columns_to_check = df['OnlineSecurity', 'OnlineBackup', 'DeviceProtection', 'StreamingTV', 'StreamingMovies'] df_internet['NumServices'] = [columns_to_check].apply(lambda row: row.str.lower().eq('yes').sum(), axis=1)

This code snippet is trying to create a new column in a DataFrame df_internet that counts the number of internet services subscribed to by a customer based on the values in the columns OnlineSecurity, OnlineBackup, DeviceProtection, StreamingTV, and StreamingMovies in another DataFrame df.

However, there are a couple of issues in the code:

1. The columns_to_check variable should be a list of column names, but it is currently written as a dictionary. It should be corrected as follows: columns_to_check = df[['OnlineSecurity', 'OnlineBackup', 'DeviceProtection', 'StreamingTV', 'StreamingMovies']]

2. The apply function is being used incorrectly. It should be applied directly to the columns_to_check DataFrame instead of wrapping it in a list. The correct usage should be: df_internet['NumServices'] = columns_to_check.apply(lambda row: row.str.lower().eq('yes').sum(), axis=1)

By making these corrections, the code should work as intended to count the number of internet services subscribed to by each customer.