[Python] How to use ColumnTransformer for categorical data?

I am trying to preprocess data.

data = {'Country':['Germany', 'Turkey', 'England', 'Turkey', 'Germany', 'Turkey'],
'Age':['44', '32', '27', '29', '31', '25'],
'Salary':['5400', '8500', '7200', '4800', '6200', '10850'],
'Purchased':['yes', 'yes', 'no', 'yes', 'no', 'yes']}
df = pd.DataFrame(data)
X = df.iloc[:,0].values


Expected result is like this:

|---|---|---|----|-------|---|
| 1 | 0 | 0 | 44 | 5400 | 1 |
| 0 | 1 | 0 | 32 | 8500 | 1 |
| 0 | 0 | 1 | 27 | 7200 | 0 |
| 0 | 1 | 0 | 29 | 4800 | 1 |
| 1 | 0 | 0 | 31 | 6200 | 0 |
| 0 | 1 | 0 | 25 | 10850 | 1 |


Here is the code that failed.

from sklearn.preprocessing import OneHotEncoder
from sklearn.compose import ColumnTransformer
ct = ColumnTransformer([("city_category", OneHotEncoder(dtype='int'), [0])], remainder="passthrough")
X = ct.fit_transform(X)


Output:

IndexError: tuple index out of range


I want to learn that how to use ColumnTransformer function in this situations?

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