Genre: eLearning | Language: English
Learn and Apply Data Analysis with Python on Real-World Datasets
What you'll learn
Understand and apply 10 essential Python functions for data analysis.
Master techniques to transform raw data into meaningful insights.
Analyze datasets efficiently using Python's powerful tools.
Learn how to clean and prepare data for analysis with Python.
Requirements
No prior programming experience needed; the course is designed for beginners.
A computer with internet access to install Python and necessary tools.
Description
Welcome to
"10 Awesome Functions in Python to Analyze Data"!
Who this Course is for
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()
