Question: This post was edited to grab the actual JSON file (large) instead of the sample snippet that I extracted,(which works in this post). I was wondering why I get a key error when i use record_path on this data set. under the results key there are 2 nested keys named 'active_ingredients' and 'packaging' when i normalize i get result = pd.json_normalize(data['results'], record_path=["packaging"],meta=['product_ndc'])  the expected columns package_ndc description marketing_start_date sample marketing_end_date product_ndcs  but when i add active_ingredients to the record_path list i get a key error. The same goes for meta as well. When i add the other columns like 'brand_name' and 'generic_name' to the meta list, I get a key error. to see the keys this doesnt work result = pd.json_normalize(data['results'], record_path=["packaging","active_ingredients"],meta=['product_ndc','brand_name','generic_name'])  Thanks for any help Here is the actual code I use to grab the data which produces the key error. import pandas as pd import json import requests, zipfile, io, os cwd = os.getcwd() zip_url = 'https://download.open.fda.gov/drug/ndc/drug-ndc-0001-of-0001.json.zip' r = requests.get(zip_url) z = zipfile.ZipFile(io.BytesIO(r.content)) z.extractall(cwd) with open('drug-ndc-0001-of-0001.json', 'r') as file: data = json.load(file) packaging_data = pd.json_normalize( data['results'], record_path=["packaging"], meta=['product_ndc', 'brand_name', 'generic_name'] ) active_ingredients_data = pd.json_normalize( data['results'], record_path=["active_ingredients"], meta=['product_ndc', 'brand_name', 'generic_name'] )  i paired it with your answer and getting the same issues I had before I posted the question.

Answer: When you specify multiple record_path entries (like "packaging" and "active_ingredients"), pandas expects that the second record_path ("active_ingredients") exists within every element of the first record_path ("packaging"), but, in your data, active_ingredients is not a nested property of packaging Do this to solve this import pandas as pd data = { "meta": { "disclaimer": "Do not rely on openFDA to make decisions regarding medical care. While we make every effort to ensure that data is accurate, you should assume all results are unvalidated. We may limit or otherwise restrict your access to the API in line with our Terms of Service.", "terms": "https://open.fda.gov/terms/", "license": "https://open.fda.gov/license/", "last_updated": "2024-11-15", "results": { "skip": 0, "limit": 2, "total": 118943 } }, "results": [ { "product_ndc": "73647-062", "generic_name": "MENTHOL, CAMPHOR", "labeler_name": "Just Brands LLC", "brand_name": "JUST CBD - CBD AND THC ULTRA RELIEF", "active_ingredients": [ { "name": "CAMPHOR (SYNTHETIC)", "strength": "2 g/100g" }, { "name": "MENTHOL", "strength": "6 g/100g" } ], "finished": True, "packaging": [ { "package_ndc": "73647-062-04", "description": "113 g in 1 BOTTLE, PUMP (73647-062-04)", "marketing_start_date": "20230314", "sample": False } ], "listing_expiration_date": "20251231", "openfda": { "manufacturer_name": ["Just Brands LLC"], "spl_set_id": ["f664eb79-8897-3a49-e053-2995a90a37b4"], "is_original_packager": [True], "unii": ["5TJD82A1ET", "L7T10EIP3A"] }, "marketing_category": "OTC MONOGRAPH DRUG", "dosage_form": "GEL", "spl_id": "16c906dd-6989-9a79-e063-6394a90afa71", "product_type": "HUMAN OTC DRUG", "route": ["TOPICAL"], "marketing_start_date": "20230314", "product_id": "73647-062_16c906dd-6989-9a79-e063-6394a90afa71", "application_number": "M017", "brand_name_base": "JUST CBD - CBD AND THC ULTRA RELIEF" }, { "product_ndc": "0591-4039", "marketing_end_date": "20250930", "generic_name": "CLOBETASOL PROPIONATE", "labeler_name": "Actavis Pharma, Inc.", "brand_name": "CLOBETASOL PROPIONATE", "active_ingredients": [ { "name": "CLOBETASOL PROPIONATE", "strength": ".05 g/mL" } ], "finished": True, "packaging": [ { "package_ndc": "0591-4039-46", "description": "1 BOTTLE in 1 CARTON (0591-4039-46) / 59 mL in 1 BOTTLE", "marketing_start_date": "20150828", "marketing_end_date": "20250930", "sample": False }, { "package_ndc": "0591-4039-74", "description": "1 BOTTLE in 1 CARTON (0591-4039-74) / 125 mL in 1 BOTTLE", "marketing_start_date": "20150828", "marketing_end_date": "20250930", "sample": False } ], "openfda": { "manufacturer_name": ["Actavis Pharma, Inc."], "rxcui": ["861512"], "spl_set_id": ["907e425a-720a-4180-b97c-9e25008a3658"], "is_original_packager": [True], "unii": ["779619577M"] }, "marketing_category": "NDA AUTHORIZED GENERIC", "dosage_form": "SPRAY", "spl_id": "33a56b8b-a9a6-4287-bbf4-d68ad0c59e07", "product_type": "HUMAN PRESCRIPTION DRUG", "route": ["TOPICAL"], "marketing_start_date": "20150828", "product_id": "0591-4039_33a56b8b-a9a6-4287-bbf4-d68ad0c59e07", "application_number": "NDA021835", "brand_name_base": "CLOBETASOL PROPIONATE", "pharm_class": [ "Corticosteroid Hormone Receptor Agonists [MoA]", "Corticosteroid [EPC]" ] } ] } packaging_data = pd.json_normalize( data['results'], record_path=["packaging"], meta=['product_ndc', 'brand_name', 'generic_name'] ) active_ingredients_data = pd.json_normalize( data['results'], record_path=["active_ingredients"], meta=['product_ndc', 'brand_name', 'generic_name'] ) combined_data = pd.merge( packaging_data, active_ingredients_data, on=['product_ndc', 'brand_name', 'generic_name'], how='outer' ) print(packaging_data) print(active_ingredients_data) print(combined_data)  which gives  package_ndc description \ 0 73647-062-04 113 g in 1 BOTTLE, PUMP (73647-062-04) 1 0591-4039-46 1 BOTTLE in 1 CARTON (0591-4039-46) / 59 mL i... 2 0591-4039-74 1 BOTTLE in 1 CARTON (0591-4039-74) / 125 mL ... marketing_start_date sample marketing_end_date product_ndc \ 0 20230314 False NaN 73647-062 1 20150828 False 20250930 0591-4039 2 20150828 False 20250930 0591-4039 brand_name generic_name 0 JUST CBD - CBD AND THC ULTRA RELIEF MENTHOL, CAMPHOR 1 CLOBETASOL PROPIONATE CLOBETASOL PROPIONATE 2 CLOBETASOL PROPIONATE CLOBETASOL PROPIONATE name strength product_ndc \ 0 CAMPHOR (SYNTHETIC) 2 g/100g 73647-062 1 MENTHOL 6 g/100g 73647-062 2 CLOBETASOL PROPIONATE .05 g/mL 0591-4039 brand_name generic_name 0 JUST CBD - CBD AND THC ULTRA RELIEF MENTHOL, CAMPHOR 1 JUST CBD - CBD AND THC ULTRA RELIEF MENTHOL, CAMPHOR 2 CLOBETASOL PROPIONATE CLOBETASOL PROPIONATE package_ndc description \ 0 0591-4039-46 1 BOTTLE in 1 CARTON (0591-4039-46) / 59 mL i... ... 0 CLOBETASOL PROPIONATE .05 g/mL 1 CLOBETASOL PROPIONATE .05 g/mL 2 CAMPHOR (SYNTHETIC) 2 g/100g 3 MENTHOL 6 g/100g  EDIT I changed the naming to mirror your changes in your edit: The first script uses the variable names packaging_df, active_ingredients_df, and combined_df for the DataFrames related to packaging, active_ingredients, and their merged result, respectively, whereas the second script uses packaging_data, active_ingredients_data, and combined_data for the same purposes. The difference lies solely in the naming conventions, with no impact on functionality or logic. The output is the same, so if you still experience issues, it must come from something else, probably in something you do before. import pandas as pd data = { "meta": { "disclaimer": "Do not rely on openFDA to make decisions regarding medical care. While we make every effort to ensure that data is accurate, you should assume all results are unvalidated. We may limit or otherwise restrict your access to the API in line with our Terms of Service.", "terms": "https://open.fda.gov/terms/", "license": "https://open.fda.gov/license/", "last_updated": "2024-11-15", "results": { "skip": 0, "limit": 2, "total": 118943 } }, "results": [ { "product_ndc": "73647-062", "generic_name": "MENTHOL, CAMPHOR", "labeler_name": "Just Brands LLC", "brand_name": "JUST CBD - CBD AND THC ULTRA RELIEF", "active_ingredients": [ { "name": "CAMPHOR (SYNTHETIC)", "strength": "2 g/100g" }, { "name": "MENTHOL", "strength": "6 g/100g" } ], "finished": True, "packaging": [ { "package_ndc": "73647-062-04", "description": "113 g in 1 BOTTLE, PUMP (73647-062-04)", "marketing_start_date": "20230314", "sample": False } ], "listing_expiration_date": "20251231", "openfda": { "manufacturer_name": ["Just Brands LLC"], "spl_set_id": ["f664eb79-8897-3a49-e053-2995a90a37b4"], "is_original_packager": [True], "unii": ["5TJD82A1ET", "L7T10EIP3A"] }, "marketing_category": "OTC MONOGRAPH DRUG", "dosage_form": "GEL", "spl_id": "16c906dd-6989-9a79-e063-6394a90afa71", "product_type": "HUMAN OTC DRUG", "route": ["TOPICAL"], "marketing_start_date": "20230314", "product_id": "73647-062_16c906dd-6989-9a79-e063-6394a90afa71", "application_number": "M017", "brand_name_base": "JUST CBD - CBD AND THC ULTRA RELIEF" }, { "product_ndc": "0591-4039", "marketing_end_date": "20250930", "generic_name": "CLOBETASOL PROPIONATE", "labeler_name": "Actavis Pharma, Inc.", "brand_name": "CLOBETASOL PROPIONATE", "active_ingredients": [ { "name": "CLOBETASOL PROPIONATE", "strength": ".05 g/mL" } ], "finished": True, "packaging": [ { "package_ndc": "0591-4039-46", "description": "1 BOTTLE in 1 CARTON (0591-4039-46) / 59 mL in 1 BOTTLE", "marketing_start_date": "20150828", "marketing_end_date": "20250930", "sample": False }, { "package_ndc": "0591-4039-74", "description": "1 BOTTLE in 1 CARTON (0591-4039-74) / 125 mL in 1 BOTTLE", "marketing_start_date": "20150828", "marketing_end_date": "20250930", "sample": False } ], "openfda": { "manufacturer_name": ["Actavis Pharma, Inc."], "rxcui": ["861512"], "spl_set_id": ["907e425a-720a-4180-b97c-9e25008a3658"], "is_original_packager": [True], "unii": ["779619577M"] }, "marketing_category": "NDA AUTHORIZED GENERIC", "dosage_form": "SPRAY", "spl_id": "33a56b8b-a9a6-4287-bbf4-d68ad0c59e07", "product_type": "HUMAN PRESCRIPTION DRUG", "route": ["TOPICAL"], "marketing_start_date": "20150828", "product_id": "0591-4039_33a56b8b-a9a6-4287-bbf4-d68ad0c59e07", "application_number": "NDA021835", "brand_name_base": "CLOBETASOL PROPIONATE", "pharm_class": [ "Corticosteroid Hormone Receptor Agonists [MoA]", "Corticosteroid [EPC]" ] } ] } packaging_data = pd.json_normalize( data['results'], record_path=["packaging"], meta=['product_ndc', 'brand_name', 'generic_name'] ) active_ingredients_data = pd.json_normalize( data['results'], record_path=["active_ingredients"], meta=['product_ndc', 'brand_name', 'generic_name'] ) combined_data = pd.merge( packaging_data, active_ingredients_data, on=['product_ndc', 'brand_name', 'generic_name'], how='outer' ) print(packaging_data) print(active_ingredients_data) print(combined_data)