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# imputation
threshold = 0.7
#Dropping columns with missing value rate higher than threshold
data = data[data.columns[data.isnull().mean() < threshold]]

#Dropping rows with missing value rate higher than threshold
data = data.loc[data.isnull().mean(axis=1) < threshold]

# categorical imputation
#Max fill function for categorical columns
data['column_name'].fillna(data['column_name'].value_counts()
.idxmax(), inplace=True)