Convert a sequence of sequences to a dictionary and vice-versa - python

One way to manually persist a dictionary to a database is to flatten it into a sequence of sequences and pass the sequence as an argument to cursor.executemany().
The opposite is also useful, i.e. reading rows from a database and turning them into dictionaries for later use.
What's the best way to go from myseq to mydict and from mydict to myseq?
>>> myseq = ((0,1,2,3), (4,5,6,7), (8,9,10,11))
>>> mydict = {0: (1, 2, 3), 8: (9, 10, 11), 4: (5, 6, 7)}

mydict = dict((s[0], s[1:]) for s in myseq)
myseq = tuple(sorted((k,) + v for k, v in mydict.iteritems()))

>>> mydict = dict((t[0], t[1:]) for t in myseq))
>>> myseq = tuple(((key,) + values) for (key, values) in mydict.items())
The ordering of tuples in myseq is not preserved, since dictionaries are unordered.

Related

How is it that "max(List, key = List.get)" manages to return the correct value? [duplicate]

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I have a dictionary of values read from two fields in a database: a string field and a numeric field. The string field is unique, so that is the key of the dictionary.
I can sort on the keys, but how can I sort based on the values?
Note: I have read Stack Overflow question here How do I sort a list of dictionaries by a value of the dictionary? and probably could change my code to have a list of dictionaries, but since I do not really need a list of dictionaries I wanted to know if there is a simpler solution to sort either in ascending or descending order.
Python 3.7+ or CPython 3.6
Dicts preserve insertion order in Python 3.7+. Same in CPython 3.6, but it's an implementation detail.
>>> x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
>>> {k: v for k, v in sorted(x.items(), key=lambda item: item[1])}
{0: 0, 2: 1, 1: 2, 4: 3, 3: 4}
or
>>> dict(sorted(x.items(), key=lambda item: item[1]))
{0: 0, 2: 1, 1: 2, 4: 3, 3: 4}
Older Python
It is not possible to sort a dictionary, only to get a representation of a dictionary that is sorted. Dictionaries are inherently orderless, but other types, such as lists and tuples, are not. So you need an ordered data type to represent sorted values, which will be a list—probably a list of tuples.
For instance,
import operator
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=operator.itemgetter(1))
sorted_x will be a list of tuples sorted by the second element in each tuple. dict(sorted_x) == x.
And for those wishing to sort on keys instead of values:
import operator
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=operator.itemgetter(0))
In Python3 since unpacking is not allowed we can use
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=lambda kv: kv[1])
If you want the output as a dict, you can use collections.OrderedDict:
import collections
sorted_dict = collections.OrderedDict(sorted_x)
As simple as: sorted(dict1, key=dict1.get)
Well, it is actually possible to do a "sort by dictionary values". Recently I had to do that in a Code Golf (Stack Overflow question Code golf: Word frequency chart). Abridged, the problem was of the kind: given a text, count how often each word is encountered and display a list of the top words, sorted by decreasing frequency.
If you construct a dictionary with the words as keys and the number of occurrences of each word as value, simplified here as:
from collections import defaultdict
d = defaultdict(int)
for w in text.split():
d[w] += 1
then you can get a list of the words, ordered by frequency of use with sorted(d, key=d.get) - the sort iterates over the dictionary keys, using the number of word occurrences as a sort key .
for w in sorted(d, key=d.get, reverse=True):
print(w, d[w])
I am writing this detailed explanation to illustrate what people often mean by "I can easily sort a dictionary by key, but how do I sort by value" - and I think the original post was trying to address such an issue. And the solution is to do sort of list of the keys, based on the values, as shown above.
You could use:
sorted(d.items(), key=lambda x: x[1])
This will sort the dictionary by the values of each entry within the dictionary from smallest to largest.
To sort it in descending order just add reverse=True:
sorted(d.items(), key=lambda x: x[1], reverse=True)
Input:
d = {'one':1,'three':3,'five':5,'two':2,'four':4}
a = sorted(d.items(), key=lambda x: x[1])
print(a)
Output:
[('one', 1), ('two', 2), ('three', 3), ('four', 4), ('five', 5)]
Dicts can't be sorted, but you can build a sorted list from them.
A sorted list of dict values:
sorted(d.values())
A list of (key, value) pairs, sorted by value:
from operator import itemgetter
sorted(d.items(), key=itemgetter(1))
In recent Python 2.7, we have the new OrderedDict type, which remembers the order in which the items were added.
>>> d = {"third": 3, "first": 1, "fourth": 4, "second": 2}
>>> for k, v in d.items():
... print "%s: %s" % (k, v)
...
second: 2
fourth: 4
third: 3
first: 1
>>> d
{'second': 2, 'fourth': 4, 'third': 3, 'first': 1}
To make a new ordered dictionary from the original, sorting by the values:
>>> from collections import OrderedDict
>>> d_sorted_by_value = OrderedDict(sorted(d.items(), key=lambda x: x[1]))
The OrderedDict behaves like a normal dict:
>>> for k, v in d_sorted_by_value.items():
... print "%s: %s" % (k, v)
...
first: 1
second: 2
third: 3
fourth: 4
>>> d_sorted_by_value
OrderedDict([('first': 1), ('second': 2), ('third': 3), ('fourth': 4)])
Using Python 3.5
Whilst I found the accepted answer useful, I was also surprised that it hasn't been updated to reference OrderedDict from the standard library collections module as a viable, modern alternative - designed to solve exactly this type of problem.
from operator import itemgetter
from collections import OrderedDict
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = OrderedDict(sorted(x.items(), key=itemgetter(1)))
# OrderedDict([(0, 0), (2, 1), (1, 2), (4, 3), (3, 4)])
The official OrderedDict documentation offers a very similar example too, but using a lambda for the sort function:
# regular unsorted dictionary
d = {'banana': 3, 'apple':4, 'pear': 1, 'orange': 2}
# dictionary sorted by value
OrderedDict(sorted(d.items(), key=lambda t: t[1]))
# OrderedDict([('pear', 1), ('orange', 2), ('banana', 3), ('apple', 4)])
Pretty much the same as Hank Gay's answer:
sorted([(value,key) for (key,value) in mydict.items()])
Or optimized slightly as suggested by John Fouhy:
sorted((value,key) for (key,value) in mydict.items())
As of Python 3.6 the built-in dict will be ordered
Good news, so the OP's original use case of mapping pairs retrieved from a database with unique string ids as keys and numeric values as values into a built-in Python v3.6+ dict, should now respect the insert order.
If say the resulting two column table expressions from a database query like:
SELECT a_key, a_value FROM a_table ORDER BY a_value;
would be stored in two Python tuples, k_seq and v_seq (aligned by numerical index and with the same length of course), then:
k_seq = ('foo', 'bar', 'baz')
v_seq = (0, 1, 42)
ordered_map = dict(zip(k_seq, v_seq))
Allow to output later as:
for k, v in ordered_map.items():
print(k, v)
yielding in this case (for the new Python 3.6+ built-in dict!):
foo 0
bar 1
baz 42
in the same ordering per value of v.
Where in the Python 3.5 install on my machine it currently yields:
bar 1
foo 0
baz 42
Details:
As proposed in 2012 by Raymond Hettinger (cf. mail on python-dev with subject "More compact dictionaries with faster iteration") and now (in 2016) announced in a mail by Victor Stinner to python-dev with subject "Python 3.6 dict becomes compact and gets a private version; and keywords become ordered" due to the fix/implementation of issue 27350 "Compact and ordered dict" in Python 3.6 we will now be able, to use a built-in dict to maintain insert order!!
Hopefully this will lead to a thin layer OrderedDict implementation as a first step. As #JimFasarakis-Hilliard indicated, some see use cases for the OrderedDict type also in the future. I think the Python community at large will carefully inspect, if this will stand the test of time, and what the next steps will be.
Time to rethink our coding habits to not miss the possibilities opened by stable ordering of:
Keyword arguments and
(intermediate) dict storage
The first because it eases dispatch in the implementation of functions and methods in some cases.
The second as it encourages to more easily use dicts as intermediate storage in processing pipelines.
Raymond Hettinger kindly provided documentation explaining "The Tech Behind Python 3.6 Dictionaries" - from his San Francisco Python Meetup Group presentation 2016-DEC-08.
And maybe quite some Stack Overflow high decorated question and answer pages will receive variants of this information and many high quality answers will require a per version update too.
Caveat Emptor (but also see below update 2017-12-15):
As #ajcr rightfully notes: "The order-preserving aspect of this new implementation is considered an implementation detail and should not be relied upon." (from the whatsnew36) not nit picking, but the citation was cut a bit pessimistic ;-). It continues as " (this may change in the future, but it is desired to have this new dict implementation in the language for a few releases before changing the language spec to mandate order-preserving semantics for all current and future Python implementations; this also helps preserve backwards-compatibility with older versions of the language where random iteration order is still in effect, e.g. Python 3.5)."
So as in some human languages (e.g. German), usage shapes the language, and the will now has been declared ... in whatsnew36.
Update 2017-12-15:
In a mail to the python-dev list, Guido van Rossum declared:
Make it so. "Dict keeps insertion order" is the ruling. Thanks!
So, the version 3.6 CPython side-effect of dict insertion ordering is now becoming part of the language spec (and not anymore only an implementation detail). That mail thread also surfaced some distinguishing design goals for collections.OrderedDict as reminded by Raymond Hettinger during discussion.
It can often be very handy to use namedtuple. For example, you have a dictionary of 'name' as keys and 'score' as values and you want to sort on 'score':
import collections
Player = collections.namedtuple('Player', 'score name')
d = {'John':5, 'Alex':10, 'Richard': 7}
sorting with lowest score first:
worst = sorted(Player(v,k) for (k,v) in d.items())
sorting with highest score first:
best = sorted([Player(v,k) for (k,v) in d.items()], reverse=True)
Now you can get the name and score of, let's say the second-best player (index=1) very Pythonically like this:
player = best[1]
player.name
'Richard'
player.score
7
I had the same problem, and I solved it like this:
WantedOutput = sorted(MyDict, key=lambda x : MyDict[x])
(People who answer "It is not possible to sort a dict" did not read the question! In fact, "I can sort on the keys, but how can I sort based on the values?" clearly means that he wants a list of the keys sorted according to the value of their values.)
Please notice that the order is not well defined (keys with the same value will be in an arbitrary order in the output list).
If values are numeric you may also use Counter from collections.
from collections import Counter
x = {'hello': 1, 'python': 5, 'world': 3}
c = Counter(x)
print(c.most_common())
>> [('python', 5), ('world', 3), ('hello', 1)]
Starting from Python 3.6, dict objects are now ordered by insertion order. It's officially in the specifications of Python 3.7.
>>> words = {"python": 2, "blah": 4, "alice": 3}
>>> dict(sorted(words.items(), key=lambda x: x[1]))
{'python': 2, 'alice': 3, 'blah': 4}
Before that, you had to use OrderedDict.
Python 3.7 documentation says:
Changed in version 3.7: Dictionary order is guaranteed to be insertion
order. This behavior was implementation detail of CPython from 3.6.
In Python 2.7, simply do:
from collections import OrderedDict
# regular unsorted dictionary
d = {'banana': 3, 'apple':4, 'pear': 1, 'orange': 2}
# dictionary sorted by key
OrderedDict(sorted(d.items(), key=lambda t: t[0]))
OrderedDict([('apple', 4), ('banana', 3), ('orange', 2), ('pear', 1)])
# dictionary sorted by value
OrderedDict(sorted(d.items(), key=lambda t: t[1]))
OrderedDict([('pear', 1), ('orange', 2), ('banana', 3), ('apple', 4)])
copy-paste from : http://docs.python.org/dev/library/collections.html#ordereddict-examples-and-recipes
Enjoy ;-)
This is the code:
import operator
origin_list = [
{"name": "foo", "rank": 0, "rofl": 20000},
{"name": "Silly", "rank": 15, "rofl": 1000},
{"name": "Baa", "rank": 300, "rofl": 20},
{"name": "Zoo", "rank": 10, "rofl": 200},
{"name": "Penguin", "rank": -1, "rofl": 10000}
]
print ">> Original >>"
for foo in origin_list:
print foo
print "\n>> Rofl sort >>"
for foo in sorted(origin_list, key=operator.itemgetter("rofl")):
print foo
print "\n>> Rank sort >>"
for foo in sorted(origin_list, key=operator.itemgetter("rank")):
print foo
Here are the results:
Original
{'name': 'foo', 'rank': 0, 'rofl': 20000}
{'name': 'Silly', 'rank': 15, 'rofl': 1000}
{'name': 'Baa', 'rank': 300, 'rofl': 20}
{'name': 'Zoo', 'rank': 10, 'rofl': 200}
{'name': 'Penguin', 'rank': -1, 'rofl': 10000}
Rofl
{'name': 'Baa', 'rank': 300, 'rofl': 20}
{'name': 'Zoo', 'rank': 10, 'rofl': 200}
{'name': 'Silly', 'rank': 15, 'rofl': 1000}
{'name': 'Penguin', 'rank': -1, 'rofl': 10000}
{'name': 'foo', 'rank': 0, 'rofl': 20000}
Rank
{'name': 'Penguin', 'rank': -1, 'rofl': 10000}
{'name': 'foo', 'rank': 0, 'rofl': 20000}
{'name': 'Zoo', 'rank': 10, 'rofl': 200}
{'name': 'Silly', 'rank': 15, 'rofl': 1000}
{'name': 'Baa', 'rank': 300, 'rofl': 20}
Try the following approach. Let us define a dictionary called mydict with the following data:
mydict = {'carl':40,
'alan':2,
'bob':1,
'danny':3}
If one wanted to sort the dictionary by keys, one could do something like:
for key in sorted(mydict.iterkeys()):
print "%s: %s" % (key, mydict[key])
This should return the following output:
alan: 2
bob: 1
carl: 40
danny: 3
On the other hand, if one wanted to sort a dictionary by value (as is asked in the question), one could do the following:
for key, value in sorted(mydict.iteritems(), key=lambda (k,v): (v,k)):
print "%s: %s" % (key, value)
The result of this command (sorting the dictionary by value) should return the following:
bob: 1
alan: 2
danny: 3
carl: 40
You can create an "inverted index", also
from collections import defaultdict
inverse= defaultdict( list )
for k, v in originalDict.items():
inverse[v].append( k )
Now your inverse has the values; each value has a list of applicable keys.
for k in sorted(inverse):
print k, inverse[k]
You can use the collections.Counter. Note, this will work for both numeric and non-numeric values.
>>> x = {1: 2, 3: 4, 4:3, 2:1, 0:0}
>>> from collections import Counter
>>> #To sort in reverse order
>>> Counter(x).most_common()
[(3, 4), (4, 3), (1, 2), (2, 1), (0, 0)]
>>> #To sort in ascending order
>>> Counter(x).most_common()[::-1]
[(0, 0), (2, 1), (1, 2), (4, 3), (3, 4)]
>>> #To get a dictionary sorted by values
>>> from collections import OrderedDict
>>> OrderedDict(Counter(x).most_common()[::-1])
OrderedDict([(0, 0), (2, 1), (1, 2), (4, 3), (3, 4)])
The collections solution mentioned in another answer is absolutely superb, because you retain a connection between the key and value which in the case of dictionaries is extremely important.
I don't agree with the number one choice presented in another answer, because it throws away the keys.
I used the solution mentioned above (code shown below) and retained access to both keys and values and in my case the ordering was on the values, but the importance was the ordering of the keys after ordering the values.
from collections import Counter
x = {'hello':1, 'python':5, 'world':3}
c=Counter(x)
print( c.most_common() )
>> [('python', 5), ('world', 3), ('hello', 1)]
You can also use a custom function that can be passed to parameter key.
def dict_val(x):
return x[1]
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=dict_val)
You can use a skip dict which is a dictionary that's permanently sorted by value.
>>> data = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
>>> SkipDict(data)
{0: 0.0, 2: 1.0, 1: 2.0, 4: 3.0, 3: 4.0}
If you use keys(), values() or items() then you'll iterate in sorted order by value.
It's implemented using the skip list datastructure.
Of course, remember, you need to use OrderedDict because regular Python dictionaries don't keep the original order.
from collections import OrderedDict
a = OrderedDict(sorted(originalDict.items(), key=lambda x: x[1]))
If you do not have Python 2.7 or higher, the best you can do is iterate over the values in a generator function. (There is an OrderedDict for 2.4 and 2.6 here, but
a) I don't know about how well it works
and
b) You have to download and install it of course. If you do not have administrative access, then I'm afraid the option's out.)
def gen(originalDict):
for x, y in sorted(zip(originalDict.keys(), originalDict.values()), key=lambda z: z[1]):
yield (x, y)
#Yields as a tuple with (key, value). You can iterate with conditional clauses to get what you want.
for bleh, meh in gen(myDict):
if bleh == "foo":
print(myDict[bleh])
You can also print out every value
for bleh, meh in gen(myDict):
print(bleh, meh)
Please remember to remove the parentheses after print if not using Python 3.0 or above
from django.utils.datastructures import SortedDict
def sortedDictByKey(self,data):
"""Sorted dictionary order by key"""
sortedDict = SortedDict()
if data:
if isinstance(data, dict):
sortedKey = sorted(data.keys())
for k in sortedKey:
sortedDict[k] = data[k]
return sortedDict
Here is a solution using zip on d.values() and d.keys(). A few lines down this link (on Dictionary view objects) is:
This allows the creation of (value, key) pairs using zip(): pairs = zip(d.values(), d.keys()).
So we can do the following:
d = {'key1': 874.7, 'key2': 5, 'key3': 8.1}
d_sorted = sorted(zip(d.values(), d.keys()))
print d_sorted
# prints: [(5, 'key2'), (8.1, 'key3'), (874.7, 'key1')]
As pointed out by Dilettant, Python 3.6 will now keep the order! I thought I'd share a function I wrote that eases the sorting of an iterable (tuple, list, dict). In the latter case, you can sort either on keys or values, and it can take numeric comparison into account. Only for >= 3.6!
When you try using sorted on an iterable that holds e.g. strings as well as ints, sorted() will fail. Of course you can force string comparison with str(). However, in some cases you want to do actual numeric comparison where 12 is smaller than 20 (which is not the case in string comparison). So I came up with the following. When you want explicit numeric comparison you can use the flag num_as_num which will try to do explicit numeric sorting by trying to convert all values to floats. If that succeeds, it will do numeric sorting, otherwise it'll resort to string comparison.
Comments for improvement welcome.
def sort_iterable(iterable, sort_on=None, reverse=False, num_as_num=False):
def _sort(i):
# sort by 0 = keys, 1 values, None for lists and tuples
try:
if num_as_num:
if i is None:
_sorted = sorted(iterable, key=lambda v: float(v), reverse=reverse)
else:
_sorted = dict(sorted(iterable.items(), key=lambda v: float(v[i]), reverse=reverse))
else:
raise TypeError
except (TypeError, ValueError):
if i is None:
_sorted = sorted(iterable, key=lambda v: str(v), reverse=reverse)
else:
_sorted = dict(sorted(iterable.items(), key=lambda v: str(v[i]), reverse=reverse))
return _sorted
if isinstance(iterable, list):
sorted_list = _sort(None)
return sorted_list
elif isinstance(iterable, tuple):
sorted_list = tuple(_sort(None))
return sorted_list
elif isinstance(iterable, dict):
if sort_on == 'keys':
sorted_dict = _sort(0)
return sorted_dict
elif sort_on == 'values':
sorted_dict = _sort(1)
return sorted_dict
elif sort_on is not None:
raise ValueError(f"Unexpected value {sort_on} for sort_on. When sorting a dict, use key or values")
else:
raise TypeError(f"Unexpected type {type(iterable)} for iterable. Expected a list, tuple, or dict")
I just learned a relevant skill from Python for Everybody.
You may use a temporary list to help you to sort the dictionary:
# Assume dictionary to be:
d = {'apple': 500.1, 'banana': 1500.2, 'orange': 1.0, 'pineapple': 789.0}
# Create a temporary list
tmp = []
# Iterate through the dictionary and append each tuple into the temporary list
for key, value in d.items():
tmptuple = (value, key)
tmp.append(tmptuple)
# Sort the list in ascending order
tmp = sorted(tmp)
print (tmp)
If you want to sort the list in descending order, simply change the original sorting line to:
tmp = sorted(tmp, reverse=True)
Using list comprehension, the one-liner would be:
# Assuming the dictionary looks like
d = {'apple': 500.1, 'banana': 1500.2, 'orange': 1.0, 'pineapple': 789.0}
# One-liner for sorting in ascending order
print (sorted([(v, k) for k, v in d.items()]))
# One-liner for sorting in descending order
print (sorted([(v, k) for k, v in d.items()], reverse=True))
Sample Output:
# Ascending order
[(1.0, 'orange'), (500.1, 'apple'), (789.0, 'pineapple'), (1500.2, 'banana')]
# Descending order
[(1500.2, 'banana'), (789.0, 'pineapple'), (500.1, 'apple'), (1.0, 'orange')]
Use ValueSortedDict from dicts:
from dicts.sorteddict import ValueSortedDict
d = {1: 2, 3: 4, 4:3, 2:1, 0:0}
sorted_dict = ValueSortedDict(d)
print sorted_dict.items()
[(0, 0), (2, 1), (1, 2), (4, 3), (3, 4)]
Iterate through a dict and sort it by its values in descending order:
$ python --version
Python 3.2.2
$ cat sort_dict_by_val_desc.py
dictionary = dict(siis = 1, sana = 2, joka = 3, tuli = 4, aina = 5)
for word in sorted(dictionary, key=dictionary.get, reverse=True):
print(word, dictionary[word])
$ python sort_dict_by_val_desc.py
aina 5
tuli 4
joka 3
sana 2
siis 1
If your values are integers, and you use Python 2.7 or newer, you can use collections.Counter instead of dict. The most_common method will give you all items, sorted by the value.
This works in 3.1.x:
import operator
slovar_sorted=sorted(slovar.items(), key=operator.itemgetter(1), reverse=True)
print(slovar_sorted)
For the sake of completeness, I am posting a solution using heapq. Note, this method will work for both numeric and non-numeric values
>>> x = {1: 2, 3: 4, 4:3, 2:1, 0:0}
>>> x_items = x.items()
>>> heapq.heapify(x_items)
>>> #To sort in reverse order
>>> heapq.nlargest(len(x_items),x_items, operator.itemgetter(1))
[(3, 4), (4, 3), (1, 2), (2, 1), (0, 0)]
>>> #To sort in ascending order
>>> heapq.nsmallest(len(x_items),x_items, operator.itemgetter(1))
[(0, 0), (2, 1), (1, 2), (4, 3), (3, 4)]

Given a list of [string, number] tuples, create a dictionary where keys are the first characters of strings and the values are sums of the numbers

I have a list of tuples, where first object is a string and second one is a number. I need to create a dictionary with using first letter of the string as a key and number (or I need to add some numbers if keys will be the same) as a value.
for example:
input
lst = [('Alex', 5), ('Addy', 7), ('Abdul', 2), ('Bob', 6), ('Carl', 8), ('Cal', 4)]
output
dct = {'A': 14, 'B': 6, 'C': 12}
The most simple, straightforward and naive way is:
dct = {}
for k, v lst:
if k in v:
dct[k] += v
else:
dct[k] = v
There are ways to progressively be more clever, the first is probably to use .get with the default:
dct = {}
for k, v in lst:
dct[k] = dct.get(k, 0) + v
Finally, you can use a collections.defaultdict, which takes a "factory" function which will be called if the key is not there, use int as the factor:
from collections import defaultdict
dct = defaultdict(int)
for k, v in lst:
dct[k] += v
NOTE: it is usually safer to create a regular dict out of this, to avoid the default behavior:
dct = dict(dct)
Or even
dct.default_factory = None
Finally, one of the more flexible ways is to create your own dict subclass and use __missing__, this is useful if need access to the key when you are making the default value, so not particularly more helpful here, but for completion's sake:
class AggDict(dict):
def __missing__(self, key):
return 0
dct = AggDict()
for k, v in dct:
dct[k] += v
Use a defaultdict:
dct = defaultdict(int) # default to 0
for name, val in lst:
dct[name[0]] += val
dct = dict(dct) # get rid of default value
You could use Counter from collections to convert the tuples to countable key/values, then use reduce from functools to add them together:
from collections import Counter
from functools import reduce
lst = [('Alex', 5), ('Addy', 7), ('Abdul', 2), ('Bob', 6), ('Carl', 8), ('Cal', 4)]
dst = reduce(Counter.__add__,(Counter({k[:1]:v}) for k,v in lst))
# Counter({'A': 14, 'C': 12, 'B': 6})

Is there a way in python to take a list and convert it to a dictionary? [duplicate]

I have a list of about 50 strings with an integer representing how frequently they occur in a text document. I have already formatted it like shown below, and am trying to create a dictionary of this information, with the first word being the value and the key is the number beside it.
string = [('limited', 1), ('all', 16), ('concept', 1), ('secondly', 1)]
The code I have so far:
my_dict = {}
for pairs in string:
for int in pairs:
my_dict[pairs] = int
Like this, Python's dict() function is perfectly designed for converting a list of tuples, which is what you have:
>>> string = [('limited', 1), ('all', 16), ('concept', 1), ('secondly', 1)]
>>> my_dict = dict(string)
>>> my_dict
{'all': 16, 'secondly': 1, 'concept': 1, 'limited': 1}
Just call dict():
>>> string = [('limited', 1), ('all', 16), ('concept', 1), ('secondly', 1)]
>>> dict(string)
{'limited': 1, 'all': 16, 'concept': 1, 'secondly': 1}
The string variable is a list of pairs. It means you can do something somilar to this:
string = [...]
my_dict = {}
for k, v in string:
my_dict[k] = v
Make a pair of 2 lists and convert them to dict()
list_1 = [1,2,3,4,5]
list_2 = [6,7,8,9,10]
your_dict = dict(zip(list_1, list_2))

comparing list of tuple elements python

I have a two list of tuples
t1 = [ ('a',3,4), ('b',3,4), ('c',4,5) ]
t2 = [ ('a',4,6), ('c',3,4), ('b',3,6), ('d',4,5) ]
Such that
the order of the tuples may not be the same order and
the lists may not contain the same amount of tuple elements.
My goal is to compare the two lists such that if the string element matches, then compare the last integer element in the tuple and return a list containing -1 if t1[2] < t2[2], 0 if they are equal and 1 if they are greater than.
I've tried different variations but the problem i have is finding a way to match the strings to do proper comparison.
return [diff_unique(x[2],y[2]) for x,y in zip(new_list,old_list) ]
Where diff_unique does the aforementioned comparison of the integers, and new_list is t1 and old_list is t2.
I've also tried this:
return [diff_unique(x[2],y[2]) for x,y in zip(new_list,old_list) if(x[0]==y[0]]
What I intend to do is use the returned list and create a new four-tuple list with the original t1 values along with the difference from the matching t2 tuple. i.e
inc_dec_list = compare_list(new,old)
final_list = [ (f,r,u,chge) for (f,r,u), chge in zip(new,inc_dec_list)]
Where new = t1 and old = t2. This may have been an important detail, sorry I missed it.
Any help in the right direction?
Edit: I have added my test case program that mimicks what my original intent is for those who want to help. Thank you all.
import os
import sys
old = [('a',10,1),('b',10,2),('c',100,4),('d',200,4),('f',45,2)]
new = [('a',10,2),('c',10,2),('b',100,2),('d',200,6),('e',233,4),('g',45,66)]
def diff_unique(a,b):
print "a:{} = b:{}".format(a,b)
if a < b:
return -1
elif a==b:
return 0
else:
return 1
def compare_list(new_list, old_list):
a = { t[0]:t[1:] for t in new_list }
b = { t[0]:t[1:] for t in old_list }
common = list( set(a.keys())&set(b.keys()))
return [diff_unique(a[key][1], b[key][1]) for key in common]
#get common tuples
#common = [x for x,y in zip(new_list,old_list) if x[0] == y[0] ]
#compare common to old list
#return [diff_unique(x[2],y[2]) for x,y in zip(new_list,old_list) ]
inc_dec_list = compare_list(new,old)
print inc_dec_list
final_list = [ (f,r,u,chge) for (f,r,u), chge in zip(new,inc_dec_list)]
print final_list
To match the tuples by string from different lists, you can use dict comprehension (order inside the tuples is preserved):
a = {t[0]:t[1:] for t in t1} # {'a': (3, 4), 'c': (4, 5), 'b': (3, 4)}
b = {t[0]:t[1:] for t in t1} # {'a': (4, 6), 'c': (3, 4), 'b': (3, 6), 'd': (4, 5)}
Then you can iterate over the keys of both dictionaries and do the comparison. Assuming you only want to do the comparison for keys/tuples present in t1 and t2, you can join the keys using sets:
common_keys = list(set(a.keys())&set(b.keys()))
And finally compare the dictionary's items and create the list you want like this:
return [diff_unique(a[key][1],b[key][1]) for key in common_keys ]
If you need the output in the order of the alphabetically sorted characters, use the sorted function on the keys:
return [diff_unique(a[key][1],b[key][1]) for key in sorted(common_keys) ]
If you want all keys to be considered, you can do the following:
all_keys = list(set(a.keys()+b.keys()))
l = list()
for key in sorted(all_keys):
try:
l.append(diff_unique(a[key][1],b[key][1]))
except KeyError:
l.append("whatever you want")
return l
With the new information about what values should be returned in what order, the solution would be this:
ordered_keys = [t[0] for t in t1]
a = {t[0]:t[1:] for t in t1} # {'a': (3, 4), 'c': (4, 5), 'b': (3, 4)}
b = {t[0]:t[1:] for t in t1} # {'a': (4, 6), 'c': (3, 4), 'b': (3, 6), 'd': (4, 5)}
l = list()
for key in sorted(ordered_keys):
try:
l.append(diff_unique(a[key][1],b[key][1]))
except KeyError:
l.append(0) # default value
return l
First, build a default dictionary from each list, with the default value for a nonexistent key being a tuple whose last element is the smallest possible value for a comparison.
SMALL = (-float['inf'],)
from collections import defaultdict
d1 = defaultdict(lambda: SMALL, [(t[0], t[1:]) for t in t1])
d2 = defaultdict(lambda: SMALL, [(t[0], t[1:]) for t in t2])
Next, iterate over the keys in each dictionary (which can be created easily with itertools.chain). You probably want to sort the keys for the resulting list to have any meaning (otherwise, how do you know which keys produced which of -1/0/1?)
from itertools import chain
all_keys = set(chain(d1, d2))
result = [cmp(d1[k][-1], d2[k][-1]) for k in sorted(all_keys)]
Here is a simple solution of your problem,
It is not one line as you tried. I hope it will still help you
for a in t1:
for b in t2:
if a[0] != b[0]:
continue
return cmp(a[-1], b[-1])
In python 3.x, you can compare two lists of tuples
a and b thus:
import operator
a = [(1,2),(3,4)]
b = [(3,4),(1,2)]
# convert both lists to sets before calling the eq function
print(operator.eq(set(a),set(b))) #True

Sorting dictionary keys by values in a list?

I have a dictionary and a list. The values of the keys match those of the list, I'm just trying to find out how to sort the values in the dictionary by the values in the list.
>>> l = [1, 2, 37, 32, 4, 3]
>>> d = {
32: 'Megumi',
1: 'Ai',
2: 'Risa',
3: 'Eri',
4: 'Sayumi',
37: 'Mai'
}
I've tried using something along the lines of...
>>> sorted(dict.keys(), key=list.index)
... but obviously that only returns the keys in the desired order.
(Should have realized at 3AM that list and dict were horrible names, I changed them to l and d accordingly.)
Don't shadow the builtins dict and list
>>> L = [1, 2, 37, 32, 4, 3]
>>> D = {
... 32: 'Megumi',
... 1: 'Ai',
... 2: 'Risa',
... 3: 'Eri',
... 4: 'Sayumi',
... 37: 'Mai'
... }
# Seems roundabout to use sorted here
# This causes an index error for keys in D that are not listed in L
>>> sorted(D.items(), key=lambda x:L.index(x[0]))
[(1, 'Ai'), (2, 'Risa'), (37, 'Mai'), (32, 'Megumi'), (4, 'Sayumi'), (3, 'Eri')]
>>>
# I think this is more direct than using sorted.
# This also ignores/skips keys in D that aren't listed in L
>>> [(i,D[i]) for i in L]
[(1, 'Ai'), (2, 'Risa'), (37, 'Mai'), (32, 'Megumi'), (4, 'Sayumi'), (3, 'Eri')]
>>>
You shouldn't call you variables dict and list, because then, you cant use the build-in methods any more. I have renamed them in this example.
>>> l = [1, 2, 37, 32, 4]
>>> d = dict = {
... 32: 'Megumi',
... 1: 'Ai',
... 2: 'Risa',
... 3: 'Eri',
... 4: 'Sayumi',
... 37: 'Mai'
... }
Note that prior to Python 3.7 you could not sort dictionaries in Python (they were hash tables sorted by the hash functions of the keys). Alternative dictionary implementations existed to work around this (OrderedDict).
But you can create a new list containing the (key, value)-tuples from any dictionary, which is sorted by the first list:
>>> s = list((i, d.get(i)) for i in L)
>>> print s
[(1, 'Ai'), (2, 'Risa'), (37, 'Mai'), (32, 'Megumi'), (4, 'Sayumi')]
Or if you are only interested in the values:
>>> s = list(d.get(i) for i in L)
>>> print s
['Ai', 'Risa', 'Mai', 'Megumi', 'Sayumi']
Hope that helps!
You can't sort a dictionary because a dictionary is not ordered.
What you can do instead is:
Get all the key-value pairs out of the dictionary, sort them and put them into a list or
What you are already doing: keep a sorted list of the keys and use the dictionary when you need the value corresponding to a key.
Sorted dict is in fact a list of 2-tuples, because in Python 2.x there're no ordered dictionaty built-in. You almost got the solution, just add a value lookup after sorting keys:
[(k,dict[k]) for k in sorted(dict.keys(), key=list.index)]
But this fails when a key is not in list. Let's add a modification to put all such values at the end of sort, ordered by value:
def _index(x): # Allow non-full key list to be used in sorting
try: return (list.index(x), x)
except ValueError: return (sys.maxint, x)
[(k,dict[k]) for k in sorted(dict.keys(), key=_index)]
In Python 3.1, you could use the OrderedDict class:
from collections import OrderedDict
l = [1, 2, 37, 32, 4]
d = {
32: 'Megumi',
1: 'Ai',
2: 'Risa',
3: 'Eri',
4: 'Sayumi',
37: 'Mai'
}
def myindex(element):
try:
return l.index(element)
except ValueError:
return -1 # nonexisting keys are appended to the beginning of the list
od = OrderedDict(sorted(d.items(), key = lambda t: myindex(t[0])))
print(od)
As I didn't know what you want to do with keys that aren't in the list, I just return -1 in that case, meaning those elements are prepended to the list somehow (i.e. in non-stable order).
My example will print
OrderedDict([(3, 'Eri'), (1, 'Ai'), (2, 'Risa'), (37, 'Mai'), (32, 'Megumi'), (4, 'Sayumi')])

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