NumPy and Pandas Basics for Future Data Scientists
By External Provider
About this course
In “NumPy and Pandas Basics for Future Data Scientists,” learn programming techniques using Python's NumPy and pandas libraries to write efficient and bug-free code for numerical computing. At the start of the course, you’ll be introduced to the NumPy library and will learn to perform basic NumPy array operations. After understanding the basics of the NumPy library, you’ll explore more advanced array manipulations, including aggregating functions, broadcasting, reshaping, sorting, and joining arrays. By the end of this course, you will have the skills to apply multiple data manipulation techniques using advanced methods and apply functions to your code. This is the second course in the four-course series, “Data-Oriented Python Programming and Debugging,” where you’ll work to strengthen your programming capabilities and enhance your problem-solving skills.
What you will learn
- Create and manipulate NumPy arrays, including performing basic arithmetic operations and handling missing data.
- Apply advanced NumPy techniques such as broadcasting, masking, and aggregation functions.
- Construct and modify pandas DataFrames and Series, use methods to filter and inspect data, and handle missing data.
- Utilize pandas for data aggregation, summary statistics, and dataframe merging to analyze a real dataset.