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Exercise

Visualize imputations

Analyzing imputations and choosing the best one, is a task that requires lots of experimentation. It is important to make sure that your data does not become biased while imputing. In this last two exercises, you created 4 different imputations using mean, median, mode, and constant filling imputations.

In this exercise, you'll create a scatterplot of the DataFrames you imputed previously. To achieve this, you'll create a dictionary of the DataFrames with the keys being their title.

The DataFrames diabetes_mean, diabetes_median, diabetes_mode and diabetes_constant have been loaded for you.

Instructions

100 XP
  • Create 4 subplots by making a plot with 2 rows and 2 columns.
  • Create the dictionary imputations by mapping each key with its matching DataFrame.
  • Loop over axes and imputations, and plot each DataFrame in imputations.
  • Set the color to the nullity and the title for each subplot to the name of the imputation.