FAQ: Handling Complex Datasets - Vertical Concatenation

This community-built FAQ covers the “Vertical Concatenation” exercise from the lesson “Handling Complex Datasets”.

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This exercise can be found in the following Codecademy content:

[Beta] Python for Data Science: Working with Data

FAQs on the exercise Vertical Concatenation

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Copypasting the solution to part 3 of this excercise produces this error: {“passed”: false, “errorMessage”: “invalid syntax (. My own solution was basically the same but with some extra spaces after the ‘:’ and such. All previous parts have been passed and i tried re-running all the cells. Also, it does seem to produce the right output in the notebook, so it’s just the “test work” step that fails.

The code currently looks like this:


# rename Location_EUROPE
dfs[3] = dfs[3].rename({'Location_EUROPE':'Location'},axis=1)

# re-do the concatenation to generate full_df
full_df = pd.concat(dfs)

#show output

Is this a bug or am i missing something?


I’ve been having the exact same problem!

Haven’t found a proper solution yet, but clicking the ‘replace with solution’ button after navigating to ‘solution’ under ‘get unstuck’ should at least get you past this exercise so you can finish the course.

I encountered a similar issue with the third question. However, I proceeded to the fourth question, executed it, and unexpectedly, the green checkmark appeared for the third question. I had to rerun it to obtain the green checkmark for question 4…

With the last question i tackled it slightly different to how they wanted it and it refused me to continue. Ive got the exact same number and even went above for what they asked. Is my code anyway incorrect?

#My Answer park_compare = fullll_df.groupby('Location').agg({'Total_Riders':'mean'}).reset_index().sort_values(by='Total_Riders',ascending=False) #Codecademy Answer park_compare = full_df.groupby('Location')['Total_Riders'].mean()

Thanks for sharing this, I could move ahead as well. Finishing 4th automatically check mark the 3rd one as well.

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