Arunav Goswami
Data Science Consultant at almaBetter
This Python cheat sheet covers basics to advanced concepts, regex, list slicing, loops and more. Perfect for quick reference and enhancing your coding skills.
Python is a versatile and powerful programming language used for various applications. Whether you’re preparing for an interview, working with data, or just getting started, this cheat sheet for Python will provide you with essential Python knowledge and tips.
int: Integer values
x = 10
float: Floating-point numbers
y = 3.14
str: Strings (text).
name = "Alice"
bool: Boolean values
is_active = True
list: Ordered, mutable collection of items.
fruits = ["apple", "banana", "cherry"]
tuple: Ordered, immutable collection of items.
coordinates = (10.0, 20.0)
dict: Collection of key-value pairs.
person = {"name": "Alice", "age": 30}
set: Unordered collection of unique items.
unique_numbers = {1, 2, 3, 4}
Comments:
# This is a comment
Variables:
x = 5
name = "Alice"
Printing:
print("Hello, World!")
Indentation:
if x > 0:
print("Positive")
x + y # Addition
x - y # Subtraction
x * y # Multiplication
x / y # Division
x % y # Modulus
x ** y # Exponentiation
x // y # Floor division
x == y # Equal to
x != y # Not equal to
x > y # Greater than
x < y # Less than
x >= y # Greater than or equal to
x <= y # Less than or equal to
x and y # Logical AND
x or y # Logical OR
not x # Logical NOT
Learn more: Operators in Python
if x > 0:
print("Positive")
elif x == 0:
print("Zero")
else:
print("Negative")
for i in range(5):
print(i)
count = 0
while count < 5:
print(count)
count += 1
Simple list comprehension
squares = [x**2 for x in range(10)]
Conditional list comprehension
even_squares = [x**2 for x in range(10) if x % 2 == 0]
Defining Functions:
def greet(name):
return f"Hello, {name}!"
Calling Functions:
print(greet("Alice"))
Define a class
class MyClass:
def __init__(self, name, age):
self.name = name
self.age = age
def greet(self):
return f"Hello, my name is {self.name} and I am {self.age} years old."
Import a module
import math
print(math.sqrt(16))
Import specific function from a module
from math import sqrt
print(sqrt(16))
try, except, finally
try:
result = 10 / 0
except ZeroDivisionError:
print("Cannot divide by zero")
finally:
print("This block always executes")
Learn more: Exception Handling in Python
Open and read a file
with open('file.txt', 'r') as file:
content = file.read()
print(content)
Write to a file
with open('file.txt', 'w') as file:
file.write("Hello, World!")
len(): Get the length of a list, tuple, dictionary, etc.
len(my_list)
type(): Get the type of an object
type(my_dict)
str(), int(), float(): Convert data types
str(123) # "123"
int("123") # 123
float("3.14") # 3.14
list(): Convert to a list
list(my_tuple)
NumPy: Numerical computing
import numpy as np
arr = np.array([1, 2, 3])
Pandas: Data manipulation and analysis
import pandas as pd
df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
Matplotlib: Plotting and visualization
import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.show()
Match a Single Character:
pattern = r"a"
Match a Digit:
pattern = r"\d"
Match a Word:
pattern = r"\w+"
Match Whitespace:
pattern = r"\s"
Importing the re Module:
import re
Search for a Pattern:
result = re.search(r"\d+", "The price is 100 dollars")
Find All Matches:
results = re.findall(r"\d+", "The prices are 100, 200, and 300 dollars")
Replace a Pattern:
updated_text = re.sub(r"\d+", "number", "The price is 100 dollars")
Learn more: Regex in Python
Importing Pandas:
import pandas as pd
Creating a DataFrame:
data = {"name": ["Alice", "Bob"], "age": [25, 30]}
df = pd.DataFrame(data)
Reading Data from a CSV File:
df = pd.read_csv("data.csv")
Writing Data to a CSV File:
df.to_csv("output.csv", index=False)
Viewing Data:
df.head()
df.info()
df.describe()
Selecting Data:
df["name"]
df[["name", "age"]]
df.loc[0]
df.iloc[0]
Filtering Data:
df[df["age"] > 25]
Grouping Data:
df.groupby("age").mean()
Key Topics to Review:
By mastering these Python concepts, you’ll be well-prepared for Python interviews and equipped to handle various programming tasks. This cheat sheet is designed to be a quick reference guide for both beginners and experienced Python programmers.
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