Crash Course : Data Analysis using Pandas in python

🌟 **Crash Course: Data Analysis using Pandas in Python** 🌟 --- ### **Course Description:** Embark on a transformative journey into the world of data analysis with our comprehensive "Crash Course: Data Analysis using Pandas in Python." This course is meticulously designed to guide you through every crucial aspect of data manipulation and analysis. Whether you're a beginner or looking to sharpen your skills, this course promises to equip you with the knowledge and techniques essential for effective data handling. --- ### **What You Will Learn:** - **Section 1: Getting Started with Python** 🚀 - Installation of Anaconda distribution and writing your first code. - A comprehensive walkthrough of the Spyder Platform to familiarize you with your new data analysis environment. - **Section 2: Working on Data** 📊 - Running SQL commands from within Python. - Understanding dataset contents and adding comments for better code readability. - Handling missing values, whether numeric or date-related, and creating copies of dataframes while filtering out records with missing values. - Mastering numerical variable analysis, including group by operations and transposing results. - Executing frequency distribution counts, including the percentage of missing values, and delving into functions and substring manipulations. - **Section 3: Working with Multiple Datasets** 🛠️ - Creating dataframes dynamically and appending or concatenating them. - Merging datasets and mastering the art of removing duplicates. - Advanced sorting techniques, finding records for max/min values, and leveraging `iterrows` to solve complex problems. - Deriving new variables from both numerical and character fields, as well as analyzing data based on date fields. - **Section 4: Data Visualization** 🎨 - Generating histograms, bar charts, line charts, pie charts, and box plots to visualize your data effectively. - Revisiting some Python fundamentals to ensure you have a solid grasp of the language's capabilities. - Understanding variable scope and utilizing range objects, casting, string slicing, and lambda functions. - **Section 5: Statistical Procedures & Advanced Topics** 🔍 - Identifying and treating outliers. - Creating Excel-formatted reports. - Crafting pivot tables on pandas dataframes, renaming column names, reading from/writing to SQLite databases, and more! - Performing linear regression and conducting a chi-square test of independence. --- ### **Course Highlights:** ✅ **Practical Approach:** Learn by doing with real-world datasets and hands-on exercises. ✅ **Expert Guidance:** Gopal Prasad Malakar, an experienced instructor, will be your guide through this data analysis journey. ✅ **Flexible Learning:** Access the course materials at your convenience and learn at your own pace. ✅ **Community Support:** Engage with peers in our community forums to share insights and challenges. --- ### **Who Should Take This Course?** This course is designed for: - Data analysts seeking to enhance their skill set. - Aspiring data scientists looking to start a career in data analysis. - Students who want to dive into the world of Python and data manipulation. - Professionals from any domain interested in leveraging data to drive decision-making. --- ### **Join Us Today!** Embark on your data analysis adventure with our "Crash Course: Data Analysis using Pandas in Python." Enroll now to transform your approach to handling and analyzing data, and unlock the power of data insights! 📈🎉