Pandas：如果预先存在的列包含某个值，则使用“是”创建一个新列，如果该列的值为“”，则创建一个“否”

Question

I am trying to add a column in my "df" that contains "Yes" in case a pre-existing column contains some value and that says "No" if the value of the column is ' ' (note the space between ' ').

Here's an example:

my_dict = {'Products': {0: 0, 1: 1, 2: 2}, 'Prices': {0: ' ', 1: ' ', 2: 'C'}}
my_df = pd.DataFrame(my_dict)

my_df['Direct debit'] = my_df['Category'].apply(lambda x: "Yes" if not "' '" else "NO")

returns:

The "output" is NO in all cases, but it should say YES where my_df['Category'] has any value.

What should I fix in my code?

Answer 1

Use np.where :

import numpy as np
my_df['Direct debit'] = np.where(my_df['Category'] != '', 'Yes', 'No')

By the way, keep in mind that ' ' , '' , are different

Answer 2

Try this. It is much faster than lambda functions on large datasets:

my_df['Direct debit'] = np.where(my_df['Category'] != '', 'YES', 'NO')