Python-pandas：一个系列的真值是模棱两可的错误

Question

in pandas_dataframe, I try to convert numerical value to categorical value

df['SalePrice_band']=0
df.loc[df['SalePrice']<50000 , 'SalesPrice_band']=1
df.loc[df['SalePrice']>=50000 & df['SalePrice']<100000 , 'SalesPrice_band'] = 2
df.loc[df['SalePrice']>=100000 & df['SalePrice']<125000 , 'SalesPrice_band'] = 3
df.loc[df['SalePrice']>=125000 & df['SalePrice']<150000 , 'SalesPrice_band'] = 4
df.loc[df['SalePrice']>=150000 & df['SalePrice']<175000 , 'SalesPrice_band'] = 5

But, above code occurs error as: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

so, I read error message and checked

df.loc[df['SalePrice']<50000 , 'SalesPrice_band']=1

Above is fine.

 df['SalePrice']>=50000 & df['SalePrice']<100000

But Here, I got error where I connect by two bool_bin

SO, I TRY Like this:

(df['SalePrice']>=50000 & df['SalePrice']<100000).all()

But DOESN'T WORK; Still error: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

How can I handle it?

Answer 1

In Pandas, you must put all boolean checks inside parenthesis, like below:

df.loc[(df['SalePrice']>=50000) & (df['SalePrice']<100000) , 'SalesPrice_band'] = 2

instead of this:

df.loc[df['SalePrice']>=50000 & df['SalePrice']<100000 , 'SalesPrice_band'] = 2

The latest will lead to the error that you provided