Dynamically Created Columns from Selected Columns in Pandas

My current dataset is in the following format.

df = pd.DataFrame({
'a' = np.random.randn(6),
'b' = np.random.randn(6),
'c' = np.random.randn(6),
'd' = np.random.randn(6),
'e' = np.random.randn(6),
'f' = np.random.randn(6)
})

My updated dataset looks like this:

df = pd.DataFrame({
'a' = np.random.randn(6),
'b' = np.random.randn(6),
'c' = np.random.randn(6),
'd' = np.random.randn(6),
'e' = np.random.randn(6),
'f' = np.random.randn(6),
'alpha' = np.random.randn(6),
'beta' = np.random.randn(6),
'gamma' = np.random.randn(6)
    })


where alpha = df['a']*2
beta = df['b']*5
gamma = df['c']*6 

Both the final 3 columns (alpha, beta & gamma) & input columns (a,b,c) and numeric values (2,5,6) are variables so getting pass from outside as list.

So, I was trying this following code:

newCol = ['alpha', 'beta', 'gamma']
oldCol = ['a', 'b', 'c']
numVal = [2, 5, 6]

for i in range(len(newCol)):
     
      df[newCol[i]] = df[oldCol[i]]*numVal[i]

But I'm getting the following error:

TypeError: unsupported operand type(s) for /: 'str' and 'float'

Can someone please tell me how to solve this problem?

Thanks!