I am new to python and couldn't find the answer to this. Referring to the code at the end of the message, can I know what does the part "for item, total in totals.items()" in the line below mean?
rankings = [(total/simSums[item], item) for item, total in totals.items()]
Also, the code failed and said
AttributeError: 'dict' object has no attribute 'predictors'
when I changed all instances of "item(s)" in the code to "predictor(s)". Why is that so?
# Return the Pearson correlation coefficient for p1 and p2 def sim_person(prefs, p1, p2): # Get the list of shared_items si={} for item in prefs[p1]: if item in prefs[p2]:si[item]=1 # Find the number of elements n=len(si) # if they have no ratings in common, return 0 if n==0: return 0 # Add up all the preferences sum1 = sum([prefs[p1][it] for it in si]) sum2 = sum([prefs[p2][it] for it in si]) # Sum up the squares sum1Sq = sum([pow(prefs[p1][it],2) for it in si]) sum2Sq = sum([pow(prefs[p2][it],2) for it in si]) # Sum up the products pSum = sum([prefs[p1][it]*prefs[p2][it] for it in si]) # Calculate Person score num = pSum - (sum1*sum2/n) den = sqrt((sum1Sq - pow(sum1,2)/n)*(sum2Sq - pow(sum2,2)/n)) if den == 0: return 0 r = num/den return r # Returns the best matches for person from the prefs dictionary. # Number of results and similarity function are optional params. def topMatch(prefs, person, n=5, similarity=sim_person): scores = [(similarity(prefs, person, other), other) for other in prefs if other!=person] # Sort the list so the highest scores appear at the top scores.sort() scores.reverse() return scores[0:n] # Gets recommendations for a person by using a weighted average # of every other user's rankings def getRecommendations(prefs, person, similarity=sim_person): totals = {} simSums = {} for other in prefs: # don't compare me to myself if other == person: continue sim = similarity(prefs, person, other) # ignore scores of zero of lower if sim<=0: continue for item in prefs[other]: # only score movies I haven't seen yet if item not in prefs[person] or prefs[person][item]==0: # Similarity * Score totals.setdefault(item, 0) totals[item]+=prefs[other][item]*sim # Sum of similarities simSums.setdefault(item, 0) simSums[item]+=sim # Create the normalized list rankings = [(total/simSums[item], item) for item, total in totals.items()] # Return the sorted list rankings.sort() rankings.reverse() return rankings
The dict.items
iterates over the key-value pairs of a dictionary. Therefore for key, value in dictionary.items()
will loop over each pair. This is documented information and you can check it out in the official web page, or even easier, open a python console and type help(dict.items)
. And now, just as an example:
>>> d = {'hello': 34, 'world': 2999} >>> for key, value in d.items(): ... print key, value ... world 2999 hello 34
The AttributeError
is an exception thrown when an object does not have the attribute you tried to access. The class dict
does not have any predictors
attribute (now you know where to check it :) ), and therefore it complains when you try to access it. As easy as that.
#Try without dot notation sample_dict = {'name': 'John', 'age': 29} print(sample_dict['name']) # John print(sample_dict['age']) # 29
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