Apply suggestions from code review

Co-authored-by: Alexander <47296670+Marsmaennchen221@users.noreply.github.com>

Author: Gerhardsa0

src/safeds/data/tabular/containers/_table.py

@@ -1730,12 +1730,12 @@ def time_columns(self, target_name: str, time_name: str, feature_names: list[str
         time_name : str
             Name of the time column.
         feature_names : list[str] | None
-            Names of the feature columns. If None, all columns except the target column are used.
+            Names of the feature columns. If None, all columns except the target and time columns are used.
 
         Returns
         -------
         time_series : TimeSeries
-            A new tagged table with the given target and feature names.
+            A new time series with the given target, time and feature names.
 
         Raises
         ------
@@ -1750,8 +1750,6 @@ def time_columns(self, target_name: str, time_name: str, feature_names: list[str
         >>> table = Table.from_dict({"time": ["01.01", "01.02", "01.03"], "price": [1.10, 1.19, 1.79], "amount_bought": [74, 72, 51]})
         >>> tagged_table = table.time_columns(target_name="amount_bought",time_name = "time", feature_names=["price"])
         """
-        from ._time_series import TimeSeries
-
         return TimeSeries._from_table_to_time_series(self, target_name, time_name, feature_names)
 
     def transform_column(self, name: str, transformer: Callable[[Row], Any]) -> Table:

src/safeds/data/tabular/containers/_tagged_table.py

@@ -396,7 +396,7 @@ def filter_rows(self, query: Callable[[Row], bool]) -> TaggedTable:
         Returns
         -------
         result : TaggedTable
-            A table containing only the rows to match the query.
+            A new tagged table containing only the rows to match the query.
         """
         return TaggedTable._from_table(
             super().filter_rows(query),

src/safeds/data/tabular/containers/_time_series.py

@@ -56,7 +56,7 @@ def _from_tagged_table(
             The tagged table.
         time_name: str
             Name of the time column.
-        Retruns
+        Returns
         -------
         time_series : TimeSeries
             the created time series
@@ -94,7 +94,6 @@ def _from_tagged_table(
         return result
 
     @staticmethod
-    # idk if this method should exist, because we cant use it like the Method in TaggedTable, but the Method is static and this seem to doesnt get checked by the megalinter.
     def _from_table_to_time_series(
         table: Table,
         target_name: str,
@@ -112,16 +111,16 @@ def _from_table_to_time_series(
         time_name: str
             Name of the date column.
         feature_names : list[str] | None
-            Names of the feature columns. If None, all columns except the target column are used.
-        Retruns
+            Names of the feature columns. If None, all columns except the target and time columns are used.
+        Returns
         -------
         time_series : TimeSeries
             the created time series
 
         Raises
         ------
         UnknownColumnNameError
-            If target_name matches none of the column names.
+            If target_name or time_name matches none of the column names.
         Value Error
             If no feature columns are specified
 
@@ -153,7 +152,7 @@ def __init__(
         feature_names: list[str] | None = None,
     ):
         """
-        Create a tagged table from a mapping of column names to their values.
+        Create a time series from a mapping of column names to their values.
 
         Parameters
         ----------
@@ -164,7 +163,7 @@ def __init__(
         time_name : str
             Name of the time column
         feature_names : list[str] | None
-            Names of the feature columns. If None, all columns except the target column are used.
+            Names of the feature columns. If None, all columns except the target and time columns are used.
 
         Raises
         ------
@@ -214,35 +213,14 @@ def time(self) -> Column:
         """
         return self._time
 
-    # ------------------------------------------------------------------------------------------------------------------
-    # Specific methods from time series class:
-    # ------------------------------------------------------------------------------------------------------------------
-
-    # def _create_moving_average(self, window_size: int) -> Column:
-    # calculate the windows and the moving average of a timeserties, this function for now only has intern use
-    # some unexpected behavior while casting to series agains, because it addds NAN values
-    # return Column._from_pandas_series(pd.Series(self.target._data.rolling(window_size).mean()))
-    # pass
-    # def plot_moving_average(self, window_size: int) -> Image:
-    # this method should plot the moving average of a time series
-    # pass
-
-    # def show_time_series(self) -> Image:
-    # this method should plot the time series
-    # pass
-
-    # def decompose_time_series(self) -> Image:
-    # this Method should show a plot of a decomposed time series
-    # pass
-
     # ------------------------------------------------------------------------------------------------------------------
     # Overriden methods from TaggedTable class:
     # ------------------------------------------------------------------------------------------------------------------
     def _as_table(self: TimeSeries) -> Table:
         """
         Return a new `Table` with the tagging removed.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------
@@ -252,7 +230,7 @@ def _as_table(self: TimeSeries) -> Table:
         Returns
         -------
         table: Table
-            The table as an untagged Table, i.e. without the information about which columns are features, target or time.
+            The time series as an untagged Table, i.e. without the information about which columns are features, target or time.
 
         """
         return Table.from_columns(super().to_columns())
@@ -261,7 +239,7 @@ def add_column(self, column: Column) -> TimeSeries:
         """
         Return a new `TimeSeries` with the provided column attached at the end, as neither target nor feature column.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------
@@ -271,7 +249,7 @@ def add_column(self, column: Column) -> TimeSeries:
         Returns
         -------
         result : TimeSeries
-            The table with the column attached as neither target nor feature column.
+            The time series with the column attached as neither target nor feature column.
 
         Raises
         ------
@@ -299,7 +277,7 @@ def add_column_as_feature(self, column: Column) -> TimeSeries:
         Returns
         -------
         result : TimeSeries
-            The table with the attached feature column.
+            The time series with the attached feature column.
 
         Raises
         ------
@@ -345,7 +323,7 @@ def add_columns(self, columns: list[Column] | Table) -> TimeSeries:
         """
         Return a new `TimeSeries` with multiple added columns, as neither target nor feature columns.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------
@@ -360,9 +338,9 @@ def add_columns(self, columns: list[Column] | Table) -> TimeSeries:
         Raises
         ------
         DuplicateColumnNameError
-            If at least one column name from the provided column list already exists in the table.
+            If at least one column name from the provided column list already exists in the time series.
         ColumnSizeError
-            If at least one of the column sizes from the provided column list does not match the table.
+            If at least one of the column sizes from the provided column list does not match the time series.
         """
         return TimeSeries._from_tagged_table(
             super().add_columns(columns),
@@ -373,7 +351,7 @@ def add_row(self, row: Row) -> TimeSeries:
         """
         Return a new `TimeSeries` with an extra Row attached.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------
@@ -388,15 +366,15 @@ def add_row(self, row: Row) -> TimeSeries:
         Raises
         ------
         UnknownColumnNameError
-            If the row has different column names than the table.
+            If the row has different column names than the time series.
         """
         return TimeSeries._from_tagged_table(super().add_row(row), time_name=self.time.name)
 
     def add_rows(self, rows: list[Row] | Table) -> TimeSeries:
         """
         Return a new `TimeSeries` with multiple extra Rows attached.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------
@@ -406,12 +384,12 @@ def add_rows(self, rows: list[Row] | Table) -> TimeSeries:
         Returns
         -------
         result : TimeSeries
-            A new time series which combines the original table and the given rows.
+            A new time series which combines the original time series and the given rows.
 
         Raises
         ------
         UnknownColumnNameError
-            If at least one of the rows have different column names than the table.
+            If at least one of the rows have different column names than the time series.
         """
         return TimeSeries._from_tagged_table(super().add_rows(rows), time_name=self.time.name)
 
@@ -440,7 +418,7 @@ def keep_only_columns(self, column_names: list[str]) -> TimeSeries:
         """
         Return a new `TimeSeries` with only the given column(s).
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------
@@ -457,7 +435,7 @@ def keep_only_columns(self, column_names: list[str]) -> TimeSeries:
         UnknownColumnNameError
             If any of the given columns does not exist.
         IllegalSchemaModificationError
-            If none of the given columns is the target column or any of the feature columns.
+            If none of the given columns is the target or time column or any of the feature columns.
         """
         if self.target.name not in column_names:
             raise IllegalSchemaModificationError("Must keep the target column.")
@@ -479,9 +457,9 @@ def keep_only_columns(self, column_names: list[str]) -> TimeSeries:
 
     def remove_columns(self, column_names: list[str]) -> TimeSeries:
         """
-        Return a new `TimeSeries` with the given column(s) removed from the table.
+        Return a new `TimeSeries` with the given column(s) removed from the time series.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------
@@ -526,7 +504,7 @@ def remove_columns_with_missing_values(self) -> TimeSeries:
         """
         Return a new `TimeSeries` with every column that misses values removed.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Returns
         -------
@@ -561,7 +539,7 @@ def remove_columns_with_non_numerical_values(self) -> TimeSeries:
         """
         Return a new `TimeSeries` with every column that contains non-numerical values removed.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Returns
         -------
@@ -665,9 +643,9 @@ def rename_column(self, old_name: str, new_name: str) -> TimeSeries:
         Parameters
         ----------
         old_name : str
-            The old name of the target column.
+            The old name of the column.
         new_name : str
-            The new name of the target column.
+            The new name of the column.
 
         Returns
         -------
@@ -705,7 +683,7 @@ def replace_column(self, old_column_name: str, new_columns: list[Column]) -> Tim
         becomes the new target or time column. If the column to be replaced is a feature column, the new columns that replace it
         all become feature columns.
 
-        The order of columns is kept. The original table is not modified.
+        The order of columns is kept. The original time series is not modified.
 
         Parameters
         ----------
@@ -717,7 +695,7 @@ def replace_column(self, old_column_name: str, new_columns: list[Column]) -> Tim
         Returns
         -------
         result : TimeSeries
-            A time series with the old column replaced by the new column.
+            A time series with the old column replaced by the new columns.
 
         Raises
         ------
@@ -728,7 +706,7 @@ def replace_column(self, old_column_name: str, new_columns: list[Column]) -> Tim
         ColumnSizeError
             If the size of the column does not match the amount of rows.
         IllegalSchemaModificationError
-            If the target column would be removed or replaced by more than one column.
+            If the target or time column would be removed or replaced by more than one column.
         """
         if old_column_name == self.time.name:
             if len(new_columns) != 1:
@@ -830,7 +808,7 @@ def sort_columns(
 
         If no comparator is given, the columns will be sorted alphabetically by their name.
 
-        The original table is not modified.
+        The original time series is not modified.
 
         Parameters
         ----------