我正在使用LabelEncorder将数据集从String更改为Numeric

Question

I have 2 dataset train_df and test_df. I need to change the columns ('ReqName','AreaChange', 'CodeChange','TestSuite') as Numeric. Hence i have used LabelEncorder , while doing so, i get below error

from sklearn.preprocessing import LabelEncoder

data = [train_df, test_df]
cols = ( 'ReqName','AreaChange', 'CodeChange','TestSuite')

for c in cols:
    lbl = LabelEncoder() 
    lbl.fit(list(data[c].values)) 
    data[c] = lbl.transform(list(data[c].values))

I get this error:

"TypeError: list indices must be integers or slices, not str"

Answer 1

You're trying to access list element via str objects ('ReqName','AreaChange' ...)

Change for loop to this:

for c, _ in enumerate(cols):

Answer 2

your error message could not be more clear :

you are trying to access the data list in index c which is a string.

you must access items in list with the corresponding index - which should be integer, for example 1,2,3 etc.

so just access it with data[1] , data[0] etc.