[英]How to apply two different functions to one column if meets the condition?
I need to apply 2 different functions to 1 columns if it meets a condition.如果满足条件,我需要将 2 个不同的功能应用于 1 列。 My dataframe looks like this.
我的 dataframe 看起来像这样。 I want to apply the functions to the column produce: veg_pro if the category is a vegetable and fruit_pro if it's a fruit.
我想将函数应用于列生产:如果类别是蔬菜,则为 veg_pro,如果是水果,则为 fruit_pro。
Produce Category
apple is good fruit
corn is bad vegetable
beans is good vegetable
grape if good fruit
My functions look like this:我的功能如下所示:
def veg_pro(text):
reg_tokenizer = RegexpTokenizer('\s+', gaps = True)
terms = reg_tokenizer.tokenize(text)
return terms
def fruit_pro(text):
reg_tokenizer = RegexpTokenizer(“[\w+.]+“)
terms = reg_tokenizer.tokenize(text)
return terms
df['produce']= df['produce'].apply(lambda x:
veg_pro(x) if df['Category'] =='vegetable’ else
fruit_pro(x))
ValueError: The truth value of a Series is ambiguous. Use
a.empty, a.bool(), a.item(), a.any() or a.all().
instead of using apply
on one column
use it on the dataframe
like this:而不是在一
column
上使用apply
它在dataframe
上使用它,如下所示:
df['produce']= df.apply(lambda x:
veg_pro(x["produce"]) if x["Category"] =="vegetable" else fruit_pro(x["produce"]),axis=1)
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