set_index on dataframe and groupby sum on duplicated index values (#93)

* set_index on dataframe and groupby sum on duplicated index values

* fixed testcase

HISTORY.rst

@@ -2,6 +2,10 @@
 History
 =======
 
+UNRELEASED
+----------
+* avoid duplicated periods in dataframe returned by `ddlpy.measurements_amount()` https://github.com/Deltares/ddlpy/pull/93
+
 0.4.0 (2024-04-08)
 ------------------
 * added `catalog_filter` argument to `ddlpy.locations()` to enabling retrieving the extended catalog in https://github.com/Deltares/ddlpy/pull/87

ddlpy/ddlpy.py

@@ -205,11 +205,13 @@ def measurements_amount(location, start_date, end_date, period="Jaar"):
                                             df["Groeperingsperiode.Dag"].apply(lambda x: f"{x:02d}"))
 
             # select columns from dataframe and append to list
-            df = df[["Groeperingsperiode","AantalMetingen"]]
+            df = df.set_index("Groeperingsperiode")
+            df = df[["AantalMetingen"]]
             df_list.append(df)
 
-        # concatenate
-        amount_all = pd.concat(df_list).sort_values("Groeperingsperiode").reset_index(drop=True)
+        # concatenate and sum duplicated index
+        amount_all = pd.concat(df_list).sort_index()
+        amount_all = amount_all.groupby(amount_all.index).sum()
         return amount_all
 
 

tests/test_ddlpy.py

@@ -67,13 +67,13 @@ def test_measurements_amount(location):
     end_date = dt.datetime(1953, 4, 5)
     data_amount_dag = ddlpy.measurements_amount(location, start_date=start_date, end_date=end_date, period="Dag")
     assert data_amount_dag.shape[0] > 50
-    assert data_amount_dag["Groeperingsperiode"].str.len().iloc[0] == 10
+    assert data_amount_dag.index.str.len()[0] == 10
     data_amount_maand = ddlpy.measurements_amount(location, start_date=start_date, end_date=end_date, period="Maand")
     assert data_amount_maand.shape[0] == 4
-    assert data_amount_maand["Groeperingsperiode"].str.len().iloc[0] == 7
+    assert data_amount_maand.index.str.len()[0] == 7
     data_amount_jaar = ddlpy.measurements_amount(location, start_date=start_date, end_date=end_date, period="Jaar")
     assert data_amount_jaar.shape[0] == 1
-    assert data_amount_jaar["Groeperingsperiode"].str.len().iloc[0] == 4
+    assert data_amount_jaar.index.str.len()[0] == 4
 
 
 def test_measurements_latest(location):