Value of LabelEncoder() is getting overwritten while traversing through DF

Question

I am quite new to ML can anyone please help me, I am facing issue while encoding and decoding below mentioned DF using preprocessing.LabelEncoder() , basically the label encoder is getting overwritten with new value

df.head()

         | Col1     |    Col2 |  Col3 |  Col4 |  Col5    |   Col6             
0        | Minor    |    Yes  |  BSS  | Data1 |  Data3   |  Packet-Core/EPC
1        | Critical |    Yes  |  OSS  | Data2 |  Data4   |  Packet-Core/OSS

le = preprocessing.LabelEncoder()
    dfCatagorical=df.apply(le.fit_transform)
    dfCatagorical.head()

         | Col1 |    Col2 |  Col3 |  Col4 |  Col5    |   Col6
 
0        | 0    |    0    |  0    | 0     |  0       |  0
1        | 1    |    0    |  1    | 1     |  1       |  1

le.classes_

array(['Packet-Core/EPC', 'Packet-Core/OSS'])

Here the last column (COl6) values are present in LE , and when I am trying to transform the value for COL1 its giving me error

   le.transform(['Minor']))

"previously unseen labels: ['Minor']"

Expected value is "0" (as per dfCatagorical[0][0])