Develop Reference

Save dict as netCDF / xarray

I have a problem. I want to save a dict. But unfortunately I got the following error - TypeError: expected bytes, list found. I want to save my my_dict as netCDF. How could I save my dict? I looked at https://docs.xarray.dev/en/stable/user-guide/io.html , Saving Python dictionary to netCDF4 file and some other links and blogs
from netCDF4 import Dataset
my_dict = {
'_key': '1',
'group': 'test',
'data': {},
'type': '',
'code': '007',
'conType': '1',
'flag': None,
'createdAt': '2021',
'currency': 'EUR',
'detail': {
'selector': {
'number': '12312',
'isTrue': True,
'requirements': [{
'type': 'customer',
'requirement': '1'}]
}
}
'identCode': [],
}
ds = Dataset(my_dict)
[OUT] TypeError: expected bytes, list found
ds.to_netcdf("saved_on_disk.nc")

Create JSON from another JSON with duplicate values in Python

I have a JSON:
[{'job': 'fireman', 'salary': 30000', 'country':'USA'}, {'job': 'doctor', 'salary': '50000': 'country': 'Canada'},{'job': 'fireman', 'salary': 60000', 'country':'France'}, {'job': 'Engineer', 'salary': 45000', 'country':'Mexico'} ]
I want to combine the duplicate values and create a JSON like:
[
{"job": "fireman",
"sumamry": [{"country": "USA", "Salary": 40000}, {"Country": "France", "Salary": 60000}]
"total" : 100000},
{"job": "doctor",
"summary": [{"country": "Canada", "Salary": 50000}]
"total" : 50000},
....
]

Try this:
non_summarized = [{'job': 'fireman', 'salary': 30000, 'country':'USA'}, {'job': 'doctor', 'salary': 50000, 'country': 'Canada'},{'job': 'fireman', 'salary': 60000, 'country':'France'}, {'job': 'Engineer', 'salary': 45000, 'country':'Mexico'}]
# sort the list of dictionary base on job keys, so we can loop in the order
non_summarized = sorted(non_summarized, key = lambda i: i['job'])
summarized = list()
last_value = dict()
for d in non_summarized:
# check if the last value has the same job or not
# if not then create a new dict value and update with new information
if last_value.get('job') != d.get('job'):
last_value = {
'job': d.get('job'),
'total': 0,
'summary': list()
}
summarized.append(last_value)
last_value['total'] += d.get('salary', 0)
last_value['summary'].append({
'country': d.get('country'),
'salary': d.get('salary')
})
print(summarized)
Please let me know if you need any clarification.

How to iterate over a JSON array and get values for a key which itself is a JSON object

I have been trying to do something simple yet something hard for me to solve it!
I have a json object that looks like:
jsonObject = {
'attributes': {
'192': { <--- This can be changed times to times meaning different number
'id': '192',
'code': 'hello',
'label': 'world',
'options': [
{
'id': '211',
'label': '5'
},
{
'id': '1202',
'label': '8.5'
},
{
'id': '54',
'label': '9'
},
{
'id': '1203',
'label': '9.5'
},
{
'id': '58',
'label': '10'
}
]
}
},
'template': '12345',
'basePrice': '51233',
'oldPrice': '51212',
'productId': 'hello',
}
and what I want to do is to get the values from options (To have both id and label saved into a list)
For now I only managed to do:
for att, value in jsonObject.items():
print(f"{att} - {value}"
How can I get the label and id?

You can try the following code:
attr = jsonObject['attributes']
temp = list(attr.values())[0] # It is same as "temp = attr['192']", but you said '192' can be changed.
options = temp['options']
for option in options:
print(f"id: {option['id']}, label: {option['label']}")

How do I use Pandas to convert an Excel file to a nested JSON?

I am a rookie programmer and I'm trying to convert an excel file into a nested JSON using Pandas.
I am posting my code and the expected output, which I am not able to achieve so far. The problem is that the excel columns which I transform into nested info, should actually fall under the name "addresses" and I can't figure out how to do that. Will be grateful for any advice.
This is how the excel file looks like:
import pandas as pd
import json
df = pd.read_excel("...", encoding = "utf-8-sig")
df.fillna('', inplace = True)
def get_nested_entry(key, grp):
entry = {}
entry['Forename'] = key[0]
entry['Middle Name'] = key[1]
entry['Surname'] = key[2]
for field in ['Address - Country']:
entry[field] = list(grp[field].unique())
return entry
entries = []
for key, grp in df.groupby(['Forename', 'Middle Name', 'Surname']):
entry = get_nested_entry(key, grp)
entries.append(entry)
print(entries)
with open("excel_to_json_output.json", "w", encoding = "utf-8-sig") as f:
json.dump(entries, f, indent = 4)
This is the expected outcome
[
{
"firstName": "Angela",
"lastName": "L.",
"middleName": "Johnson",
"addresses": [
{
"postcode": "32807",
"city": "Orlando",
"state": "FL",
"country": "United States of America"
}
],
What I get is this
[
{
"Forename": "Angela",
"Middle Name": "L.",
"Surname": "Johnson",
"Address - Country": [
"United States of America"
]
},

Try this
b = {'First_Name': ["Angela","Peter","John"],
'Middle_Name': ["L","J","A"],
'Last_Name': ["Johnson","Roth","Williams"],
'City': ["chicago","seattle","st.loius"],
'state': ["IL","WA","MO"],
'zip': [60007,98105,63115],
'country': ["USA","USA","USA"]}
df = pd.DataFrame(b)
predict = df.iloc[:,:3].to_dict(orient='records')
postdict = df.iloc[:,3:].to_dict(orient='records')
entities=[]
for i in range(df.shape[0]):
tm = predict[i]
tm["addresses"] = [postdict[i]]
entities.append(tm)
output
[{'First_Name': 'Angela',
'Middle_Name': 'L',
'Last_Name': 'Johnson',
'addresses': [{'City': 'chicago',
'state': 'IL',
'zip': 60007,
'country': 'USA'}]},
{'First_Name': 'Peter',
'Middle_Name': 'J',
'Last_Name': 'Roth',
'addresses': [{'City': 'seattle',
'state': 'WA',
'zip': 98105,
'country': 'USA'}]},
{'First_Name': 'John',
'Middle_Name': 'A',
'Last_Name': 'Williams',
'addresses': [{'City': 'st.loius',
'state': 'MO',
'zip': 63115,
'country': 'USA'}]}]

Create 2 records from JSON Array having Structs

I have a JSON array which is in format below:
{
"id": "1",
"active": "True",
"gender": "female",
"coding": [
{
"system": "http://loinc.org",
"code": "8310-5",
"display": "Body temperature"
},
{
"system": "http://loinc.org",
"code": "8716-3",
"display": "Vital Signs grouping"
}
]
}
- I need output as two records. is it possible can someone help me with the Python code
{"id": "1","active": "True","gender": "female",{"system": "http://loinc.org","code": "8310-5","display": "Body temperature"},
{"id": "1","active": "True","gender": "female",{"system": "http://loinc.org","code": "8716-3","display": "Vital Signs grouping"}

I'm going to assume you want the codings in their own key since your question wasn't clear
import json
obj = json.loads(s) # where s is your json string
objs = [] # where we will store the results
for coding in obj['coding']:
new_obj = obj.copy()
new_obj['coding'] = coding # set the coding entry to one coding
objs.append(new_obj)
Output of objs:
[{'active': 'True',
'coding': {'code': '8310-5',
'display': 'Body temperature',
'system': 'http://loinc.org'},
'gender': 'female',
'id': '1'},
{'active': 'True',
'coding': {'code': '8716-3',
'display': 'Vital Signs grouping',
'system': 'http://loinc.org'},
'gender': 'female',
'id': '1'}]
If you want just a flat dict then
objs = []
for coding in obj['coding']:
new_obj = obj.copy()
del new_obj['coding']
new_obj.update(coding)
objs.append(new_obj)
Now objs is:
[{'active': 'True',
'code': '8310-5',
'display': 'Body temperature',
'gender': 'female',
'id': '1',
'system': 'http://loinc.org'},
{'active': 'True',
'code': '8716-3',
'display': 'Vital Signs grouping',
'gender': 'female',
'id': '1',
'system': 'http://loinc.org'}]

You can do it like this:
import json
input_dict = json.loads(myjson)
base = input_dict.copy()
base.pop('coding')
output = [dict(base, **c) for c in input_dict['coding']]
print(output)
Output:
[{'active': 'True', 'code': '8310-5', 'display': 'Body temperature', 'gender': 'female', 'id': '1', 'system': 'http://loinc.org'},
{'active': 'True', 'code': '8716-3', 'display': 'Vital Signs grouping', 'gender': 'female', 'id': '1', 'system': 'http://loinc.org'}]