diff --git a/ebay_api.py b/ebay_api.py
index 6c058cc..892a0b6 100644
--- a/ebay_api.py
+++ b/ebay_api.py
@@ -41,31 +41,18 @@ class FindingApi:
         get_ids_from cats creates a 20-itemId list to use for the ShoppingApi
         call
         '''
+        data = self.get_data()
         itemid_results_list = []
-        for category_id in cat_list:
-            for i in self.pageNumber:
-                params = {
-                    "OPERATION-NAME":self.service,
-                    "SECURITY-APPNAME":"scottbea-xlister-PRD-6796e0ff6-14862949",
-                    "SERVICE-VERSION":"1.13.0",
-                    "RESPONSE-DATA-FORMAT":"JSON",
-                    "categoryId":category_id,
-                    "paginationInput.entriesPerPage":"100",
-                    "paginationInput.PageNumber":i
-                    }
-                response = requests.get("https://svcs.ebay.com/services/search/FindingService/v1",
-                        params=params)
-                data = response.json()
-                for item in data['findItemsByCategoryResponse'][0]['searchResult'][0]['item']:
-                    if item not in big_data.values:
-                        itemid_results_list.append(item['itemId'][0]) # itemId
-                        # values are in lists for some reason
+        for item in data['findItemsByCategoryResponse'][0]['searchResult'][0]['item']:
+            if item not in big_data.values:
+                itemid_results_list.append(item['itemId'][0]) # itemId
+                # values are in lists for some reason
         item_id_results = [','.join(itemid_results_list[n:n+20]) for n in list(range(0,
             len(itemid_results_list), 20))]
 
         return item_id_results
 
-class ShoppingApi(FindingApi):
+class ShoppingApi():
     '''
     Creates objects from ShoppingApi service calls that can interact with
     pandas dataframes
@@ -86,11 +73,11 @@ class ShoppingApi(FindingApi):
 
             names = []
             values = []
-            nvl = data['Item'][0]['ItemSpecifics']['NameValueList']
+            nvl = data['Item'][0]['ItemSpecifics']['NameValueList'][0]
 
             for nvl_dict in nvl:
                 names.append(nvl_dict['Name'])
-                values.append(nvl_dict['Value'])
+            values.append(nvl_dict['Value']) # Try to excract value from list here
 
             nvl_dict = dict(zip(names, values))
             data.update(nvl_dict)
@@ -102,6 +89,7 @@ class ShoppingApi(FindingApi):
 # to divide these up into the categories. This will leave you with about 6.25K results per cat.
 # More than enough data for your dataset.
 
-# Need to make sure dataframe gets important stuff outside of nvl. Also need to
-# change init method in findingapi to have variable pages and possibly variable
-# services. 
+# Need to make sure dataframe gets important stuff outside of nvl in order to
+# access values for cross referencing itemIds from calls
+# Need to decide if list gets accessed from df or if you're just going to have
+# list contents extracted and possibly placed into separate cells/labels