feat: added normal plot for time series

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

@@ -6,6 +6,7 @@
 
 import matplotlib.pyplot as plt
 import pandas as pd
+import seaborn as sns
 
 from safeds.data.image.containers import Image
 from safeds.data.tabular.containers import Column, Row, Table, TaggedTable
@@ -36,7 +37,7 @@ def _from_tagged_table(
 
         Parameters
         ----------
-        table : TaggedTable
+        tagged_table: TaggedTable
             The tagged table.
         time_name: str
             Name of the time column.
@@ -906,3 +907,150 @@ def plot_lagplot(self, lag: int) -> Image:
         plt.close()  # Prevents the figure from being displayed directly
         buffer.seek(0)
         return Image.from_bytes(buffer.read())
+
+    def plot_lineplot(self, x_column_name: str | None = None, y_column_name: str | None = None) -> Image:
+        """
+
+        Plot the time series target or the given column(s) as line plot.
+
+        The function will take the time column as the default value for y_column_name and the target column as the
+        default value for x_column_name.
+
+        Parameters
+        ----------
+        x_column_name:
+            The column name of the column to be plotted on the x-Axis, default is the time column.
+        y_column_name:
+            The column name of the column to be plotted on the y-Axis, default is the target column.
+
+        Returns
+        -------
+        plot:
+            The plot as an image.
+
+        Raises
+        ------
+        NonNumericColumnError
+            If the time series given columns contain non-numerical values.
+
+        UnknownColumnNameError
+            If one of the given names does not exist in the table
+
+        Examples
+        --------
+                >>> from safeds.data.tabular.containers import TimeSeries
+                >>> table = TimeSeries({"time":[1, 2], "target": [3, 4], "feature":[2,2]}, target_name= "target", time_name="time", feature_names=["feature"], )
+                >>> image = table.plot_lineplot()
+
+        """
+        self._data.index.name = "index"
+        if x_column_name is not None and not self.get_column(x_column_name).type.is_numeric():
+            raise NonNumericColumnError("The time series plotted column contains non-numerical columns.")
+
+        if y_column_name is None:
+            y_column_name = self.target.name
+
+        elif y_column_name not in self._data.columns:
+            raise UnknownColumnNameError([y_column_name])
+
+        if x_column_name is None:
+            x_column_name = self.time.name
+
+        if not self.get_column(y_column_name).type.is_numeric():
+            raise NonNumericColumnError("The time series plotted column contains non-numerical columns.")
+
+        fig = plt.figure()
+        ax = sns.lineplot(
+            data=self._data,
+            x=x_column_name,
+            y=y_column_name,
+        )
+        ax.set(xlabel=x_column_name, ylabel=y_column_name)
+        ax.set_xticks(ax.get_xticks())
+        ax.set_xticklabels(
+            ax.get_xticklabels(),
+            rotation=45,
+            horizontalalignment="right",
+        )  # rotate the labels of the x Axis to prevent the chance of overlapping of the labels
+        plt.tight_layout()
+
+        buffer = io.BytesIO()
+        fig.savefig(buffer, format="png")
+        plt.close()  # Prevents the figure from being displayed directly
+        buffer.seek(0)
+        self._data = self._data.reset_index()
+        return Image.from_bytes(buffer.read())
+
+    def plot_scatterplot(
+        self,
+        x_column_name: str | None = None,
+        y_column_name: str | None = None,
+    ) -> Image:
+        """
+        Plot the time series target or the given column(s) as scatter plot.
+
+        The function will take the time column as the default value for x_column_name and the target column as the
+        default value for y_column_name.
+
+        Parameters
+        ----------
+        x_column_name:
+            The column name of the column to be plotted on the x-Axis.
+        y_column_name:
+            The column name of the column to be plotted on the y-Axis.
+
+        Returns
+        -------
+        plot:
+            The plot as an image.
+
+        Raises
+        ------
+        NonNumericColumnError
+            If the time series given columns contain non-numerical values.
+
+        UnknownColumnNameError
+            If one of the given names does not exist in the table
+
+        Examples
+        --------
+                >>> from safeds.data.tabular.containers import TimeSeries
+                >>> table = TimeSeries({"time":[1, 2], "target": [3, 4], "feature":[2,2]}, target_name= "target", time_name="time", feature_names=["feature"], )
+                >>> image = table.plot_scatterplot()
+
+        """
+        self._data.index.name = "index"
+        if x_column_name is not None and not self.get_column(x_column_name).type.is_numeric():
+            raise NonNumericColumnError("The time series plotted column contains non-numerical columns.")
+
+        if y_column_name is None:
+            y_column_name = self.target.name
+        elif y_column_name not in self._data.columns:
+            raise UnknownColumnNameError([y_column_name])
+        if x_column_name is None:
+            x_column_name = self.time.name
+
+        if not self.get_column(y_column_name).type.is_numeric():
+            raise NonNumericColumnError("The time series plotted column contains non-numerical columns.")
+
+        fig = plt.figure()
+        ax = sns.scatterplot(
+            data=self._data,
+            x=x_column_name,
+            y=y_column_name,
+        )
+        ax.set(xlabel=x_column_name, ylabel=y_column_name)
+        ax.set_xticks(ax.get_xticks())
+        ax.set_xticklabels(
+            ax.get_xticklabels(),
+            rotation=45,
+            horizontalalignment="right",
+        )  # rotate the labels of the x Axis to prevent the chance of overlapping of the labels
+        plt.tight_layout()
+
+        buffer = io.BytesIO()
+        fig.savefig(buffer, format="png")
+        plt.close()  # Prevents the figure from being displayed directly
+        buffer.seek(0)
+        self._data = self._data.reset_index()
+        return Image.from_bytes(buffer.read())