Py3 Find common words in multiple strings - python-3.x

Question

I have a problem and i can't get a proper and good solution.
Here is the thing, i have my list, which contains addresses:
addresses = ['Paris, 9 rue VoltaIre', 'Paris, 42 quai Voltaire', 'Paris, 87 rue VoLtAiRe']
And I want to get after treatment:
to_upper_words = ['paris', 'voltaire']
Because 'Paris' and 'Voltaire' are in all strings.
The goal is to upper all common words, and results for example:
'PARIS, 343 BOULEVARD SAINT-GERMAIN'
'PARIS, 458 BOULEVARD SAINT-GERMAIN'
'Paris', 'Boulevard', 'Saint-Germain' are in upper case because all strings (two in this case) have these words in common.
I found multiple solutions but only for two strings, and the result is ugly to apply for N strings.
If anyone can help...
Thank you in advance !

Answer 1

Remove the commas so that the words can be picked out simply by splitting on blanks. Then find the words that common to all of the addresses using set intersection. (There is only one such word for my collection, namely Montréal.) Now look through the original collection of addresses replacing each occurrence of common words with its uppercase equivalent. The most likely mistake in doing this might be to try to assign a value to an individual value in the list. However, these are, in effect, copies which is why I arranged to assign the modified values to addressses[i].
>>> addresses = [ 'Montréal, 3415 Chemin de la Côte-des-Neiges', 'Montréal, 3655 Avenue du Musée', 'Montréal, 3475 Rue de la Montagne', 'Montréal, 3450 Rue Drummond' ]
>>> sans_virgules = [address.replace(',', ' ') for address in addresses]
>>> listes_de_mots = [sans_virgule.split() for sans_virgule in sans_virgules]
>>> mots_en_commun = set(listes_de_mots[0])
>>> for liste in listes_de_mots[1:]:
... mots_en_commun = mots_en_commun.intersection(set(liste))
...
>>> mots_en_commun
{'Montréal'}
>>> for i, address in enumerate(addresses):
... for mot in list(mots_en_commun):
... addresses[i] = address.replace(mot, mot.upper())
...
>>> addresses
['MONTRÉAL, 3415 Chemin de la Côte-des-Neiges', 'MONTRÉAL, 3655 Avenue du Musée', 'MONTRÉAL, 3475 Rue de la Montagne', 'MONTRÉAL, 3450 Rue Drummond']