The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

Question

Dataset

df['sales']

abd	sales
atf	1.2
adstys	0.9
tyugug	5.6
gfygv	1.1

I want to create a new column based on sales values. If sales value is above 1.2 it should replace with 1 or 0 if anything less than 1.2

Applying list comprehension on a float column is throwing truth value error

df['new_sales_index']=df['sales'].apply(lambda x: [1 if y > 1.2 else 0])