π Python Roadmap for Data Analytics πππ₯
π§ STEP 1: Learn Python Basics
β Variables & Data Types
β Loops & Functions
β Lists, Tuples & Dictionaries
β File Handling
β Exception Handling
π Tools to Learn:
β Jupyter Notebook
β Visual Studio Code
π STEP 2: Learn Data Handling
β Reading CSV & Excel Files
β Data Cleaning
β Handling Missing Values
β Data Transformation
π Libraries to Learn:
β Pandas
β NumPy
π STEP 3: Learn Data Visualization
β Line Charts
β Bar Charts
β Pie Charts
β Heatmaps
β Interactive Dashboards
π Visualization Libraries:
β Matplotlib
β Seaborn
β Plotly
π§ STEP 4: Learn Statistics Basics
β Mean, Median & Mode
β Probability
β Correlation
β Hypothesis Testing
β A/B Testing
β‘ STEP 5: Learn SQL with Python
β Database Connections
β SQL Queries
β Fetching Data
β Data Integration
π Libraries to Learn:
β sqlite3
β SQLAlchemy
β PyMySQL
π€ STEP 6: Learn Basic Machine Learning
β Regression
β Classification
β Clustering
β Model Evaluation
π Frameworks to Learn:
β Scikit-learn
β XGBoost
π STEP 7: Learn Automation & Reporting
β Automating Reports
β Excel Automation
β API Data Collection
β Scheduling Tasks
π Libraries to Learn:
β openpyxl
β requests
β schedule
π₯ STEP 8: Build Real Projects
β Sales Data Analysis
β HR Analytics Dashboard
β Customer Churn Analysis
β Financial Analytics
β Netflix Dataset Analysis
Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
π¬ Tap β€οΈ if this helped you!
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