feat: class for time series

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

@@ -4,10 +4,12 @@
 from ._row import Row
 from ._table import Table
 from ._tagged_table import TaggedTable
+from ._time_series import TimeSeries
 
 __all__ = [
  "Column",
  "Row",
  "Table",
  "TaggedTable",
+ "TimeSeries",
 ]

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

@@ -36,6 +36,7 @@
  from safeds.data.tabular.transformation import InvertibleTableTransformer, TableTransformer
 
  from ._tagged_table import TaggedTable
+ from ._time_series import TimeSeries
 
 # Enable copy-on-write for pandas dataframes
 pd.options.mode.copy_on_write = True
@@ -1715,6 +1716,44 @@ def tag_columns(self, target_name: str, feature_names: list[str] | None = None)
 
  return TaggedTable._from_table(self, target_name, feature_names)
 
+ # rethink name here
+ def time_columns(self, target_name: str, time_name: str, feature_names: list[str] | None = None) -> TimeSeries:
+ """
+ Return a new `TimeSeries` with columns marked as a target and time column or feature columns.
+
+ The original table is not modified.
+
+ Parameters
+ ----------
+ target_name : str
+ Name of the target column.
+ 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.
+
+ Returns
+ -------
+ time_series : TimeSeries
+ A new tagged table with the given target and feature names.
+
+ Raises
+ ------
+ ValueError
+ If the target column is also a feature column.
+ ValueError
+ If no feature columns are specified.
+
+ Examples
+ --------
+ >>> from safeds.data.tabular.containers import Table, TimeSeries
+ >>> 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:
  """
  Return a new `Table` with the provided column transformed by calling the provided transformer.

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

@@ -350,7 +350,7 @@ def add_row(self, row: Row) -> TaggedTable:
  Returns
  -------
  table : TaggedTable
- A new table with the added row at the end.
+ A new tagged table with the added row at the end.
 
  Raises
  ------
@@ -373,7 +373,7 @@ def add_rows(self, rows: list[Row] | Table) -> TaggedTable:
  Returns
  -------
  result : TaggedTable
- A new table which combines the original table and the given rows.
+ A new tagged table which combines the original table and the given rows.
 
  Raises
  ------
@@ -386,7 +386,7 @@ def filter_rows(self, query: Callable[[Row], bool]) -> TaggedTable:
  """
  Return a new `TaggedTable` containing only rows that match the given Callable (e.g. lambda function).
 
- The original table is not modified.
+ The original tagged table is not modified.
 
  Parameters
  ----------
@@ -395,7 +395,7 @@ def filter_rows(self, query: Callable[[Row], bool]) -> TaggedTable:
 
  Returns
  -------
- table : TaggedTable
+ result : TaggedTable
  A table containing only the rows to match the query.
  """
  return TaggedTable._from_table(