message: [viz] Revert dropna logic for pivot tables
diff: @@ -629,9 +629,7 @@ class TimeTableViz(BaseViz):
  if fd.get("groupby"):
  values = self.metric_labels[0]
  columns = fd.get("groupby")
  - pt = df.pivot_table(
  - index=DTTM_ALIAS, columns=columns, values=values, dropna=False
  - )
  + pt = df.pivot_table(index=DTTM_ALIAS, columns=columns, values=values)
  pt.index = pt.index.map(str)
  pt = pt.sort_index()
  return dict(
  @@ -697,7 +695,6 @@ class PivotTableViz(BaseViz):
  values=[utils.get_metric_name(m) for m in self.form_data.get("metrics")],
  aggfunc=aggfunc,
  margins=self.form_data.get("pivot_margins"),
  - dropna=False,
  )
  # Display metrics side by side with each column
  if self.form_data.get("combine_metric"):
  @@ -1153,14 +1150,10 @@ class NVD3TimeSeriesViz(NVD3Viz):
  values=self.metric_labels,
  fill_value=0,
  aggfunc=sum,
  - dropna=False,
  )
  else:
  df = df.pivot_table(
  - index=DTTM_ALIAS,
  - columns=fd.get("groupby"),
  - values=self.metric_labels,
  - dropna=False,
  + index=DTTM_ALIAS, columns=fd.get("groupby"), values=self.metric_labels
  )
  rule = fd.get("resample_rule")
  @@ -1371,7 +1364,7 @@ class NVD3DualLineViz(NVD3Viz):
  metric = utils.get_metric_name(fd.get("metric"))
  metric_2 = utils.get_metric_name(fd.get("metric_2"))
  - df = df.pivot_table(index=DTTM_ALIAS, values=[metric, metric_2], dropna=False)
  + df = df.pivot_table(index=DTTM_ALIAS, values=[metric, metric_2])
  chart_data = self.to_series(df)
  return chart_data
  @@ -1423,7 +1416,6 @@ class NVD3TimePivotViz(NVD3TimeSeriesViz):
  index=DTTM_ALIAS,
  columns="series",
  values=utils.get_metric_name(fd.get("metric")),
  - dropna=False,
  )
  chart_data = self.to_series(df)
  for serie in chart_data:
  @@ -1459,7 +1451,7 @@ class DistributionPieViz(NVD3Viz):
  def get_data(self, df):
  metric = self.metric_labels[0]
  - df = df.pivot_table(index=self.groupby, values=[metric], dropna=False)
  + df = df.pivot_table(index=self.groupby, values=[metric])
  df.sort_values(by=metric, ascending=False, inplace=True)
  df = df.reset_index()
  df.columns = ["x", "y"]
  @@ -1547,9 +1539,7 @@ class DistributionBarViz(DistributionPieViz):
  row = df.groupby(self.groupby).sum()[metrics[0]].copy()
  row.sort_values(ascending=False, inplace=True)
  columns = fd.get("columns") or []
  - pt = df.pivot_table(
  - index=self.groupby, columns=columns, values=metrics, dropna=False
  - )
  + pt = df.pivot_table(index=self.groupby, columns=columns, values=metrics)
  if fd.get("contribution"):
  pt = pt.T
  pt = (pt / pt.sum()).T
  