed by indexing, but cannot be changed.

Operations on Python Sequences

Common Sequence Operations

Python provides several operations that can be performed on sequences such as lists and strings.

Operation Name	Operator/Function	Explanation
Indexing	[ ]	Accesses an element of a sequence by its position.
Concatenation	+	Combines sequences of the same type.
Repetition	*	Concatenates a repeated number of times.
Membership	in	Asks whether an item is in a sequence.
Non-membership	not in	Asks whether an item is not in a sequence.
Length	len	Asks the number of items in the sequence.
Slicing	[ : ]	Extracts a part of a sequence.

Additional info: Lists support the del statement to delete items, which is not available for strings.

Mutability of Lists and Strings

Lists are mutable, allowing modification of their elements, while strings are immutable and do not support item assignment.

• List items can be changed by assignment.

• String items cannot be changed; attempting to do so raises an error.

List Methods

Common List Methods

Python lists provide several methods for manipulating their contents.

Method or Function Name	Use	Explanation
list(sequence)	Function	Creates a list from the elements in sequence.
append(item)	Method	Adds an item to the end of a list.
insert(i, item)	Method	Inserts item at position i.
pop()	Method	Removes and returns the last item.
pop(i)	Method	Removes and returns item at position i.
sort()	Method	Arranges items in order.
reverse()	Method	Reverses the order of items.
index(item)	Method	Returns the index of the first occurrence of item.
count(item)	Method	Returns the number of occurrences of item.
remove(item)	Method	Removes the first occurrence of item.
clear()	Method	Removes all items from the list.
copy()	Method	Returns a copy of the list.

Creating Lists

Using the list() Function

The list() function can be used to create lists from sequences such as ranges or strings.

• Example: list(range(10)) produces [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

• Example: list("the quick fox") produces ['t', 'h', 'e', ' ', 'q', 'u', 'i', 'c', 'k', ' ', 'f', 'o', 'x']

Dictionaries

Introduction to Dictionaries

A dictionary is a non-sequential collection that stores data as key-value pairs. Dictionaries are defined using curly braces {} and allow fast lookup of values by their keys.

• Definition: A dictionary is a collection of associated key-value pairs.

• Example: myDict = {"name": "Alice", "age": 25}

• Dictionaries are mutable and can be modified after creation.

Dictionary Operations and Methods

Operator/Method	Explanation
[key]	Accesses the value associated with a key.
in	Checks if a key exists in the dictionary.
del	Deletes a key-value pair.
keys()	Returns a list of all keys.
values()	Returns a list of all values.
items()	Returns a list of key-value pairs.
get(key)	Returns the value for a key, or None if not found.
update(dict2)	Updates the dictionary with another dictionary.

Elementary Statistics with Python

Basic Statistical Functions

Python provides built-in functions and modules to compute elementary statistics on lists of data. These include minimum, maximum, sum, range, mean, median, and mode.

• min(sequence): Returns the smallest item in the sequence.

• max(sequence): Returns the largest item in the sequence.

• sum(sequence): Returns the sum of the items in a numeric sequence.

• Range: $\text{Range}(aList) = \max(aList) - \min(aList)$

• Mean (Average): $\text{Mean} = \frac{\sum x_i}{n}$

• Median: The middle value in a sorted list. If the list has an even number of items, the median is the average of the two middle values.

• Mode: The value(s) that appear most frequently in the list.

Standard Deviation

Standard deviation measures the dispersion of data points from the mean. It is calculated as:

• $s = \sqrt{\frac{\sum (x - \bar{x})^2}{n-1}}$

Data Visualization: Histograms

Producing a Histogram Using Matplotlib

Histograms are graphical representations of the distribution of numeric data. In Python, the matplotlib.pyplot module is commonly used to create histograms.

• Frequency count data can be visualized using plt.hist() from matplotlib.pyplot.

• Histograms help in understanding the spread and central tendency of data.

Summary Table: Python Collections

Type	Sequential	Non-sequential
Strings	Yes	No
Lists	Yes	No
Dictionaries	No	Yes

Additional info:

• Lists and dictionaries are mutable, while strings are immutable.

• Python's statistics module provides functions such as mean(), median(), mode(), and stdev() for statistical analysis.

• Data must be collected and stored before analysis can be performed.