Replacing rating with group median

In the last exercise, you replaced the missing values in the rating column with the column median. But could you do better? Yes! You can replace the missing values with the median rating of chocolates from the same company. Let's do it!

There is a predefined replace_missing() function that takes two arguments - a DataFrame group and a column col. It tries to compute a median of the column col and returns it if it is successful. If calculating the median fails, for example, because there are no values, then it returns a predefined value.

The chocolates dataset and the DataFrames and Statistics packages have been loaded for you.

Deze oefening maakt deel uit van de cursus

Data Manipulation in Julia

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Oefeninstructies

Group chocolates by company and iterate over the GroupedDataFrame.
Subset each group using ismissing() and the rating column, replacing the missing values by the value of replace_missing() function.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Group by company and iterate
for group in ____(____)

	# Subset each group using ismissing() and the rating column, assign a new value 
	group[____, ____] .= replace_missing(group, :rating)
end

println(describe(chocolates, :nmissing))

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