Using these plots, your friend argues that there are correlations between the 'Pclass' 'Sex' and 'Age'...

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Using these plots, your friend argues that there are correlations between the 'Pclass' 'Sex' and 'Age' features within the dataset, and that 'Age" shows influence in predicting a given passenger's survival. Aware of this new knowledge, you decide to create a function, conditional_impute, which performs imputation upon an age column within a Pandas DataFrame based upon both Sex and Pclass columns. Given that you are uncertain which statistic best models your data, you decide to once again to add a choice parameter which allows either the mean or median to be used for imputing the data. Function arguments: ▪ input_df -> input Pandas DataFrame. choice > Python string of either 'mean' or 'median' Default is 'median' Function Specifications: • Name the function conditional_impute ▪ Must take a Pandas DataFrame as input and return a DataFrame as output. • Instead of imputing the missing Age values using all of the data, use only the relevant subsets of the data to capture the choice of average age per Sex and Pclass in each case. . Should impute Age values based upon the descriptive statistic method specified by choice. Round all imputed answers to 1 decimal point. • If choice is not either 'mean' or 'median', a ValueError must be raised M Using these plots, your friend argues that there are correlations between the 'Pclass' 'Sex' and 'Age' features within the dataset, and that 'Age" shows influence in predicting a given passenger's survival. Aware of this new knowledge, you decide to create a function, conditional_impute, which performs imputation upon an age column within a Pandas DataFrame based upon both Sex and Pclass columns. Given that you are uncertain which statistic best models your data, you decide to once again to add a choice parameter which allows either the mean or median to be used for imputing the data. Function arguments: ▪ input_df -> input Pandas DataFrame. choice > Python string of either 'mean' or 'median' Default is 'median' Function Specifications: • Name the function conditional_impute ▪ Must take a Pandas DataFrame as input and return a DataFrame as output. • Instead of imputing the missing Age values using all of the data, use only the relevant subsets of the data to capture the choice of average age per Sex and Pclass in each case. . Should impute Age values based upon the descriptive statistic method specified by choice. Round all imputed answers to 1 decimal point. • If choice is not either 'mean' or 'median', a ValueError must be raised M

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