FAQ: Data Summaries - Central Tendency for Quantitative Data

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This community-built FAQ covers the “Central Tendency for Quantitative Data” exercise from the lesson “Data Summaries”.

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This exercise can be found in the following Codecademy content:

Exploratory Data Analysis in Python

FAQs on the exercise Central Tendency for Quantitative Data

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2

Why the mode output looks different from the other methods?

0    20000000.0
dtype: float64
3

because of how this function is written, the mode is returned as a pandas series. In order to convert it to a single value, we can extract the first value in the series

movies.production_budget.mode()[0]
4

Is there another way to get the trimmed mean in this exercise without using another library? Or is there a reason why scipy is best option?

5

Yep:

df['col_name'].mean().round(2)

#or, in this exercise, 

variable_name = df.column.mean().round(2)
print(variable_name)
6

@lisalisaj I am not sure if I follow here. I tried doing this using your method but round just rounds it down to the 2 decimal places. Trimmed mean takes out the top and bottom X% in the data frame for the column and then calculate the mean?