pandas 基于过滤器更改数据框列的值
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Change Value of a Dataframe Column Based on a Filter
提问by anc1revv
I have a Dataframe that consists of 2 columns:
我有一个由 2 列组成的数据框：
- "Time Spent on website"
- "Dollars spent on the website"
- “在网站上花费的时间”
- “在网站上花费的美元”
I want to perform some classification analysis on this dataset and I only care whether a user made a purchase or not. So I want to run through the "Dollars spent on the website" column and transform the value to "1" if the user spent over $0.00 and have the value be "0" if the user spent nothing.
我想对这个数据集进行一些分类分析，我只关心用户是否进行了购买。因此，我想遍历“在网站上花费的美元”列，如果用户花费超过 0.00 美元，则将值转换为“1”，如果用户什么都没花，则将值转换为“0”。
What is the proper way to do this with a pandas dataframe?
使用Pandas数据框执行此操作的正确方法是什么？
回答by SO44
df['purchase'] = 0
df.loc[df['dollars_spent'] > 0, 'purchase'] = 1
or
或者
df['purchase'] = df['dollars_spent'].apply(lambda x: 1 if x > 0 else 0)
