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Data Manipulation with Pandas Masterclass
Learn the main functions of Pandas for data analysis and visualization in less than 2 hours. Theory and hands-on.
This Course Includes
udemy
5 (33 reviews )
1h 6m 
english
Online - Self Paced
professional certificate
Udemy
About Data Manipulation with Pandas Masterclass
This masterclass introduces you to concepts and practices for building compelling analyses and dashboards on datasets of any size. It is designed to be self contained and to be consumed quickly in a single session. It will get you up to speed from zero knowledge of Pandas to understanding how the library operates and using it in several different scenarios. You will learn:
What tabular data is and where you find it
How Pandas allows you to load from, and save to, multiple data formats
How to use two main components of Pandas: the Series and the DataFrame
The main methods to select, group and summarize your data using Pandas
How to perform complex operations such as pivot tables and split-apply-combine
How to create compelling visualizations using Seaborn and Matplotlib directly from Pandas The masterclass is designed to maximize the learning experience for everyone and includes 50% theory and 50% hands-on practice. It includes a lab with hands-on exercises and solutions. No software installation required. You can run the code on Google CoLab and get started right away. This class is the fastest way to get up to speed in Pandas.
Why Pandas?
Pandas is the most famous data manipulation library and it is used by millions of people every day to analyze and manipulate large datasets. It is mature, robust, easy to use and it has extensive documentation, so it's the perfect entry point for beginners and pros.
What You Will Learn?
- This is a short masterclass in Pandas, the most famous library for data manipulation in Python. .
- You will learn what Pandas is, and how it can help you load, manage, and transform tabular data. .
- Learn to analyze real world data using Python & Pandas. .
- Import data from multiple sources, clean, reshape, impute and visualize your data. .
- Use Python and Pandas to select, group and summarize your data. .
- Decide what data to keep and what to ignore. .
- Create compelling visualizations using Seaborn and Matplotlib..