I currently have the following:
mydict = {'a': [1, 2, 3], 'b': [1, 2]}
I want to return a string containing quantities of items available in the dictionary. For example
a: 3
b: 2
However, I want my output to update if I add another key value pair to the dictionary. For example mydict['c'] = [1, 2, 3]
I have thought about how to do this and this is all that comes to mind:
def quantities() -> str:
mydict = {'a': [1, 2, 3], 'b': [1, 2]}
for k, v in mydict:
print(f'{k}: {len(v)})
But I am not sure if this is correct. Are there any other ways to do this.
The statement:
for <variable> in mydict:
Iterates through only the keys of the dictionary. So, you can either use the key to get the item like:
mydict = {'a': [1, 2, 3], 'b': [1, 2]}
for k in mydict:
print(f'{k}: {len(mydict[k])}')
Or use mydict.items() This makes it iterate through every (key, value). USe it as:
mydict = {'a': [1, 2, 3], 'b': [1, 2]}
for k, v in mydict.items():
print(f'{k}: {len(v)}')
I don't think your sample code will work. I used this documentation and use sorted() I think what you want is something like this.
mydict = {'a': [1, 2, 3, 4], 'b': [1, 2]}
def quantities():
for k, v in sorted(mydict.items()):
print(k, len(v))
quantities()
You can do this with str.join and a generator expression:
def quantities(mydict):
return '\n'.join('{}: {}'.format(k, len(v)) for k, v in mydict.items())
Let's say I have a dictionary containing multiple lists of different sizes, how would I split the dictionary into 4 dictionaries of equal length based on the length of the lists. Is there a simple way of doing this?
dict = {"A":[1,2,3,4,5], "B":[1,2,3], "C":[1,2,3,4,5,6,7,8]}
How would I split this into 4 dictionaries of the same length so that I get the result of:
dict1 = {"A":[1,2,3,4]}
dict2 = {"A":[5], "B":[1,2,3]}
dict3 = {"C":[1,2,3,4]}
dict4 = {"C":[5,6,7,8]}
Edit: if it couldn't be split evenly then one of the dictionaries would end up being slightly longer than the others.
Here is a way to do it, using a generator to yield the successive key-value pairs:
data = {"A":[1,2,3,4,5], "B":[1,2,3], "C":[1,2,3,4,5,6,7,8]}
def key_value_gen(data):
# will yield ('A', 1), ('A', 2), .... ('C', 8)
for key, values in data.items():
for value in values:
yield key, value
out = []
size = 4
for index, (key, value) in enumerate(key_value_gen(data)):
# if the index is a multiple of size, we add a new dict
if index % size == 0:
out.append({})
out[-1].setdefault(key, []).append(value)
print(out)
# [{'A': [1, 2, 3, 4]}, {'A': [5], 'B': [1, 2, 3]}, {'C': [1, 2, 3, 4]}, {'C': [5, 6, 7, 8]}]
Another way with just an iterative approach:
def group_by_count(dic, size):
output, temp, count = [], {}, 0
for k, v in dic.items():
for x in v:
if count == size:
output.append(temp)
temp, count = {}, 0
temp[k] = temp.get(k, []) + [x]
count += 1
if temp:
output.append(temp)
return output
d = {"A":[1,2,3,4,5], "B":[1,2,3], "C":[1,2,3,4,5,6,7,8]}
output = group_by_count(d, 4)
for dic in output:
print(dic)
Output:
{'A': [1, 2, 3, 4]}
{'A': [5], 'B': [1, 2, 3]}
{'C': [1, 2, 3, 4]}
{'C': [5, 6, 7, 8]}
What is the pythonic way to iterate over a dictionary with a setup like this:
dict = {'a': [1, 2, 3], 'b': [3, 4, 5], 'c': 6}
if I only wanted to iterate a for loop over all the values in a and b and skip c. There's obviously a million ways to solve this but I'd prefer to avoid something like:
for each in dict['a']:
# do something
pass
for each in dict['b']:
# do something
pass
of something destructive like:
del dict['c']
for k,v in dict.iteritems():
pass
The more generic way is using filter-like approaches by putting an if in the end of a generator expression.
If you want to iterate over every iterable value, filter with hasattr:
for key in (k for k in dict if hasattr(dict[k], '__iter__')):
for item in dict[key]:
print(item)
If you want to exclude some keys, use a "not in" filter:
invalid = set(['c', 'd'])
for key in (k for k in dict if key not in invalid):
....
If you want to select only specific keys, use a "in" filter:
valid = set(['a', 'b'])
for key in (k for k in dict if key in valid):
....
Similar to SSDMS's solution you can also just do:
mydict = {'a': [1, 2, 3], 'b': [3, 4, 5], 'c': 6}
for each in mydict['a']+mydict['b']:
....
You can use chain from the itertools module to do this:
In [29]: from itertools import chain
In [30]: mydict = {'a': [1, 2, 3], 'b': [3, 4, 5], 'c': 6}
In [31]: for item in chain(mydict['a'], mydict['b']):
...: print(item)
...:
1
2
3
3
4
5
To iterate over only the values the keys' value in the dictionary that are instance of list simply use chain.from_iterable.
wanted_key = ['a', 'b']
for item in chain.from_iterable(mydict[key] for key in wanted_key if isinstance(mydict[key], list)):
# do something with the item
This question already has answers here:
How to merge dicts, collecting values from matching keys?
(17 answers)
Closed 12 days ago.
Given n dictionaries, write a function that will return a unique dictionary with a list of values for duplicate keys.
Example:
d1 = {'a': 1, 'b': 2}
d2 = {'c': 3, 'b': 4}
d3 = {'a': 5, 'd': 6}
result:
>>> newdict
{'c': 3, 'd': 6, 'a': [1, 5], 'b': [2, 4]}
My code so far:
>>> def merge_dicts(*dicts):
... x = []
... for item in dicts:
... x.append(item)
... return x
...
>>> merge_dicts(d1, d2, d3)
[{'a': 1, 'b': 2}, {'c': 3, 'b': 4}, {'a': 5, 'd': 6}]
What would be the best way to produce a new dictionary that yields a list of values for those duplicate keys?
Python provides a simple and fast solution to this: the defaultdict in the collections module. From the examples in the documentation:
Using list as the default_factory, it is easy to group a sequence of
key-value pairs into a dictionary of lists:
>>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
>>> d = defaultdict(list)
>>> for k, v in s:
... d[k].append(v)
...
>>> d.items()
[('blue', [2, 4]), ('red', 1), ('yellow', [1, 3])]
When each key is encountered for the first time, it is not already in
the mapping; so an entry is automatically created using the
default_factory function which returns an empty list. The
list.append() operation then attaches the value to the new list. When
keys are encountered again, the look-up proceeds normally (returning
the list for that key) and the list.append() operation adds another
value to the list.
In your case, that would be roughly:
import collections
def merge_dicts(*dicts):
res = collections.defaultdict(list)
for d in dicts:
for k, v in d.iteritems():
res[k].append(v)
return res
>>> merge_dicts(d1, d2, d3)
defaultdict(<type 'list'>, {'a': [1, 5], 'c': [3], 'b': [2, 4], 'd': [6]})
def merge_dicts(*dicts):
d = {}
for dict in dicts:
for key in dict:
try:
d[key].append(dict[key])
except KeyError:
d[key] = [dict[key]]
return d
This retuns:
{'a': [1, 5], 'b': [2, 4], 'c': [3], 'd': [6]}
There is a slight difference to the question. Here all dictionary values are lists. If that is not to be desired for lists of length 1, then add:
for key in d:
if len(d[key]) == 1:
d[key] = d[key][0]
before the return d statement. However, I cannot really imagine when you would want to remove the list. (Consider the situation where you have lists as values; then removing the list around the items leads to ambiguous situations.)
I want to change back and forth between a dictionary of (equal-length) lists:
DL = {'a': [0, 1], 'b': [2, 3]}
and a list of dictionaries:
LD = [{'a': 0, 'b': 2}, {'a': 1, 'b': 3}]
For those of you that enjoy clever/hacky one-liners.
Here is DL to LD:
v = [dict(zip(DL,t)) for t in zip(*DL.values())]
print(v)
and LD to DL:
v = {k: [dic[k] for dic in LD] for k in LD[0]}
print(v)
LD to DL is a little hackier since you are assuming that the keys are the same in each dict. Also, please note that I do not condone the use of such code in any kind of real system.
If you're allowed to use outside packages, Pandas works great for this:
import pandas as pd
pd.DataFrame(DL).to_dict(orient="records")
Which outputs:
[{'a': 0, 'b': 2}, {'a': 1, 'b': 3}]
You can also use orient="list" to get back the original structure
{'a': [0, 1], 'b': [2, 3]}
Perhaps consider using numpy:
import numpy as np
arr = np.array([(0, 2), (1, 3)], dtype=[('a', int), ('b', int)])
print(arr)
# [(0, 2) (1, 3)]
Here we access columns indexed by names, e.g. 'a', or 'b' (sort of like DL):
print(arr['a'])
# [0 1]
Here we access rows by integer index (sort of like LD):
print(arr[0])
# (0, 2)
Each value in the row can be accessed by column name (sort of like LD):
print(arr[0]['b'])
# 2
To go from the list of dictionaries, it is straightforward:
You can use this form:
DL={'a':[0,1],'b':[2,3], 'c':[4,5]}
LD=[{'a':0,'b':2, 'c':4},{'a':1,'b':3, 'c':5}]
nd={}
for d in LD:
for k,v in d.items():
try:
nd[k].append(v)
except KeyError:
nd[k]=[v]
print nd
#{'a': [0, 1], 'c': [4, 5], 'b': [2, 3]}
Or use defaultdict:
nd=cl.defaultdict(list)
for d in LD:
for key,val in d.items():
nd[key].append(val)
print dict(nd.items())
#{'a': [0, 1], 'c': [4, 5], 'b': [2, 3]}
Going the other way is problematic. You need to have some information of the insertion order into the list from keys from the dictionary. Recall that the order of keys in a dict is not necessarily the same as the original insertion order.
For giggles, assume the insertion order is based on sorted keys. You can then do it this way:
nl=[]
nl_index=[]
for k in sorted(DL.keys()):
nl.append({k:[]})
nl_index.append(k)
for key,l in DL.items():
for item in l:
nl[nl_index.index(key)][key].append(item)
print nl
#[{'a': [0, 1]}, {'b': [2, 3]}, {'c': [4, 5]}]
If your question was based on curiosity, there is your answer. If you have a real-world problem, let me suggest you rethink your data structures. Neither of these seems to be a very scalable solution.
Here are the one-line solutions (spread out over multiple lines for readability) that I came up with:
if dl is your original dict of lists:
dl = {"a":[0, 1],"b":[2, 3]}
Then here's how to convert it to a list of dicts:
ld = [{key:value[index] for key,value in dl.items()}
for index in range(max(map(len,dl.values())))]
Which, if you assume that all your lists are the same length, you can simplify and gain a performance increase by going to:
ld = [{key:value[index] for key, value in dl.items()}
for index in range(len(dl.values()[0]))]
Here's how to convert that back into a dict of lists:
dl2 = {key:[item[key] for item in ld]
for key in list(functools.reduce(
lambda x, y: x.union(y),
(set(dicts.keys()) for dicts in ld)
))
}
If you're using Python 2 instead of Python 3, you can just use reduce instead of functools.reduce there.
You can simplify this if you assume that all the dicts in your list will have the same keys:
dl2 = {key:[item[key] for item in ld] for key in ld[0].keys() }
cytoolz.dicttoolz.merge_with
Docs
from cytoolz.dicttoolz import merge_with
merge_with(list, *LD)
{'a': [0, 1], 'b': [2, 3]}
Non-cython version
Docs
from toolz.dicttoolz import merge_with
merge_with(list, *LD)
{'a': [0, 1], 'b': [2, 3]}
The python module of pandas can give you an easy-understanding solution. As a complement to #chiang's answer, the solutions of both D-to-L and L-to-D are as follows:
import pandas as pd
DL = {'a': [0, 1], 'b': [2, 3]}
out1 = pd.DataFrame(DL).to_dict('records')
Output:
[{'a': 0, 'b': 2}, {'a': 1, 'b': 3}]
In the other direction:
LD = [{'a': 0, 'b': 2}, {'a': 1, 'b': 3}]
out2 = pd.DataFrame(LD).to_dict('list')
Output:
{'a': [0, 1], 'b': [2, 3]}
Cleanest way I can think of a summer friday. As a bonus, it supports lists of different lengths (but in this case, DLtoLD(LDtoDL(l)) is no more identity).
From list to dict
Actually less clean than #dwerk's defaultdict version.
def LDtoDL (l) :
result = {}
for d in l :
for k, v in d.items() :
result[k] = result.get(k,[]) + [v] #inefficient
return result
From dict to list
def DLtoLD (d) :
if not d :
return []
#reserve as much *distinct* dicts as the longest sequence
result = [{} for i in range(max (map (len, d.values())))]
#fill each dict, one key at a time
for k, seq in d.items() :
for oneDict, oneValue in zip(result, seq) :
oneDict[k] = oneValue
return result
I needed such a method which works for lists of different lengths (so this is a generalization of the original question). Since I did not find any code here that the way that I expected, here's my code which works for me:
def dict_of_lists_to_list_of_dicts(dict_of_lists: Dict[S, List[T]]) -> List[Dict[S, T]]:
keys = list(dict_of_lists.keys())
list_of_values = [dict_of_lists[key] for key in keys]
product = list(itertools.product(*list_of_values))
return [dict(zip(keys, product_elem)) for product_elem in product]
Examples:
>>> dict_of_lists_to_list_of_dicts({1: [3], 2: [4, 5]})
[{1: 3, 2: 4}, {1: 3, 2: 5}]
>>> dict_of_lists_to_list_of_dicts({1: [3, 4], 2: [5]})
[{1: 3, 2: 5}, {1: 4, 2: 5}]
>>> dict_of_lists_to_list_of_dicts({1: [3, 4], 2: [5, 6]})
[{1: 3, 2: 5}, {1: 3, 2: 6}, {1: 4, 2: 5}, {1: 4, 2: 6}]
>>> dict_of_lists_to_list_of_dicts({1: [3, 4], 2: [5, 6], 7: [8, 9, 10]})
[{1: 3, 2: 5, 7: 8},
{1: 3, 2: 5, 7: 9},
{1: 3, 2: 5, 7: 10},
{1: 3, 2: 6, 7: 8},
{1: 3, 2: 6, 7: 9},
{1: 3, 2: 6, 7: 10},
{1: 4, 2: 5, 7: 8},
{1: 4, 2: 5, 7: 9},
{1: 4, 2: 5, 7: 10},
{1: 4, 2: 6, 7: 8},
{1: 4, 2: 6, 7: 9},
{1: 4, 2: 6, 7: 10}]
Here my small script :
a = {'a': [0, 1], 'b': [2, 3]}
elem = {}
result = []
for i in a['a']: # (1)
for key, value in a.items():
elem[key] = value[i]
result.append(elem)
elem = {}
print result
I'm not sure that is the beautiful way.
(1) You suppose that you have the same length for the lists
Here is a solution without any libraries used:
def dl_to_ld(initial):
finalList = []
neededLen = 0
for key in initial:
if(len(initial[key]) > neededLen):
neededLen = len(initial[key])
for i in range(neededLen):
finalList.append({})
for i in range(len(finalList)):
for key in initial:
try:
finalList[i][key] = initial[key][i]
except:
pass
return finalList
You can call it as follows:
dl = {'a':[0,1],'b':[2,3]}
print(dl_to_ld(dl))
#[{'a': 0, 'b': 2}, {'a': 1, 'b': 3}]
If you don't mind a generator, you can use something like
def f(dl):
l = list((k,v.__iter__()) for k,v in dl.items())
while True:
d = dict((k,i.next()) for k,i in l)
if not d:
break
yield d
It's not as "clean" as it could be for Technical Reasons: My original implementation did yield dict(...), but this ends up being the empty dictionary because (in Python 2.5) a for b in c does not distinguish between a StopIteration exception when iterating over c and a StopIteration exception when evaluating a.
On the other hand, I can't work out what you're actually trying to do; it might be more sensible to design a data structure that meets your requirements instead of trying to shoehorn it in to the existing data structures. (For example, a list of dicts is a poor way to represent the result of a database query.)
List of dicts ⟶ dict of lists
from collections import defaultdict
from typing import TypeVar
K = TypeVar("K")
V = TypeVar("V")
def ld_to_dl(ld: list[dict[K, V]]) -> dict[K, list[V]]:
dl = defaultdict(list)
for d in ld:
for k, v in d.items():
dl[k].append(v)
return dl
defaultdict creates an empty list if one does not exist upon key access.
Dict of lists ⟶ list of dicts
Collecting into "jagged" dictionaries
from typing import TypeVar
K = TypeVar("K")
V = TypeVar("V")
def dl_to_ld(dl: dict[K, list[V]]) -> list[dict[K, V]]:
ld = []
for k, vs in dl.items():
ld += [{} for _ in range(len(vs) - len(ld))]
for i, v in enumerate(vs):
ld[i][k] = v
return ld
This generates a list of dictionaries ld that may be missing items if the lengths of the lists in dl are unequal. It loops over all key-values in dl, and creates empty dictionaries if ld does not have enough.
Collecting into "complete" dictionaries only
(Usually intended only for equal-length lists.)
from typing import TypeVar
K = TypeVar("K")
V = TypeVar("V")
def dl_to_ld(dl: dict[K, list[V]]) -> list[dict[K, V]]:
ld = [dict(zip(dl.keys(), v)) for v in zip(*dl.values())]
return ld
This generates a list of dictionaries ld that have the length of the smallest list in dl.
DL={'a':[0,1,2,3],'b':[2,3,4,5]}
LD=[{'a':0,'b':2},{'a':1,'b':3}]
Empty_list = []
Empty_dict = {}
# to find length of list in values of dictionry
len_list = 0
for i in DL.values():
if len_list < len(i):
len_list = len(i)
for k in range(len_list):
for i,j in DL.items():
Empty_dict[i] = j[k]
Empty_list.append(Empty_dict)
Empty_dict = {}
LD = Empty_list