The correct answer is: A. corrwith
The corrwith method is implemented on DataFrame to compute the correlation between like-labeled Series contained in different DataFrame objects. It takes two arguments: the first is the DataFrame object that contains the Series to be correlated, and the second is the name of the Series to be correlated. The method returns a DataFrame object with one column for each Series in the first DataFrame, and one row for each Series in the second DataFrame. The value in each cell is the correlation coefficient between the two Series.
The corwith method is useful for comparing the correlation between two different sets of data. For example, you could use it to compare the correlation between the prices of two different stocks, or the correlation between the heights and weights of two different groups of people.
The corrwith method is also useful for identifying relationships between different variables. For example, you could use it to identify which variables are most correlated with the price of a stock, or which variables are most correlated with the height of a person.
The corrwith method is a powerful tool that can be used to analyze data and identify relationships between different variables. It is a relatively simple method to use, and it can be used to analyze a wide variety of data.
The other options are incorrect because they are not implemented on DataFrame to compute the correlation between like-labeled Series contained in different DataFrame objects.