Fixing broken pd.merge due to Pandas upgrade

We can only pass argument "on" OR "left_index" and "right_index", not a combination of both in pd.merge()
Fix for the issue:
e-mission/e-mission-docs#856 (comment)

emission/analysis/intake/cleaning/filter_accuracy.py

@@ -100,7 +100,8 @@ def filter_accuracy(user_id):
                 logging.debug("Partial filtered points %d found" % len(filtered_points_df))
                 filtered_points_df = filtered_points_df[SEL_FIELDS_FOR_DUP]
                 filtered_points_df["msts"] = filtered_points_df.ts.apply(lambda x: int(x * 10**3))
-                matched_points_df = filtered_from_unfiltered_df.merge(filtered_points_df, on="msts", right_index=True)
+                matched_points_df = filtered_from_unfiltered_df.reset_index().merge(filtered_points_df, on="msts")
+                matched_points_df.set_index('index', inplace=True)
                 to_insert_df = filtered_from_unfiltered_df.drop(index=matched_points_df.index)
             for idx, entry in to_insert_df.iterrows():
                 unfiltered_entry = unfiltered_points_list[idx]

emission/tests/analysisTests/intakeTests/TestFilterAccuracy.py

@@ -165,8 +165,9 @@ def testPandasMergeBehavior(self):
         import pandas as pd
         df_a = pd.DataFrame({"ts": [1,2,3,4]})
         df_b = pd.DataFrame({"ts": [1,3]})
-        merged_left_idx = df_a.merge(df_b, on="ts", how="inner", left_index=True)
-        merged_right_idx = df_a.merge(df_b, on="ts", how="inner", right_index=True)
+        merged_left_idx = df_a.merge(df_b, on="ts", how="inner")
+        merged_right_idx = df_a.reset_index().merge(df_b, on="ts", how="inner")
+        merged_right_idx.set_index('index', inplace=True)
         self.assertEqual(merged_left_idx.index.to_list(), [0,1])
         self.assertEqual(merged_right_idx.index.to_list(), [0,2])