Fixing Plotting Bug

verticapy/core/vdataframe/_plotting.py

@@ -167,6 +167,11 @@ def bar(
         """
         columns = format_type(columns, dtype=list)
         columns, of = self.format_colnames(columns, of, expected_nb_of_cols=[1, 2])
+        if not (isinstance(max_cardinality, Iterable)):
+            max_cardinality = (max_cardinality, max_cardinality)
+        if not (isinstance(h, Iterable)):
+            h = (h, h)
+
         if len(columns) == 1:
             return self[columns[0]].bar(
                 method=method,
@@ -282,6 +287,11 @@ def barh(
         """
         columns = format_type(columns, dtype=list)
         columns, of = self.format_colnames(columns, of, expected_nb_of_cols=[1, 2])
+        if not (isinstance(max_cardinality, Iterable)):
+            max_cardinality = (max_cardinality, max_cardinality)
+        if not (isinstance(h, Iterable)):
+            h = (h, h)
+
         if len(columns) == 1:
             return self[columns[0]].barh(
                 method=method,
@@ -413,10 +423,6 @@ def hist(
             AVG(column1) + 5
         of: str, optional
             The  vDataColumn used to compute the  aggregation.
-        max_cardinality: tuple, optional
-            Maximum number of distinct elements for vDataColumns
-            to be used as categorical. For these elements, no
-            h is picked or computed.
         h: tuple, optional
             Interval width of the  input vDataColumns. Optimized
             h  will be  computed if  the  parameter  is empty or
@@ -1793,6 +1799,10 @@ def hist(
             to be used as categorical.
             The less frequent  elements are gathered together
             to create a new category : 'Others'.
+            This parameter is used to discretize the vDataColumn
+            'by' when the main input nvDataColumn is nnumerical.
+            Otherwise, it  is  used  to   discretize    all the
+            vDataColumn inputs.
         cat_priority: PythonScalar / ArrayLike, optional
             ArrayLike list of the different categories to consider
             when drawing the box plot.  The other categories are

verticapy/plotting/_highcharts/heatmap.py

@@ -49,7 +49,6 @@ def _init_style(self) -> None:
             y_label = ""
         if isinstance(self.layout["y_labels"], list):
             y_labels = copy.deepcopy(self.layout["y_labels"])
-            y_labels.reverse()
         else:
             y_labels = self.layout["y_labels"]
         self.init_style = {
@@ -165,7 +164,11 @@ def draw(self, chart: Optional[HChart] = None, **style_kwargs) -> HChart:
         data = []
         for i in range(len(self.layout["x_labels"])):
             for j in range(len(self.layout["y_labels"])):
-                data += [[i, j, round(X[i, j], self.layout["mround"])]]
+                if "mround" in self.layout:
+                    Xij = round(X[i, j], self.layout["mround"])
+                else:
+                    Xij = X[i, j]
+                data += [[i, j, Xij]]
         chart.add_data_set(data, **self.init_style_matrix)
         chart.set_dict_options(
             {"colorAxis": self._get_cmap_style(style_kwargs=style_kwargs)}