transform a dataframe to list ans delete NaN values

hi I have the following dataset

df = pd.DataFrame({'fruits': ['orange', 'mango', 'apple', 'grapes', 'NaN', 'mango'],
                   'price': ['40', '80', 'NaN', '40', '30', '80']
                   })

    fruits  price
0   orange  40
1   mango   80
2   apple   NaN
3   grapes  40
4   NaN     30

I want to return a list that does not have the NaN values. So I am using the following code:

dfd= [[y for y in x if pd.notna(y)] for x in df.values.tolist()]

However, the NaN values are still there

[['orange', '40'],
 ['mango', '80'],
 ['apple', 'NaN'],
 ['grapes', '40'],
 ['NaN', '30'],
 ['mango', '80']]

Any ideas?

Because NaN is string pd.notna return False, if need remove 'NaN's strings use:

dfd= [[y for y in x if Y != 'NaN'] for x in df.values.tolist()]

If convert NaNs strings to missing values:

df = df.replace('NaN', np.nan)
dfd= [[y for y in x if pd.notna(y)] for x in df.values.tolist()]