[Python] Pandas Groupby Show Non-Matching Values

I have the following dataframe:

data = [['123456ABCD234567', 'A'], ['8502', 'A'],
['74523654894WRZI3', 'B'], ['85CGNK6987541236', 'B'],
['WF85Z4HJ95R4CF2V', 'C'], ['VB52FG85RT74DF96', 'C'],
['WERTZ852146', 'D'], ['APUNGF', 'D']
]
df = pd.DataFrame(data, columns=['CODE', 'STOCK'])
df

CODE STOCK
0 123456ABCD234567 A
1 8502 A
2 74523654894WRZI3 B
3 85CGNK6987541236 B
4 WF85Z4HJ95R4CF2V C
5 VB52FG85RT74DF96 C
6 WERTZ852146 D
7 APUNGF D


Each stock is part of various codes. The code should have a length of 16 characters. My objective is to filter out any stocks that have no codes attached which are not composed of 16 characters. In this example, stock A has at least one code with a length of 16 characters, so it should be kept. However, stock D has no codes with a length of 16 characters.

I believe this can be accomplished using the groupby-function in Pandas.

Ultimately, I aim at obtaining below output:

CODE STOCK
6 WERTZ852146 D
7 APUNGF D


Many thanks for any suggestions in advance!

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