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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

Making NumPy arrays from lists

Recall how lists can contain anything? They can even contain other lists. In this exercise, you're going to demonstrate this feature and show how useful it is for creating our own NumPy arrays.

Seven lists are loaded into your workspace, each named after a day of the week: monday, tuesday, and so on. Each list contains the average hourly bicycle traffic across the Fremont bridge.

Instructions

100 XP
  • Create a list weekdays where each element is a daily list, starting on Monday.
  • Create a NumPy array traffic from the list weekdays.
  • Calculate the mean hourly traffic.
  • Plot the mean hourly traffic for weekdays.