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Data Analysis with Pandas pt.1

📊 Data analytics is essential for gaining insights and understanding large amounts of data. In this Python Pandas series, we explore the top 10 Pandas functions that every data analyst or professional working with data should know. Pandas is a fast, powerful, and flexible open-source data analysis and manipulation tool built on top of Python. In this tutorial, we cover the following topics: 1️⃣ Reading Data: Learn how to import data from CSV and Excel files using the read_csv and read_excel functions. 2️⃣ Preview DataFrame: Use the head() and tail() functions to preview the top and bottom rows of your DataFrame. 3️⃣ Describe DataFrame: Get a statistical summary of the numerical columns in your DataFrame using the describe() function. 4️⃣ Get Information on DataFrame: Use the info() method to obtain information on the non-null values and data types in each column. 5️⃣ Find Duplicates: Identify duplicate rows in your DataFrame using the duplicated() function. By the end of this tutorial, you'll have a solid understanding of these essential Pandas functions, which will greatly enhance your data analysis skills. 🚀 📚 This video is based on the medium article below:   / data-analysis-with-pandas-top-10-essential...   📚 You can find the code used in this video over here: https://colab.research.google.com/dri... Don't miss out on mastering Pandas for data manipulation and analysis! Watch the full tutorial and level up your data analytics game. 🎥 Subscribe to our channel for more tutorials and data analysis tips. 📚