FAQ: Learn Seaborn: Distributions - KDE Plots, Part II

This community-built FAQ covers the “KDE Plots, Part II” exercise from the lesson “Learn Seaborn: Distributions”.

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This exercise can be found in the following Codecademy content:

Data Science

Data Visualization in Python

FAQs on the exercise KDE Plots, Part II

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Most of the Seaborn lessons have deprecated code, making it impossible to progress through the lesson. The answer to the question, and even copy-pasting the Solution to run again, will result in an error.

/usr/local/lib/python3.5/dist-packages/scipy/stats/stats.py:1633: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq] . In the future this will be interpreted as an array index, arr[np.array(seq)] , which will result either in an error or a different result. return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval {“passed”: true}


Confirmed. Seaborn is grounding in shallow water

what is the meaning of this code and why n is taken as 500?


df = pd.DataFrame({

"label": ["set_one"] * n + ["set_two"] * n + ["set_three"] * n + ["set_four"] * n,

"value": np.concatenate([set_one, set_two, set_three, set_four])


When I run my code I’m getting a KDE plot on the right but no legend. Is anyone else having this problem? The code in the lesson seems to suggest that including plt.legend() before plt.show() includes a legend however my final plot has none.

Some advice would be appreciated.


Hi! It is explained in this thread

Cheers! :slight_smile:

I came here looking to see this, I pulled up the solutions and pasted my code onto the same page and used cntl+f after highlighting each line to see that they were exactly the same.

I like to make sure i get the green check mark myself to make sure my understanding of a code is complete. but this one was acting fishy. im glad to know its an error with the page. are there any work arounds?