Visualize forward fill imputation
To visualize time-series imputations, we can create two plots with the plot of original DataFrame overlapping the imputed DataFrame. Additionally, changing the linestyle
, color
and marker
for the imputed DataFrame, helps to clearly distinguish the non-missing values and the imputed values. The imputed DataFrames can be plotted using the .plot()
method.
In this exercise, you will first impute and then plot the time-series plot of forward filled DataFrame. The airquality
DataFrame has been loaded for you.
Cet exercice fait partie du cours
Dealing with Missing Data in Python
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Impute airquality DataFrame with ffill method
ffill_imputed = ___