FAQ: Summary Statistics for Categorical Variables - Ordinal Categorical Variables - Central Tendency I

This community-built FAQ covers the “Ordinal Categorical Variables - Central Tendency I” exercise from the lesson “Summary Statistics for Categorical Variables”.

Paths and Courses
This exercise can be found in the following Codecademy content:

Master Statistics with Python

FAQs on the exercise Ordinal Categorical Variables - Central Tendency I

There are currently no frequently asked questions associated with this exercise – that’s where you come in! You can contribute to this section by offering your own questions, answers, or clarifications on this exercise. Ask or answer a question by clicking reply (reply) below.

If you’ve had an “aha” moment about the concepts, formatting, syntax, or anything else with this exercise, consider sharing those insights! Teaching others and answering their questions is one of the best ways to learn and stay sharp.

Join the Discussion. Help a fellow learner on their journey.

Ask or answer a question about this exercise by clicking reply (reply) below!
You can also find further discussion and get answers to your questions over in #get-help.

Agree with a comment or answer? Like (like) to up-vote the contribution!

Need broader help or resources? Head to #get-help and #community:tips-and-resources. If you are wanting feedback or inspiration for a project, check out #project.

Looking for motivation to keep learning? Join our wider discussions in #community

Learn more about how to use this guide.

Found a bug? Report it online, or post in #community:Codecademy-Bug-Reporting

Have a question about your account or billing? Reach out to our customer support team!

None of the above? Find out where to ask other questions here!

in this block of code (for full exercise see link below):

# Convert to categorical type
nyc_trees['health'] = pd.Categorical(
    nyc_trees['health'], health_categories, ordered=True

# Calculate median values
median_index = np.median(nyc_trees['health'].cat.codes)
median_health_status = health_categories[int(median_index)]

In the line where I calculate the median_index, I do not understand how when i call cat .codes, it knows the order of the categories and assigns the right integer to them. Could someone explain that to me?

Thanks in advance :slight_smile:

When you use pd.Categorial and pass a list with ordered=True you are giving Python an order of values.

Print in the console nyc_trees['health] and you will see the following:

Name: health, Length: 50000, dtype: category
Categories (3, object): [Poor < Fair < Good]

That makes sense, thank you bjrompal!