Cheat sheet

On this page you will find a collection of useful PDF files and code snippets.

Overview of Important Python Syntax

Data Types	Operators	Control Structures	Loops	Libraries
Integers	Addition (+)	If Statements	For Loop	numpy
x = 5	result = a + b	if x > 5:	for i in range(10):	import numpy as np
Floats	Subtraction (-)	Else Statements	While Loop	pandas
y = 3.5	result = a - b	else:	while x > 0:	import pandas as pd
Strings	Multiplication (*)	Elif Statements		matplotlib
name = "John"	result = a * b	elif x < 10:		import matplotlib.pyplot as plt
Lists	Division (/)	Try and Except
my_list = [1, 2, 3]	result = a / b	try:
DataFrames	Modulus (%)	Break and Continue
df = pd.DataFrame(data)	result = a % b	break / continue
Arrays	Exponentiation (**)
np.array([1, 2, 3])	result = a ** b

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Basic Data Types

Python is dynamically typed, meaning variables do not need explicit declarations. Common basic data types:

Integers, Floats, Strings, Booleans

x = 10       # Integer
y = 3.14     # Float
name = "Alice"  # String
is_student = True  # Boolean

Object Data Types

Arrays

Arrays come from the NumPy library and allow efficient operations on large data sets. Arrays are homogeneous (one data type).

import numpy as np

arr = np.array([1, 2, 3, 4])
print(arr * 2)  # Outputs [2, 4, 6, 8]

DataFrames

DataFrames are powerful table-like data structures from Pandas, great for analysis.

import pandas as pd

data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data)
print(df)

Importing and Exporting Data with Pandas

Read data

import pandas as pd

df = pd.read_csv("data.csv")
df_excel = pd.read_excel("data.xlsx")

Write data

df.to_csv("output.csv", index=False)
df.to_excel("output.xlsx", index=False)

Visualization with Matplotlib

Matplotlib allows you to create plots and visualizations easily.

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y = [10, 20, 25, 30]

plt.plot(x, y, label="Line")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.title("Simple Plot")
plt.legend()
plt.show()

Control Structures

If-Else

if x > 5:
    print("x is greater than 5")
else:
    print("x is 5 or smaller")

For Loop

for i in range(5):
    print(i)  # Outputs 0 to 4

While Loop

n = 0
while n < 5:
    print(n)
    n += 1

Error Handling (Try and Except)

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Division by zero is not allowed")

Object-Oriented Programming (OOP)

OOP is a paradigm that organizes code using objects, which bundle data (attributes) and behavior (methods).

class Vehicle:
    def __init__(self, brand, year):
        self.brand = brand
        self.year = year

    def display_info(self):
        print(f"Brand: {self.brand}, Year: {self.year}")

# Create an object
car = Vehicle("Toyota", 2020)
car.display_info()

Modules and Packages

Modules are Python files containing functions, classes, and variables. You can import them using import.

import math

print(math.sqrt(16))  # Outputs 4.0

Useful Libraries

NumPy: Fast numerical operations on arrays and matrices.

Pandas: Data analysis and manipulation with DataFrames.

Matplotlib: Creating plots and visualizations.

Download the Python Cheat Sheet (PDF)