A = {0:{a:1, b:7}, 1:{a:5,b:5}, 2:{a:4,b:6}}
I want to attach an item guess to each sub dictionary based on the value b accounting of all b's in each sub dictionary.
Saying, in Dictionary A:
0-b-7 percentage of b: 7/(7+5+6)
1-b-5 percentage of b: 5/(7+5+6)
2-b-6 percentage of b: 1 - 7/(7+5+6) - 5/(7+5+6)
The desired Dictionary should be like
A = {0:{a:1, b:7, 'guess': 7/(7+5+6)},
1:{a:5,b:5, 'guess': 5/(7+5+6)},
2:{a:4,b:6, 'guess': 1 - 7/(7+5+6) - 5/(7+5+6)}}
I don't know how to incorporate the other two b's for a specific subdictionary.
One approach is to precompute the sum of all bs and then use it to add a new key-value pair to your dictionary.
b_total = float(sum(A[k]['b'] for k in A))
for k in A:
A[k]['guess'] = A[k]['b'] / b_total
#{0: {'a': 1, 'b': 7, 'guess': 0.3888888888888889},
# 1: {'a': 5, 'b': 5, 'guess': 0.2777777777777778},
# 2: {'a': 4, 'b': 6, 'guess': 0.3333333333333333}}
A = {0:{"a":1, "b":7}, 1:{"a":5,"b":5}, 2:{"a":4,"b":6}}
char = "b"
denominator = 0
# =========================
# First Calculate the sum
# =========================
for key in A:
inner_map = A[key]
denominator += inner_map[char]
# ========================================
# Now insert the new key to the inner_map
# ========================================
for key in A:
inner_map = A[key]
inner_map["guess"] = inner_map[char]/denominator
print(A)
Output:
{0: {'a': 1, 'b': 7, 'guess': 0.3888888888888889}, 1: {'a': 5, 'b': 5, 'guess': 0.2777777777777778}, 2: {'a': 4, 'b': 6, 'guess': 0.3333333333333333}}
Try this:
def add_calc(my_dict):
total_guesses = sum(map(lambda x: my_dict.get(x).get('b'), my_dict))
for item in my_dict.itervalues():
item.update({'guess': 1.0 * item.get('b') / total_guesses})
return my_dict
d = add_calc(A)
{0: {'a': 1, 'b': 7, 'guess': 0.3888888888888889},
1: {'a': 5, 'b': 5, 'guess': 0.2777777777777778},
2: {'a': 4, 'b': 6, 'guess': 0.3333333333333333}}
I'm on Python 2 btw, you didn't specify version
You can use dictionary unpacking:
A = {0:{'a':1, 'b':7}, 1:{'a':5, 'b':5}, 2:{'a':4, 'b':6}}
results = {a:{**b, **{'guess':b['b']/float(sum(c['b'] for _, c in A.items()))}} for a, b in A.items()}
Output:
{0: {'guess': 0.3888888888888889, 'b': 7, 'a': 1}, 1: {'guess': 0.2777777777777778, 'b': 5, 'a': 5}, 2: {'guess': 0.3333333333333333, 'b': 6, 'a': 4}}
Related
Given
listOfDict = [{'ref': 1, 'a': 1, 'b': 2, 'c': 3},
{'ref': 2, 'a': 4, 'b': 5, 'c': 6},
{'ref': 3, 'a': 7, 'b': 8, 'c': 9}]
Lets' consider a list of permutable integer
[7,8,9]=[7,9,8]=[8,7,9]=[8,9,7]=[9,7,8]=[9,8,7] # (3!)
Each of this list has a unique mapping ref, so how given for (8,7,9) can I get ref=3 ?
Also in real case I might until 10 (a,b,c,d,e,f,g,h,i,j)...
You can generate a dictionary that maps the values as frozenset to the value of ref:
listOfDict = [{'ref': 1, 'a': 1, 'b': 2, 'c': 3},
{'ref': 2, 'a': 4, 'b': 5, 'c': 6},
{'ref': 3, 'a': 7, 'b': 8, 'c': 9}]
keys = ['a', 'b', 'c']
out = {frozenset(d[k] for k in keys): d['ref'] for d in listOfDict}
# {frozenset({1, 2, 3}): 1,
# frozenset({4, 5, 6}): 2,
# frozenset({7, 8, 9}): 3}
example:
check = frozenset((8,7,9))
out[check]
# 3
but I don't know in advance the name of the other keys!
Then use this approach:
out = {}
for d in listOfDict:
d2 = d.copy() # this is to avoid modifying the original object
out[frozenset(d2.values())] = d2.pop('ref')
out
or as a comprehension:
out = dict(((d2:=d.copy()).pop('ref'), frozenset(d2.values()))[::-1]
for d in listOfDict)
Here is a commented solution to your problem. The idea is to compare the sorted list of the values in a, b, c etc with the sorted values in list_of_ints. The sorted values will be the same for all permutations of a given set of numbers.
def get_ref(list_of_ints):
# Loop through dictionaries in listOfDict.
for dictionary in listOfDict:
# Get list of values in each dictionary.
vals = [dictionary[key] for key in dictionary if key != "ref"]
if sorted(vals) == sorted(list_of_ints):
# If sorted values are equal to sorted list of ints, return ref.
return dictionary["ref"])
By the way, I believe it would be cleaner to structure this data as a dict of dicts in the following way:
dicts = {
1: {'a': 1, 'b': 2, 'c': 3},
2: {'a': 4, 'b': 5, 'c': 6},
3: {'a': 7, 'b': 8, 'c': 9}
}
The code would then be:
def get_ref(list_of_ints):
for ref, dictionary in dicts.items():
if sorted(dictionary.values()) == sorted(list_of_ints):
return ref
Assuming that all integers in the permutations are unique, the code can be simplified further using sets instead of sorted lists.
Since its a list of dict I can call each dict as it self by using for loop
and record the first number on ref
for i in listOfDict:
ref_num=i["ref"]
and to turn dictunary to list we simply use:
z=list(i.values())
then the last step is to find if its the same input list if so we print/return the ref number
if z[1:]==InputList:
return ref_num
and the code should be like this:
listOfDict = [
{"ref": 1,
"a": 1,
"b": 2,
"c": 3},
{"ref": 2,
"a": 4,
"b": 5,
"c": 6},
{"ref": 3,
"a": 7,
"b": 8,
"c": 9},]
def find_ref_Num(InputList):
for i in listOfDict:
ref_num=i["ref"]
z=list(i.values())
if z[1:]==InputList:
return ref_num
print ("your ref number is: "+str(find_ref_Num([7,8,9])))
Suppose I have the following dictionary:
{'a': 0, 'b': 1, 'c': 2, 'c.1': 3, 'd': 4, 'd.1': 5, 'd.1.2': 6}
I wish to write an algorithm which outputs the following:
{
"a": 0,
"b": 1,
"c": {
"c": 2,
"c.1": 3
},
"d":{
"d": 4,
"d.1": {
"d.1": 5,
"d.1.2": 6
}
}
}
Note how the names are repeated inside the dictionary. And some have variable level of nesting (eg. "d").
I was wondering how you would go about doing this, or if there is a python library for this? I know you'd have to use recursion for something like this, but my recursion skills are quite poor. Any thoughts would be highly appreciated.
You can use a recursive function for this or just a loop. The tricky part is wrapping existing values into dictionaries if further child nodes have to be added below them.
def nested(d):
res = {}
for key, val in d.items():
t = res
# descend deeper into the nested dict
for x in [key[:i] for i, c in enumerate(key) if c == "."]:
if x in t and not isinstance(t[x], dict):
# wrap leaf value into another dict
t[x] = {x: t[x]}
t = t.setdefault(x, {})
# add actual key to nested dict
if key in t:
# already exists, go one level deeper
t[key][key] = val
else:
t[key] = val
return res
Your example:
d = {'a': 0, 'b': 1, 'c': 2, 'c.1': 3, 'd': 4, 'd.1': 5, 'd.1.2': 6}
print(nested(d))
# {'a': 0,
# 'b': 1,
# 'c': {'c': 2, 'c.1': 3},
# 'd': {'d': 4, 'd.1': {'d.1': 5, 'd.1.2': 6}}}
Nesting dictionary algorithm ...
how you would go about doing this,
sort the dictionary items
group the result by index 0 of the keys (first item in the tuples)
iterate over the groups
if there are is than one item in a group make a key for the group and add the group items as the values.
Slightly shorter recursion approach with collections.defaultdict:
from collections import defaultdict
data = {'a': 0, 'b': 1, 'c': 2, 'c.1': 3, 'd': 4, 'd.1': 5, 'd.1.2': 6}
def group(d, p = []):
_d, r = defaultdict(list), {}
for n, [a, *b], c in d:
_d[a].append((n, b, c))
for a, b in _d.items():
if (k:=[i for i in b if i[1]]):
r['.'.join(p+[a])] = {**{i[0]:i[-1] for i in b if not i[1]}, **group(k, p+[a])}
else:
r[b[0][0]] = b[0][-1]
return r
print(group([(a, a.split('.'), b) for a, b in data.items()]))
Output:
{'a': 0, 'b': 1, 'c': {'c': 2, 'c.1': 3}, 'd': {'d': 4, 'd.1': {'d.1': 5, 'd.1.2': 6}}}
I have three dictionaries:
X = {'a':2, 'b':3,'e':4}
Y = {'c':3, 'b':4,'a':5, 'd':7}
Z = {'c':8, 'b':7,'a':9, 'e':10,'f':10}
I want to add elements of X and Y if they are present in both dicts and then subtract them from z i.e. Z-X+Y
How can I do that ?
expected result:
res = {'a':2,'b':0,'c':5,'d':7,'e':6,'f':10}
What I tried:
from collections import Counter
xy = Counter(X) + Counter(Y)
res = Counter(Z) - xy
which return:
Counter({'c': 5, 'a': 2, 'e': 6, 'f': 10})
as you can see b and d are missing from my attempt
Your expected result is actually an operation of symmetric difference in terms of sets, but since collections.Counter doesn't support such an operation, you can emulate it with:
xy = Counter(X) + Counter(Y)
z = Counter(Z)
res = z - xy | xy - z
res becomes:
Counter({'f': 10, 'd': 7, 'e': 6, 'c': 5, 'a': 2})
But if you do want keys with value of 0, which Counter would hide from its output, you would have to iterate through a union of the keys of the 3 dicts:
{k: res.get(k, 0) for k in {*X, *Y, *Z}}
This returns:
{'a': 2, 'd': 7, 'e': 6, 'b': 0, 'f': 10, 'c': 5}
Here's some code to take a linear combination of two dictionaries:
def linearcombination(a1,d1,a2,d2):
return {k:a1*d1.get(k,0)+a2*d2.get(k,0) for k in {**d1,**d2}.keys()}
choosy1={"a":1,"b":2,"c":3}
choosy2={"a":1,"d":1}
choosy=linearcombination(1,choosy1,10,choosy2)
choosy is:
{'a': 11, 'c': 3, 'd': 10, 'b': 2}
How can I generalise it to allow linear combinations of arbitrary numbers of dictionaries?
Solution using sum in a dict comprehension over a set of keys:
from itertools import chain
def linear_combination_of_dicts(dicts, weights):
return {
k: sum( w * d.get(k, 0) for d, w in zip(dicts, weights) )
for k in set(chain.from_iterable(dicts))
}
Example:
>>> dicts = [{'a': 1, 'b': 2, 'c': 3}, {'a': 1, 'd': 1}]
>>> weights = [1, 10]
>>> linear_combination_of_dicts(dicts, weights)
{'c': 3, 'd': 10, 'a': 11, 'b': 2}
Here's an approach with pandas to handle dict key alignment:
def lc(coeffs, dicts):
return (pd.concat(pd.Series(d).fillna(0)*a for a,d in zip(coeffs,dicts))
.sum(level=0)
.to_dict()
)
lc([1,10], [choosy1, choosy2])
# {'a': 11, 'b': 2, 'c': 3, 'd': 10}
Im trying to multiple some values from dictionary
example
price_list = {'a': 3, 'b': 2, 'c': 5, 'd': 10}
when i type
total=sum(price_list.values())
print("Total sum is ",total)
it result 20
But now i want to multiple a with 3, b with 5, c with 2 and d with 3 and my desired output to be 59. What is easiest way to do that?
Assuming your numbers are stored in the list, iterate through the values, and multiply with your required number like so
price_dict = {'a': 3, 'b': 2, 'c': 5, 'd': 10}
numbers_dict = {'a': 3, 'b': 5, 'c': 2, 'd': 3}
result = 0
for key, value in price_dict.items():
result += numbers_dict[key] * value
print(result)
#59
You can just perform operations on the dictionary item like you would any other variable:
# multiply 'a' by 3
price_list['a'] *= 3
Try this:
price_list = {'a': 3, 'b': 2, 'c': 5, 'd': 10}
numbers = [3,5,2,3]
for k,n in list(zip(price_list, numbers)):
price_list[k] *= n
then the price list will change, you can use sum as you did to calculate the result.