Fixed bug where requests for date-like keywords would raise a broadcast

error.

pytrends/request.py

@@ -179,7 +179,9 @@ def interest_over_time(self):
         result_df = df['value'].apply(lambda x: pd.Series(str(x).replace('[', '').replace(']', '').split(',')))
         # rename each column with its search term, relying on order that google provides...
         for idx, kw in enumerate(self.kw_list):
-            result_df[kw] = result_df[idx].astype('int')
+            # there is currently a bug with assigning columns that may be
+            # parsed as a date in pandas: use explicit insert column method
+            result_df.insert(len(result_df.columns), kw, result_df[idx].astype('int'))
             del result_df[idx]
 
         if 'isPartial' in df:
@@ -377,29 +379,29 @@ def categories(self):
     def get_historical_interest(self, keywords, year_start=2018, month_start=1, day_start=1, hour_start=0, year_end=2018, month_end=2, day_end=1, hour_end= 0, cat=0, geo='', gprop='', sleep=0):
         """Gets historical hourly data for interest by chunking requests to 1 week at a time (which is what Google allows)"""
 
-        # construct datetime obejcts - raises ValueError if invalid parameters       
+        # construct datetime obejcts - raises ValueError if invalid parameters
         start_date = datetime(year_start, month_start, day_start, hour_start)
         end_date = datetime(year_end, month_end, day_end, hour_end)
 
-        # the timeframe has to be in 1 week intervals or Google will reject it 
+        # the timeframe has to be in 1 week intervals or Google will reject it
         delta = timedelta(days=7)
 
         df = pd.DataFrame()
 
         date_iterator = start_date
-        date_iterator += delta 
+        date_iterator += delta
 
         while True:
             if (date_iterator > end_date):
-                # has retrieved all of the data 
+                # has retrieved all of the data
                 break
 
-            # format date to comply with API call 
+            # format date to comply with API call
             start_date_str = start_date.strftime('%Y-%m-%dT%H')
             date_iterator_str = date_iterator.strftime('%Y-%m-%dT%H')
             tf = start_date_str + ' ' + date_iterator_str
 
-            try: 
+            try:
                 self.build_payload(keywords,cat, tf, geo, gprop)
                 week_df = self.interest_over_time()
                 df = df.append(week_df)
@@ -408,10 +410,10 @@ def get_historical_interest(self, keywords, year_start=2018, month_start=1, day_
                 pass
 
             start_date += delta
-            date_iterator += delta 
+            date_iterator += delta
 
-            # just in case you are rate-limited by Google. Recommended is 60 if you are. 
+            # just in case you are rate-limited by Google. Recommended is 60 if you are.
             if sleep > 0:
                 time.sleep(sleep)
 
-        return df 
+        return df