I am trying to filter a dataframe by a dictionary.

However, I want to treat `filters['age']` as a list of values to exclude from the df, not include.

Can I somehow rewrite the follwing code so the output would be `john 42 London` instead of the current `john 11 Warsaw`?

My only idea is to write two filter dictionaries, one with values to include, and the other with values to exclude, and then filter the df by them separately with `.isin` and `~isin`. But maybe there is another way? 

```
import pandas as pd

d = {
    'name': ['john', 'mike', 'john', 'tim'],
    'age': [42, 24, 11, 66],
    'city': ['London', 'Tokyo', 'Warsaw', 'New York'],
}

filters = {
    'name': ['john', 'mike'],
    'age': [66, 11, 24], # I want these to be excluded. So that age 66 and 11 are not included in the filtered df
    'city': ['Warsaw', 'London', 'Tokyo'],
}

def get_filtered_df(df, filters):
    for filter_name, filter_value in filters.items():
        mask = df[filter_name].isin(filter_value)
        df = df[mask]
    return df

df = pd.DataFrame(d)
filtered_df = get_filtered_df(df, filters)
print(filtered_df)

# output is:
# name  age    city
# john   11  Warsaw 

```