title: Problems with group by multiple columns (different amount of rows each time)
body: <p>I have a data frame which stores information on roughly 30.000 documents spread over 200.000 rows. Thats because one document can have multiple subject terms. So, the rows discussing the same document are identical except for the column "SubjectTerm".</p>
  
  <p>My goal: a data frame in which one row represents one document with all its subject terms in a list. As all columns of the same document are the same, I used group by. I grouped the rows by different columns. However, I get a different amount of rows each time. That's what I tried so far. Any idea what I did wrong?</p>
  
  <pre><code>SubjectTerms_Kreuztabelle = EBSCOhost_unselektiert.copy(deep=True)
  SubjectTerms_Kreuztabelle.dropna(subset=["SubjectTerm"], inplace = True)
  
  SubjectTerms_Kreuztabelle2 = SubjectTerms_Kreuztabelle.groupby(["Jahr", "Titel"])["SubjectTerm"].apply(list).reset_index()  #29.338 rows
  
  SubjectTerms_Kreuztabelle4 = SubjectTerms_Kreuztabelle.groupby(["Jahr", "Datum", "Medium-Typ", "Titel"])["SubjectTerm"].apply(list).reset_index() #29.606 rows
  </code></pre>