Mid-levelMultiple choiceHow do you handle missing values in a dataset?ABy deleting them, imputing with mean/median/mode, or using advanced methods like KNN.BBy ignoring them completely.CBy replacing them with zeros.DBy randomly generating new values.Check answer
Mid-levelMultiple choiceHow do you handle missing data?AImpute missing values using mean, median, or mode.BUse advanced imputation techniques like KNN or iterative imputer.CDrop rows with missing values regardless of the pattern.DIgnore missing data as it doesn't affect analysis.Check answer
Mid-levelMultiple choiceHow would you approach categorical and continuous variables differently during preprocessing?AScale categorical variables using normalization.BApply one-hot encoding to continuous variables.CScale continuous variables using normalization or standardization.DApply one-hot encoding to categorical variables.Check answer
JuniorMultiple choiceHow can you remove duplicates from a DataFrame in Python?Adf = df.drop_duplicates()Bdf.clear_duplicates()Cdf.delete_duplicates()Ddf.remove_duplicates()Check answer
Mid-levelMultiple choiceIf removing missing values from a dataset causes bias, what would you do?ARemove more data to ensure balance.BChange the entire dataset.CIgnore the missing values and proceed with the analysis.DUse imputation techniques to estimate the missing values.Check answer
