feat: move plotting methods into Column and Table classes

docs/tutorials/data_visualization.ipynb

@@ -102,9 +102,7 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "from safeds.plotting import correlation_heatmap\n",
-    "\n",
-    "correlation_heatmap(titanic_numerical)"
+    "titanic_numerical.correlation_heatmap()"
    ],
    "metadata": {
     "collapsed": false,
@@ -145,9 +143,7 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "from safeds.plotting import lineplot\n",
-    "\n",
-    "lineplot(titanic_numerical, \"survived\", \"fare\")"
+    "titanic_numerical.lineplot(\"survived\", \"fare\")"
    ],
    "metadata": {
     "collapsed": false,
@@ -180,9 +176,7 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "from safeds.plotting import boxplot\n",
-    "\n",
-    "boxplot(titanic_numerical.get_column(\"age\"))"
+    "titanic_numerical.get_column(\"age\").boxplot()"
    ],
    "metadata": {
     "collapsed": false,
@@ -206,9 +200,7 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "from safeds.plotting import histogram\n",
-    "\n",
-    "histogram(titanic_numerical.get_column(\"fare\"))"
+    "titanic_numerical.get_column(\"fare\").histogram()"
    ],
    "metadata": {
     "collapsed": false,
@@ -232,9 +224,7 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "from safeds.plotting import scatterplot\n",
-    "\n",
-    "scatterplot(titanic_numerical, \"age\", \"fare\")\n"
+    "titanic_numerical.scatterplot(\"age\", \"fare\")\n"
    ],
    "metadata": {
     "collapsed": false,

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

@@ -3,8 +3,10 @@
 from numbers import Number
 from typing import Any, Callable, Iterable, Iterator, Optional
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
+import seaborn as sns
 from IPython.core.display_functions import DisplayHandle, display
 from safeds.data.tabular.typing import ColumnType
 from safeds.exceptions import (
@@ -483,3 +485,43 @@ def idness(self) -> float:
         if self._data.size == 0:
             raise ColumnSizeError("> 0", "0")
         return self._data.nunique() / self._data.size
+
+    def boxplot(self) -> None:
+        """
+        Plot this column in a boxplot. This function can only plot real numerical data.
+
+        Raises
+        -------
+        TypeError
+            If the column contains non-numerical data or complex data.
+        """
+        for data in self._data:
+            if (
+                not isinstance(data, int)
+                and not isinstance(data, float)
+                and not isinstance(data, complex)
+            ):
+                raise NonNumericColumnError(self.name)
+            if isinstance(data, complex):
+                raise TypeError(
+                    "The column contains complex data. Boxplots cannot plot the imaginary part of complex "
+                    "data. Please provide a Column with only real numbers"
+                )
+        ax = sns.boxplot(data=self._data)
+        ax.set(xlabel=self.name)
+        plt.tight_layout()
+        plt.show()
+
+    def histogram(self) -> None:
+        """
+        Plot a column in a histogram.
+        """
+
+        ax = sns.histplot(data=self._data)
+        ax.set_xticks(ax.get_xticks())
+        ax.set(xlabel=self.name)
+        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()
+        plt.show()

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

@@ -6,8 +6,10 @@
 from pathlib import Path
 from typing import Callable, Optional, Union
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
+import seaborn as sns
 from IPython.core.display_functions import DisplayHandle, display
 from pandas import DataFrame, Series
 from safeds.data.tabular.containers._column import Column
@@ -970,3 +972,96 @@ def shuffle(self) -> Table:
         new_df = self._data.sample(frac=1.0)
         new_df.columns = self.schema.get_column_names()
         return Table(new_df)
+
+    def correlation_heatmap(self) -> None:
+        """
+        Plot a correlation heatmap of an entire table. This function can only plot real numerical data.
+
+        Raises
+        -------
+        TypeError
+            If the table contains non-numerical data or complex data.
+        """
+        for column in self.to_columns():
+            if not column.type.is_numeric():
+                raise NonNumericColumnError(column.name)
+        sns.heatmap(
+            data=self._data.corr(),
+            vmin=-1,
+            vmax=1,
+            xticklabels=self.get_column_names(),
+            yticklabels=self.get_column_names(),
+            cmap="vlag",
+        )
+        plt.tight_layout()
+        plt.show()
+
+    def lineplot(self, x_column_name: str, y_column_name: str) -> None:
+        """
+        Plot two columns against each other in a lineplot. If there are multiple x-values for a y-value,
+        the resulting plot will consist of a line representing the mean and the lower-transparency area around the line
+        representing the 95% confidence interval.
+
+        Parameters
+        ----------
+        x_column_name : str
+            The column name of the column to be plotted on the x-Axis.
+        y_column_name : str
+            The column name of the column to be plotted on the y-Axis.
+
+        Raises
+        ---------
+        UnknownColumnNameError
+            If either of the columns do not exist.
+        """
+        if not self.has_column(x_column_name):
+            raise UnknownColumnNameError([x_column_name])
+        if not self.has_column(y_column_name):
+            raise UnknownColumnNameError([y_column_name])
+
+        ax = sns.lineplot(
+            data=self._data,
+            x=self.schema._get_column_index_by_name(x_column_name),
+            y=self.schema._get_column_index_by_name(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()
+        plt.show()
+
+    def scatterplot(self, x_column_name: str, y_column_name: str) -> None:
+        """
+        Plot two columns against each other in a scatterplot.
+
+        Parameters
+        ----------
+        x_column_name : str
+            The column name of the column to be plotted on the x-Axis.
+        y_column_name : str
+            The column name of the column to be plotted on the y-Axis.
+
+        Raises
+        ---------
+        UnknownColumnNameError
+            If either of the columns do not exist.
+        """
+        if not self.has_column(x_column_name):
+            raise UnknownColumnNameError([x_column_name])
+        if not self.has_column(y_column_name):
+            raise UnknownColumnNameError([y_column_name])
+
+        ax = sns.scatterplot(
+            data=self._data,
+            x=self.schema._get_column_index_by_name(x_column_name),
+            y=self.schema._get_column_index_by_name(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()
+        plt.show()