feat: add resample operator in post processing

superset/charts/schemas.py

@@ -749,6 +749,7 @@ class ChartDataPostProcessingOperationSchema(Schema):
                 "sort",
                 "diff",
                 "compare",
+                "resample",
             )
         ),
         example="aggregate",

superset/utils/pandas_postprocessing.py

@@ -916,3 +916,29 @@ def outliers(series: Series) -> Set[float]:
         for metric in metrics
     }
     return aggregate(df, groupby=groupby, aggregates=aggregates)
+
+
+def resample(
+    df: DataFrame,
+    resample_rule: str,
+    resample_method: str,
+    time_column: str,
+    resample_fill_zero: bool = False,
+) -> DataFrame:
+    """
+    resample a timeseries dataframe.
+
+    :param df: DataFrame to resample.
+    :param resample_rule: The offset string representing target conversion.
+    :param resample_method: How to fill the NaN value after resample.
+    :param time_column: existing columns in DataFrame.
+    :param resample_fill_zero: fill missing values with zero.
+    :return: DataFrame after resample
+    :raises QueryObjectValidationError: If the request in incorrect
+    """
+    df = df.set_index(time_column)
+    if resample_method == "asfreq" and resample_fill_zero:
+        df = df.resample(resample_rule).asfreq(fill_value=0)
+    else:
+        df = getattr(df.resample(resample_rule), resample_method)()
+    return df.reset_index()

tests/integration_tests/pandas_postprocessing_tests.py

@@ -870,3 +870,29 @@ def test_boxplot_percentile_incorrect_params(self):
                 metrics=["cars"],
                 percentiles=[10, 90, 10],
             )
+
+    def test_resample(self):
+        df = timeseries_df.copy()
+        df.index.name = "time_column"
+        df.reset_index(inplace=True)
+
+        post_df = proc.resample(
+            df=df,
+            resample_rule="1D",
+            resample_method="ffill",
+            time_column="time_column",
+        )
+        self.assertListEqual(
+            post_df["label"].tolist(), ["x", "y", "y", "y", "z", "z", "q"]
+        )
+        self.assertListEqual(post_df["y"].tolist(), [1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 4.0])
+
+        post_df = proc.resample(
+            df=df,
+            resample_rule="1D",
+            resample_method="asfreq",
+            time_column="time_column",
+            resample_fill_zero=True,
+        )
+        self.assertListEqual(post_df["label"].tolist(), ["x", "y", 0, 0, "z", 0, "q"])
+        self.assertListEqual(post_df["y"].tolist(), [1.0, 2.0, 0, 0, 3.0, 0, 4.0])