In Python, which of the following functions in the

Solution

The correct method for merging two DataFrames in Pandas is merge(). This function is used when you want to combine DataFrames based on a common column or index. In this case, df1.merge(df2, on='id') merges df1 and df2 based on the column id that is common to both DataFrames. This is a typical operation in data analysis where you want to combine two datasets that share a key variable. Why Other Options Are Incorrect: • B: pd.concat() is used to concatenate DataFrames along a particular axis, but it does not merge based on a common column. It is typically used for stacking DataFrames on top of each other or side by side. • C: df1.join(df2, on='id') is used for joining DataFrames by index, not by a specific column like id. It can be used for indexing-based joins but not for merging on non-index columns. • D: pd.merge(df1, df2, axis=0) is incorrect because the axis parameter is used for concatenation and determines whether to concatenate along rows or columns. It does not merge based on a common column. • E: df1.merge(df2, axis=1) will merge the DataFrames along columns, but it will not merge based on a common column like id. The axis=1 parameter is meant for column-wise operations, not for merging.