I am trying to convert a list :
[A, B, A, A, B, C]
to a dictionnary with each item and the indexes where it was found :
{ A : [0,2,3], B : [1,4], C : [5] }
Any idea of an efficient way to do that ?
Use a defaultdict and enumerate:
>>> lst = ['a','b','a','a','b','c']
>>> from collections import defaultdict
>>> d = defaultdict(list)
>>> for i, value in enumerate(lst):
... d[value].append(i)
...
>>> d
defaultdict(<class 'list'>, {'a': [0, 2, 3], 'c': [5], 'b': [1, 4]})
Or, this can be accomplished with a plain dict, although, it is usually slower:
>>> lst = ['a','b','a','a','b','c']
>>> d = {}
>>> for i, value in enumerate(lst):
... d.setdefault(value, []).append(i)
...
>>> d
{'a': [0, 2, 3], 'c': [5], 'b': [1, 4]}
You could have, of course, converted the defaultdict to a dict:
>>> d
defaultdict(<class 'list'>, {'a': [0, 2, 3], 'c': [5], 'b': [1, 4]})
>>> dict(d)
{'a': [0, 2, 3], 'c': [5], 'b': [1, 4]}
>>> help(dict)
Try this,
lst = ['A', 'B', 'A', 'A', 'B', 'C']
print {i:[j[0] for j in enumerate(lst) if j[1] == i] for i in set(lst)}
Result
{'A': [0, 2, 3], 'B': [1, 4], 'C': [5]}
Use list comprehension and a dict comprehension. Create a set out of the list first. Then you can easily use enumerate and do this.
>>> l = ["A", "B", "A", "A", "B", "C"]
>>> {i:[j for j,k in enumerate(l) if k==i] for i in set(l)}
{'C': [5], 'B': [1, 4], 'A': [0, 2, 3]}
Related
Hi can someone help me with the below requirement ?
Please note the list length can be any number , for example i have just put 4.
I need the output as list of dictionaries with 1 value as key and rest of the values clubbed as list of all possible combination.
Thanks in advance.
Input:
List1 = [1,2,3,4]
Output:
List2 = [ {1:[2,3,4]},{2:[1,3,4]},{3:[1,2,4]} ,{4:[1,2,3]}
Try:
List1 = [1, 2, 3, 4]
out = [
{v: [v for idx2, v in enumerate(List1) if idx != idx2]}
for idx, v in enumerate(List1)
]
print(out)
Prints:
[{1: [2, 3, 4]}, {2: [1, 3, 4]}, {3: [1, 2, 4]}, {4: [1, 2, 3]}]
You can do this with a list comprehension. This approach will only remove the index based.
In [1]: [{i: List1[:idx]+List1[idx+1:]}for idx, i in enumerate(List1)]
Out[1]: [{1: [2, 3, 4]}, {2: [1, 3, 4]}, {3: [1, 2, 4]}, {4: [1, 2, 3]}]
if you want to remove all occurrences of the list, you can use this,
[{i: list(filter((i).__ne__, List1[:]))}for idx, i in List1]
Execution with string list,
In [2]: [{i: list(filter((i).__ne__, List1[:]))}for idx, i in enumerate(List1)]
Out[2]:
[{'a': ['b', 'c', 'd']},
{'b': ['a', 'c', 'd']},
{'c': ['a', 'b', 'd']},
{'d': ['a', 'b', 'c']}]
I would like to merge two dictionaries, but if they have the same key, I would only merge non-duplicate values.
The following code works, but I have a question if it's possible to rewrite this when trying to get a union by using | or (**dict1, **dict2)? When I tried using |, my output would be from this dict_merge({ 'A': [1, 2, 3] }, { 'A': [2, 3, 4] }) to this {'A': [2, 3, 4]}
def dict_merge(dict1, dict2):
for key in dict2.keys():
if key in dict1.keys():
d3 = dict1[key] + dict2[key]
d3 = set(d3)
dict1[key] = list(d3)
else:
dict1[key] = dict2[key]
return dict1
dict_merge({ 'A': [1, 2, 3] }, { 'B': [2, 4, 5, 6]})
Output
{ 'A': [1, 2, 3], 'B': [2, 4, 5, 6] }
Giving your two dictionaries names, let's get the union of their keys.
>>> d1 = { 'A': [1, 2, 3] }
>>> d2 = { 'A': [2, 3, 4] }
>>> d1.keys() | d2.keys()
{'A'}
Assuming the lists are really sets based on your code, we can now iterate over the union of the keys in a dictionary comprehension, and union those two sets and turning them back into a list.
>>> {k: list(set(d1.get(k, [])) | set(d2.get(k, []))) for k in d1.keys() | d2.keys()}
{'A': [1, 2, 3, 4]}
If we incorporate some more interesting dictionaries and repeat the same dictionary comprehension:
>>> d1 = {'A': [1,2,3], 'B': [4,5,6]}
>>> d2 = {'B': [5,6,7,8], 'C': [9,10]}
>>> {k: list(set(d1.get(k, [])) | set(d2.get(k, []))) for k in d1.keys() | d2.keys()}
{'C': [9, 10], 'A': [1, 2, 3], 'B': [4, 5, 6, 7, 8]}
Is that the solution you're wanting?
In [61]: my_dict = {}
...: d1 = {'A': [1, 2, 3], 'C': 123}
...: d2 = {'B': [2, 3, 4], 'A': [1, 2, 3]}
...: for i in set(d1).symmetric_difference(set(d2)):
...: my_dict[i] = d1[i] if i in d1 else d2[i]
...: print(my_dict)
Output :
{'B': [2, 3, 4], 'C': 123}
There is this list of string that I need to use to create a nested dictionary with some values ['C/A', 'C/B/A', 'C/B/B']
The output will be in the format {'C': {'A': [1, 2, 3], 'B': {'A': [1, 2, 3], 'B': [1, 2, 3]}}}
I've tried to use the below code to create the nested dictionary and update the value, but instead I get {'C': {'A': [1, 2, 3], 'C': {'B': {'A': [1, 2, 3], 'C': {'B': {'B': [1, 2, 3]}}}}}} as the output which is not the correct format. I'm still trying to figure out a way. any ideas?
s = ['C/A', 'C/B/A', 'C/B/B']
new = current = dict()
for each in s:
lst = each.split('/')
for i in range(len(lst)):
current[lst[i]] = dict()
if i != len(lst)-1:
current = current[lst[i]]
else:
current[lst[i]] = [1,2,3]
print(new)
You can create a custom Tree class:
class Tree(dict):
'''
Create arbitrarily nested dicts.
>>> t = Tree()
>>> t[1][2][3] = 4
>>> t
{1: {2: {3: 4}}}
>>> t.set_nested_item('a', 'b', 'c', value=5)
>>> t
{1: {2: {3: 4}}, 'a': {'b': {'c': 5}}}
'''
def __missing__(self, key):
self[key] = type(self)()
return self[key]
def set_nested_item(self, *keys, value):
head, *rest = keys
if not rest:
self[head] = value
else:
self[head].set_nested_item(*rest, value=value)
>>> s = ['C/A', 'C/B/A', 'C/B/B']
>>> output = Tree()
>>> default = [1, 2, 3]
>>> for item in s:
... output.set_nested_item(*item.split('/'), value=list(default))
>>> output
{'C': {'A': [1, 2, 3], 'B': {'A': [1, 2, 3], 'B': [1, 2, 3]}}}
You do not need numpy for this problem, but you may want to use recursion. Here is a recursive function add that adds a list of string keys lst and eventually a list of numbers to the dictionary d:
def add(lst, d):
key = lst[0]
if len(lst) == 1: # if the list has only 1 element
d[key] = [1, 2, 3] # That element is the last key
return
if key not in d: # Haven't seen that key before
d[key] = dict()
add(lst[1:], d[key]) # The recursive part
To use the function, create a new dictionary and apply the function to each splitter string:
d = dict()
for each in s:
add(each.split("/"), d)
# d
# {'C': {'A': [1, 2, 3], 'B': {'A': [1, 2, 3], 'B': [1, 2, 3]}}}
If I have a nested dictionary in Python, is there any way to restructure it based on keys?
I'm bad at explaining, so I'll give a little example.
d = {'A':{'a':[1,2,3],'b':[3,4,5],'c':[6,7,8]},
'B':{'a':[7,8,9],'b':[4,3,2],'d':[0,0,0]}}
Re-organize like this
newd = {'a':{'A':[1,2,3],'B':[7,8,9]},
'b':{'A':[3,4,5],'B':[4,3,2]},
'c':{'A':[6,7,8]},
'd':{'B':[0,0,0]}}
Given some function with inputs like
def mysteryfunc(olddict,newkeyorder):
????
mysteryfunc(d,[1,0])
Where the [1,0] list passed means to put the dictionaries 2nd level of keys in the first level and the first level in the 2nd level. Obviously the values need to be associated with their unique key values.
Edit:
Looking for an answer that covers the general case, with arbitrary unknown nested dictionary depth.
Input:
d = {'A':{'a':[1,2,3],'b':[3,4,5],'c':[6,7,8]},
'B':{'a':[7,8,9],'b':[4,3,2],'d':[0,0,0]}}
inner_dict={}
for k,v in d.items():
print(k)
for ka,va in v.items():
val_list=[]
if ka not in inner_dict:
val_dict={}
val_dict[k]=va
inner_dict[ka]=val_dict
else:
val_dict=inner_dict[ka]
val_dict[k]=va
inner_dict[ka]=val_dict
Output:
{'a': {'A': [1, 2, 3], 'B': [7, 8, 9]},
'b': {'A': [3, 4, 5], 'B': [4, 3, 2]},
'c': {'A': [6, 7, 8]},
'd': {'B': [0, 0, 0]}}
you can use 2 for loops, one to iterate over each key, value pair and the second for loop to iterate over the nested dict, at each step form the second for loop iteration you can build your desired output:
from collections import defaultdict
new_dict = defaultdict(dict)
for k0, v0 in d.items():
for k1, v1 in v0.items():
new_dict[k1][k0] = v1
print(dict(new_dict))
output:
{'a': {'A': [1, 2, 3], 'B': [7, 8, 9]},
'b': {'A': [3, 4, 5], 'B': [4, 3, 2]},
'c': {'A': [6, 7, 8]},
'd': {'B': [0, 0, 0]}}
You can use recursion with a generator to handle input of arbitrary depth:
def paths(d, c = []):
for a, b in d.items():
yield from ([((c+[a])[::-1], b)] if not isinstance(b, dict) else paths(b, c+[a]))
from collections import defaultdict
def group(d):
_d = defaultdict(list)
for [a, *b], c in d:
_d[a].append([b, c])
return {a:b[-1][-1] if not b[0][0] else group(b) for a, b in _d.items()}
print(group(list(paths(d))))
Output:
{'a': {'A': [1, 2, 3], 'B': [7, 8, 9]}, 'b': {'A': [3, 4, 5], 'B': [4, 3, 2]}, 'c': {'A': [6, 7, 8]}, 'd': {'B': [0, 0, 0]}}
I'm posting this question after not finding the answer in the many existing issues related to this topic.
I have a dictionary similar to this one:
foo = {'a': [(1, 0.5), (2, 0.3)], 'b': [(3, 0.4), (4, 0.1)]}
and would like to access the items of the nested tupels, in order to create the following dictionary out of it:
foo = {'a': [1, 2], 'b': [3, 4]}
How do I go about doing this, preferably in a pythonic way?
I think these two solutions are easiest to read:
>>> from operator import itemgetter
>>> {k:map(itemgetter(0), foo[k]) for k in foo}
{'a': [1, 2], 'b': [3, 4]}
or import-less:
>>> {k:[x[0] for x in foo[k]] for k in foo}
{'a': [1, 2], 'b': [3, 4]}
what about?
{x: map(lambda z: z[0], y) for x, y in foo.iteritems()}
Using dict comprehension:
In [214]: {key:list(map(lambda x: x[0], foo[key])) for key in foo}
Out[214]: {'a': [1, 2], 'b': [3, 4]}
{k:list(zip(x,y)[0]) for k,(x,y) in foo.iteritems()}
This gives:
{'a': [1, 2], 'b': [3, 4]}
You can do it with defaultdict from collections module:
>>> from collections import defaultdict
>>> d = defaultdict(list)
>>> d = defaultdict(list)
>>> for k in foo:
for v in foo[k]:
d[k].append(v[0])
>>> d
defaultdict(<class 'list'>, {'a': [1, 2], 'b': [3, 4]})
>>> d['a']
[1, 2]