Reverse dictionary where values are listsConvert dictionary of lists of tuples to list of lists/tuples in...
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Reverse dictionary where values are lists
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$begingroup$
I'm working on the following problem: I've got a dictionary like this one:
dic={0:[0,1,2],1:[3,4,5]}
And I want to reverse it so it looks like this:
dic2={0:0,1:0,2:0,3:1,4:1,5:1}
I managed to make it, but doing this:
dic2={}
for i in dic:
for j in dic[i]:
dic2[j]=i
I know about list and dict comprehensions and this code reeks of it, but I'm not good at them when there are nested for
and dicts
. How would you make it more efficiently?
python dictionary
New contributor
$endgroup$
add a comment |
$begingroup$
I'm working on the following problem: I've got a dictionary like this one:
dic={0:[0,1,2],1:[3,4,5]}
And I want to reverse it so it looks like this:
dic2={0:0,1:0,2:0,3:1,4:1,5:1}
I managed to make it, but doing this:
dic2={}
for i in dic:
for j in dic[i]:
dic2[j]=i
I know about list and dict comprehensions and this code reeks of it, but I'm not good at them when there are nested for
and dicts
. How would you make it more efficiently?
python dictionary
New contributor
$endgroup$
add a comment |
$begingroup$
I'm working on the following problem: I've got a dictionary like this one:
dic={0:[0,1,2],1:[3,4,5]}
And I want to reverse it so it looks like this:
dic2={0:0,1:0,2:0,3:1,4:1,5:1}
I managed to make it, but doing this:
dic2={}
for i in dic:
for j in dic[i]:
dic2[j]=i
I know about list and dict comprehensions and this code reeks of it, but I'm not good at them when there are nested for
and dicts
. How would you make it more efficiently?
python dictionary
New contributor
$endgroup$
I'm working on the following problem: I've got a dictionary like this one:
dic={0:[0,1,2],1:[3,4,5]}
And I want to reverse it so it looks like this:
dic2={0:0,1:0,2:0,3:1,4:1,5:1}
I managed to make it, but doing this:
dic2={}
for i in dic:
for j in dic[i]:
dic2[j]=i
I know about list and dict comprehensions and this code reeks of it, but I'm not good at them when there are nested for
and dicts
. How would you make it more efficiently?
python dictionary
python dictionary
New contributor
New contributor
edited 5 hours ago
Sᴀᴍ Onᴇᴌᴀ
10.1k62167
10.1k62167
New contributor
asked 5 hours ago
Juan CJuan C
1185
1185
New contributor
New contributor
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
There's really not much to say about this code, it is straightforward.
Style
These are only nitpicks.
- Generic dictionary keys are typically named
k
instead ofi
orj
, but in a specific application a more descriptive name would be even better. - Collections should be named by their purpose in the application, not their type.
- By convention, assignments and other binary operators should be surrounded by spaces:
a = b
, nota=b
. See PEP 8 for reference, if you're not already aware of it. Following this style guide makes your code easier to read for others.
Code improvements
When iterating over the keys and values of a dictionary at the same time, you can use
for k, v in dic.items():
# ... use k, v ...
instead of
for k in dic:
v = dic[k]
# ...
The nested loop can be transformed to a dictionary comprehension like this:
dic2 = {v: k for k, values in dic.items() for v in values}
You can remember that the order of for
clauses in the comprehension is the same as the order of corresponding nested for
loops.
Potential pitfalls
You should be aware that this transformation from a dictionary of lists to a reverse dictionary only works if all items in the original lists are unique. Counterexample:
>>> dic = {0: [1, 2], 1: [2, 3]}
>>> {v: k for k, values in dic.items() for v in values}
{1: 0, 2: 1, 3: 1} # missing 2: 0
To correct this, the output dictionary should have the same format as the input, namely mapping each of the items in the input lists to a list of corresponding keys.
If the input represents a directed graph (mapping nodes to lists of neighbours), this corresponds to computing the transposed or reversed graph. It can be done by using a collections.defaultdict
. I don't see an easy way to write it as a comprehension in this case.
from collections import defaultdict
graph = {0: [1, 2], 1: [2, 3]}
transposed_graph = defaultdict(list)
for node, neighbours in graph.items():
for neighbour in neighbours:
transposed_graph[neighbour].append(node)
# {1: [0], 2: [0, 1], 3: [1]}
$endgroup$
add a comment |
Your Answer
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1 Answer
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active
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1 Answer
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active
oldest
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oldest
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oldest
votes
$begingroup$
There's really not much to say about this code, it is straightforward.
Style
These are only nitpicks.
- Generic dictionary keys are typically named
k
instead ofi
orj
, but in a specific application a more descriptive name would be even better. - Collections should be named by their purpose in the application, not their type.
- By convention, assignments and other binary operators should be surrounded by spaces:
a = b
, nota=b
. See PEP 8 for reference, if you're not already aware of it. Following this style guide makes your code easier to read for others.
Code improvements
When iterating over the keys and values of a dictionary at the same time, you can use
for k, v in dic.items():
# ... use k, v ...
instead of
for k in dic:
v = dic[k]
# ...
The nested loop can be transformed to a dictionary comprehension like this:
dic2 = {v: k for k, values in dic.items() for v in values}
You can remember that the order of for
clauses in the comprehension is the same as the order of corresponding nested for
loops.
Potential pitfalls
You should be aware that this transformation from a dictionary of lists to a reverse dictionary only works if all items in the original lists are unique. Counterexample:
>>> dic = {0: [1, 2], 1: [2, 3]}
>>> {v: k for k, values in dic.items() for v in values}
{1: 0, 2: 1, 3: 1} # missing 2: 0
To correct this, the output dictionary should have the same format as the input, namely mapping each of the items in the input lists to a list of corresponding keys.
If the input represents a directed graph (mapping nodes to lists of neighbours), this corresponds to computing the transposed or reversed graph. It can be done by using a collections.defaultdict
. I don't see an easy way to write it as a comprehension in this case.
from collections import defaultdict
graph = {0: [1, 2], 1: [2, 3]}
transposed_graph = defaultdict(list)
for node, neighbours in graph.items():
for neighbour in neighbours:
transposed_graph[neighbour].append(node)
# {1: [0], 2: [0, 1], 3: [1]}
$endgroup$
add a comment |
$begingroup$
There's really not much to say about this code, it is straightforward.
Style
These are only nitpicks.
- Generic dictionary keys are typically named
k
instead ofi
orj
, but in a specific application a more descriptive name would be even better. - Collections should be named by their purpose in the application, not their type.
- By convention, assignments and other binary operators should be surrounded by spaces:
a = b
, nota=b
. See PEP 8 for reference, if you're not already aware of it. Following this style guide makes your code easier to read for others.
Code improvements
When iterating over the keys and values of a dictionary at the same time, you can use
for k, v in dic.items():
# ... use k, v ...
instead of
for k in dic:
v = dic[k]
# ...
The nested loop can be transformed to a dictionary comprehension like this:
dic2 = {v: k for k, values in dic.items() for v in values}
You can remember that the order of for
clauses in the comprehension is the same as the order of corresponding nested for
loops.
Potential pitfalls
You should be aware that this transformation from a dictionary of lists to a reverse dictionary only works if all items in the original lists are unique. Counterexample:
>>> dic = {0: [1, 2], 1: [2, 3]}
>>> {v: k for k, values in dic.items() for v in values}
{1: 0, 2: 1, 3: 1} # missing 2: 0
To correct this, the output dictionary should have the same format as the input, namely mapping each of the items in the input lists to a list of corresponding keys.
If the input represents a directed graph (mapping nodes to lists of neighbours), this corresponds to computing the transposed or reversed graph. It can be done by using a collections.defaultdict
. I don't see an easy way to write it as a comprehension in this case.
from collections import defaultdict
graph = {0: [1, 2], 1: [2, 3]}
transposed_graph = defaultdict(list)
for node, neighbours in graph.items():
for neighbour in neighbours:
transposed_graph[neighbour].append(node)
# {1: [0], 2: [0, 1], 3: [1]}
$endgroup$
add a comment |
$begingroup$
There's really not much to say about this code, it is straightforward.
Style
These are only nitpicks.
- Generic dictionary keys are typically named
k
instead ofi
orj
, but in a specific application a more descriptive name would be even better. - Collections should be named by their purpose in the application, not their type.
- By convention, assignments and other binary operators should be surrounded by spaces:
a = b
, nota=b
. See PEP 8 for reference, if you're not already aware of it. Following this style guide makes your code easier to read for others.
Code improvements
When iterating over the keys and values of a dictionary at the same time, you can use
for k, v in dic.items():
# ... use k, v ...
instead of
for k in dic:
v = dic[k]
# ...
The nested loop can be transformed to a dictionary comprehension like this:
dic2 = {v: k for k, values in dic.items() for v in values}
You can remember that the order of for
clauses in the comprehension is the same as the order of corresponding nested for
loops.
Potential pitfalls
You should be aware that this transformation from a dictionary of lists to a reverse dictionary only works if all items in the original lists are unique. Counterexample:
>>> dic = {0: [1, 2], 1: [2, 3]}
>>> {v: k for k, values in dic.items() for v in values}
{1: 0, 2: 1, 3: 1} # missing 2: 0
To correct this, the output dictionary should have the same format as the input, namely mapping each of the items in the input lists to a list of corresponding keys.
If the input represents a directed graph (mapping nodes to lists of neighbours), this corresponds to computing the transposed or reversed graph. It can be done by using a collections.defaultdict
. I don't see an easy way to write it as a comprehension in this case.
from collections import defaultdict
graph = {0: [1, 2], 1: [2, 3]}
transposed_graph = defaultdict(list)
for node, neighbours in graph.items():
for neighbour in neighbours:
transposed_graph[neighbour].append(node)
# {1: [0], 2: [0, 1], 3: [1]}
$endgroup$
There's really not much to say about this code, it is straightforward.
Style
These are only nitpicks.
- Generic dictionary keys are typically named
k
instead ofi
orj
, but in a specific application a more descriptive name would be even better. - Collections should be named by their purpose in the application, not their type.
- By convention, assignments and other binary operators should be surrounded by spaces:
a = b
, nota=b
. See PEP 8 for reference, if you're not already aware of it. Following this style guide makes your code easier to read for others.
Code improvements
When iterating over the keys and values of a dictionary at the same time, you can use
for k, v in dic.items():
# ... use k, v ...
instead of
for k in dic:
v = dic[k]
# ...
The nested loop can be transformed to a dictionary comprehension like this:
dic2 = {v: k for k, values in dic.items() for v in values}
You can remember that the order of for
clauses in the comprehension is the same as the order of corresponding nested for
loops.
Potential pitfalls
You should be aware that this transformation from a dictionary of lists to a reverse dictionary only works if all items in the original lists are unique. Counterexample:
>>> dic = {0: [1, 2], 1: [2, 3]}
>>> {v: k for k, values in dic.items() for v in values}
{1: 0, 2: 1, 3: 1} # missing 2: 0
To correct this, the output dictionary should have the same format as the input, namely mapping each of the items in the input lists to a list of corresponding keys.
If the input represents a directed graph (mapping nodes to lists of neighbours), this corresponds to computing the transposed or reversed graph. It can be done by using a collections.defaultdict
. I don't see an easy way to write it as a comprehension in this case.
from collections import defaultdict
graph = {0: [1, 2], 1: [2, 3]}
transposed_graph = defaultdict(list)
for node, neighbours in graph.items():
for neighbour in neighbours:
transposed_graph[neighbour].append(node)
# {1: [0], 2: [0, 1], 3: [1]}
answered 4 hours ago
mkrieger1mkrieger1
1,4131824
1,4131824
add a comment |
add a comment |
Juan C is a new contributor. Be nice, and check out our Code of Conduct.
Juan C is a new contributor. Be nice, and check out our Code of Conduct.
Juan C is a new contributor. Be nice, and check out our Code of Conduct.
Juan C is a new contributor. Be nice, and check out our Code of Conduct.
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