sklearn NearestNeighbors returning misaligned results
You can refactor your code to make this issue easier to investigate. 

Something like this:

nbrs = NearestNeighbors(n_neighbors=1, n_jobs=-1).fit(tfidf) 
orgs = list(set(names['VariationName'].values))

queryTFIDF_ = vectorizer.transform(orgs)
distances, indices = nbrs.kneighbors(queryTFIDF_)

matches = pd.DataFrame(columns=['Match confidence (lower is better)', 'Matched name', 'Original name'])

for distance, index, org in zip(distances, indices, orgs):
    match_confidence = round(distance, 2)
    matched_name = clean_org_names.values[index][0][0]
    matches.append(match_confidence, matched_name, org)