This course is tailored for anyone eager to step into the world of data analysis using Python, whether you have coding experience or not. There’s no need for prior knowledge—just a computer, an internet connection, and a willingness to learn.
What You Need
To start analyzing data with Python, you’ll need to set up a Python environment on your computer. But don’t worry — I’m here to help every step of the way. We’ll be using tools like Anaconda (which includes Jupyter Notebooks) or Visual Studio Code, both of which are free and widely used for data analysis.
What You’ll Learn
In this class, you’ll dive into 10 of the most powerful and practical functions in Python that are essential for data analysis. Each lesson focuses on a specific function, explaining its purpose and demonstrating how to use it with real-world datasets. By the end of the course, you’ll have a solid toolkit of Python skills that you can apply directly to your own data projects. Here’s what you’ll cover:
- How to load and view data with read_csv() and head()
- Summarizing your data with info() and describe()
- Cleaning and handling missing data using dropna() and fillna()
- Grouping and sorting data with groupby() and sort_values()
- Filtering data with query()
- Combining datasets using merge()
By the end of this class you will not only understand the methods presented but also be able to apply the 10 functions on your own datasets and have gained great skills regarding data analysis.
