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.

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.

Exercise

Visualize imputations

Instructions