Python is one of the many languages used by the data science community to perform data manipulation, statistical modeling and machine learning. Its design philosophy emphasizes code readability. The python community is huge, offering an enormous library of technical support documentation. If you don't know how to do something in Python, chances are, someone else asked a similar question online and received a comprehensive answer.

Resources

• Python Website

• Python Tutorials

• Think Python: How to Think Like a Computer Scientist

• Hypermodern Python

This page provides syntax for different data types in Python as well as some of their associated functions. Each section includes an example to demonstrate the described syntax or function.

Strings

• A string is a sequence of one or more characters (index values start at 0)

Some functions and index methods that can be performed on strings

Input:

# strings.py

letter = "b"
word = "good-bye"
subword = "good"

word_length = len(word)
word_first_char = word[0]
word_subword = word[5:8]

print(f"Length of word: {word_length}")
print(f"First letter: {word_first_char}")
print(f"Last three characters: {word_subword}")

print(f"{letter} is in {word}: {(word.index(letter))}")
print(f"{subword} is in {word}: {(subword in word)}")
print(f"remove the last character: {(word[:-1])}")

Output:

Length of word: 8
First character: g
Last three characters: bye
b is in good-bye: 5
good is in good-bye: True
chop off the last character: good-by

Resources

• W3 Schools: Python Strings

Instructions for installing Python on macOS and Windows operating systems can be found here.

For most users, it is recommended to download the current stable release from https://www.python.org/downloads/.

Some developers might wish to use a different version, or to switch between versions. For this, the Python version manager can be useful.

Python is also available for use in Brown's Computing Environments:

• Oscar (for high-performance computing)

• Stronghold (for secure computing)

macOS 16.X Ventura

The following instructions have been tested on computers running macOS 16 Big Ventura. In order to check the macOS version running on your computer, click on the "apple" icon in the top left hand corner of your screen and select "About This Mac." A window will pop up that includes a version number. Confirm you are running at least Version 16.X (where 'X' is any number). These instructions will likely work with earlier versions of macOS as well. If you are not running macOS 11.X Big Sur, you can upgrade for free following the instructions provided on Apple's website.

1. Download Python

Navigate to https://www.python.org/downloads/ and download the most recent version of Python for macOS.

1. Install Python

Open the downloaded file (e.g., python-3.12.3-macos11.pkg). A window will pop up with installation instructions. Progress through the prompts until Python has been installed in your Applications folder. Next, double click on the Python folder shortcut in your Applications folder to open it.

1. Run Python

Open, Terminal, type python3, and hit return. Python should open. To quit Python, type quit() and hit return.

1. Troubleshooting

If you get a Permission denied error, rerun the command prepended with sudo. You will be prompted to enter your computer password.

WindowsOS

The following instructions have been tested on computers running Windows 10. Confirm that you are running at least Windows 10. These instructions will likely work with earlier versions of Windows, however they have not been tested.

1. Download Python

Navigate to https://www.python.org/downloads/ and download the most recent version of Python for Windows (32-bit or 64-bit depending on the specifications of your device).

1. Install Python

Open the downloaded file (e.g., python-3.10.10-amd64.exe). A window will pop up with installation instructions. Progress through the prompts until Python has been installed on your device. When prompted with Advanced Options, make sure to check "Add Python to environment variables".

1. Run Python

Open Command Prompt, type py, and hit enter. Python should open to quit Python, type quit() and hit return.

"Hello, World!" Program

This is the typical first program for those new to a general purpose programming language like Python. It can be used to test that the Installation of Python is working and also introduce Python's basic syntax using the REPL environment or running code written using a Text Editor at the Unix command line.

Input:

# hello.py
# This is a single line comment 
'''
This is a block comment to show 
comments across multiple lines.
'''

print("Hello, World!")

Output:

Hello, World!

Here are variations of the "Hello, World!" programming using variables and different print statements.

Input:

# hello2.py

greeting = "Hello, World!"

print(greeting) # print greeting
print(f"Greeting 1: {greeting}") # print greeting as part of a string phrase
print(f"Greeting 2: {greeting}\n") # print with newline (\n) character

Output:

Hello, World!
Greeting 1: Hello, World!
Greeting 2: Hello, World!

Variable Assignment

In order to assign variables in Python, you write the desired name for your variable, an “=” sign, and what the value of the variable should be.

Input:

x = 7
x

Output:

7

Comments

• We can write comments on our code, which do not run, to describe what certain lines of code or section of code do

  • These comments are just for the programmer, they will not appear anywhere in the output and just are there to explain what the code is doing or to provide helpful notes

  • To make a comment in Python, you can use the “#” symbol and then type your comment

• Sometimes you might want to write longer comments that span multiple lines – to do this you can surround these comments with three tick marks above the start as well as three tick marks below the end

Input:

# Assigns variable x to have value 7
x = 7

'''
Now we want to print out what x is. We can do this by simply typing x and 
hitting run. This comment spans multiple lines. These types of comments are 
useful when describing complex functions or algorithms.
'''

x

Output:

7

Print Statements

Without using a print statement, Python will only print out the most recent item that has an output. In order to print multiple things, we can use the print() function

Input:

# Assign x, y, and z variables 
x = 7
y = 10
z = 4

z
print(x)
print(y)

Output:

7
10

Indentation

Python is very sensitive with its indentation notation. Indentation should only be used in hierarchical structures, such as a class, function, or loop. Indents in improper locations will cause an error

Input:

# Assign x and y variables 

x = 7
    y = 10
    
print(x)
print(y)

Output:

IndentationError: unexpected indent

Exercises

• Use Python in Brown Oscar Computing Environment - Forthcoming!

• Use Python in Brown Stronghold Computing Environment - Forthcoming!

Resources

• Real Python: Variables

• W3 Schools: Comments

In computer programming, a package is a collection of modules or programs that are often published as tools for a range of common use cases, such as text processing and doing math. Programmers can install these packages and take advantage of their functionality within their own code.

This page provides instructions for installing, using, and troubleshooting packages in Python.

This page provides syntax for using numbers and mathematic operations in Python. Each section includes an example to demonstrate the described syntax and operations.

Types of Numbers

• Integer (positive and negative counting number) - e.g., -3, -2, -1, 0, 1, 2, and 3:

  • int - holds signed integers of non-limited length

  • long - holds long integers (exists in Python 2.X, depreciated in Python 3.X)

• Float (real or floating point numbers) - e.g., -2.14, 0.0, and 3.777

  • float

• Boolean: (0 = False and 1 = True)

  • bool

Use type() function to determine type

Input:

# Define two variables x and y
x = 100
y = 3.14

# Print out the variable types for each
print(type(x))
print(type(y))

Output:

<class 'int'>
<class 'float'>

Arithmetic Operators

Input:

# Demonstrates different math operations
using f-strings

n1 = 7    # First number
n2 = 3    # Second number
 
# Output results of different math operations
print(f"{n1} + {n2} = {(n1 + n2)}")           # Addition
print(f"{n1} - {n2} = {(n1 - n2)}")           # Subtraction 
print(f"{n1} * {n2} = {(n1 * n2)}")           # Multiplication 
print(f"{n1} / {n2} = {(n1 / n2)}")           # Division 
print(f"{n1} // {n2} = {(n1 // n2)}")         # Floor Division
print(f"{n1} ** {n2} = {(n1 ** n2)}")         # Power/Exponent
print(f"{n1} % {n2} = {(n1 % n2)}")           # Modulo/Remainder

Output:

7 + 3 = 10
7 - 3 = 4
7 * 3 = 21
7 / 3 = 2.3333333333333335
7 // 3 = 2
7 ^ 3 = 343
7 % 3 = 1

Comparison Operators and Functions

Input:

# compare.py
# Demonstrate comparison operators                                                                               

# Assign values to variables using parallel assignment                                                           
c1, c2, c3, c4 = 25, 50, 75, 50
print(f"  c1 = {c1}, c2 = {c2}, c3 = {c3}), c4 = {c4}")

# Output results of different comparison operations                                                             
 
# Testing equality                                                                                               
print(f"c1 = c3 is {(c1 == c3)}")

# Changing values using abbreviated assignment operators                                                        
c1 *= 3    	# Shorthand for c1 = c1 * 3                                                                       
c4 += 1    	# Shorthand for c4 = c4 + 1                                                                       

print(f"c1 = {c1}, c2 = {c2}, c3 = {c3}, c4 = {c4}")
 
# Testing less than and greater than
print(f"  c1 < c2 is {(c1 < c2)}")
print(f"  c4 <= c2 is {(c4 <= c2)}")
print(f"  c1 > c2 is {(c1 > c2)}")
print(f"  c3 >= c2 is {(c3 >= c2)}")

Output:

 c1 = 25, c2 = 50, c3 = 75), c4 = 50
c1 = c3 is False
c1 = 75, c2 = 50, c3 = 75, c4 = 51
  c1 < c2 is False
  c4 <= c2 is False
  c1 > c2 is True
  c3 >= c2 is True

Exercises

• Create a Health Calculator Using Python - Forthcoming!

Resources

• W3 Schools: Python Data Types

• W3 Schools: Python Arithmetic Operators

• W3 Schools: Python Numbers

In computer science, control flow (or flow of control) is the order in which individual statements, instructions or function calls of an imperative program are executed or evaluated. [1]

This page provides syntax for some of the common control flow methods in Python. Each section includes an example to demonstrate the described methods

Use Cases and Syntax

• Test if a specified expression is true or false

• Short-circuit evaluation

  • Test if all of the conditions are true x and y

  • Test if any of the conditions are true x or y

  • Test if a condition is not true not z

• Conditional evaluation

  • if statement

  • if-else

  • if-elif-else

  • Ternary operator

    • true_value if condition else false_value

Conditional Statements

Input:

x, y, z = 100, 200, 300
print(f"x = {x}, y = {y}, z = {z}")

# Test if x equals 100
if x == 100:
    print(f"{x} equals 100")
    
# Test if y does not equal z
if y != z:
    print(f"{y} does not equal {z}")
    
# Test multiple conditions
if x < y < z:
    print(f"{y} is less than {z} and greater than {x}")

# Test multiple conditions using "and"
if x < y and x < z:
    print(f"{x} is less than {y} and {z}")

# Test multiple conditions using "or"
if y < x or y < z:
    print(f"{y} is less than {x} or {z]")

# if-else statement 
if x < 100:
    print(f"{x} less than 100")
else:
    print(f"{x} is equal to or greater than 100")
    
# Same logic as above but using the ternary operator
print(f"{x} less than 100 again" if x < 100 else f"{x} equal to or greater than 100 again")

# if-elif-else statement
if y < 100:
    print(f"{y} is less than 100")
elif y < 200:
    print(f"{y} is less than 200")
elif y < 300:
    print(f"{y} is less than 300")
else:
    print(f"{y} is greater than or equal to 300")

Output:

x = 100, y = 200, z = 300
100 equals 100
200 does not equal 300
200 is less than 300 and greater than 100
100 is less than 200 and 300
200 is less than 100 or 300
100 is equal to or greater than 100
100 equal to or greater than 100 again
200 is less than 300

Loops

• Repeat a block of code a specified number of times or until some condition is met

• while loop

• for loop

• Use break to terminate loop

Input:

# Demonstrates use of loops

i = 1

# while loop for incrementing i by 1 from 1 to 3
while i <= 3:
    print(f"while: {i}")
    i +=1

# for loop 
for j in range(1,4):
    print(f"for: {j}")
    
for j in range(1,4):
    print(f"for again: {j}")
    
# nested for loop
for j in range(1,4):
    for k in range(1,4):
        print(f"nested for: {j} * {k} = {j*k}")

Output:

while: 1
while: 2
while: 3
for: 1
for: 2
for: 3
for again: 1
for again: 2
for again: 3
nested for: 1 * 1 = 1
nested for: 1 * 2 = 2
nested for: 1 * 3 = 3
nested for: 2 * 1 = 2
nested for: 2 * 2 = 4
nested for: 2 * 3 = 6
nested for: 3 * 1 = 3
nested for: 3 * 2 = 6
nested for: 3 * 3 = 9

Comparison Operators and Functions

Input:

# Demonstrate comparison operators

# Assign values to variables using parallel assignment
c1, c2, c3, c4 = 25, 50, 75, 50
print(f"c1 = {c1}, c2 = {c2}, c3 = {c3}, c4 = {c4}")

# Output results of different comparison operations

# Testing equality
print(f" c1 = c3 is {c1 == c3}")
print(f" c2 = c4 is {c2 == c4}")

# Changing values using abbreviated assignment operators 
c1 *= 3     # shorthand for c1 = c1 * 3
c4 += 1     # shorthand for c4 = c4 + 1

print(f"c1 = {c1}, c2 = {c2}, c3 = {c3}, c4 = {c4}")

# Testing less than and greater than 
print(f" c1 < c2 is {c1 < c2}")
print(f" c4 <= c2 is {c4 < c2}")
print(f" c1 > c2 is {c1 > c2}")
print(f" c3 >= c2 is {c3 >= c2}")

Output:

c1 = 25, c2 = 50, c3 = 75, c4 = 50
 c1 = c3 is False
 c2 = c4 is True
c1 = 75, c2 = 50, c3 = 75, c4 = 51
 c1 < c2 is False
 c4 <= c2 is False
 c1 > c2 is True
 c3 >= c2 is True

Resources

• Python Documentation: Control Flow

• Python Wiki: For Loops

• W3 Schools: Python For Loops

• W3 Schools: Python Conditionals and If Statements

Python comes with a full-featured interactive command-line REPL (read-eval-print loop) built into the pythonexecutable. In addition to allowing quick and easy evaluation of Python statements, it has a searchable history, tab-completion, many helpful keybindings, and dedicated help ? and shell modes ;.

This page provides examples of using REPL on the command line

Python REPL Example (local)

• Type python in terminal to launch REPL

Python REPL Help Pages (local)

• Type "help" to enter help pages within REPL

• Type a function from Python to read help pages (ex:print)

• Press q to quit

Resources

• Real Python: The Python Standard REPL: Try Out Code and Ideas Quickly

Regular expressions are powerful tools for pattern matching and text processing. They are represented as a pattern that consists of a special set of characters to search for in a string str. The regex module needs to be imported before use.

This page provides syntax for regular expressions in Python . Each section includes an example to demonstrate the described methods.

Functions

Character Class

Character class specifies a list of characters to match ([...] where ... represents the list) or not match ([^...])

Anchors

Anchors are special characters that can be used to match a pattern at a specified position

Repetition and Quantifier Characters

Repetition or quantifier characters specify the number of times to match a particular character or set of characters

Input:

# regex.jl
number1 = "(555)123-4567"
number2 = "123-45-6789"

# check if matches
if occursin(r"\([0-9]{3}\)[0-9]{3}-[0-9]{4}", number1)
   println("match!")
end

if occursin(r"\([0-9]{3}\)[0-9]{3}-[0-9]{4}", number2)
  println("match!")
else
  println("no match!")
end

# capture matches
# use parentheses to "capture" different parts of a regular 
# expression for later use the first set of parentheses corresponds 
# to index 1, second to index 2, etc.

number_details = match(r"\(([0-9]{3})\)([0-9]{3}-[0-9]{4})", number1)

if number_details != nothing
   area_code = number_details[1]
   phone_number = number_details[2]

   println("area code: $area_code")
   println("phone number: $phone_number")
end

Output:

match!
no match!
area code: 555
phone number: 123-4567

Resources

• Regular Expressions 101

• Regular Expressions Library

• Regular Expressions Cheat Sheet

• W3 Schools: Python RegEx

In computer programming, a collection is a grouping of some variable number of data items (possibly zero) that have some shared significance to the problem being solved and need to be operated upon together in some controlled fashion. []

This page provides syntax for different types of collections and data structures in Python (arrays, sets, dictionaries, etc.). Each section includes an example to demonstrate the described methods

Arrays

Arrays are ordered collections of elements. In Python they are automatically indexed (consecutively numbered) by an integer starting with 0.

Creating Array From String

Accessing Elements

Adding and Removing Elements

Sort and Unique

Compare Arrays

Input:

Output:

Sets

Sets are an unordered collection of unique elements.

Creating Sets

Interacting With Sets

Comparing Sets

Input:

Output:

Dictionaries

Dictionaries are unordered collection of key-value pairs where the key serves as the index (“associative collection”). Similar to elements of a set, keys are always unique.

Creating Dictionaries

Accessing Dictionaries

Converting Dictionaries

Sorting Dictionaries

Input:

Output:

References

Resources

Many Python programs involve the input and output of files. When analyzing a dataset, that dataset file will need to be pulled into your program (input). If you want to see the results of your analysis, your program will need an output.

This section provides the syntax for inputting files (reading) and outputting results (writing) using base Python (i.e, no packages such as Pandas)

UC Irvine Machine Learning Repository: Adult Data Set

• Tabulate and report counts for sex in from the .

Dataset (example lines from adult.data)

Input (process_file.py)

Output

Terminal

Exercises

• Analyze the MIMIC-IV Demo Files Using Julia - Forthcoming!

• Analyze the SyntheticRI Demo Files Using Julia - Forthcoming

Resources