issue with oneHotEncoding So i have a PandasDataFrame with categorical variables in a column which i want to one hot encode i've used the following code from an ML udemy course

from sklearn.preprocessing import OneHotEncoder
onehotencoder=OneHotEncoder(categorical_features=[10])
Y= onehotencoder.fit_transform(X).toarray()


However i get the following error 

ValueError: could not convert string to float:


A bit of information Y is converted to an object from a df using 

Y=df.iloc[:,:].values


I want to oneHotencode the 10th column of y which contains string values. The type of Y in variable explorer is object and if execute 

type(Y)


i get numpy.ndarray

I'm new to Pandas and sklearn and would really appreciate any help.
There is an easy way to use one hot encoding in pandas and you can read about it in the following link:

https://pandas.pydata.org/pandas-docs/stable/generated/pandas.get_dummies.html

The get_dummies method is easy and optimized for use in pandas Data Frames.

Good luck!