diff --git a/optimus/dataframe/columns.py b/optimus/dataframe/columns.py
index 823df6b3..1b73e8d9 100644
--- a/optimus/dataframe/columns.py
+++ b/optimus/dataframe/columns.py
@@ -153,8 +153,10 @@ def copy(input_cols, output_cols=None, columns=None):
             columns = list(zip(input_cols, output_cols))
 
         for input_col, output_col in columns:
+            current_meta = self.get_meta()
             df = df.withColumn(output_col, F.col(input_col))
-            df = df.preserve_meta(self, Actions.COPY.value, output_col)
+            df = df.set_meta(value=current_meta)
+            df = df.copy_meta({input_col: output_col})
         return df
 
     @add_attr(cols)
diff --git a/optimus/dataframe/extension.py b/optimus/dataframe/extension.py
index 8b077d3d..cdf803ea 100644
--- a/optimus/dataframe/extension.py
+++ b/optimus/dataframe/extension.py
@@ -436,13 +436,14 @@ def debug(self):
     """
     print(self.rdd.toDebugString().decode("ascii"))
 
+
 @add_method(DataFrame)
 def reset(self):
-
     df = self.set_meta("transformations.actions", {})
     Profiler.instance.output_columns = {}
     return df
 
+
 @add_method(DataFrame)
 def send(self, name=None, infer=True, mismatch=None, stats=True):
     """
@@ -459,11 +460,11 @@ def send(self, name=None, infer=True, mismatch=None, stats=True):
         df.set_name(name)
 
     columns, output = Profiler.instance.dataset(df, columns="*", buckets=35, infer=infer, relative_error=RELATIVE_ERROR,
-                                       approx_count=True,
-                                       sample=10000,
-                                       stats=stats,
-                                       format="json",
-                                       mismatch=mismatch)
+                                                approx_count=True,
+                                                sample=10000,
+                                                stats=stats,
+                                                format="json",
+                                                mismatch=mismatch)
 
     if Comm:
         Comm.instance.send(output)
@@ -471,6 +472,29 @@ def send(self, name=None, infer=True, mismatch=None, stats=True):
         raise Exception("Comm is not initialized. Please use comm=True param like Optimus(comm=True)")
 
 
+@add_method(DataFrame)
+def copy_meta(self, old_new_columns):
+    """
+    Shortcut to add transformations to a dataframe
+    :param self:
+    :param old_new_columns:
+    :return:
+    """
+
+    key = "transformations.actions.copy"
+
+    df = self
+
+    copy_cols = df.get_meta(key)
+    if copy_cols is None:
+        copy_cols = {}
+    copy_cols.update(old_new_columns)
+
+    df = df.set_meta(key, copy_cols)
+
+    return df
+
+
 @add_method(DataFrame)
 def rename_meta(self, old_new_columns):
     """
diff --git a/optimus/helpers/constants.py b/optimus/helpers/constants.py
index 8238fc0d..dd0ff66a 100644
--- a/optimus/helpers/constants.py
+++ b/optimus/helpers/constants.py
@@ -103,7 +103,6 @@ class Actions(Enum):
     NEST = "nest"
     UNNEST = "unnest"
     DROP_ROW = "drop_row"
-    COPY = "copy"
 
     @staticmethod
     def list():
diff --git a/optimus/profiler/profiler.py b/optimus/profiler/profiler.py
index 4f0c4739..7a00baf8 100644
--- a/optimus/profiler/profiler.py
+++ b/optimus/profiler/profiler.py
@@ -9,7 +9,7 @@
 
 from optimus.audf import *
 from optimus.dataframe.plots.functions import plot_frequency, plot_missing_values, plot_hist
-from optimus.helpers.check import is_column_a
+from optimus.helpers.check import is_column_a, is_dict, is_list_of_one_element
 from optimus.helpers.columns import parse_columns
 from optimus.helpers.columns_expression import zeros_agg, count_na_agg, hist_agg, percentile_agg, count_uniques_agg
 from optimus.helpers.constants import RELATIVE_ERROR, Actions
@@ -253,6 +253,7 @@ def dataset(self, df, columns="*", buckets=10, infer=False, relative_error=RELAT
         if is_cached and are_actions:
 
             drop = ["drop"]
+            copy = ["copy"]
 
             def match_actions_names(_actions):
                 """
@@ -285,20 +286,30 @@ def match_names(_col_names):
                 _renamed_columns = []
                 _actions = df.get_meta("transformations.actions")
                 _rename = _actions.get("rename")
+
+                def get_name(_col_name):
+                    c = _actions["rename"].get(_col_name)
+                    # The column has not been rename. Get the actual column name
+                    if c is None:
+                        c = _col_name
+                    return c
+
                 if _rename:
-                    for _col_name in _col_names:
-                        # The column name has been changed. Get the new name
-                        c = _actions["rename"].get(_col_name)
-                        # The column has not been rename. Get the actual
-                        if c is None:
-                            c = _col_name
-                        _renamed_columns.append(c)
+                    # if a list
+                    if is_list_of_one_element(_col_names):
+                        for _col_name in _col_names:
+                            # The column name has been changed. Get the new name
+                            _renamed_columns.append(get_name(_col_name))
+                    # if a dict
+                    if is_dict(_col_names):
+                        for _col1, _col2 in _col_names.items():
+                            _renamed_columns.append({get_name(_col1):get_name(_col2)})
+
                 else:
                     _renamed_columns = _col_names
                 return _renamed_columns
 
             # New columns
-
             new_columns = []
 
             current_col_names = df.cols.names()
@@ -315,10 +326,14 @@ def match_names(_col_names):
                 for k, v in actions["rename"].items():
                     profiler_columns[v] = profiler_columns.pop(k)
 
-            # # Drop Keys
+            # Drop Keys
             for col_names in match_actions_names(drop):
                 profiler_columns.pop(col_names)
 
+            # Copy Keys
+            for source, target in df.get_meta("transformations.actions.copy").items():
+                profiler_columns[target] = profiler_columns[source]
+
             # Actions applied to current columns
 
             modified_columns = match_actions_names(Actions.list())