Adaface Sample Pandas Questions

You are working with a dataset, `df`, that contains columns 'A', 'B', and 'C'. You need to perform the following tasks:
            
            1. Group the DataFrame `df` by column 'A'.
            2. Compute the sum of column 'B' for each group.
            3. Append this sum as a new column 'D' to the original DataFrame `df`.
            
            You wrote the following code to perform these tasks:

However, you notice that the new column 'D' contains many missing values. What is the cause of this issue?

A: The groupby method did not work as expected.
            B: The sum method did not work as expected.
            C: The new column 'D' should be appended to grouped instead of df.
            D: The grouped object should be mapped to df['A'] before assigning to a new column in df
            E: The groupby method should be called on df['A'] instead of df.

You are working with a dataset, `df`, that contains several columns with missing values. You want to replace all missing values in the dataset with the mean of the non-missing values of their respective columns.
            
            You wrote the following code to perform this task:

However, you notice that some missing values are still not replaced. What is the cause of this issue?

A: The fillna method does not work with the mean method.
            B: The mean method does not work with missing values.
            C: The fillna method should be called on df.mean() instead of df.
            D: The fillna method does not work inplace by default. You should use df.fillna(df.mean(), inplace=True).
            E: The mean method should be called on df.fillna() instead of df.