Question

How would you perform a function on every item in a row or column in a dataframe?

A) for loop with conditional statements
B) apply() function
C) merge() operation
D) groupby() method

Answer 1

The apply() function allows you to perform a function on every item in a row or column of a dataframe. It is more efficient and concise than using a for loop with conditional statements, and is different from the groupby() method and merge() operation.

Correct option is B) apply() function

Step-by-step explanation:

To perform a function on every item in a row or column in a dataframe, you can use the apply() function. This function allows you to apply a specified function to each row or column of a dataframe. For example, if you have a dataframe called 'df' and you want to calculate the sum of each column, you can use the code: df.apply(sum, axis=0).

Another option mentioned in the question, but not suitable for this task, is the groupby() method. This method is used to group dataframe rows based on certain criteria, not perform functions on individual items. Similarly, the merge() operation is used to combine two or more dataframes based on a common column or index, and is not applicable for this task.

While a for loop with conditional statements can also be used to iterate over each item in a row or column, the apply() function is generally more efficient and concise.