You are required to impute missing values in a dataset containing the GDP value of many countries over many years. GDP typically increases year over year, but some years have a missing value. What method would you apply to impute the missing value? Choose the most appropriate method.

df['gdp'].interpolate(method='linear', inplace=True) df['gdp'].fillna(method='bfill', inplace=True) df['gdp'].fillna(df['gdp'].mean()) df['gdp'].fillna(df['gdp'].median()) Since GDP typically follows a trend, linear interpolation is the most appropriate method to estimate the missing values based on the surrounding years. Using `bfill`, mean, or median would not account for the time-series nature of the data.

Exercise