I have a data set which follows the structure of the following example:
exampleset = {
'body' : {
'abdomen' : [{
'arms' : {
'value' : 2,
}
},{
'legs': {
'value' : 2,
}
}],
'hands' : {
'fingers' : {
'value' : 5,
}
},
}
}
I am trying to reverse this so I get something like:
{'value': {'value1': {5: {'fingers': {'hands': {'body': {}}}}},
'value2': {2: {'legs': {'abdomen': {'body': {}}}}},
'value3': {2: {'arms': {'abdomen': {'body': {}}}}}},
}
(I hope I got the bracket matching right, but you get the idea.)
I am using a couple of recursion functions to do this, like so:
def recurse_find(data, values, count):
global conf
for key in data:
for v in conf['value_names']:
if key == v:
values[v+str(count)] = {}
values[v+str(count)][data[key]] = {}
count += 1
# originally just using this line:
# values[data[key]] = {}
if type(data[key]) is list:
for i in data[key]:
if type(i) is dict:
values = recurse_find(i, values, count)
values = add_new_level(values, key)
elif type(data[key]) is dict:
values = recurse_find(data[key], values, count)
values = add_new_level(values, key)
return values
def add_new_level(data, new_key):
for key in data:
if data[key] == {}:
data[key][new_key] = {}
else:
data[key] = add_new_level(data[key], new_key)
return data
conf = { "value_names": ["value"] }
for value in conf['value_names']:
values[value] = recurse_find(exampleset, {}, 1)
print(values)
At the moment I only get one value returned correctly, obviously I would like them all. Originally I didn't label the values (value1, value2 etc), but when doing this example set I realised that of course if the values are the same I'll only get one! If I remove the value name keys it finds all the values (unless duplicate) but still doesn't return the correct levels as it includes some of the others while it loops round. I don't care about the order of the values, just that they are labelled differently so I don't miss out any.
Current result:
{'value': {'value1': {5: {'fingers': {'hands': {'body': {}}}}}}}
I think that the solution is the inclusion of a pretty simple step, but I can't see it at the moment and I've already spent too long looking at this.
Any help appreciated.
EDIT:
I've gotten a little further by changing my recursive function to make count a global variable and having count=1 outside the function which has sorted out the getting all the values problem.
I have narrowed down the addition of extra keys to the add_new_level function, but haven't yet figured out how to change it.
Output:
{'value': {'value1': {2: {'arms': {'abdomen': {'legs': {'abdomen': {'fingers': {'hands': {'body': {}}}}}}}}},
'value2': {2: {'legs': {'abdomen': {'fingers': {'hands': {'body': {}}}}}}},
'value3': {5: {'fingers': {'hands': {'body': {}}}}}}}
I have adjusted your output type slightly to make the dictionary containing 'value1' 'value2' etc... to an array. I believe this is better because the order of these will be lost anyway unless an OrderedDict (from collections package) is used and in any case an array will translate quite easily from index 0,1,2,3.. to val1, val2, val3, etc...
res = {'value': []}
def revnest(inp, keys=[]):
res2 = res['value']
if type(inp) == list:
inp = {i:j[i] for j in inp for i in j}
for x in inp:
if x == 'value':
res2.append({inp[x]:{}})
res2 = res2[-1][inp[x]]
for y in keys[::-1]:
res2[y] = {}
res2 = res2[y]
else:
revnest(inp[x], keys+[x])
revnest(exampleset)
print res
which given your exampleset, prints:
{'value': [{2: {'legs': {'abdomen': {'body': {}}}}}, {2: {'arms': {'abdomen': {'body': {}}}}}, {5: {'fingers': {'hands': {'body': {}}}}}]}
Related
I received the output from my Vector AutoRegression (VAR) algorithm as a data frame and converted it into a dictionary giving me the following structure:
{
'Date': '2021-05-07',
'BMI': 40.53002073252068,
'BP': 123.00463807559225,
'BloodSugar': 126.85415609085157,
'ThyroidFunction': 3.0,
'TF': 5.0
}
and I want to restructure it in this form :
# {Vital : {date : value, risk_value : 1}}
{
'BMI' : {'2021-05-07' : 40.53002073252068, risk_value : 1},
'BP': {'2021-05-07' : 123.00463807559225, risk_value : 1},
'BloodSugar' :{'2021-05-07' : 126.85415609085157, risk_value : 1},
'ThyroidFunction' : {'2021-05-07' : 3.0, risk_value:1},
'TF' : {'2021-05-07' : 5.0, risk_value:1}
}
Here the "risk_value : 1" is static for now.
The only thing constant in the output from VAR in the 1st dictionary would be the 1st key- date.
The value of date will change everyday.
The Vitals(BMI, BP, BloodSugar, ThyroidFunction, TF) may vary with input with either new vitals such as (weight, height, BMI, BP, BloodSugar) or completely different vitals(cholestrolLevel, HeartRate, LDL). Like so:
{
'Date': '2021-05-07',
'weight': '170lbs',
'height': '175cm',
'BMI': 39.3252068004638,
'BP': 104.530020707559225,
'BloodSugar': 126.85415609085157,
}
I wanted to make a function which dynamically restructures the dictionary. so I tried creating a function which would take all the keys of the dictionary and tried to run it through while loop and which then creates a dictionary with vitals and the values but was unsuccessful.
I've been stuck on this for a long time and any help will be greatly appreciated.
your_dict = {
'Date': '2021-05-07',
'BMI': 40.53002073252068,
'BP': 123.00463807559225,
'BloodSugar': 126.85415609085157,
'ThyroidFunction': 3.0,
'TF': 5.0
}
def parse_dict(dict_in):
dictionary = {}
for x in dict_in:
if x != 'Date':
dictionary[x] = {dict_in['Date']: dict_in[x], 'risk_value': 1}
return dictionary
dict_out = parse_dict(your_dict)
Seems #peter beat me to it but since I've already bothered...
def foo(some_dict, **kwargs):
ret = {}
date_key = some_dict.pop('Date')
for k, v in some_dict.items():
ret[k] = {date_key: v}
ret[k].update(kwargs)
return ret
d = {
'Date': '2021-05-07',
'weight': '170lbs',
'height': '175cm',
'BMI': 39.3252068004638,
'BP': 104.530020707559225,
'BloodSugar': 126.85415609085157,
}
from pprint import pprint
pprint(foo(d, risk_value=42, abc='x'))
Here you go!
def restructure (dct):
date = dct['Date'] #store the date
dct.pop('Date') #remove 'Date' key from the dict since it not needed anymore
for key, value in dct.items():
dct[key] = {date:value, 'risk_value' : 1} #update values for each key
return dct
print(restructure(d))
I couldn't find any examples that match my use case. Still working through my way in python lists and dictionaries.
Problem:
all_cars = {'total_count': 3,'cars': [{'name': 'audi','model': 'S7'}, {'name': 'honda', 'model': 'accord'},{'name': 'jeep', 'model': 'wrangler'} ]}
owners = {'users':[{'owner': 'Nick', 'car': 'audi'},{'owner': 'Jim', 'car': 'ford'},{'owner': 'Mike', 'car': 'mercedes'} ]}
def duplicate():
for c in all_cars['cars']:
if c['name'] == [c['users']for c in owners['users']]:
pass
else:
res = print(c['name'])
return res
output = ['honda', 'jeep', audi']
and
def duplicate():
for c in all_cars['cars']:
if c['name'] == 'audi':
pass
else:
res = print(c['name'])
return res
output - ['honda', 'jeep']
I am trying to find matching values in both dictionaries, using list comprehension, then return non-matching values only.
Solution: Using 'in' rather than '==' operator, I was able to compare values between both lists and skip duplicates.
def duplicate():
for c in all_cars['cars']:
if c['name'] in [c['users']for c in owners['users']]:
pass
else:
res = print(c['name'])
return res
To answer the question in your title, you can conditionally add elements during a list comprehension using the syntax [x for y in z if y == a], where y == a is any condition you need - if the condition evaluates to True, then the element y will be added to the list, otherwise it will not.
I would just keep a dictionary of all of the owner data together:
ownerData = { "Shaft" : {
"carMake" : "Audi",
"carModel" : "A8",
"year" : "2015" },
"JamesBond" : {
"carMake" : "Aston",
"carModel" : "DB8",
"year" : "2012" },
"JeffBezos" : {
"carMake" : "Honda",
"carModel" : "Accord"
"year" : "1989"}
}
Now you can loop through and query it something like this:
for o in ownerData:
if "Audi" in o["carMake"]:
print("Owner %s drives a %s %s %s" % (o, o["year"], o["carMake"], o["carModel"]))
Should output:
"Owner Shaft drives a 2015 Audi A8"
This way you can expand your data set for owners without creating multiple lists.
OK, based on your feedback on the solution above, here is how I would tackle your problem. Drop your common items into lists and then use "set" to print out the diff.
all_cars = {'total_count': 3,'cars': [{'name': 'audi','model': 'S7'},
{'name': 'honda', 'model': 'accord'},{'name': 'jeep', 'model': 'wrangler'} ]}
owners = {'users':[{'owner': 'Nick', 'car': 'audi'},{'owner': 'Jim',
'car': 'ford'},{'owner': 'Mike', 'car': 'mercedes'} ]}
allCarList = []
ownerCarList = []
for auto in all_cars['cars']:
thisCar = auto['name']
if thisCar not in allCarList:
allCarList.append(thisCar)
for o in owners['users']:
thisCar = o['car']
if thisCar not in ownerCarList:
ownerCarList.append(thisCar)
diff = list(set(allCarList) - set(ownerCarList))
print(diff)
I put this in and ran it and came up with this output:
['jeep', 'honda']
Hope that helps!
I have below 2 dictionaries that I want to merge. I want to merge on the same keys and I want to keep the values of both the dictionary.
I used dict1.update(dict2) but that replaced the values from 2nd to 1st dictionary.
u'dict1', {160: {u'na': u'na'}, 162: {u'test_': u'qq', u'wds': u'wew'}, 163: {u'test_env': u'test_env_value', u'env': u'e'}, 159: {u'no' : u'test_no'}
u'dict2', {160: {u'naa': u'na'}, 162: {u'envi_specs': u'qq', u'wds': u'wew'}, 163: {u'test_env': u'test_env_value', u'ens': u's'}}
What I got?
{160: {u'naa': u'na'}, 162: {u'envi_specs': u'qq', u'wds': u'wew'}, 163: {u'test_env': u'test_env_value', u'ens': u's'}}
What I need
{160: {u'naa': u'na', u'na': u'na'}, 162: {u'envi_specs': u'qq', u'wds': u'wew', u'test_': u'qq'}, 163: {u'test_env': u'test_env_value', u'ens': u's', u'env': u'e'}}
I followed merging "several" python dictionaries but I have two different dictionaries that I need to merge. Help please...
Loop over the keys in dict1, and retrieve the corresponding value from dict2, and update -
for k in dict1:
dict1[k].update(dict2.get(k, {})) # dict1.get(k).update(dict2.get(k, {}))
print(dict1)
{
"160": {
"naa": "na",
"na": "na"
},
"162": {
"wds": "wew",
"test_": "qq",
"envi_specs": "qq"
},
"163": {
"test_env": "test_env_value",
"ens": "s",
"env": "e"
},
"159": {
"no": "test_no"
}
}
Here, I use dict.get because it allows you to specify a default value to be returned in the event that k does not exist as a key in dict2. In this case, the default value is the empty dictionary {}, and calling dict.update({}) does nothing (and causes no problems).
def m3(a,b):
if not isinstance(a,dict) and not isinstance(b,dict):return b
for k in b:
if k in a :
a[k] = m3(a[k], b[k])
else: a[k] = b[k]
return a
d1 = {1:{"a":"A"}, 2:{"b":"B"}}
d2 = {2:{"c":"C"}, 3:{"d":"D"}}
d3 = {1:{"a":{1}}, 2:{"b":{2}}}
d4 = {2:{"c":{222}}, 3:{"d":{3}}}
d5 = {'employee':{'dev1': 'Roy'}}
d6 = {'employee':{'dev2': 'Biswas'}}
print(m3(d1,d2))
print(m3(d3,d4))
print(m3(d5,d6))
"""
Output :
{1: {'a': 'A'}, 2: {'b': 'B', 'c': 'C'}, 3: {'d': 'D'}}
{1: {'a': {1}}, 2: {'b': {2}, 'c': {222}}, 3: {'d': {3}}}
{'employee': {'dev1': 'Roy', 'dev2': 'Biswas'}}
"""
For some post-processing, I need to flatten a structure like this
{'foo': {
'cat': {'name': 'Hodor', 'age': 7},
'dog': {'name': 'Mordor', 'age': 5}},
'bar': { 'rat': {'name': 'Izidor', 'age': 3}}
}
into this dataset:
[{'foobar': 'foo', 'animal': 'dog', 'name': 'Mordor', 'age': 5},
{'foobar': 'foo', 'animal': 'cat', 'name': 'Hodor', 'age': 7},
{'foobar': 'bar', 'animal': 'rat', 'name': 'Izidor', 'age': 3}]
So I wrote this function:
def flatten(data, primary_keys):
out = []
keys = copy.copy(primary_keys)
keys.reverse()
def visit(node, primary_values, prim):
if len(prim):
p = prim.pop()
for key, child in node.iteritems():
primary_values[p] = key
visit(child, primary_values, copy.copy(prim))
else:
new = copy.copy(node)
new.update(primary_values)
out.append(new)
visit(data, { }, keys)
return out
out = flatten(a, ['foo', 'bar'])
I was not really satisfied because I have to use copy.copy to protect my inputs. Obviously, when using flatten one does not want the inputs be altered.
Then I thought about one alternative that uses more global variables (at least global to flatten) and uses an index instead of directly passing primary_keys to visit. However, this does not really help me to get rid of the ugly initial copy:
keys = copy.copy(primary_keys)
keys.reverse()
So here is my final version:
def flatten(data, keys):
data = copy.copy(data)
keys = copy.copy(keys)
keys.reverse()
out = []
values = {}
def visit(node, id):
if id:
id -= 1
for key, child in node.iteritems():
values[keys[id]] = key
visit(child, id)
else:
node.update(values)
out.append(node)
visit(data, len(keys))
return out
Is there a better implementation (that can avoid the use of copy.copy)?
Edit: modified to account for variable dictionary depth.
By using the merge function from my previous answer (below), you can avoid calling update which modifies the caller. There is then no need to copy the dictionary first.
def flatten(data, keys):
out = []
values = {}
def visit(node, id):
if id:
id -= 1
for key, child in node.items():
values[keys[id]] = key
visit(child, id)
else:
out.append(merge(node, values)) # use merge instead of update
visit(data, len(keys))
return out
One thing I don't understand is why you need to protect the keys input. I don't see them being modified anywhere.
Previous answer
How about list comprehension?
def merge(d1, d2):
return dict(list(d1.items()) + list(d2.items()))
[[merge({'foobar': key, 'animal': sub_key}, sub_sub_dict)
for sub_key, sub_sub_dict in sub_dict.items()]
for key, sub_dict in a.items()]
The tricky part was merging the dictionaries without using update (which returns None).
I have a bit of a complex question that I can't seem to get to the bottom of. I have a list of keys corresponding to a position in a Python dictionary. I would like to be able to dynamically change the value at the position (found by the keys in the list).
For example:
listOfKeys = ['car', 'ford', 'mustang']
I also have a dictionary:
DictOfVehiclePrices = {'car':
{'ford':
{'mustang': 'expensive',
'other': 'cheap'},
'toyota':
{'big': 'moderate',
'small': 'cheap'}
},
'truck':
{'big': 'expensive',
'small': 'moderate'}
}
Via my list, how could I dynamically change the value of DictOfVehiclePrices['car']['ford']['mustang']?
In my actual problem, I need to follow the list of keys through the dictionary and change the value at the end position. How can this be done dynamically (with loops, etc.)?
Thank you for your help! :)
Use reduce and operator.getitem:
>>> from operator import getitem
>>> lis = ['car', 'ford', 'mustang']
Update value:
>>> reduce(getitem, lis[:-1], DictOfVehiclePrices)[lis[-1]] = 'cheap'
Fetch value:
>>> reduce(getitem, lis, DictOfVehiclePrices)
'cheap'
Note that in Python 3 reduce has been moved to functools module.
A very simple approach would be:
DictOfVehiclePrices[listOfKeys[0]][listOfKeys[1]][listOfKeys[2]] = 'new value'
print reduce(lambda x, y: x[y], listOfKeys, dictOfVehiclePrices)
Output
expensive
In order to change the values,
result = dictOfVehiclePrices
for key in listOfKeys[:-1]:
result = result[key]
result[listOfKeys[-1]] = "cheap"
print dictOfVehiclePrices
Output
{'car': {'toyota': {'small': 'cheap', 'big': 'moderate'},
'ford': {'mustang': 'cheap', 'other': 'cheap'}},
'truck': {'small': 'moderate', 'big': 'expensive'}}
You have a great solution here by #Joel Cornett.
based on Joel method you can use it like this:
def set_value(dict_nested, address_list):
cur = dict_nested
for path_item in address_list[:-2]:
try:
cur = cur[path_item]
except KeyError:
cur = cur[path_item] = {}
cur[address_list[-2]] = address_list[-1]
DictOfVehiclePrices = {'car':
{'ford':
{'mustang': 'expensive',
'other': 'cheap'},
'toyota':
{'big': 'moderate',
'small': 'cheap'}
},
'truck':
{'big': 'expensive',
'small': 'moderate'}
}
set_value(DictOfVehiclePrices,['car', 'ford', 'mustang', 'a'])
print DictOfVehiclePrices
STDOUT:
{'car': {'toyota': {'small': 'cheap', 'big': 'moderate'}, 'ford':
{'mustang': 'a', 'other': 'cheap'}}, 'truck': {'small': 'moderate',
'big': 'expensive'}}
def update_dict(parent, data, value):
'''
To update the value in the data if the data
is a nested dictionary
:param parent: list of parents
:param data: data dict in which value to be updated
:param value: Value to be updated in data dict
:return:
'''
if parent:
if isinstance(data[parent[0]], dict):
update_dict(parent[1:], data[parent[0]], value)
else:
data[parent[0]] = value
parent = ["test", "address", "area", "street", "locality", "country"]
data = {
"first_name": "ttcLoReSaa",
"test": {
"address": {
"area": {
"street": {
"locality": {
"country": "india"
}
}
}
}
}
}
update_dict(parent, data, "IN")
Here is a recursive function to update a nested dict based on a list of keys:
1.Trigger the update dict function with the required params
2.The function will iterate the list of keys, and retrieves the value from the dict.
3.If the retrieved value is dict, it pops the key from the list and also it updates the dict with the value of the key.
4.Sends the updated dict and list of keys to the same function recursively.
5.When the list gets empty, it means that we have reached the desired the key, where we need to apply our replacement. So if the list is empty, the funtion replaces the dict[key] with the value