Recall that you had converted the response variable from Yes/No to 1/0 using find and replace. Which of the following functions can be used to convert Yes and No to 1 and 0, respectively?

In Python, you can use the map() function to convert 'Yes' and 'No' to 1 and 0, respectively. Here's how you can do it:

1. First, create a dictionary where 'Yes' is mapped to 1 and 'No' is mapped to 0. It would look like this:

mapping_dict = {'Yes': 1, 'No': 0}

2. Then, use the map() function on the column of the DataFrame that you want to convert. If the column is named 'ColumnName', you would do it like this:

df['ColumnName'] = df['ColumnName'].map(mapping_dict)

In this code, df is the name of your DataFrame. Replace 'ColumnName' with the name of your column.

This will replace all instances of 'Yes' in the column with 1 and all instances of 'No' with 0.

In Python, you can use the map() function to convert 'Yes' and 'No' to 1 and 0, respectively. Here's how you can do it:

1. First, create a dictionary where 'Yes' is mapped to 1 and 'No' is mapped to 0. It would look like this:

mapping_dict = {'Yes': 1, 'No': 0}

2. Then, use the map() function on the column of the DataFrame that you want to convert. Suppose the column's name is 'ColumnName', and the DataFrame is called 'df'. You would do it like this:

df['ColumnName'] = df['ColumnName'].map(mapping_dict)

This will replace all 'Yes' and 'No' in the 'ColumnName' column with 1 and 0, respectively.