Python for Data Analysts
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Find top Python resources from global universities, cool projects, and learning materials for data analytics.

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Useful links: heylink.me/DataAnalytics
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Complete roadmap to learn Python for data analysis

Step 1: Fundamentals of Python

1. Basics of Python Programming
- Introduction to Python
- Data types (integers, floats, strings, booleans)
- Variables and constants
- Basic operators (arithmetic, comparison, logical)

2. Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
- List comprehensions

3. Functions and Modules
- Defining functions
- Function arguments and return values
- Importing modules
- Built-in functions vs. user-defined functions

4. Data Structures
- Lists, tuples, sets, dictionaries
- Manipulating data structures (add, remove, update elements)

Step 2: Advanced Python
1. File Handling
- Reading from and writing to files
- Working with different file formats (txt, csv, json)

2. Error Handling
- Try, except blocks
- Handling exceptions and errors gracefully

3. Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance and polymorphism
- Encapsulation

Step 3: Libraries for Data Analysis
1. NumPy
- Understanding arrays and array operations
- Indexing, slicing, and iterating
- Mathematical functions and statistical operations

2. Pandas
- Series and DataFrames
- Reading and writing data (csv, excel, sql, json)
- Data cleaning and preparation
- Merging, joining, and concatenating data
- Grouping and aggregating data

3. Matplotlib and Seaborn
- Data visualization with Matplotlib
- Plotting different types of graphs (line, bar, scatter, histogram)
- Customizing plots
- Advanced visualizations with Seaborn

Step 4: Data Manipulation and Analysis
1. Data Wrangling
- Handling missing values
- Data transformation
- Feature engineering

2. Exploratory Data Analysis (EDA)
- Descriptive statistics
- Data visualization techniques
- Identifying patterns and outliers

3. Statistical Analysis
- Hypothesis testing
- Correlation and regression analysis
- Probability distributions

Step 5: Advanced Topics
1. Time Series Analysis
- Working with datetime objects
- Time series decomposition
- Forecasting models

2. Machine Learning Basics
- Introduction to machine learning
- Supervised vs. unsupervised learning
- Using Scikit-Learn for machine learning
- Building and evaluating models

3. Big Data and Cloud Computing
- Introduction to big data frameworks (e.g., Hadoop, Spark)
- Using cloud services for data analysis (e.g., AWS, Google Cloud)

Step 6: Practical Projects
1. Hands-on Projects
- Analyzing datasets from Kaggle
- Building interactive dashboards with Plotly or Dash
- Developing end-to-end data analysis projects

2. Collaborative Projects
- Participating in data science competitions
- Contributing to open-source projects

๐Ÿ‘จโ€๐Ÿ’ป FREE Resources to Learn & Practice Python 

1. https://www.freecodecamp.org/learn/data-analysis-with-python/#data-analysis-with-python-course
2. https://www.hackerrank.com/domains/python
3. https://www.hackerearth.com/practice/python/getting-started/numbers/practice-problems/
4. https://t.iss.one/PythonInterviews
5. https://www.w3schools.com/python/python_exercises.asp
6. https://t.iss.one/pythonfreebootcamp/134
7. https://t.iss.one/pythonanalyst
8. https://pythonbasics.org/exercises/
9. https://t.iss.one/pythondevelopersindia/300
10. https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial
11. https://t.iss.one/pythonspecialist/33

Join @free4unow_backup for more free resources

ENJOY LEARNING ๐Ÿ‘๐Ÿ‘
โค4
Must-know Pandas Functions for Data Analysis
โค6
๐Ÿฏ ๐—š๐—ฎ๐—บ๐—ฒ-๐—–๐—ต๐—ฎ๐—ป๐—ด๐—ถ๐—ป๐—ด ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฟ๐—ฒ๐—ฒ๐Ÿ˜

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These are top 5 data structures and algorithms projects, allowing you to dive deep into the world of DSA ๐Ÿ’ช๐Ÿป

โ€ขProject 1: Snakes Game (Arrays)

The Snakes Game project is a classic implementation of the popular game
Snake.

This project allows you to understand the concepts of arrays, loops, and conditional statements. You can further enhance the game by incorporating additional features such as score tracking and power-ups.

โ€ขProject 2: Cash Flow Minimizer (Graphs/ Multisets/Heaps)

The Cash Flow Minimizer project involves solving a cash flow optimization problem using graphs, multisets, and heaps. Given a set of transactions among a group of people, the objective is to minimize the total number of transactions required to settle all debts

โ€ขProject 3: Sudoku Solver (Backtracking)

The Sudoku Solver project aims to solve the popular Sudoku puzzle using backtracking. This project allows you to understand the backtracking algorithm, which is widely used in solving constraint satisfaction problems.

โ€ขProject 4: File Zipper (Greedy Huffman
Encoder)

The File Zipper project focuses on implementing a file compression utility using the Greedy Huffman encoding algorithm. This project provides a practical application of the greedy algorithm and helps you understand the trade-offs between
compression ratio and execution time.

โ€ขProject 5: Map Navigator (Dijkstraโ€™s
Algorithm)

The Map Navigator project aims to develop a navigation system using Dijkstraโ€™s algorithm. It involves finding the shortest path between two locations on a map, considering factors such as distance and traffic.

You can check these amazing resources for DSA Preparation

Join for more: https://t.iss.one/crackingthecodinginterview

All the best ๐Ÿ‘๐Ÿ‘
โค4
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๐Ÿ”น Week 1: Python Mini Projects (Daily Practice)
โฆ Calculator
โฆ To-Do List (CLI)
โฆ Number Guessing Game
โฆ Unit Converter
โฆ Digital Clock

๐Ÿ”น Week 2: Data Handling & APIs
โฆ Read/Write CSV & Excel files
โฆ JSON parsing
โฆ API Calls using Requests
โฆ Weather App using OpenWeather API
โฆ Currency Converter using Real-time API

๐Ÿ”น Week 3: Automation with Python
โฆ File Organizer Script
โฆ Email Sender
โฆ WhatsApp Automation
โฆ PDF Merger
โฆ Excel Report Generator

๐Ÿ”น Week 4: Data Analysis with Pandas & Matplotlib
โฆ Load & Clean CSV
โฆ Data Aggregation
โฆ Data Visualization
โฆ Trend Analysis
โฆ Dashboard Basics

๐Ÿ”น Week 5: AI & ML Projects (Beginner Friendly)
โฆ Predict House Prices
โฆ Email Spam Classifier
โฆ Sentiment Analysis
โฆ Image Classification (Intro)
โฆ Basic Chatbot

๐Ÿ“Œ Each project includes: 
โœ… Problem Statement 
โœ… Code with explanation 
โœ… Sample input/output 
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โค6