Pandas dataframe to a dynamic nested JSON

Question

I want to create my dataframe which looks like this:

    employeeId  firstName   lastName    emailAddress    isDependent employeeIdTypeCode  entityCode  sour         


        

Answer 1

Perhaps you can iterate over a group by, then do another iteration for each row within that group. Thus, creating a nested dictionary structure:

This explains one way going through with it:

import pandas as pd
df = pd.DataFrame({"entityCode":[1,1,3,3],"sourceCode":[4,4,6,6],'identityTypeCode':[7,8,9,10]})
results = []
for i, sub_df in df.groupby(["entityCode","sourceCode"]):
    entityCode, sourceCode = i
    d = {}
    d["individualInfo"] = {"entityCode":entityCode, "sourceCode":sourceCode}
    sub_result = []
    for _, row in sub_df[["identityTypeCode"]].drop_duplicates().iterrows():
        sub_result.append(row.to_dict())
    d["individualIdentifier"] = sub_result
    results.append(d)
results

which returns something like this:

[{'individualInfo': {'entityCode': 1, 'sourceCode': 4},
  'individualIdentifier': [{'identityTypeCode': 7}, {'identityTypeCode': 8}]},
 {'individualInfo': {'entityCode': 3, 'sourceCode': 6},
  'individualIdentifier': [{'identityTypeCode': 9}, {'identityTypeCode': 10}]}]

afterwards, you can convert the dictionary to json.