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Remove dictionary if we have value is nan/None/NaN/null for key using python

I want to remove dictionary if value is nan/None/NaN/null for key . If nan is the only value in case of phone_type work then remove full dictionary itself.
Input Data
dic = ['Customer_Number': 12345,'Phone_Number': [{'Phone_Type': 'Mobile', 'Phone': [1217]}, {'Phone_Type': 'work', 'Phone': [nan]}]]
Expected Output Data
dic = ['Customer_Number': 12345,'Phone_Number': [{'Phone_Type': 'Mobile', 'Phone': [1217]}]]
code tried
#define which elements you want to remove:
to_be_deleted = [[], {}, "", None, "nan",nan, "NaN", NaN]
def remove_empty_elements(jsonData):
if isinstance(jsonData, list):
print("jsonDAta:", jsonData)
jsonData = [remove_empty_elements(elem) for elem in jsonData
if remove_empty_elements(elem) not in to_be_deleted]
elif isinstance(jsonData, dict):
jsonData = {key: remove_empty_elements(value) for key, value in jsonData.items()
if remove_empty_elements(value) not in to_be_deleted}
if len(jsonData) == 1:
return None
return jsonData
res = remove_empty_elements(dic)

Example solution:
to_delete = [ None, [None], "", None, "nan", "NaN"]
dic = {'Customer_Number': 12345,'Phone_Number': [{'Phone_Type': 'Mobile', 'Phone': [1217]}, {'Phone_Type': 'work', 'Phone': [None]}]}
for key in dic.keys():
if isinstance(dic[key], list):
for item in dic[key]:
if isinstance(item, dict):
item_keys = list(item.keys())
for key_2 in item_keys:
if item[key_2] in to_delete:
del item[key_2]
output
{'Customer_Number': 12345, 'Phone_Number': [{'Phone_Type': 'Mobile', 'Phone': [1217]}, {'Phone_Type': 'work'}]}
Change accordingly in order to catch more cases. This one only works if you have a list of dictionaries as value for the top level keys

Trying to return all nested json dictionary values that contain a substring python

I want to return a list of all of the text that comes after the nested 'en' key and before the comma that separates that key from the rest of the dictionary
dictionary = {'title': 'a',
'labels': {'label0': {'en': 'Statement',
'ca': 'dog1',
'bd': 'ေမးခြန္း ၁၀'},
'label1': {'en': 'Hello how are you',
'ca': 'cat6979309',
'bd': 'turkey89'},
'option0': {'en': 'No',
'bd': 'turkey232',
'ca': 'dog2'},
'option1': {'en': 'Absoluelty not',
'bd': 'turkey3',
'ca': 'dog3'},
'option2': {'en': 'Neutral ', 'bd': 'snake3', 'ca':'bat1'},
'option3': {'en': 'Somewhat Disagree',
'bd': 'turkey4',
'ca': 'dog4'},
'option4': {'en': 'For Sure',
'bd': 'turkey5',
'ca': 'dog5'}},```
I have tried this which isn't working, the goal is to have the function return something like sentences = ['Statement', 'Hello how are you', 'No', 'Absolutely not','Neutral'...]
def json(dic):
sentences = []
for (key, value) in dic.items():
if "en" in value:
sentences.append(value)
return sentences

You will need to recurse through the nested structure. Here is a generator function that does so:
def get_key(data, key):
if key in data:
yield data[key]
for k, v in data.items():
if isinstance(v, dict):
yield from get_key(v, key)
>>> list(get_key(dictionary, "en"))
['Statement', 'Hello how are you', 'No', 'Absoluelty not', 'Neutral ',
'Somewhat Disagree', 'For Sure']

Removing mulitple key items with dict comprehension python

I want to remove multiple key from my json and I'm using dictionary comprehensions like this
remove_key = ['name', 'description']
data = {'full-workflow': {'task_defaults': {'retry': {'count': 3, 'delay': 2}}, 'tasks': {'t1': {'action': 'nn.postgres.export-db', 'description': 'Dump prod DB with default settings', 'input': {'database': 'prod', 'filepath': '/var/tmp/prod-dump.pgsql', 'host': 'postgres.local', 'password': 'mypass', 'username': 'myuser'}, 'name': 'db export', 'on-success': ['t2']}, 't2': {'action': 'nn.aws.upload-to-s3', 'description': 'Upload to S3 bucket for development', 'input': {'sourcepath': '{{ tasks(t1).result.filepath }}', 'targetpath': 's3://mybucket/prod-dump.pgsql'}, 'name': 'Upload to S3', 'on-success': ['t3'], 'retry': {'count': 5, 'delay': 5}}, 't3': {'action': 'nn.shell.command', 'description': 'Remove temp file from batch folder ', 'input': {'cmd': 'rm {{ tasks(t1).result.filepath }}'}, 'name': 'Remove temp file', 'on-complete': ['t4']}, 't4': {'action': 'nn.notify.send-mail', 'description': 'Send email to admin containing target path', 'input': {'from': 'bot#nn.io', 'message': 'DB Dump {{ tasks(t1).result.filepath }} was stored to S3', 'subject': 'Prod DB Backup', 'to': 'admin#nn.io'}, 'name': 'Send email', 'target': 'nn'}}}, 'version': '2'}
def remove_additional_key(data):
return {
key: data[key] for key in data if key not in remove_key
}
then just
new_data = remove_additional_key(data)
Because this is nested dict, I want to remove_key from tasks dict, so what am I doing wrong?

Your data are nested dictionaries. If you want to remove any data with a key contained in remove_key, then I suggest a recursive approach. This can be achieved, based on your exiting function remove_additional_key, with ease:
def remove_additional_key(data):
sub_data = {}
for key in data:
if key not in remove_key:
if isinstance(data[key], dict): # if is dictionary
sub_data[key] = remove_additional_key(data[key])
else:
sub_data[key] = data[key]
return sub_data
new_data = remove_additional_key(data)
Note, if a entry is a dictionary can be checked by isinstance(data[key], dict). See How to check if a variable is a dictionary in Python?

You have a dictionary with a few nested dictionaries. If you know exactly which subdictionary you have those keys to remove, you can use:
data['full-workflow']['tasks']['t1'].pop('name')
Using the lookup approach (key: data[key]) in a dictionary comprehension is inefficient however, on such a small data amount you won't notice a difference.
If you don't know the exact path to your nested dictionary, you can use a function (posting another answer for your convenience)
def delete_keys_from_dict(d, lst_keys):
for k in lst_keys:
try:
del dict_del[k]
except KeyError:
pass
for v in dict_del.values():
if isinstance(v, dict):
delete_keys_from_dict(v, lst_keys)
return dict_del
Then you could call
delete_keys_from_dict(data, ['name', 'description'])
Needless to say, should you have name key in multiple nested dictionaries, all of them would be deleted, so be careful.

KeyError: 'name' Why can't I use 'name'?

I wanna make a dictionary has name's key & data.In views.py I wrote
data_dict ={}
def try_to_int(arg):
try:
return int(arg)
except:
return arg
def main():
book4 = xlrd.open_workbook('./data/excel1.xlsx')
sheet4 = book4.sheet_by_index(0)
data_dict_origin = OrderedDict()
tag_list = sheet4.row_values(0)[1:]
for row_index in range(1, sheet4.nrows):
row = sheet4.row_values(row_index)[1:]
row = list(map(try_to_int, row))
data_dict_origin[row_index] = dict(zip(tag_list, row))
if data_dict_origin['name'] in data_dict:
data_dict[data_dict_origin['name']].update(data_dict_origin)
else:
data_dict[data_dict_origin['name']] = data_dict_origin
main()
When I printed out data_dict,it is
OrderedDict([(1, {'user_id': '100', 'group': 'A', 'name': 'Tom', 'dormitory': 'C'}), (2, {'user_id': '50', 'group': 'B', 'name': 'Blear', 'dormitory': 'E'})])
My ideal dictionary is
dicts = {
Tom: {
'user_id': '100',
'group': 'A',
'name': 'Tom',
'dormitory': 'C'
},
Blear: {
},
}
How should I fix this?What should I write it?

The code is using the wrong key in the dictionary. The keys are 1, 2, and do not have the name key. You can use this code instead:
for value in data_dict.values():
if value['name'] in data_dict:
data_dict[value['name']].update(value)
else:
data_dict[value['name']] = value

Your data_dict_origin has numbers as keys and dicts as values (which technically makes it a sparse array of dicts). The "name" key exists in those dicts, not in your data_dict.

Create a key in a nested dict without using update function

Input :
{'Name': 'A','Blood Group': 'O +ve', 'Age': '1', 'Sex': 'M','Phone Number': '01234567', 'Mobile Number': '9876543210', 'Date of Birth': '01-01-95'}
1.
d.update({'Contact Info': {'Mobile Number':d['Mobile Number'],'Phone
Number':d['Phone Number'] }})
2.
d['Contact Info']={}
d['Contact Info']['Mobile Number']=d['Mobile Number']
Can you say any better way or different way to create a dictionary key which can be assigned to a dict item as value???
Original Code:
import csv
import copy
from collections import namedtuple
d={}
ls=[]
def nest():
with open ("details.csv", 'r') as f:
reader=csv.DictReader(f)
for row in reader:
d.update(row)
PersonalDetails = namedtuple('PersonalDetails','blood_group age sex')
ContactInfo = namedtuple('ContactInfo','phone_number mobile_number')
d1=copy.deepcopy(d)
ls.append(d1)
print ls
nest()

This is how I would update my dict of dicts:
I would create a function that will take a 3 arguments(The key of the subdict, the subkey of said subdict and the value you want to change.) I assign to be updated and then update that value.
d = {
'Name': 'A',
'Personal Details': {'Blood Group': 'O +ve', 'Age': '1', 'Sex': 'M'},
'Contact Info': {'Phone Number': '01234567', 'Mobile Number': '9876543210'},
'Date of Birth': '01-01-95'
}
def updateInfo(toBeUpdated, subkey, ValueToUpdate):
if toBeUpdated in d:
tempdict = d[toBeUpdated]
tempdict[subkey] = ValueToUpdate
d[toBeUpdated] = tempdict
print (d)
else:
print ("No %s to update" % (toBeUpdated))
updateInfo('Contact Info','Mobile Number','999 999 9999')
the result I get from this:
{'Name': 'A', 'Personal Details': {'Blood Group': 'O +ve', 'Age': '1', 'Sex': 'M'}, 'Contact Info': {'Phone Number': '01234567', 'Mobile Number': '999 999 9999'}, 'Date of Birth': '01-01-95'}