feat: remove operations without replacement from tabular containers (#…

…747) ### Summary of Changes Remove the following methods: * `Table.to_excel_file` * `Table.from_excel_file` * `Table.add_row` * `Table.add_rows` * `Table.get_row` * `Table.group_rows` * `Table.to_html` * `Column.sum` * `Row.to_html` * `Row.sort_columns` --------- Co-authored-by: megalinter-bot <[email protected]>
Safe-DS · May 10, 2024 · 0e5a54b · 0e5a54b
1 parent 22d6cb6
commit 0e5a54b
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Showing 16 changed files with 8 additions and 1,092 deletions.
diff --git a/docs/tutorials/data_processing.ipynb b/docs/tutorials/data_processing.ipynb
@@ -66,29 +66,7 @@
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "3. Extract a `Row` from your `Table`:"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "source": [
-    "titanic_slice.get_row(0)"
-   ],
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": []
-  },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "4. Extract a `Column` from your `Table`:"
-   ],
+   "source": "3. Extract a `Column` from your `Table`:",
    "metadata": {
     "collapsed": false
    }
@@ -106,32 +84,7 @@
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "5. Combine a list of `Row`s to a `Table` (make sure the `Row`s have the same columns):"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "source": [
-    "Table.from_rows([\n",
-    "    titanic_slice.get_row(0),\n",
-    "    titanic_slice.get_row(1)\n",
-    "])"
-   ],
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": []
-  },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "6. Combine a list of `Column`s to a `Table` (make sure the `Column`s have the same amount of rows):"
-   ],
+   "source": "4. Combine a list of `Column`s to a `Table` (make sure the `Column`s have the same amount of rows):",
    "metadata": {
     "collapsed": false
    }
@@ -152,9 +105,7 @@
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "7. Drop columns from a `Table`:"
-   ],
+   "source": "5. Drop columns from a `Table`:",
    "metadata": {
     "collapsed": false
    }
@@ -179,9 +130,7 @@
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "8. Keep only specified columns of a `Table`:"
-   ],
+   "source": "6. Keep only specified columns of a `Table`:",
    "metadata": {
     "collapsed": false
    }

diff --git a/poetry.lock b/poetry.lock
diff --git a/pyproject.toml b/pyproject.toml
@@ -17,7 +17,6 @@ python = "^3.11,<3.13"
 apipkg = "^3.0.2"
 levenshtein = ">=0.21.1,<0.26.0"
 matplotlib = "^3.6.3"
-openpyxl = "^3.1.2"
 pandas = "^2.0.0"
 pillow = ">=9.5,<11.0"
 polars = {extras = ["numpy", "pyarrow"], version = "^0.20.25"}

diff --git a/src/safeds/data/tabular/containers/_column.py b/src/safeds/data/tabular/containers/_column.py
@@ -916,31 +916,6 @@ def standard_deviation(self) -> float:
             raise NonNumericColumnError(f"{self.name} is of type {self._type}.")
         return self._data.std()
 
-    def sum(self) -> float:
-        """
-        Return the sum of the column. The column has to be numerical.
-
-        Returns
-        -------
-        sum:
-            The sum of all values.
-
-        Raises
-        ------
-        NonNumericColumnError
-            If the data contains non-numerical data.
-
-        Examples
-        --------
-        >>> from safeds.data.tabular.containers import Column
-        >>> column = Column("test", [1, 2, 3])
-        >>> column.sum()
-        6
-        """
-        if not self.type.is_numeric():
-            raise NonNumericColumnError(f"{self.name} is of type {self._type}.")
-        return self._data.sum()
-
     def variance(self) -> float:
         """
         Return the variance of the column. The column has to be numerical.

diff --git a/src/safeds/data/tabular/containers/_experimental_column.py b/src/safeds/data/tabular/containers/_experimental_column.py
@@ -502,6 +502,7 @@ def correlation_with(self, other: ExperimentalColumn) -> float:
         Calculate the Pearson correlation between this column and another column.
 
         The Pearson correlation is a value between -1 and 1 that indicates how much the two columns are linearly related:
+
         * A correlation of -1 indicates a perfect negative linear relationship.
         * A correlation of 0 indicates no linear relationship.
         * A correlation of 1 indicates a perfect positive linear relationship.

diff --git a/src/safeds/data/tabular/containers/_row.py b/src/safeds/data/tabular/containers/_row.py
@@ -1,8 +1,7 @@
 from __future__ import annotations
 
-import functools
 import sys
-from collections.abc import Callable, Mapping
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any
 
 from safeds._utils import _structural_hash
@@ -470,57 +469,6 @@ def get_column_type(self, column_name: str) -> ColumnType:
         """
         return self._schema.get_column_type(column_name)
 
-    # ------------------------------------------------------------------------------------------------------------------
-    # Transformations
-    # ------------------------------------------------------------------------------------------------------------------
-
-    def sort_columns(
-        self,
-        comparator: Callable[[str, Any, str, Any], int] = lambda name_1, _value_1, name_2, _value_2: (
-            name_1[0] > name_2[0]
-        )
-        - (name_1[0] < name_2[0]),
-    ) -> Row:
-        """
-        Sort the columns of a `Row` with the given comparator and return a new `Row`.
-
-        The original row is not modified. The comparator is a function with four parameters:
-
-        * `name_1` is the name of the first column.
-        * `value_1` is the value of the first column.
-        * `name_2` is the name of the second column.
-        * `value_2` is the value of the second column.
-
-        It should return an integer, indicating the desired order of the columns:
-
-        * If `col1` should be ordered before `col2`, the function should return a negative number.
-        * If `col1` should be ordered after `col2`, the function should return a positive number.
-        * If the original order of `col1` and `col2` should be kept, the function should return 0.
-
-        If no comparator is given, the columns will be sorted alphabetically by their name.
-
-        Parameters
-        ----------
-        comparator:
-            The function used to compare two tuples of (ColumnName, Value).
-
-        Returns
-        -------
-        new_row:
-            A new row with sorted columns.
-        """
-
-        def cmp(column_1: tuple[str, Any], column_2: tuple[str, Any]) -> int:
-            return comparator(column_1[0], column_1[1], column_2[0], column_2[1])
-
-        sorted_row_dict = dict(
-            sorted(
-                self.to_dict().items(),
-                key=functools.cmp_to_key(cmp),
-            ),
-        )
-        return Row.from_dict(sorted_row_dict)
-
     # ------------------------------------------------------------------------------------------------------------------
     # Conversion
     # ------------------------------------------------------------------------------------------------------------------
@@ -543,23 +491,6 @@ def to_dict(self) -> dict[str, Any]:
         """
         return {column_name: self.get_value(column_name) for column_name in self.column_names}
 
-    def to_html(self) -> str:
-        """
-        Return an HTML representation of the row.
-
-        Returns
-        -------
-        output:
-            The generated HTML.
-
-        Examples
-        --------
-        >>> from safeds.data.tabular.containers import Row
-        >>> row = Row({"a": 1, "b": 2})
-        >>> html = row.to_html()
-        """
-        return self._data.to_html(max_rows=1, max_cols=self._data.shape[1])
-
     # ------------------------------------------------------------------------------------------------------------------
     # IPython integration
     # ------------------------------------------------------------------------------------------------------------------