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Python for Data Analysts Python for Data Analysts @pythonanalyst · 51.8K subscribers
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Python CheatSheet 📚 ✅

1. Basic Syntax
- Print Statement: print("Hello, World!")
- Comments: # This is a comment

2. Data Types
- Integer: x = 10
- Float: y = 10.5
- String: name = "Alice"
- List: fruits = ["apple", "banana", "cherry"]
- Tuple: coordinates = (10, 20)
- Dictionary: person = {"name": "Alice", "age": 25}

3. Control Structures
- If Statement:

     if x > 10:
print("x is greater than 10")

- For Loop:

     for fruit in fruits:
print(fruit)

- While Loop:

     while x < 5:
x += 1

4. Functions
- Define Function:

     def greet(name):
return f"Hello, {name}!"

- Lambda Function: add = lambda a, b: a + b

5. Exception Handling
- Try-Except Block:

     try:
result = 10 / 0
except ZeroDivisionError:
print("Cannot divide by zero.")

6. File I/O
- Read File:

     with open('file.txt', 'r') as file:
content = file.read()

- Write File:

     with open('file.txt', 'w') as file:
file.write("Hello, World!")

7. List Comprehensions
- Basic Example: squared = [x**2 for x in range(10)]
- Conditional Comprehension: even_squares = [x**2 for x in range(10) if x % 2 == 0]

8. Modules and Packages
- Import Module: import math
- Import Specific Function: from math import sqrt

9. Common Libraries
- NumPy: import numpy as np
- Pandas: import pandas as pd
- Matplotlib: import matplotlib.pyplot as plt

10. Object-Oriented Programming
- Define Class:

      class Dog:
def __init__(self, name):
self.name = name
def bark(self):
return "Woof!"


11. Virtual Environments
- Create Environment: python -m venv myenv
- Activate Environment:
- Windows: myenv\Scripts\activate
- macOS/Linux: source myenv/bin/activate

12. Common Commands
- Run Script: python script.py
- Install Package: pip install package_name
- List Installed Packages: pip list

This Python checklist serves as a quick reference for essential syntax, functions, and best practices to enhance your coding efficiency!

Checklist for Data Analyst: https://dataanalytics.beehiiv.com/p/data

Here you can find essential Python Interview Resources👇
https://t.me/DataSimplifier

Like for more resources like this 👍 ♥️

Share with credits: https://t.me/sqlspecialist

Hope it helps :)
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