Reputation: 193
I have a dictionary of dictionaries, d
:
d = {'redFish': {'redFish': 'inf', 'blueFish': 9, 'twoFish': 10, 'oneFish': 6},
'blueFish': {'redFish': 9, 'blueFish': 'inf', 'twoFish': 11, 'oneFish': 10},
'twoFish': {'redFish': 10, 'blueFish': 11, 'twoFish': 'inf', 'oneFish': 8},
'oneFish': {'redFish': 6, 'blueFish': 10, 'twoFish': 8, 'oneFish': 'inf'}}
I have a function that finds and returns the key-key-value pair with the lowest value:
lowestPair = ['name1', 'name2', float('inf')]
for name1 in d.keys():
for name2 in d[name1].keys():
if d[name1][name2] < lowestPair[2]:
lowestPair = [name1, name2, d[name1][name2]]
My lowest pair acts as a cluster that will be treated as one entity. I am now trying to go through my dictionary of dictionaries, and for each species find the values which are the average between the species I am looking at, and both the species in my new cluster.
i.e. as redFish and oneFish are the species in lowest Pair, I want to find the average between redFish blueFish and oneFish Bluefish, and also the average between oneFish twoFish and oneFish blueFish.
I have a piece of code that does this:
averageList = []
for name in lowestPair[0:2]:
for otherName in d[name].keys():
if otherName not in lowestPair:
average = (d[lowestPair[0]][otherName] + d[lowestPair[1]][otherName])/2
nameDict[name][otherName] = average
averageList.append(average)
However, the average list returns as [9, 9, 9, 9]
which is not the correct answer, as the average for redFish blueFish and oneFish Bluefish, and the average between oneFish twoFish and redFish twoFish should be 9
and 9.5
. What am I doing wrong?
Upvotes: 0
Views: 76
Reputation: 1540
Using the code with a couple of minor calculations, I was able to get [9.5, 9.0, 9.75, 8.5]
The two changes I made was that I had to cast the output of dictionary d
to a float()
, and I changed nameDict
to d
, since nameDict
was not defined in the example code provided. Here is the resulting code below:
d = {'redFish': {'redFish': 'inf', 'blueFish': 9, 'twoFish': 10, 'oneFish': 6}, 'blueFish': {'redFish': 9, 'blueFish': 'inf', 'twoFish': 11, 'oneFish': 10}, 'twoFish': {'redFish': 10, 'blueFish': 11, 'twoFish': 'inf', 'oneFish': 8}, 'oneFish': {'redFish': 6, 'blueFish': 10, 'twoFish': 8, 'oneFish': 'inf'}}
lowestPair = ['name1', 'name2', float('inf')]
for name1 in d.keys():
for name2 in d[name1].keys():
if float( d[name1][name2] ) < lowestPair[2]:
lowestPair = [name1, name2, d[name1][name2]]
averageList = []
for name in lowestPair[0:2]:
for otherName in d[name].keys():
if otherName not in lowestPair:
average = (float( d[lowestPair[0]][otherName] ) + float( d[lowestPair[1]][otherName] ))/2
d[name][otherName] = average
averageList.append(average)
print( averageList )
Upvotes: 1