Question: BackgroundI have a complex nested JSON object, which I am trying to unpack into a pandas df in a very specific way. JSON Objectthis is an extract, containing randomized data of the JSON object, which shows examples of the hierarchy (inc. children) for 1x family (i.e. 'Falconer Family'), however there is 100s of them in total and this extract just has 1x family, however the full JSON object has multiple - { "meta": { "columns": [{ "key": "value", "display_name": "Adjusted Value (No Div, USD)", "output_type": "Number", "currency": "USD" }, { "key": "time_weighted_return", "display_name": "Current Quarter TWR (USD)", "output_type": "Percent", "currency": "USD" }, { "key": "time_weighted_return_2", "display_name": "YTD TWR (USD)", "output_type": "Percent", "currency": "USD" }, { "key": "_custom_twr_audit_note_911328", "display_name": "TWR Audit Note", "output_type": "Word" } ], "groupings": [{ "key": "_custom_name_747205", "display_name": "* Reporting Client Name" }, { "key": "_custom_new_entity_group_453577", "display_name": "NEW Entity Group" }, { "key": "_custom_level_2_624287", "display_name": "* Level 2" }, { "key": "legal_entity", "display_name": "Legal Entity" } ] }, "data": { "type": "portfolio_views", "attributes": { "total": { "name": "Total", "columns": { "time_weighted_return": -0.046732301295604683, "time_weighted_return_2": -0.046732301295604683, "_custom_twr_audit_note_911328": null, "value": 23132492.905107163 }, "children": [{ "name": "Falconer Family", "grouping": "_custom_name_747205", "columns": { "time_weighted_return": -0.046732301295604683, "time_weighted_return_2": -0.046732301295604683, "_custom_twr_audit_note_911328": null, "value": 23132492.905107163 }, "children": [{ "name": "Wealth Bucket A", "grouping": "_custom_new_entity_group_453577", "columns": { "time_weighted_return": -0.045960317420568164, "time_weighted_return_2": -0.045960317420568164, "_custom_twr_audit_note_911328": null, "value": 13264448.506587159 }, "children": [{ "name": "Asset Class A", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": 0.000003434094574039648, "time_weighted_return_2": 0.000003434094574039648, "_custom_twr_audit_note_911328": null, "value": 3337.99 }, "children": [{ "entity_id": 10604454, "name": "HUDJ Trust", "grouping": "legal_entity", "columns": { "time_weighted_return": 0.000003434094574039648, "time_weighted_return_2": 0.000003434094574039648, "_custom_twr_audit_note_911328": null, "value": 3337.99 }, "children": [] }] }, { "name": "Asset Class B", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.025871339096964152, "time_weighted_return_2": -0.025871339096964152, "_custom_twr_audit_note_911328": null, "value": 1017004.7192636987 }, "children": [{ "entity_id": 10604454, "name": "HUDG Trust", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.025871339096964152, "time_weighted_return_2": -0.025871339096964152, "_custom_twr_audit_note_911328": null, "value": 1017004.7192636987 }, "children": [] }] }, { "name": "Asset Class C", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.030370376329670656, "time_weighted_return_2": -0.030370376329670656, "_custom_twr_audit_note_911328": null, "value": 231142.67772000004 }, "children": [{ "entity_id": 10604454, "name": "HKDJ Trust", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.030370376329670656, "time_weighted_return_2": -0.030370376329670656, "_custom_twr_audit_note_911328": null, "value": 231142.67772000004 }, "children": [] }] }, { "name": "Asset Class D", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.05382756475465478, "time_weighted_return_2": -0.05382756475465478, "_custom_twr_audit_note_911328": null, "value": 9791282.570000006 }, "children": [{ "entity_id": 10604454, "name": "HUDW Trust", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.05382756475465478, "time_weighted_return_2": -0.05382756475465478, "_custom_twr_audit_note_911328": null, "value": 9791282.570000006 }, "children": [] }] }, { "name": "Asset Class E", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.01351630404081805, "time_weighted_return_2": -0.01351630404081805, "_custom_twr_audit_note_911328": null, "value": 2153366.6396034593 }, "children": [{ "entity_id": 10604454, "name": "HJDJ Trust", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.01351630404081805, "time_weighted_return_2": -0.01351630404081805, "_custom_twr_audit_note_911328": null, "value": 2153366.6396034593 }, "children": [] }] }, { "name": "Asset Class F", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.002298190175237247, "time_weighted_return_2": -0.002298190175237247, "_custom_twr_audit_note_911328": null, "value": 68313.90999999999 }, "children": [{ "entity_id": 10604454, "name": "HADJ Trust", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.002298190175237247, "time_weighted_return_2": -0.002298190175237247, "_custom_twr_audit_note_911328": null, "value": 68313.90999999999 }, "children": [] }] } ] }, { "name": "Wealth Bucket B", "grouping": "_custom_new_entity_group_453577", "columns": { "time_weighted_return": -0.04769870075659244, "time_weighted_return_2": -0.04769870075659244, "_custom_twr_audit_note_911328": null, "value": 9868044.398519998 }, "children": [{ "name": "Asset Class A", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": 0.000028632718065191298, "time_weighted_return_2": 0.000028632718065191298, "_custom_twr_audit_note_911328": null, "value": 10234.94 }, "children": [{ "entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": 0.0000282679297198829, "time_weighted_return_2": 0.0000282679297198829, "_custom_twr_audit_note_911328": null, "value": 244.28 }, "children": [] }, { "entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": 0.000049373572795108345, "time_weighted_return_2": 0.000049373572795108345, "_custom_twr_audit_note_911328": null, "value": 5081.08 }, "children": [] }, { "entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": { "time_weighted_return": 0.000006609603754315074, "time_weighted_return_2": 0.000006609603754315074, "_custom_twr_audit_note_911328": null, "value": 1523.62 }, "children": [] }, { "entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": { "time_weighted_return": 0.000010999769004760296, "time_weighted_return_2": 0.000010999769004760296, "_custom_twr_audit_note_911328": null, "value": 1828.9 }, "children": [] }, { "entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": { "time_weighted_return": 0.000006466673995619843, "time_weighted_return_2": 0.000006466673995619843, "_custom_twr_audit_note_911328": null, "value": 1557.06 }, "children": [] } ] }, { "name": "Asset Class B", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.024645947842438676, "time_weighted_return_2": -0.024645947842438676, "_custom_twr_audit_note_911328": null, "value": 674052.31962 }, "children": [{ "entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.043304004172576405, "time_weighted_return_2": -0.043304004172576405, "_custom_twr_audit_note_911328": null, "value": 52800.96 }, "children": [] }, { "entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.022408434778798836, "time_weighted_return_2": -0.022408434778798836, "_custom_twr_audit_note_911328": null, "value": 599594.11962 }, "children": [] }, { "entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.039799855483646174, "time_weighted_return_2": -0.039799855483646174, "_custom_twr_audit_note_911328": null, "value": 7219.08 }, "children": [] }, { "entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.039799855483646174, "time_weighted_return_2": -0.039799855483646174, "_custom_twr_audit_note_911328": null, "value": 7219.08 }, "children": [] }, { "entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.039799855483646174, "time_weighted_return_2": -0.039799855483646174, "_custom_twr_audit_note_911328": null, "value": 7219.08 }, "children": [] } ] }, { "name": "Asset Class C", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.03037038746301135, "time_weighted_return_2": -0.03037038746301135, "_custom_twr_audit_note_911328": null, "value": 114472.69744 }, "children": [{ "entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.030370390035505124, "time_weighted_return_2": -0.030370390035505124, "_custom_twr_audit_note_911328": null, "value": 114472.68744000001 }, "children": [] }, { "entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": 0, "time_weighted_return_2": 0, "_custom_twr_audit_note_911328": null, "value": 0.01 }, "children": [] } ] }, { "name": "Asset Class D", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.06604362523792162, "time_weighted_return_2": -0.06604362523792162, "_custom_twr_audit_note_911328": null, "value": 5722529.229999997 }, "children": [{ "entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.06154960593668424, "time_weighted_return_2": -0.06154960593668424, "_custom_twr_audit_note_911328": null, "value": 1191838.9399999995 }, "children": [] }, { "entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.06750460387418267, "time_weighted_return_2": -0.06750460387418267, "_custom_twr_audit_note_911328": null, "value": 4416618.520000002 }, "children": [] }, { "entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.05604507809250081, "time_weighted_return_2": -0.05604507809250081, "_custom_twr_audit_note_911328": null, "value": 38190.33 }, "children": [] }, { "entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.05604507809250081, "time_weighted_return_2": -0.05604507809250081, "_custom_twr_audit_note_911328": null, "value": 37940.72 }, "children": [] }, { "entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.05604507809250081, "time_weighted_return_2": -0.05604507809250081, "_custom_twr_audit_note_911328": null, "value": 37940.72 }, "children": [] } ] }, { "name": "Asset Class E", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.017118805423322003, "time_weighted_return_2": -0.017118805423322003, "_custom_twr_audit_note_911328": null, "value": 3148495.0914600003 }, "children": [{ "entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.015251157805867277, "time_weighted_return_2": -0.015251157805867277, "_custom_twr_audit_note_911328": null, "value": 800493.06146 }, "children": [] }, { "entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.01739609576880241, "time_weighted_return_2": -0.01739609576880241, "_custom_twr_audit_note_911328": null, "value": 2215511.2700000005 }, "children": [] }, { "entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.02085132265594647, "time_weighted_return_2": -0.02085132265594647, "_custom_twr_audit_note_911328": null, "value": 44031.21 }, "children": [] }, { "entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.02089393244695803, "time_weighted_return_2": -0.02089393244695803, "_custom_twr_audit_note_911328": null, "value": 44394.159999999996 }, "children": [] }, { "entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.020607507059866248, "time_weighted_return_2": -0.020607507059866248, "_custom_twr_audit_note_911328": null, "value": 44065.39000000001 }, "children": [] } ] }, { "name": "Asset Class F", "grouping": "_custom_level_2_624287", "columns": { "time_weighted_return": -0.0014710489231547497, "time_weighted_return_2": -0.0014710489231547497, "_custom_twr_audit_note_911328": null, "value": 198260.12 }, "children": [{ "entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.0014477244560456848, "time_weighted_return_2": -0.0014477244560456848, "_custom_twr_audit_note_911328": null, "value": 44612.33 }, "children": [] }, { "entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": { "time_weighted_return": -0.001477821083437858, "time_weighted_return_2": -0.001477821083437858, "_custom_twr_audit_note_911328": null, "value": 153647.78999999998 }, "children": [] } ] } ] } ] }] } }, "included": [] } }  Notes on JSON Object extract  data - data in here can be ignored, these are aggregated values for underlying children. meta - columns – contains the column header values I want to use for each applicable children ‘column` key:pair values. groupings - can be ignored. children hierarchy – there are 4x levels of children which can be identified by their name as follows –  Family name (i.e., ‘Falconer Family’) Wealth Bucket name (e.g., ‘Wealth Bucket A’) Asset Class name (e.g., ‘Asset Class A’) Fund name (e.g., ‘HUDJ Trust’)    Target Outputthis is an extract of target df structure I am trying to achieve -     portfolio name entity_id Adjusted Value (No Div, USD) Current Quarter TWR (USD) YTD TWR (USD) TWR Audit Note     Falconer Family Falconer Family  23132492.90510712 -0.046732301295604683 -0.046732301295604683 None   Falconer Family Wealth Bucket A  13264448.506587146 -0.045960317420568164 -0.045960317420568164 None   Falconer Family Asset Class A  3337.99 0.000003434094574039648 0.000003434094574039648 None   Falconer Family HUDJ Trust 10604454 3337.99 0.000003434094574039648 0.000003434094574039648 None   Falconer Family Asset Class B  1017004.7192636987 -0.025871339096964152 -0.025871339096964152 None   Falconer Family HUDG Trust 10604454 1017004.7192636987 -0.025871339096964152 -0.025871339096964152 None   Falconer Family Asset Class C  231142.67772000004 -0.030370376329670656 -0.030370376329670656 None   Falconer Family HKDJ Trust 10604454 231142.67772000004 -0.030370376329670656 -0.030370376329670656 None   Falconer Family Asset Class D  9791282.570000006 -0.05382756475465478 -0.05382756475465478 None   Falconer Family HUDW Trust 10604454 9791282.570000006 -0.05382756475465478 -0.05382756475465478 None     Notes on Target Output  Portfolio header – for every row, I would like to map the top-level children name value [family name]. E.g., ‘Falconer Family. Name header – this should simply be the name value from each respective children. Entity ID – all 4th level children entity_id value should be mapped to this column. Data columns – regardless of level, all children have identical time_weighted_return, time-weighted_return2 and value columns which should be mapped respectively. TWR Audit Note – these children _custom_twr_audit_note_911318 values are currently blank, but will be utilized in the future.  Current OutputMy main issue is that you can see that I have only been able to tap into the 1st [Family] and 2nd [Wealth Bucket] children level. This leaves me missing the 3rd [Asset Class] and 4th [Fund] -      portfolio name Adjusted Value (No Div, USD) Current Quarter TWR (USD) YTD TWR (USD) TWR Audit Note)     0 Falconer Family Falconer Family 2.313249e+07 -0.046732 -0.046732 None   1 Falconer Family Wealth Bucket A 1.326445e+07 -0.045960 -0.045960 None   2 Falconer Family Wealth Bucket B 9.868044e+06 -0.047699 -0.047699 None     Current codeThis is a function which gets me the correct df formatting, however my main issue is that I haven't been able to find a solution to returning all children, but rather only the top-level - # Function to read API response / JSON Object def response_writer(): with open('api_response_2022-02-13.json') as f: api_response = json.load(f) return api_response # Function to unpack JSON response into pandas dataframe. def unpack_response(): while True: try: api_response = response_writer() portfolio_views_children = api_response['data']['attributes']['total']['children'] portfolios = [] for portfolio in portfolio_views_children: entity_columns = [] # include portfolio itself within an iterable so the total is the header for entity in itertools.chain([portfolio], portfolio["children"]): entity_data = entity["columns"].copy() # don't mutate original response entity_data["portfolio"] = portfolio["name"] # from outer entity_data["name"] = entity["name"] entity_columns.append(entity_data) df = pd.DataFrame(entity_columns) portfolios.append(df) # combine dataframes df = pd.concat(portfolios) # reorder and rename column_ordering = {"portfolio": "portfolio", "name": "name"} column_ordering.update({c["key"]: c["display_name"] for c in api_response["meta"]["columns"]}) df = df[column_ordering.keys()] # beware: un-named cols will be dropped df = df.rename(columns=column_ordering) break except KeyError: print("-----------------------------------\n","API TIMEOUT ERROR: TRY AGAIN...", "\n-----------------------------------\n") return df unpack_response()  HelpIn short, I am looking for some advice on how I can tap into the remaining children by enhancing the existing code. Whilst I have taken much time to fully explain my problem, please ask if anything isn't clear. Please note that the JSON may have multiple families, so the solution / advice offered must observe this

Answer: jsonpath-ng can parse even such a nested json object very easily. You can install this convenient library by the following command: pip install --upgrade jsonpath-ng  Code: import json import jsonpath_ng as jp import pandas as pd def unpack_response(r): # Create a dataframe from extracted data expr = jp.parse('$..children.[*]') data = [{'full_path': str(m.full_path), **m.value} for m in expr.find(r)] df = pd.json_normalize(data).sort_values('full_path', ignore_index=True) # Append a portfolio column df['portfolio'] = df.loc[df.full_path.str.contains(r'total\.children\.\[\d+]$'), 'name'] df['portfolio'].fillna(method='ffill', inplace=True) # Deal with columns trans = {'columns.' + c['key']: c['display_name'] for c in r['meta']['columns']} cols = ['full_path', 'portfolio', 'name', 'entity_id', 'Adjusted Value (No Div, USD)', 'Current Quarter TWR (USD)', 'YTD TWR (USD)', 'TWR Audit Note'] df = df.rename(columns=trans)[cols] return df # Load the sample data from file # with open('api_response_2022-02-13.json', 'r') as f: # api_response = json.load(f) # Load the sample data from string api_response = json.loads('{"meta": {"columns": [{"key": "value", "display_name": "Adjusted Value (No Div, USD)", "output_type": "Number", "currency": "USD"}, {"key": "time_weighted_return", "display_name": "Current Quarter TWR (USD)", "output_type": "Percent", "currency": "USD"}, {"key": "time_weighted_return_2", "display_name": "YTD TWR (USD)", "output_type": "Percent", "currency": "USD"}, {"key": "_custom_twr_audit_note_911328", "display_name": "TWR Audit Note", "output_type": "Word"}], "groupings": [{"key": "_custom_name_747205", "display_name": "* Reporting Client Name"}, {"key": "_custom_new_entity_group_453577", "display_name": "NEW Entity Group"}, {"key": "_custom_level_2_624287", "display_name": "* Level 2"}, {"key": "legal_entity", "display_name": "Legal Entity"}]}, "data": {"type": "portfolio_views", "attributes": {"total": {"name": "Total", "columns": {"time_weighted_return": -0.046732301295604683, "time_weighted_return_2": -0.046732301295604683, "_custom_twr_audit_note_911328": null, "value": 23132492.905107163}, "children": [{"name": "Falconer Family", "grouping": "_custom_name_747205", "columns": {"time_weighted_return": -0.046732301295604683, "time_weighted_return_2": -0.046732301295604683, "_custom_twr_audit_note_911328": null, "value": 23132492.905107163}, "children": [{"name": "Wealth Bucket A", "grouping": "_custom_new_entity_group_453577", "columns": {"time_weighted_return": -0.045960317420568164, "time_weighted_return_2": -0.045960317420568164, "_custom_twr_audit_note_911328": null, "value": 13264448.506587159}, "children": [{"name": "Asset Class A", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": 3.434094574039648e-06, "time_weighted_return_2": 3.434094574039648e-06, "_custom_twr_audit_note_911328": null, "value": 3337.99}, "children": [{"entity_id": 10604454, "name": "HUDJ Trust", "grouping": "legal_entity", "columns": {"time_weighted_return": 3.434094574039648e-06, "time_weighted_return_2": 3.434094574039648e-06, "_custom_twr_audit_note_911328": null, "value": 3337.99}, "children": []}]}, {"name": "Asset Class B", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.025871339096964152, "time_weighted_return_2": -0.025871339096964152, "_custom_twr_audit_note_911328": null, "value": 1017004.7192636987}, "children": [{"entity_id": 10604454, "name": "HUDG Trust", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.025871339096964152, "time_weighted_return_2": -0.025871339096964152, "_custom_twr_audit_note_911328": null, "value": 1017004.7192636987}, "children": []}]}, {"name": "Asset Class C", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.030370376329670656, "time_weighted_return_2": -0.030370376329670656, "_custom_twr_audit_note_911328": null, "value": 231142.67772000004}, "children": [{"entity_id": 10604454, "name": "HKDJ Trust", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.030370376329670656, "time_weighted_return_2": -0.030370376329670656, "_custom_twr_audit_note_911328": null, "value": 231142.67772000004}, "children": []}]}, {"name": "Asset Class D", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.05382756475465478, "time_weighted_return_2": -0.05382756475465478, "_custom_twr_audit_note_911328": null, "value": 9791282.570000006}, "children": [{"entity_id": 10604454, "name": "HUDW Trust", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.05382756475465478, "time_weighted_return_2": -0.05382756475465478, "_custom_twr_audit_note_911328": null, "value": 9791282.570000006}, "children": []}]}, {"name": "Asset Class E", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.01351630404081805, "time_weighted_return_2": -0.01351630404081805, "_custom_twr_audit_note_911328": null, "value": 2153366.6396034593}, "children": [{"entity_id": 10604454, "name": "HJDJ Trust", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.01351630404081805, "time_weighted_return_2": -0.01351630404081805, "_custom_twr_audit_note_911328": null, "value": 2153366.6396034593}, "children": []}]}, {"name": "Asset Class F", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.002298190175237247, "time_weighted_return_2": -0.002298190175237247, "_custom_twr_audit_note_911328": null, "value": 68313.90999999999}, "children": [{"entity_id": 10604454, "name": "HADJ Trust", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.002298190175237247, "time_weighted_return_2": -0.002298190175237247, "_custom_twr_audit_note_911328": null, "value": 68313.90999999999}, "children": []}]}]}, {"name": "Wealth Bucket B", "grouping": "_custom_new_entity_group_453577", "columns": {"time_weighted_return": -0.04769870075659244, "time_weighted_return_2": -0.04769870075659244, "_custom_twr_audit_note_911328": null, "value": 9868044.398519998}, "children": [{"name": "Asset Class A", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": 2.8632718065191298e-05, "time_weighted_return_2": 2.8632718065191298e-05, "_custom_twr_audit_note_911328": null, "value": 10234.94}, "children": [{"entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": 2.82679297198829e-05, "time_weighted_return_2": 2.82679297198829e-05, "_custom_twr_audit_note_911328": null, "value": 244.28}, "children": []}, {"entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": 4.9373572795108345e-05, "time_weighted_return_2": 4.9373572795108345e-05, "_custom_twr_audit_note_911328": null, "value": 5081.08}, "children": []}, {"entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": {"time_weighted_return": 6.609603754315074e-06, "time_weighted_return_2": 6.609603754315074e-06, "_custom_twr_audit_note_911328": null, "value": 1523.62}, "children": []}, {"entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": {"time_weighted_return": 1.0999769004760296e-05, "time_weighted_return_2": 1.0999769004760296e-05, "_custom_twr_audit_note_911328": null, "value": 1828.9}, "children": []}, {"entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": {"time_weighted_return": 6.466673995619843e-06, "time_weighted_return_2": 6.466673995619843e-06, "_custom_twr_audit_note_911328": null, "value": 1557.06}, "children": []}]}, {"name": "Asset Class B", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.024645947842438676, "time_weighted_return_2": -0.024645947842438676, "_custom_twr_audit_note_911328": null, "value": 674052.31962}, "children": [{"entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.043304004172576405, "time_weighted_return_2": -0.043304004172576405, "_custom_twr_audit_note_911328": null, "value": 52800.96}, "children": []}, {"entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.022408434778798836, "time_weighted_return_2": -0.022408434778798836, "_custom_twr_audit_note_911328": null, "value": 599594.11962}, "children": []}, {"entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.039799855483646174, "time_weighted_return_2": -0.039799855483646174, "_custom_twr_audit_note_911328": null, "value": 7219.08}, "children": []}, {"entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.039799855483646174, "time_weighted_return_2": -0.039799855483646174, "_custom_twr_audit_note_911328": null, "value": 7219.08}, "children": []}, {"entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.039799855483646174, "time_weighted_return_2": -0.039799855483646174, "_custom_twr_audit_note_911328": null, "value": 7219.08}, "children": []}]}, {"name": "Asset Class C", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.03037038746301135, "time_weighted_return_2": -0.03037038746301135, "_custom_twr_audit_note_911328": null, "value": 114472.69744}, "children": [{"entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.030370390035505124, "time_weighted_return_2": -0.030370390035505124, "_custom_twr_audit_note_911328": null, "value": 114472.68744000001}, "children": []}, {"entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": 0, "time_weighted_return_2": 0, "_custom_twr_audit_note_911328": null, "value": 0.01}, "children": []}]}, {"name": "Asset Class D", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.06604362523792162, "time_weighted_return_2": -0.06604362523792162, "_custom_twr_audit_note_911328": null, "value": 5722529.229999997}, "children": [{"entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.06154960593668424, "time_weighted_return_2": -0.06154960593668424, "_custom_twr_audit_note_911328": null, "value": 1191838.9399999995}, "children": []}, {"entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.06750460387418267, "time_weighted_return_2": -0.06750460387418267, "_custom_twr_audit_note_911328": null, "value": 4416618.520000002}, "children": []}, {"entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.05604507809250081, "time_weighted_return_2": -0.05604507809250081, "_custom_twr_audit_note_911328": null, "value": 38190.33}, "children": []}, {"entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.05604507809250081, "time_weighted_return_2": -0.05604507809250081, "_custom_twr_audit_note_911328": null, "value": 37940.72}, "children": []}, {"entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.05604507809250081, "time_weighted_return_2": -0.05604507809250081, "_custom_twr_audit_note_911328": null, "value": 37940.72}, "children": []}]}, {"name": "Asset Class E", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.017118805423322003, "time_weighted_return_2": -0.017118805423322003, "_custom_twr_audit_note_911328": null, "value": 3148495.0914600003}, "children": [{"entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.015251157805867277, "time_weighted_return_2": -0.015251157805867277, "_custom_twr_audit_note_911328": null, "value": 800493.06146}, "children": []}, {"entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.01739609576880241, "time_weighted_return_2": -0.01739609576880241, "_custom_twr_audit_note_911328": null, "value": 2215511.2700000005}, "children": []}, {"entity_id": 10598341, "name": "Cht 11th Tr HBO Shirley", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.02085132265594647, "time_weighted_return_2": -0.02085132265594647, "_custom_twr_audit_note_911328": null, "value": 44031.21}, "children": []}, {"entity_id": 10598337, "name": "Cht 11th Tr HBO Hannah", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.02089393244695803, "time_weighted_return_2": -0.02089393244695803, "_custom_twr_audit_note_911328": null, "value": 44394.159999999996}, "children": []}, {"entity_id": 10598334, "name": "Cht 11th Tr HBO Lau", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.020607507059866248, "time_weighted_return_2": -0.020607507059866248, "_custom_twr_audit_note_911328": null, "value": 44065.39000000001}, "children": []}]}, {"name": "Asset Class F", "grouping": "_custom_level_2_624287", "columns": {"time_weighted_return": -0.0014710489231547497, "time_weighted_return_2": -0.0014710489231547497, "_custom_twr_audit_note_911328": null, "value": 198260.12}, "children": [{"entity_id": 10868778, "name": "2012 Desc Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.0014477244560456848, "time_weighted_return_2": -0.0014477244560456848, "_custom_twr_audit_note_911328": null, "value": 44612.33}, "children": []}, {"entity_id": 10643052, "name": "2013 Irrev Tr HBO Thalia", "grouping": "legal_entity", "columns": {"time_weighted_return": -0.001477821083437858, "time_weighted_return_2": -0.001477821083437858, "_custom_twr_audit_note_911328": null, "value": 153647.78999999998}, "children": []}]}]}]}]}}, "included": []}}') df = unpack_response(api_response)  Explanation: Firstly, you can confirm the expected output by the following command: print(df.iloc[:5:,1:])      portfolio name entity_id Adjusted Value (No Div, USD) Current Quarter TWR (USD) YTD TWR (USD) TWR Audit Note     Falconer Family Falconer Family nan 2.31325e+07 -0.0467323 -0.0467323    Falconer Family Wealth Bucket A nan 1.32644e+07 -0.0459603 -0.0459603    Falconer Family Asset Class A nan 3337.99 3.43409e-06 3.43409e-06    Falconer Family HUDJ Trust 1.06045e+07 3337.99 3.43409e-06 3.43409e-06    Falconer Family Asset Class B nan 1.017e+06 -0.0258713 -0.0258713      Subsequently, you can see one of the wonderful features in jsonpath-ng by the following command: print(df.iloc[:10,:3])      full_path portfolio name     data.attributes.total.children.[0] Falconer Family Falconer Family   data.attributes.total.children.[0].children.[0] Falconer Family Wealth Bucket A   data.attributes.total.children.[0].children.[0].children.[0] Falconer Family Asset Class A   data.attributes.total.children.[0].children.[0].children.[0].children.[0] Falconer Family HUDJ Trust   data.attributes.total.children.[0].children.[0].children.[1] Falconer Family Asset Class B   data.attributes.total.children.[0].children.[0].children.[1].children.[0] Falconer Family HUDG Trust   data.attributes.total.children.[0].children.[0].children.[2] Falconer Family Asset Class C   data.attributes.total.children.[0].children.[0].children.[2].children.[0] Falconer Family HKDJ Trust   data.attributes.total.children.[0].children.[0].children.[3] Falconer Family Asset Class D   data.attributes.total.children.[0].children.[0].children.[3].children.[0] Falconer Family HUDW Trust     Thanks to the full_path column, you can grasp the nesting level of the extracted data in each row instantaneously. Actually, I appended the correct portfolio values by using these paths. In terms of the code, the key point is the following line: expr = jp.parse('$..children.[*]')  By the above expression, you can search the children attributes at any level of the json object. README.rst tells you what each syntax stands for.     Syntax Meaning     $ The root object   jsonpath1 .. jsonpath2 All nodes matched by jsonpath2 that descend from any node matching jsonpath1   [*] any array index    Speed: I compared the speed between the above method with jsonpath-ng and a nested-for-loop method shown below. # Comparison:     Method Duration Speed ratio     jsonpath-ng 9.72 ms ± 342 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) 5.7 (faster)   Nested-for-loop 55.4 ms ± 7.39 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) 1    # Code of the nested-for-loop method: def unpack_response(r): df = pd.DataFrame() for _, r1 in pd.json_normalize(r, ['data', 'attributes', 'total', 'children']).iterrows(): r1['portfolio'] = r1['name'] df = df.append(r1) for _, r2 in pd.json_normalize(r1.children).iterrows(): df = df.append(r2) for _, r3 in pd.json_normalize(r2.children).iterrows(): df = df.append(r3).append(pd.json_normalize(r3.children)) df['portfolio'].fillna(method='ffill', inplace=True) trans = {'columns.' + c['key']: c['display_name'] for c in r['meta']['columns']} cols = ['portfolio', 'name', 'entity_id', 'Adjusted Value (No Div, USD)', 'Current Quarter TWR (USD)', 'YTD TWR (USD)', 'TWR Audit Note'] df = df.rename(columns=trans)[cols].reset_index(drop=True) return df