Python Cheatsheet: The Basics

Author: Narendra Mandadapu
Posted: Jul 22, 2023

Python Data Types
Comparison Operators
Python Operators
Operator precedence
Conditional Operators
Loops
- For Loops
- While Loops
Conditional Statements
Try/Except
Error Types
Range
Webscraping
Requests
Functions
Working with Files
- Reading a File
- Writing to a File
Objects and Classes

Python Data Types

String

Series of characters or data stored as text

my_string = "Hello"

String Operations

# returns the string with all uppercase letters
my_string.upper()

# returns the length of a string
len(my_string)

# returns the index of the first instance of the string inside the
# subject string, otherwise -1

my_string.find('l')

# replaces any instance of the first string with the second in my_string
my_string.replace('H', 'C')

Integer

A whole number

my_integer = 12321

Boolean

Discrete value true or false

a = True
b = False

Dictionary

Changeable collection of key value pairs

my_dictionary = {'banana': 1, 12: 'laptop', (0,0):'center'}

Dictionary Operations

Changeable collection of key value pairs

# Access value using key
my_dictionary['banana']

# Get all keys in a dictionary as a list
my_dictionary.keys()

# Get all values in a dictionary as a list
my_dictionary.values()

Tuple

Unchangeable collection of objects

# Access value using key
tup = (1, 3.12, False, "Hi")

List

Changeable collection of objects

my_collection = [1, 1, 3.12, False, "Hi" ]

List Operations

# returns the length of a list
len(my_collection)

# Add multiple items to a list
my_collection.extend([ "More", "Items"])

# Add a single item to a list
my_collection.append("Single")

# Delete the object of a list at a specified index
del(my_collection[2])

# Clone a list
clone = my_collection[:]

# Concatenate two lists
my_collection_2 = ["a", "b", "c"]
my_collection_3 = my_collection + my_collection_2

# Calculate the sum of a list of ints or floats
number_collection = [1,2,3,4.5]
sum(number_collection)

# Check if an item is in a list, returns Boolean
item in my_collection

# Check if an item is not in a list, returns Boolean
item not in my_collection

Set

Unordered collection of unique objects

a = {100, 3.12, False, "Bye"}
b = {100, 3.12, "Welcome"}

Set Operations

# Convert a list to a set
my_set = set([1,1,2,3])

# Add an item to the set
a.add(4)

# Remove an item from a set
a.remove("Bye")

# Returns set a minus b
a.difference(b)

# Returns intersection of set a and b
a.intersection(b)

# Returns the union of set a and b
a.union(b)

# Returns True if a is a subset of b, false otherwise
a.issubset(b)

# Returns True if a is a superset of b, false otherwise
a.issuperset(b)

Indexing

Accessing data from a string, list, or tuple using an element number

my_string[element_number]
my_collection[element_number]
my_tup[element_number]

Slicing

Accessing a subset of data from a string, list, or tuple using element numbers from start to stop -1

my_string[start:stop]
my_collection[start:stop]
my_tup[start:stop]

Comparison Operators

Comparison Operators compare operands and return a result of true or false

Equal

a == b

Less Than

a < b

Greater Than

a > b

Greater Than or Equal

a >= b

Less Than or Equal

a <= b

Not Equal

a != b

Python Operators

+ Addition
- Subtraction
* Multiplication
/ division
// Integer Division (Result rounded to the nearest integer)

Operator precedence

Operator	Precedence
Parenthesis	`( )`
Unary	negative (`-`), logical NOT (`!`)
Multiplication	`*`, `/` ,`%`
Additive	`+`, `-`
Relational	`<`, `>`, `<=`, `>=`
Equality	`==`, `!=`
Logical AND	`&&`
Logical OR	`\|\|`

It's considered good practice to utilise parentheses ( ) to specify to Python which operation should be performed first. The operations within the parentheses will take precedence over all other operations.

Example 1:

# Order of arithmetic operations
print(1 + 2 * 3 + 4)

# Output
11

Example 2:

# Use parentheses to determine the order of computation
print((1 + 2) * (3 + 4))

# output
21

Conditional Operators

Conditional Operators evaluate the operands and produce a true of false result

And - returns true if both statement a and b are true, otherwise false

a and b

Or - returns true if either statement a or b are true, otherwise false

a or b

Not - returns the opposite of the statement

not a

Loops

For Loops

for x in range(x):
    # Executes loop x number of times

for x in iterable:
    # Executes loop for each object in an iterable like a string, tuple,
list, or set

While Loops

while statement:
    # Executes the loop while statement is true

Conditional Statements

if statement_1:
    # Execute of statement_1 is true

elif statement_2:
    # Execute if statement_1 is false and statement_2 is true

else:
    # Execute if all previous statements are false

Try/Except

try:
    # Code to try to execute

except a:
    # Code to execute if there is an error of type a

except b:
    # Code to execute if there is an error of type b

except:
    # Code to execute if there is any exception that has not been handled

else:
    # Code to execute if there is no exception

Error Types

IndexError - When an index is out of range
NameError - When a variable name is not found
SyntaxError - When there is an error with how the code is written
ZeroDivisionError - When your code tries to divide by zero

Range

Produce an iterable sequence from 0 to stop-1

range(stop)

Produce an iterable sequence from start to stop-1 incrementing by step

range(start, stop, step)

Webscraping

# Import BeautifulSoup
from bs4 import BeautifulSoup

# Parse HTML stored as a string
soup = BeautifulSoup(html, 'html5lib')

# Returns formatted html
soup.prettify()

# Find the first instance of an HTML tag
soup.find(tag)

# Find all instances of an HTML tag
soup.find_all(tag)

Requests

# Import the requests library
import requests

# Send a get requests to the url with optional parameters
response = requests.get(url, parameters)

# Get the url of the response
response.url

# Get the status code of the response
response.status_code

# Get the headers of the request
response.request.headers

# Get the body of the requests
response.request.body

# Get the headers of the response
response.headers

# Get the content of the response in text
response.text

# Get the content of the response in json
response.json()

# Send a post requests to the url with optional parameters
requests.post(url, parameters)

Functions

# Create a function
def function_name(optional_parameter_1, optional_prameter_2):
    # code to execute
    return optional_output

# Calling a function
output = function_name(parameter_1, parameter_2)

Working with Files

Reading a File

# Opens a file in read mode
file = open(file_name, "r")

# Returns the file name
file.name

# Returns the mode the file was opened in
file.mode

# Reads the contents of a file
file.read()

# Reads a certain number of characters of a file
file.read(characters)

# Read a single line of a file
file.readline()

# Read all the lines of a file and stores it in a list
file.readlines()

# Closes a file
file.close()

Writing to a File

# Opens a file in write mode
file = open(file_name, "w" )

# Writes content to a file
file.write(content)

# Adds content to the end of a file
file.append(content)

Objects and Classes

# Creating a class
class class_name:
    def __init__(self, optional_parameter_1, optional_parameter_2):
      self.attribute_1 = optional_parameter_1
      self.attribute_2 = optional_parameter_2


    def method_name(self, optional_parameter_1):
      # Code to execute
      return optional_output

# Create an instance of a class
object = class_name(parameter_1, parameter_2)

# Calling an object method
object.method_name(parameter_3)

Example implementation:

# Creating a class
class ClassName:
    def __init__(self, optional_parameter_1, optional_parameter_2):
        self.attribute_1 = optional_parameter_1
        self.attribute_2 = optional_parameter_2

    def method_name(self, optional_parameter_1):
        # Code to execute
        # For example, let's return the sum of attribute_1, attribute_2, and optional_parameter_1
        return self.attribute_1 + self.attribute_2 + optional_parameter_1

# Create an instance of a class
parameter_1 = 5
parameter_2 = 10
object = ClassName(parameter_1, parameter_2)

# Calling an object method
parameter_3 = 7
result = object.method_name(parameter_3)
print(result)  # Output: 22 (5 + 10 + 7)

You might be thinking, can I do like this 👇?

result = object(1, 2) # it will raise a TypeError

No, you cannot do result = object(1, 2) as it will raise a TypeError.

In Python, you can create an instance of a class by calling the class name followed by parentheses with any required arguments. When you do object = ClassName(parameter_1, parameter_2), you create an instance of the ClassName class and store it in the variable object.

After creating the object, you can then call the methods of the class using the object, as shown in the previous examples. However, the object itself is not callable like a function, so you cannot use it as result = object(1, 2).

If you want to call the method_name method and get a result using the object, you should do it like this:

Remember, in Python, you can only call methods of a class using the object, not the object itself as a callable.

Post Tags:

Previous: Numpy for Data Analysis: the Ultimate Guide
Next: Data Engineer vs Data Scientist