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  3. Python for MATLAB Users
  • 1

    From MATLAB to Python

    Free

    This chapter gets you started moving from MATLAB to Python. You'll learn about some of the similarities and differences between MATLAB and Python, how to use methods and packages, and be introduced to the popular NumPy package.

  • 2

    NumPy and Matplotlib

    In this chapter, you will build on your new NumPy knowledge. You will dive into NumPy arrays, the Python analog to matrices by performing mathematical operations and indexing. You will also begin to explore another important Python data structure, the list, and then round out the chapter by making customs plots of your arrays using Matplotlib.

  • 3

    Dictionaries and pandas

    This chapter introduces some powerful Python data structures: the dictionary and the pandas DataFrame. You will learn to create dictionaries by setting key-value pairs, and view then how to view and modify your dictionary. Then you will be introduced to one of the most important packages in the Pythonista's toolbox, pandas. Specifically, you'll focus on the pandas' structure, the DataFrame, which organizes tabular data in an easily accessible way. Lastly, you'll learn how to transform different data types into DataFrames to make your data easier to work with.

  • 4

    Control Flow and Loops

    You'll finish the course by controlling your Python flow. You will learn how to iterate through different Python data structures using for loops. You will also learn about Python contingencies using if, else, and elif and the Python comparison operators (greater than, less than, etc.) that will decide which lines of your code will be executed. Lastly, you'll circle back to NumPy arrays by using Python comparison operators to filter your arrays.

Initializing

Exercise

Filtering arrays with Boolean indexing

You can also index arrays using Boolean indexing. By creating a Boolean array where the values are True for the indices you want to retain, you can filter an array. This can be especially convenient for filtering one array based upon the values in another array.

In this exercise, you'll explore how birth weight varies between animals that tend to have one baby per birth versus those that have multiple. Two NumPy arrays are loaded into your workspace, along with the NumPy package as np.

  • litter_size is the average size of a litter for each of 1200+ animals
  • birth_weight is the corresponding average birth weight in grams for each animal

Instructions

100 XP
  • Create Boolean arrays mono_births and multi_births for animals that typically have a single offspring per litter and those that have greater than one, respectively.
  • Create arrays mono_birth_weight and multi_birth_weight, which contain the birth weights of single offspring animals and multi-offspring animals, respectively.
  • Print the mean birth weight of animals which tend to have a single offspring per litter and those that have greater than one.