diff --git a/loesungen/dictionaries_aufgabe.ipynb b/loesungen/dictionaries_aufgabe.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Rekapitulation Lösung Dictionaries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Ausgangslage\n",
+    "\n",
+    "salaries_1 = {'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500}\n",
+    "salaries_2 = {'Barbara': 3000, 'Elke': 3300, 'Michael': 2800, 'Johann': 2000}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500}\n",
+      "salaries_1: {'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500}\n",
+      "salaries_all: {'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500, 'Barbara': 3000, 'Elke': 3300, 'Michael': 2800, 'Johann': 2000}\n",
+      "Summe: 22100\n"
+     ]
+    }
+   ],
+   "source": [
+    "salaries_all = {}\n",
+    "\n",
+    "for key in salaries_1:\n",
+    "    salaries_all[key] = salaries_1[key]\n",
+    "\n",
+    "print(salaries_all)\n",
+    "\n",
+    "for key in salaries_2:\n",
+    "    salaries_all[key] = salaries_2[key]\n",
+    "\n",
+    "print(\"salaries_1:\", salaries_1)\n",
+    "print(\"salaries_all:\", salaries_all)\n",
+    "\n",
+    "\n",
+    "print(\"Summe:\", sum(salaries_all.values()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "salaries_1: {'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500}\n",
+      "salaries_all: {'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500}\n",
+      "salaries_1: {'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500}\n",
+      "salaries_2: {'Barbara': 3000, 'Elke': 3300, 'Michael': 2800, 'Johann': 2000}\n",
+      "salaries_all: {'Anna': 2000, 'Mark': 3000, 'Judith': 3500, 'Thomas': 2500, 'Barbara': 3000, 'Elke': 3300, 'Michael': 2800, 'Johann': 2000}\n",
+      "8\n"
+     ]
+    }
+   ],
+   "source": [
+    "salaries_all = salaries_1.copy()\n",
+    "\n",
+    "print(\"salaries_1:\", salaries_1)\n",
+    "print(\"salaries_all:\", salaries_all)\n",
+    "\n",
+    "salaries_all.update(salaries_2)\n",
+    "\n",
+    "print(\"salaries_1:\", salaries_1)\n",
+    "print(\"salaries_2:\", salaries_2)\n",
+    "print(\"salaries_all:\", salaries_all)\n",
+    "\n",
+    "print(len(salaries_all))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'Anna': 2200.0, 'Mark': 3300.0000000000005, 'Judith': 3850.0000000000005, 'Thomas': 2750.0, 'Barbara': 3300.0000000000005, 'Elke': 3630.0000000000005, 'Michael': 3080.0000000000005, 'Johann': 2200.0}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Alternative 1\n",
+    "salaries_new = salaries_all.copy()\n",
+    "salaries_new.update((key, value * 1.1) for key, value in salaries_new.items())\n",
+    "\n",
+    "# Alternative 2\n",
+    "results = []\n",
+    "for key, value in salaries_all.items():\n",
+    "    results.append((key, value * 1.1))\n",
+    "salaries_new = dict(results)\n",
+    "\n",
+    "# Alternative 3\n",
+    "salaries_new = {}\n",
+    "for key, value in salaries_all.items():\n",
+    "    salaries_new[key] = value * 1.1\n",
+    "\n",
+    "print(salaries_new)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "softed",
+   "language": "python",
+   "name": "softed"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}