Add data structure

main.py

-import requests, time, os, sys
-import pandas, msgpack
+import requests, time, os, sys, json, csv
 from bs4 import BeautifulSoup
 
+class DataPocket:
+    def __init__(self):
+        self.rows = {}
+
+    def addRow(self, rownum, name=None, values=None):
+        ### values should be a list in column order
+        rownum = int(rownum)
+        d = {'name': name,
+             'values': [] if values == None else [x for x in values]
+            }
+        self.rows[rownum] = d
+
+    def addName(self, rownum, name):
+        if int(rownum) in self.rows.keys():
+            self.rows[rownum]['name'] = name
+        else:
+            print("No such row.")
+
+    def addValues(self, rownum, values):
+        ### values should be a list in column order
+        if int(rownum) in self.rows.keys():
+            self.rows[rownum]['values'] = [x for x in values]
+        else:
+            print("No such row.")
+
+    def setValue(self, rownum, value, col):
+        ### col should be a zero-indexed integer
+        col = int(col)
+        if int(rownum) in self.rows.keys():
+            try:
+                self.rows[rownum]['values'][col] = value
+            except IndexError:
+                while len(self.rows[rownum]['values'] < col):
+                    self.rows[rownum]['values'].append(None)
+                self.rows[rownum]['values'].append(value)
+        else:
+            print("No such row.")
+
+    def printRow(self, rownum):
+        if int(rownum) in self.rows.keys():
+            print("Row {} (\"{}\"): {}".format(rownum, self.rows[rownum]['name'], self.rows[rownum]['values']))
+        else:
+            print("No such row.")
+
+    def printData(self):
+        for row in self.rows.keys():
+            self.printRow(row)
+
 class DataColl:
     def __init__(self):
         self._year = None
     df.fmt = "json"
     print(df.endpoint)
 
-#    df.setFilename(False, "txt")
-    df.setFilename(False, "json")
+    df.setFilename(False, "csv")
 
     r = requests.get(df.endpoint)
- #   t = msgpack.unpackb(r.content)
- #   with open(df.filename, "w", newline='', encoding="utf-8") as file:
- #       file.write(str(t[b'results']))
 
-    rs = r.json()["results"]
-
-    for k,_v in rs.items():
-        print(k)
-    #data = pandas.read_json(r.text, orient="columns")
-    
-#    with open(df.filename, "w", newline='') as file:
-#        data.to_csv(file)
-    #print(r.json())