Indexing using value from another DataFrame

pandas version 1.1.3.

I am working with two dataframes (form csv's) in pandas, one containing the data I'm analysing, the other containing labels. Both contain a column with identification numbers. I have set the row indeces of dataframe 2 as the identification numbers. I am using a nlp processing library to analyse the data inside dataframe 1, which returns a boole. I want to index a value in dataframe 2, using the identification numbers form dataframe 1 in a fancy indexing method.

df1 looks like this:

  ID report

1 A1 'bla bla'
2 A1 'blo blo'
3 A1 'blo bla'
4 A2 'bla bla'
5 A2 'blo blo'
6 A3 'foo blo'

df2 looks like this:

   label hypothesis
ID
A1 0     0
A2 1     0 
A3 1     0
A4 0     0
A5 1     0
A6 0     0

This is my code:

for i, row in df1.iterrows():
    index = row['ID']
    display(index)
    report = row['report']
    doc = nlp(report)
    if boole_is_True(doc):
        df2[[index, 'hypothesis']] = 1

This is the result:

'A1'

'A1'

'A1'

'A2'

bla bla
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-22-f9ba77c1e7ea> in <module>
     17         print(report)
---> 18         df2[[index, 'hypothesis']] = 1

~\anaconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   2906             if is_iterator(key):
   2907                 key = list(key)
-> 2908             indexer = self.loc._get_listlike_indexer(key, axis=1, raise_missing=True)[1]
   2909 
   2910         # take() does not accept boolean indexers

~\anaconda3\lib\site-packages\pandas\core\indexing.py in _get_listlike_indexer(self, key, axis, raise_missing)
   1252             keyarr, indexer, new_indexer = ax._reindex_non_unique(keyarr)
   1253 
-> 1254         self._validate_read_indexer(keyarr, indexer, axis, raise_missing=raise_missing)
   1255         return keyarr, indexer
   1256 

~\anaconda3\lib\site-packages\pandas\core\indexing.py in _validate_read_indexer(self, key, indexer, axis, raise_missing)
   1302             if raise_missing:
   1303                 not_found = list(set(key) - set(ax))
-> 1304                 raise KeyError(f"{not_found} not in index")
   1305 
   1306             # we skip the warning on Categorical

KeyError: "['A2'] not in index"

How do I strip the square brackets? Why are there brackets? What is a better title for this question, so it's easier to find for others?

Thanks in advance! My actual data contains medical reports, so I'm afraind I cannot show you my actual data and code.