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Can I use list comprehension syntax to create a dictionary?
For example, by iterating over pairs of keys and values:
d = {... for k, v in zip(keys, values)}
Use a dict comprehension (Python 2.7 and later):
{key: value for (key, value) in iterable}
Alternatively for simpler cases or earlier version of Python, use the dict constructor, e.g.:
pairs = [('a', 1), ('b', 2)]
dict(pairs) #=> {'a': 1, 'b': 2}
dict([(k, v+1) for k, v in pairs]) #=> {'a': 2, 'b': 3}
Given separate arrays of keys and values, use the dict constructor with zip:
keys = ['a', 'b']
values = [1, 2]
dict(zip(keys, values)) #=> {'a': 1, 'b': 2}
2) "zip'ped" from two separate iterables of keys/vals
dict(zip(list_of_keys, list_of_values))
In Python 3 and Python 2.7+, dictionary comprehensions look like the below:
d = {k:v for k, v in iterable}
For Python 2.6 or earlier, see fortran's answer.
In fact, you don't even need to iterate over the iterable if it already comprehends some kind of mapping, the dict constructor doing it graciously for you:
>>> ts = [(1, 2), (3, 4), (5, 6)]
>>> dict(ts)
{1: 2, 3: 4, 5: 6}
>>> gen = ((i, i+1) for i in range(1, 6, 2))
>>> gen
<generator object <genexpr> at 0xb7201c5c>
>>> dict(gen)
{1: 2, 3: 4, 5: 6}
Create a dictionary with list comprehension in Python
I like the Python list comprehension syntax.
Can it be used to create dictionaries too? For example, by iterating
over pairs of keys and values:
mydict = {(k,v) for (k,v) in blah blah blah}
You're looking for the phrase "dict comprehension" - it's actually:
mydict = {k: v for k, v in iterable}
Assuming blah blah blah is an iterable of two-tuples - you're so close. Let's create some "blahs" like that:
blahs = [('blah0', 'blah'), ('blah1', 'blah'), ('blah2', 'blah'), ('blah3', 'blah')]
Dict comprehension syntax:
Now the syntax here is the mapping part. What makes this a dict comprehension instead of a set comprehension (which is what your pseudo-code approximates) is the colon, : like below:
mydict = {k: v for k, v in blahs}
And we see that it worked, and should retain insertion order as-of Python 3.7:
>>> mydict
{'blah0': 'blah', 'blah1': 'blah', 'blah2': 'blah', 'blah3': 'blah'}
In Python 2 and up to 3.6, order was not guaranteed:
>>> mydict
{'blah0': 'blah', 'blah1': 'blah', 'blah3': 'blah', 'blah2': 'blah'}
Adding a Filter:
All comprehensions feature a mapping component and a filtering component that you can provide with arbitrary expressions.
So you can add a filter part to the end:
>>> mydict = {k: v for k, v in blahs if not int(k[-1]) % 2}
>>> mydict
{'blah0': 'blah', 'blah2': 'blah'}
Here we are just testing for if the last character is divisible by 2 to filter out data before mapping the keys and values.
In Python 2.7, it goes like:
>>> list1, list2 = ['a', 'b', 'c'], [1,2,3]
>>> dict( zip( list1, list2))
{'a': 1, 'c': 3, 'b': 2}
Zip them!
Python version >= 2.7, do the below:
d = {i: True for i in [1,2,3]}
Python version < 2.7(RIP, 3 July 2010 - 31 December 2019), do the below:
d = dict((i,True) for i in [1,2,3])
To add onto #fortran's answer, if you want to iterate over a list of keys key_list as well as a list of values value_list:
d = dict((key, value) for (key, value) in zip(key_list, value_list))
or
d = {(key, value) for (key, value) in zip(key_list, value_list)}
Just to throw in another example. Imagine you have the following list:
nums = [4,2,2,1,3]
and you want to turn it into a dict where the key is the index and value is the element in the list. You can do so with the following line of code:
{index:nums[index] for index in range(0,len(nums))}
Here is another example of dictionary creation using dict comprehension:
What i am tring to do here is to create a alphabet dictionary where each pair; is the english letter and its corresponding position in english alphabet
>>> import string
>>> dict1 = {value: (int(key) + 1) for key, value in
enumerate(list(string.ascii_lowercase))}
>>> dict1
{'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4, 'g': 7, 'f': 6, 'i': 9, 'h': 8,
'k': 11, 'j': 10, 'm': 13, 'l': 12, 'o': 15, 'n': 14, 'q': 17, 'p': 16, 's':
19, 'r': 18, 'u': 21, 't': 20, 'w': 23, 'v': 22, 'y': 25, 'x': 24, 'z': 26}
>>>
Notice the use of enumerate here to get a list of alphabets and their indexes in the list and swapping the alphabets and indices to generate the key value pair for dictionary
Hope it gives a good idea of dictionary comp to you and encourages you to use it more often to make your code compact
This code will create dictionary using list comprehension for multiple lists with different values that can be used for pd.DataFrame()
#Multiple lists
model=['A', 'B', 'C', 'D']
launched=[1983,1984,1984,1984]
discontinued=[1986, 1985, 1984, 1986]
#Dictionary with list comprehension
keys=['model','launched','discontinued']
vals=[model, launched,discontinued]
data = {key:vals[n] for n, key in enumerate(keys)}
#Convert dict to dataframe
df=pd.DataFrame(data)
display(df)
enumerate will pass n to vals to match each key with its list
Try this,
def get_dic_from_two_lists(keys, values):
return { keys[i] : values[i] for i in range(len(keys)) }
Assume we have two lists country and capital
country = ['India', 'Pakistan', 'China']
capital = ['New Delhi', 'Islamabad', 'Beijing']
Then create dictionary from the two lists:
print get_dic_from_two_lists(country, capital)
The output is like this,
{'Pakistan': 'Islamabad', 'China': 'Beijing', 'India': 'New Delhi'}
Adding to #Ekhtiar answer, if you want to make look up dict from list, you can use this:
names = ['a', 'b', 'd', 'f', 'c']
names_to_id = {v:k for k, v in enumerate(names)}
# {'a': 0, 'b': 1, 'c': 2, 'd': 3, 'f': 4}
Or in rare case that you want to filter duplicate, use set first (best in list of number):
names = ['a', 'b', 'd', 'f', 'd', 'c']
sorted_list = list(set(names))
sorted_list.sort()
names_to_id = {v:k for k, v in enumerate(sorted_list)}
# {'a': 0, 'b': 1, 'c': 2, 'd': 3, 'f': 4}
names = [1,2,5,5,6,2,1]
names_to_id = {v:k for k, v in enumerate(set(names))}
# {1: 0, 2: 1, 5: 2, 6: 3}
>>> {k: v**3 for (k, v) in zip(string.ascii_lowercase, range(26))}
Python supports dict comprehensions, which allow you to express the creation of dictionaries at runtime using a similarly concise syntax.
A dictionary comprehension takes the form {key: value for (key, value) in iterable}. This syntax was introduced in Python 3 and backported as far as Python 2.7, so you should be able to use it regardless of which version of Python you have installed.
A canonical example is taking two lists and creating a dictionary where the item at each position in the first list becomes a key and the item at the corresponding position in the second list becomes the value.
The zip function used inside this comprehension returns an iterator of tuples, where each element in the tuple is taken from the same position in each of the input iterables. In the example above, the returned iterator contains the tuples (“a”, 1), (“b”, 2), etc.
Output:
{'i': 512, 'e': 64, 'o': 2744, 'h': 343, 'l': 1331, 's': 5832, 'b': 1, 'w': 10648, 'c': 8, 'x': 12167, 'y': 13824, 't': 6859, 'p': 3375, 'd': 27, 'j': 729, 'a': 0, 'z': 15625, 'f': 125, 'q': 4096, 'u': 8000, 'n': 2197, 'm': 1728, 'r': 4913, 'k': 1000, 'g': 216, 'v': 9261}
Yes, it's possible. In python, Comprehension can be used in List, Set, Dictionary, etc.
You can write it this way
mydict = {k:v for (k,v) in blah}
Another detailed example of Dictionary Comprehension with the Conditional Statement and Loop:
parents = [father, mother]
parents = {parent:1 - P["mutation"] if parent in two_genes else 0.5 if parent in one_gene else P["mutation"] for parent in parents}
You can create a new dict for each pair and merge it with the previous dict:
reduce(lambda p, q: {**p, **{q[0]: q[1]}}, bla bla bla, {})
Obviously this approaches requires reduce from functools.
Assuming blah blah blah is a two-tuples list:
Let's see two methods:
# method 1
>>> lst = [('a', 2), ('b', 4), ('c', 6)]
>>> dict(lst)
{'a': 2, 'b': 4, 'c': 6}
# method 2
>>> lst = [('a', 2), ('b', 4), ('c', 6)]
>>> d = {k:v for k, v in lst}
>>> d
{'a': 2, 'b': 4, 'c': 6}
this approach uses iteration over the given date using a for loop.
Syntax: {key: value for (key, value) in data}
Eg:
# create a list comprehension with country and code:
Country_code = [('China', 86), ('USA', 1),
('Ghana', 233), ('Uk', 44)]
# use iterable method to show results
{key: value for (key, value) in Country_code}
I have a list of dictionaries, I would like to create a new dictionary where the first key 'value' corresponds to the second value of the 'b' key of each dictionary in the list. The second key 'number' of the new dictionary corresponds to the third (therefore last) value of the 'b' key of each dictionary in the list.
my_list = [
{
'a': (2.6, 0.08, 47.0, 1),
'b': (5.7, 0.05, 1)
},
{
'a': (2.6, 0.08, 47.0, 2),
'b': (5.7, 0.06, 2)
}
]
expected output:
new_dic = {'value': (0.05, 0.06), number = (1, 2)}
you can use comprehension as follows:
new_dict = {}
new_dict['value'] = tuple(val['b'][1] for val in my_list)
new_dict['number'] = tuple(val['b'][2] for val in my_list)
Note that you need to call the tuple constructor, because (val['b'][2] for val in my_list) alone returns a generator object.
I have two multi-index dataframes: mean and std
arrays = [['A', 'A', 'B', 'B'], ['Z', 'Y', 'X', 'W']]
mean=pd.DataFrame(data={0.0:[np.nan,2.0,3.0,4.0], 60.0: [5.0,np.nan,7.0,8.0], 120.0:[9.0,10.0,np.nan,12.0]},
index=pd.MultiIndex.from_arrays(arrays, names=('id', 'comp')))
mean.columns.name='Times'
std=pd.DataFrame(data={0.0:[10.0,10.0,10.0,10.0], 60.0: [10.0,10.0,10.0,10.0], 120.0:[10.0,10.0,10.0,10.0]},
index=pd.MultiIndex.from_arrays(arrays, names=('id', 'comp')))
std.columns.name='Times'
My task is to combine them in a dictionary with '{id:' as first level, followed by second level dictionary with '{comp:' and then for each comp a list of tuples, which combines the (time-points, mean, std). So, the result should look like that:
{'A': {
'Z': [(60.0,5.0,10.0),
(120.0,9.0,10.0)],
'Y': [(0.0,2.0,10.0),
(120.0,10.0,10.0)]
},
'B': {
'X': [(0.0,3.0,10.0),
(60.0,7.0,10.0)],
'W': [(0.0,4.0,10.0),
(60.0,8.0,10.0),
(120.0,12.0,10.0)]
}
}
Additionally, when there is NaN in data, the triplets are left out, so value A,Z at time 0, A,Y at time 60 B,X at time 120.
How do I get there? I constructed already a dict of dict of list of tuples for a single line:
iter=0
{mean.index[iter][0]:{mean.index[iter][1]:list(zip(mean.columns, mean.iloc[iter], std.iloc[iter]))}}
>{'A': {'Z': [(0.0, 1.0, 10.0), (60.0, 5.0, 10.0), (120.0, 9.0, 10.0)]}}
Now, I need to extend to a dictionary with a loop over each line {inner dict) and adding the ids each {outer dict}. I started with iterrows and dic comprehension, but here I have problems, indexing with the iter ('A','Z') which i get from iterrows(), and building the whole dict, iteratively.
{mean.index[iter[1]]:list(zip(mean.columns, mean.loc[iter[1]], std.loc[iter[1]])) for (iter,row) in mean.iterrows()}
creates errors, and I would only have the inner loop
KeyError: 'the label [Z] is not in the [index]'
Thanks!
EDIT: I exchanged the numbers to float in this example, because here integers were generated before which was not consistent with my real data, and which would fail in following json dump.
Here is a solution using a defaultdict:
from collections import defaultdict
mean_as_dict = mean.to_dict(orient='index')
std_as_dict = std.to_dict(orient='index')
mean_clean_sorted = {k: sorted([(i, j) for i, j in v.items()]) for k, v in mean_as_dict.items()}
std_clean_sorted = {k: sorted([(i, j) for i, j in v.items()]) for k, v in std_as_dict.items()}
sol = {k: [j + (std_clean_sorted[k][i][1],) for i, j in enumerate(v) if not np.isnan(j[1])] for k, v in mean_clean_sorted.items()}
solution = defaultdict(dict)
for k, v in sol.items():
solution[k[0]][k[1]] = v
Resulting dict will be defaultdict object that you can change to dict easily:
solution = dict(solution)
con = pd.concat([mean, std])
primary = dict()
for i in set(con.index.values):
if i[0] not in primary.keys():
primary[i[0]] = dict()
primary[i[0]][i[1]] = list()
for x in con.columns:
primary[i[0]][i[1]].append((x, tuple(con.loc[i[0]].loc[i[1][0].values)))
Here is sample output
I found a very comprehensive way of putting up this nested dict:
mean_dict_items=mean.to_dict(orient='index').items()
{k[0]:{u[1]:list(zip(mean.columns, mean.loc[u], std.loc[u]))
for u,v in mean_dict_items if (k[0],u[1]) == u} for k,l in mean_dict_items}
creates:
{'A': {'Y': [(0.0, 2.0, 10.0), (60.0, nan, 10.0), (120.0, 10.0, 10.0)],
'Z': [(0.0, nan, 10.0), (60.0, 5.0, 10.0), (120.0, 9.0, 10.0)]},
'B': {'W': [(0.0, 4.0, 10.0), (60.0, 8.0, 10.0), (120.0, 12.0, 10.0)],
'X': [(0.0, 3.0, 10.0), (60.0, 7.0, 10.0), (120.0, nan, 10.0)]}}
I'm looking to convert lists like:
idx = ['id','m','x','y','z']
a = ['1, 1.0, 1.11, 1.11, 1.11']
b = ['2, 2.0, 2.22, 2.22, 2,22']
c = ['3, 3.0, 3.33, 3.33, 3.33']
d = ['4, 4.0, 4.44, 4.44, 4.44']
e = ['5, 5.0, 5.55, 5.55, 5.55']
Into a dictionary where:
dictlist = {
'id':[1,2,3,4,5],
'm':[1.0,2.0,3.0,4.0,5.0],
'x':[1.11,2.22,3.33,4.44,5.55],
'y':[1.11,2.22,3.33,4.44,5.55],
'z':[1.11,2.22,3.33,4.44,5.55]
}
But I would like to be able to do this for a longer set of lists >> 6 elements per list. So I assume a function would be best to be able to create dict for the len of elements in the idx list.
**Edit:
in response to g.d.d.c:
I had tried something like:
def make_dict(indx):
data=dict()
for item in xrange(0,len(indx)):
data.update({a[item]:''})
return data
data = make_dict(idx)
Which worked for making:
{'id': '', 'm': '', 'x': '', 'y': '', 'z': ''}
but then adding each value to the dictionary became an issue.
result = {}
keys = idx
lists = [a, b, c, d, e]
for index, key in enumerate(keys):
result[key] = []
for l in lists:
result[key].append(l[index])
As a single comprehension
Start by grouping your lists {a,b,c,d,e,...} into a list of lists
dataset = [a,b,c,d,e]
idx = ['id','m','x','y','z']
d = { k: [v[i] for v in dataset] for i,k in enumerate(idx) }
The last line builds a dictionary by enumerating over idx using the value for the dict key, and its index to pick out the correct column of each data sample.
The comprehension will work regardless of the number of fields, as long as each list has the same length as idx
You can try this:
idx = ['id','m','x','y','z']
a = [1, 1.0, 1.11, 1.11, 1.11]
b = [2, 2.0, 2.22, 2.22, 2,22]
c = [3, 3.0, 3.33, 3.33, 3.33]
d = [4, 4.0, 4.44, 4.44, 4.44]
e = [5, 5.0, 5.55, 5.55, 5.55]
dictlist = {x[0] : list(x[1:]) for x in zip(idx,a,b,c,d,e)}
print dictlist
answer = {}
for key, a,b,c,d,e in zip(idx, map(lambda s:[float(i) for i in s.split(',')], [a,b,c,d,e])):
answer[key] = [a,b,c,d,e]
I have two lists that are of the same length:
alist = ['XX', 'HH', 'GG', 'XX', 'II', 'PP', 'LL', 'TT', 'KK', 'XX']
blist = [2, 3, 5, 5, 9, 8, 9, 4, 7, 2]
I want to know what values in alist have the same number in blist. I want the outcome to look like this:
2 = XX; 3 = HH; 5 = GG, XX; 9 = II, LL; 8 = PP; 4 = TT; 7 = KK
I solved it like this:
from collections import defaultdict
adict = {}
a = zip(blist, alist)
for key, value in a:
adict.setdefault(k, []).append(v)
which gives this result:
adict:
{2: ['XX', 'XX'], 3: ['HH'], 4: ['TT'], 5: ['GG', 'XX'], 7: ['KK'], 8: ['PP'], 9: ['II', 'LL']}
but I dont want the same value twice, for example 2: ['XX', 'XX'] - I would like to have instead 2: ['XX'].
I tried this using 'set' before the list of values:
a = zip(blist, alist)
for key, value in a:
a.setdefault(k, set[]).append(v)
but it complained...
any ideas?
I'd personally use Martijn's defaultdict approach, but I thought I'd address the issues with your current attempt.
The problem with your code:
a = zip(blist, alist)
for key, value in a:
a.setdefault(k, set[]).append(v)
Is That:
after the zip, a is now a list, so it won't support .setdefault
k is not used in the for loop - it should be key
v is not used in the for loop = it should be value
set[] is invalid synatx - to create a new set - use set()
A set does not have an .append - instead you want to use add
Corrected code:
d = {}
a = zip(blist, alist)
for key, value in a:
d.setdefault(key, set()).add(value)
Adapt the following as desired to print:
for k, v in d.iteritems():
if k > 5:
print '{0}: {1}'.format(k, ','.join(v))
Use the defaultdict type you imported but otherwise ignore:
from collections import defaultdict
a = defaultdict(set)
for k, v in zip(blist, alist):
a[k].add(v)
results in:
>>> a
defaultdict(<type 'set'>, {2: set(['XX']), 3: set(['HH']), 4: set(['TT']), 5: set(['GG', 'XX']), 7: set(['KK']), 8: set(['PP']), 9: set(['II', 'LL'])})
defaultdict is a subclass of dict and behaves in the same way otherwise.
Use your code and then add:
a = {x: set(a[x]) for x in a }