Hi team,
It worked for me this way:
df3 = pd.json_normalize(json2["value"], "Addresses")
print(df3)
ContactId AssociatedEntity
0 35aa05d1-21c7-493d-96e3-00003c966732
ac7a9ec8-b71b-486b-8b3b-41b6bc11f936
1 ca717463-734d-4f2f-a01e-00006ff0c806
bda08493-7ae0-47cf-8d3a-f1a486498836
Solved.
On 2021-07-12 12:07, Marchello wrote:
Hi team,
My need is to extract particular sub-elements (ContactId and
AssociatedEntity) from below json using pandas.
Json:
{
"odata.metadata": "https://example1.com/odata/$metadata#Contacts";,
"value": [
{
"Addresses": [
{
"ContactId": "35aa05d1-21c7-493d-96e3-00003c966732",
"AssociatedEntity": "ac7a9ec8-b71b-486b-8b3b-41b6bc11f936"
}
],
"ContactId2": "35aa05d1-21c7-493d-96e3-00003c966732"
},
{
"Addresses": [
{
"ContactId": "ca717463-734d-4f2f-a01e-00006ff0c806",
"AssociatedEntity": "bda08493-7ae0-47cf-8d3a-f1a486498836"
}
],
"ContactId2": "ca717463-734d-4f2f-a01e-00006ff0c806"
}
]
}
My code so far:
import json
import pandas as pd
txt1 =
'{"odata.metadata":"https://example1.com/odata/$metadata#Contacts","value":[
{ "Addresses":[ {
"ContactId":"35aa05d1-21c7-493d-96e3-00003c966732","AssociatedEntity":"ac7a9ec8-b71b-486b-8b3b-41b6bc11f936"
} ],"ContactId2":"35aa05d1-21c7-493d-96e3-00003c966732"
},{ "Addresses":[ {
"ContactId":"ca717463-734d-4f2f-a01e-00006ff0c806","AssociatedEntity":"bda08493-7ae0-47cf-8d3a-f1a486498836"
} ],"ContactId2":"ca717463-734d-4f2f-a01e-00006ff0c806"
}]}'
json2 = json.loads(txt1)
print("json:\n")
print(json2)
df = pd.json_normalize(json2['value'])
print("\npandas df (1):\n")
df1a = df['Addresses'].copy()
print(df1a)
pandas df (1):
0 [{'ContactId': '35aa05d1-21c7-493d-96e3-00003c...
1 [{'ContactId': 'ca717463-734d-4f2f-a01e-00006f...
Name: Addresses, dtype: object
Now how do I get ContactId and AssociatedEntity?
Please advise.
Best,
Marchello
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