Lesson plan

[gigtieup]

Learning Objectives:

Understand the basics of NumPy and Pandas.
Learn how to create NumPy arrays and Pandas data frames.
Practice using NumPy and Pandas to manipulate data.
Materials:

Computers with Python and Jupyter Notebook installed.
NumPy and Pandas libraries installed in Python.

Introduction (10 minutes):

Begin the lesson by introducing the topic of NumPy and Pandas.

Explain that NumPy is a library for Python that allows for efficient numerical computations, and Pandas is a library for Python that allows for easy data manipulation and analysis.

Discuss how these libraries are used in data science and other fields where numerical computations and data analysis are important.
Ask classmates if they have any prior experience with these libraries.

James - Activity 1: Creating NumPy Arrays (30 minutes):

Explain what NumPy arrays are and how they differ from Python lists.
Demonstrate how to create a NumPy array by importing the library and using the np.array() function.
Have classmates create their own NumPy arrays using various functions provided by the library.
Instruct classmates to perform basic calculations on their arrays, such as adding, subtracting, and multiplying values.

Yasha - Activity 2: Creating Pandas Data Frames:

Explain what Pandas data frames are and how they differ from NumPy arrays.
Demonstrate how to create a Pandas data frame by importing the library and using the pd.DataFrame() function.
Have classmates create their own Pandas data frames using various functions provided by the library.
Instruct classmates to manipulate their data frames by adding, deleting, and modifying rows and columns.

Quinn - Activity 3: Data Manipulation with NumPy and Pandas:

Provide classmates with a set of data in a text file, such as a CSV.
Instruct classmates to import the data into Python using Pandas and manipulate it using NumPy and Pandas.
Encourage classmates to use a combination of NumPy and Pandas functions to perform complex operations on the data.

Conclusion:

Have classmates share their experiences working with NumPy and Pandas.
Discuss the various applications of these libraries in data science and other fields.
Provide resources for classmates who wish to continue learning more about NumPy and Pandas.

Assessment / Possible Hacks:

Test classmates understanding of NumPy and Pandas through their participation in the activities and their ability to manipulate data using these libraries.
Provide feedback and guidance to classmates as needed throughout the lesson.