diff --git a/Kapitel_1._Einstieg_in_die_Welt_von_Python.ipynb b/Kapitel_1._Einstieg_in_die_Welt_von_Python.ipynb
index f079791..bdeda9e 100644
--- a/Kapitel_1._Einstieg_in_die_Welt_von_Python.ipynb
+++ b/Kapitel_1._Einstieg_in_die_Welt_von_Python.ipynb
@@ -32,25 +32,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.511195Z",
-     "start_time": "2019-10-27T12:26:11.504240Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "5"
-      ]
-     },
-     "execution_count": 115,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "3 + 2"
    ]
@@ -174,75 +158,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.527053Z",
-     "start_time": "2019-10-27T12:26:11.518434Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-1.3333333333333335"
-      ]
-     },
-     "execution_count": 116,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "2 / 3 - 2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.542542Z",
-     "start_time": "2019-10-27T12:26:11.529137Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10"
-      ]
-     },
-     "execution_count": 117,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "3**2 * 2 - 8  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 118,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.560548Z",
-     "start_time": "2019-10-27T12:26:11.545269Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "81"
-      ]
-     },
-     "execution_count": 118,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "3**2**2"
    ]
@@ -256,50 +192,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.577576Z",
-     "start_time": "2019-10-27T12:26:11.563352Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10"
-      ]
-     },
-     "execution_count": 119,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "3**2 * 2 - 8  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.592854Z",
-     "start_time": "2019-10-27T12:26:11.580500Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-54"
-      ]
-     },
-     "execution_count": 120,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "3**2 * (2 - 8 ) "
    ]
@@ -313,13 +217,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 121,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.609873Z",
-     "start_time": "2019-10-27T12:26:11.597179Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "a = 5"
@@ -327,38 +226,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 122,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.627541Z",
-     "start_time": "2019-10-27T12:26:11.612880Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "5"
-      ]
-     },
-     "execution_count": 122,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "a"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 123,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.643914Z",
-     "start_time": "2019-10-27T12:26:11.629582Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "variable = 2"
@@ -366,25 +244,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 124,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.659328Z",
-     "start_time": "2019-10-27T12:26:11.646431Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10"
-      ]
-     },
-     "execution_count": 124,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "a * variable"
    ]
@@ -398,25 +260,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 125,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.674632Z",
-     "start_time": "2019-10-27T12:26:11.662827Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "21"
-      ]
-     },
-     "execution_count": 125,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "a = 4\n",
     "b = 3\n",
@@ -434,13 +280,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 126,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.690316Z",
-     "start_time": "2019-10-27T12:26:11.677704Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "a = 7"
@@ -448,13 +289,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 127,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.706441Z",
-     "start_time": "2019-10-27T12:26:11.692773Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "a = 4"
@@ -462,25 +298,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 128,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.721624Z",
-     "start_time": "2019-10-27T12:26:11.709163Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "12"
-      ]
-     },
-     "execution_count": 128,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "a * b"
    ]
@@ -494,25 +314,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 129,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.737726Z",
-     "start_time": "2019-10-27T12:26:11.721624Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10"
-      ]
-     },
-     "execution_count": 129,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "a = 2\n",
     "b = 5\n",
@@ -522,25 +326,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 130,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.757359Z",
-     "start_time": "2019-10-27T12:26:11.741666Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10.0"
-      ]
-     },
-     "execution_count": 130,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "a = 2\n",
     "b = 5.0\n",
@@ -574,25 +362,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 131,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.773040Z",
-     "start_time": "2019-10-27T12:26:11.759880Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Dies ist eine Zeichenkette'"
-      ]
-     },
-     "execution_count": 131,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "'Dies ist eine Zeichenkette'"
    ]
@@ -606,22 +378,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 132,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.790081Z",
-     "start_time": "2019-10-27T12:26:11.776184Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0123456789 äöü *+~`´?ß-@€ python 3.7>\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "s1 = '0123456789'\n",
     "s2 = 'äöü'\n",
@@ -640,24 +399,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 133,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.805410Z",
-     "start_time": "2019-10-27T12:26:11.792628Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Dies ist Syntaxvariante eins\n",
-      "\n",
-      "Dies ist Syntaxvariante 2\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "a = 'eins'\n",
     "b = 2\n",
@@ -676,24 +420,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 134,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.821505Z",
-     "start_time": "2019-10-27T12:26:11.807484Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Dies ist pi auf 4 signifikante Stellen gerundet: 3.142\n",
-      "\n",
-      "Dies ist pi auf 4 signifikante Stellen gerundet: 3.142\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "pi = 3.1415926535\n",
     "\n",
@@ -711,25 +440,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 135,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.837390Z",
-     "start_time": "2019-10-27T12:26:11.823604Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "An einem Widerstand R wurden die folgenden Werte gemessen:\n",
-      "Spannung: 12.0+/-0.1 V\n",
-      "Strom:    0.3+/-0.01 mA\n",
-      "Hierraus resultiert ein Widerstand von 40.0+/-1.4 kOhm \n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "U = 12.0   #V\n",
     "dU = 0.1   #V\n",
@@ -760,13 +473,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 136,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.852541Z",
-     "start_time": "2019-10-27T12:26:11.839941Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def Spannung(Widerstand, Strom):  # U(R,I)\n",
@@ -782,25 +490,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 137,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.868415Z",
-     "start_time": "2019-10-27T12:26:11.855987Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10.0"
-      ]
-     },
-     "execution_count": 137,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# Leider müssen wir hier auf die Einheiten selbst achten.\n",
     "# Deshalb ist es ratsam sich die Einheiten zu den Werten zu notieren.\n",
@@ -829,13 +521,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 138,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.884347Z",
-     "start_time": "2019-10-27T12:26:11.871135Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def Spannung(Strom, Widerstand):\n",
@@ -868,25 +555,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.900144Z",
-     "start_time": "2019-10-27T12:26:11.887370Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert1', 'Wert2', 'Wert3']"
-      ]
-     },
-     "execution_count": 139,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Messwerte1 = ['Wert1', 'Wert2', 'Wert3']  # Variante 1\n",
     "Messwerte1"
@@ -894,25 +565,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 140,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.915757Z",
-     "start_time": "2019-10-27T12:26:11.901901Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[2, 0.9, '1']"
-      ]
-     },
-     "execution_count": 140,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Messwerte2 = list([2, 0.9, '1'])          # Variante 2\n",
     "Messwerte2"
@@ -929,25 +584,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 141,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.932392Z",
-     "start_time": "2019-10-27T12:26:11.916752Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert1', 'Wert2', 'Wert3', 'Wert5']"
-      ]
-     },
-     "execution_count": 141,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Messwerte1.append('Wert5')\n",
     "Messwerte1"
@@ -955,25 +594,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 142,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.947965Z",
-     "start_time": "2019-10-27T12:26:11.935910Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert1', 'Wert2', 'Wert3', 'Wert5', 'Wert4']"
-      ]
-     },
-     "execution_count": 142,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Messwerte1.insert(4, 'Wert4')\n",
     "Messwerte1"
@@ -990,13 +613,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 143,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.963385Z",
-     "start_time": "2019-10-27T12:26:11.950437Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "NeueWerte = ['Wert1', 'Wert2', 'Wert3', 'Wert4', 'Wert5', 'Wert6'] "
@@ -1011,50 +629,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 144,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.978721Z",
-     "start_time": "2019-10-27T12:26:11.965411Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Wert1'"
-      ]
-     },
-     "execution_count": 144,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "NeueWerte[0]  # Hier seht ihr, dass der erste Wert den Index 0 hat."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 145,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:11.994023Z",
-     "start_time": "2019-10-27T12:26:11.980553Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Wert3'"
-      ]
-     },
-     "execution_count": 145,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "wert_index_2 = NeueWerte[2]   \n",
     "wert_index_2"
@@ -1069,100 +655,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.010686Z",
-     "start_time": "2019-10-27T12:26:11.996882Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert1', 'Wert2', 'Wert3']"
-      ]
-     },
-     "execution_count": 146,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "NeueWerte[0:3]    "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.026218Z",
-     "start_time": "2019-10-27T12:26:12.012554Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert3', 'Wert4', 'Wert5']"
-      ]
-     },
-     "execution_count": 147,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "NeueWerte[2:5] # Ihr seht Python behandelt den letzten Wert wie in einem offenen Intervall [2,5)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.041422Z",
-     "start_time": "2019-10-27T12:26:12.029154Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert3', 'Wert4', 'Wert5', 'Wert6']"
-      ]
-     },
-     "execution_count": 148,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "NeueWerte[2:]  # Hier werden alle Werte mit dem Index >= 2 zurück gegeben"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 149,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.057959Z",
-     "start_time": "2019-10-27T12:26:12.043979Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert4', 'Wert5', 'Wert6']"
-      ]
-     },
-     "execution_count": 149,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "NeueWerte[-3:] # Mit negativen Zahlen fangt ihr vom Ende der Liste an"
    ]
@@ -1176,35 +698,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 150,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.073093Z",
-     "start_time": "2019-10-27T12:26:12.060135Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert1',\n",
-       " 'Wert2',\n",
-       " 'Wert3',\n",
-       " 'Wert5',\n",
-       " 'Wert4',\n",
-       " 'Wert1',\n",
-       " 'Wert2',\n",
-       " 'Wert3',\n",
-       " 'Wert4',\n",
-       " 'Wert5',\n",
-       " 'Wert6']"
-      ]
-     },
-     "execution_count": 150,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Messwerte1 + NeueWerte"
    ]
@@ -1218,30 +714,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 151,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.088532Z",
-     "start_time": "2019-10-27T12:26:12.078147Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert1',\n",
-       " 'Wert2',\n",
-       " 'Wert3',\n",
-       " 'Wert5',\n",
-       " 'Wert4',\n",
-       " ['Wert1', 'Wert2', 'Wert3', 'Wert4', 'Wert5', 'Wert6']]"
-      ]
-     },
-     "execution_count": 151,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Messwerte1.append(NeueWerte)\n",
     "Messwerte1"
@@ -1256,36 +731,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 152,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.103764Z",
-     "start_time": "2019-10-27T12:26:12.091184Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Wert1',\n",
-       " 'Wert2',\n",
-       " 'Wert3',\n",
-       " 'Wert5',\n",
-       " 'Wert4',\n",
-       " ['Wert1', 'Wert2', 'Wert3', 'Wert4', 'Wert5', 'Wert6'],\n",
-       " 'Wert1',\n",
-       " 'Wert2',\n",
-       " 'Wert3',\n",
-       " 'Wert4',\n",
-       " 'Wert5',\n",
-       " 'Wert6']"
-      ]
-     },
-     "execution_count": 152,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Messwerte1 = Messwerte1 + NeueWerte\n",
     "# Tipp dies könnt ihr auch einfach mit Hilfe von\n",
@@ -1304,32 +752,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 153,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.119046Z",
-     "start_time": "2019-10-27T12:26:12.106470Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['Wert1', 'Wert2', 'Wert3', 'Wert5', 'Wert4', ['Wert1', 'Wert2', 'Wert3', 'Wert4', 'Wert5', 'Wert6'], 'Wert1', 'Wert2', 'Wert3', 'Wert4', 'Wert5', 'Wert6']\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "12"
-      ]
-     },
-     "execution_count": 153,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "print(Messwerte1)\n",
     "len(Messwerte1)"
@@ -1344,25 +769,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 154,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.135058Z",
-     "start_time": "2019-10-27T12:26:12.123078Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "range(0, 5, 2)"
-      ]
-     },
-     "execution_count": 154,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "range(0,  # <-- Startwert\n",
     "      5,  # <-- Endwert (nicht mehr enthalten, offenes Ende)\n",
@@ -1379,25 +788,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 155,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.150810Z",
-     "start_time": "2019-10-27T12:26:12.139084Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[0, 2, 4]"
-      ]
-     },
-     "execution_count": 155,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "list(range(0,5,2))"
    ]
@@ -1413,29 +806,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 156,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.190364Z",
-     "start_time": "2019-10-27T12:26:12.152805Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Wert: 1\n",
-      "Ergebnis: 3\n",
-      "Wert: 2\n",
-      "Ergebnis: 4\n",
-      "Wert: 3\n",
-      "Ergebnis: 5\n",
-      "Wert: 4\n",
-      "Ergebnis: 6\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "liste = [1, 2, 3, 4]\n",
     "\n",
@@ -1454,32 +827,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 157,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.221796Z",
-     "start_time": "2019-10-27T12:26:12.194886Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Hier läuft das Hauptprogramm\n",
-      "Schleife\n",
-      "Wert: 1\n",
-      "Schleife\n",
-      "Wert: 2\n",
-      "Schleife\n",
-      "Wert: 3\n",
-      "Schleife\n",
-      "Wert: 4\n",
-      "Hier läuft wieder das Hauptprogramm\n",
-      "Letztes Ergebnis + 5:  11\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "liste = [1, 2, 3, 4]\n",
     "print('Hier läuft das Hauptprogramm')\n",
@@ -1503,25 +853,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 158,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.254001Z",
-     "start_time": "2019-10-27T12:26:12.227788Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[10.1, 10.5, 9.8, 8.7, 11.2]"
-      ]
-     },
-     "execution_count": 158,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Stromwerte = [101, 105, 98, 87, 112]    # mA\n",
     "Spannungswerte = []# Einheit? <-- Deshlab Docstrings und Help!\n",
@@ -1542,13 +876,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 159,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.269295Z",
-     "start_time": "2019-10-27T12:26:12.256646Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "Spannungswerte = [Spannung(Strom, 1000) for Strom in Stromwerte]"
@@ -1563,25 +892,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 160,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.286560Z",
-     "start_time": "2019-10-27T12:26:12.271505Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "A  und  0\n",
-      "B  und  1\n",
-      "C  und  2\n",
-      "D  und  3\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "Werte1 = ['A', 'B', 'C', 'D']\n",
     "Werte2 = [0, 1, 2, 3]\n",
@@ -1599,23 +912,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 161,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.302437Z",
-     "start_time": "2019-10-27T12:26:12.288197Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[335.4904, 347.3442, 343.6145, 337.275, 331.6212, 342.0115, 336.2262]\n",
-      "[335.4904, 347.3442, 343.6145, 337.275, 331.6212, 342.0115, 336.2262]\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# Gemessene Werte:\n",
     "frequenzen = [30.17, 30.63, 30.01, 29.98, 30.12, 29.87, 29.94] #kHz\n",
@@ -1643,24 +942,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 162,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.318819Z",
-     "start_time": "2019-10-27T12:26:12.304012Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "a und 1 und x\n",
-      "b und 2 und y\n",
-      "c und 3 und z\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "l1 = ['a', 'b', 'c']\n",
     "l2 = [1, 2, 3]\n",
@@ -1713,13 +997,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 163,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.336089Z",
-     "start_time": "2019-10-27T12:26:12.321658Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt   "
@@ -1734,27 +1013,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 164,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:12.652722Z",
-     "start_time": "2019-10-27T12:26:12.339189Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "plt.plot([1,2,3,4,5],   # <-- x-Daten\n",
     "         [1,2,3,4,5]    # <-- y-Daten\n",
@@ -1780,27 +1041,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 165,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:13.143697Z",
-     "start_time": "2019-10-27T12:26:12.655985Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "xdaten = [1,2,3,4,5]\n",
     "ydaten = [1,2,2,4,5]\n",
@@ -1842,27 +1085,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 166,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:13.676781Z",
-     "start_time": "2019-10-27T12:26:13.146215Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "xdaten = [1,2,3,4,5]\n",
     "ydaten = [1,2,2,4,5]\n",
@@ -1897,27 +1122,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 167,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:14.109984Z",
-     "start_time": "2019-10-27T12:26:13.677777Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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OQghxDtYfWc/8hPlcf971XNXhKrPDqTOSHIQQopYyCzN5YvUTtAtqxxN9nzA7nDolw0pCCFELWmueXvM0mUWZzLpsFn5WP7NDqlPScxBCiFr4aOdH/JL0C4/FPUbXsK5mh1PnJDk42dGjR7nlllvo2LEj3bt356qrrjrpyuhTRUZGkpaWVmn722+/XX4x3dkICHCvYl9CuIOdGTv5fxv/HxdHXMytXW81OxynkGElJ9Jac8MNN3DHHXfwySefABAfH09KSgqdO3c+q8+67777nBGiEOIs5ZfkM+7XcYR6h/L8gOfdqgz32ZCegxOtXLkSq9V60ok9JiYGm8120o16HnroId57773yx6+88gp9+/alb9++7N27FzDKcpddofzGG2/QvXt3oqOjueWWWwDIzc3lrrvuIioqiujo6JNqOk2aNIlevXrRr18/UlJSnHnIQjR4L69/mYM5B3n5opcJ9Qk1OxynaRQ9h2nrp7EzY2edfmbXsK5M6Duhxtds27atVldCBwUFsX79et5//30eeeSR8hLbZaZOncr+/fvx9vYmKysLgOeff57g4GC2bjVKk2dmZgKQl5dHv379ePHFFxk/fjzz589n8uTJZx2TEAK+3fctX+39irHRY+nbsq/Z4TiV9Bxc0KhRo8q///7775Wej46OZvTo0Xz44Yd4ehr5fcWKFTz44IPlrwkNNVo0Xl5e5b0UKa8tRO0dOn6I59Y9R0x4DPf3ut/scJyuUfQcTtfCd5YePXrw2WefVdru6emJ3W4vf1xWkrtMxTHMqsYzly1bxqpVq1i6dCnPP/88iYmJ1ZbXtlqt5dulvLYQtVNiL2HCqglYlIVpg6bhaWn4p07pOTjRpZdeSlFREfPnzy/ftmHDBmw2G9u3b6eoqIjs7Gx++umnk963ePHi8u8XXnjhSc+Vlfi+5JJLmD59OllZWeTm5jJ06FDeeuut8teVDSsJIc7dm3++yda0rTx74bO0Cmhldjj1QpKDE5WV7F6+fDkdO3akR48ePPvss7Rq1YqRI0eWDw/17t37pPcVFRVxwQUX8Prrr1cqrW2z2RgzZgxRUVH07t2b//u//yMkJITJkyeTmZlZXnZ75cqV9XmoQjRYa5PXsnDbQm7qfBNDI4eaHU69kZLdwmnkdyDcXVpBGjctvYlQn1A+uvojfD19zQ6pTknJbiGEOEt2bWfyb5PJLcll/tD5DS4xnI4MKwkhRBXeT3yfNYfXMC5uHJ1CO5kdTr1r0MmhIQyZuSv5txfubFvaNl7f/DpD2g5hZJeRZodjigabHHx8fEhPT5eTlAm01qSnp+Pj42N2KEKctdziXMavGk9Tv6ZM6T+lwZbHOJ0GO+cQERFBUlISqampZofSKPn4+BAREWF2GEKcFa01L/zxAsm5ySy8YiHB3sFmh2QaU5ODUmoBcA1wTGvd07EtDFgMRAIHgJFa67NetG+1Wmnfvn3dBSuEaPC+2fcNy/Yt44GYB4htHmt2OKYye1jpPeDKU7ZNBH7SWncCfnI8FkIIpzqQfYAX1r1AXPM4xkaNNTsc05maHLTWq4CMUzZfByxy/LwIuL5egxJCNDrFtmLGrxqPl4cXL1/0Mh4WD7NDMp0rzjk011ofAdBaH1FKNavqRUqpscBYgLZt29ZjeEKIhmbGphnsyNjB65e8Tgv/FmaH4xLMHlaqNa31PK11nNY6Ljw83OxwhBBualXSKj7c8SGjuo7i0raXmh2Oy3DF5JCilGoJ4Ph+zOR4hBAN1LH8Y0z+bTJdQrvwWNxjZofjUlwxOSwF7nD8fAfwtdP2lLYHvhgLe38Cu81puxFCuB6b3caTq5+k0FbI9Iun4+3hbXZIZ05rSN4M302End86ZRdmL2X9GBgMNFVKJQHPAFOBT5VS/wT+BkY4LYDUXbDre0hYDAHNIWoERI+EFtHQSC98EaKxWJi4kD+O/sGU/lPoENzB7HDOTOZB2PopJHwKabvBwwsCwqHrVXW+qwZblfWMlRTCnh+Mf+zdP4C9BMK7QvTNRrIIaVO3wQohTBd/LJ47v7+Ty9tdzvRB0137KuiCTEj8yjhH/b3W2NZugNGQ7X4d+Nb+PtY1VWWV5FBRfgYkfmn8Eg6tM7ZFXmT8EroNB9+Qc9+HEMJUOcU5jFg6AqUUS65dQqBXoNkhVVZaBHt+NEY1dv8AtmJo2tlotEaPhJC6WaEpyaE2MvbD1iXGLyd9L3h4Q5dhxi/nvMvA06tu9yeEcCqtNeuOrOP1za+zM2Mni4Ytold4L7PDOkFr+Hudcc5J/BIKs8C/GUTdZJx3Wvaq8+FuSQ7nomziJ2ExbPsc8tPANwx63mj8wiLOl/kJIVzc+iPrmRU/i83HNtPcrzmPn/84V0aeWpzBJGl7jPNLwmLI+husftD1GuP80mEweDhvaliSQ12xlcBfPxu/xJ3LoLQQQtuf6Oo16ej8GIQQZ2zD0Q3Mjp/NxpSNNPNtxj3R9/CPTv/Ay8Pknn9uqtHYTFgMhzeDshiJIPpmIzF4B9RLGJIcnKEwB3Z8Y/xy968CtNGLiL4ZetwI/k3qNx4hRLnNKZuZHT+bP47+QVPfptwTdQ83db7J3OWqxfmw61vjnLH3J9A2Y2Vk9M3G0FFg/V+ZLcnB2bKTYdtnxkR2yjaweMJ5lxu9iS7DwNq4bi8ohFnij8UzO342vx/5nTCfMP7Z85+M7DISH0+T7i1itxmNx4RPYcdSKM6FoAiIHmEkhWbm3mNdkkN9OrrNaBlsXQLHj4B3EHQfbvxHaDcQLK543aEQ7i0hNYHZ8bNZc3gNYT5h3N3zbkZ2GWnefZ+PbnWcBz6rcB64znEeGOAy5wFJDmaw2+DAaqPFsP1rR4uhteNCu5uheXezIxTC7SWmJTIrfhark1cT4h3CXT3v4pYut+Bn9av/YLKTHSscP4VjicYIQqehxghC5ytdcgRBkoPZyscaP4W9K4yxxuZR0Otm6HkTBLU0O0Ih3Mr29O3Mjp/Nr0m/EuwdzJ097mRU11H4W/3rN5DCHGO4KGEx7F+NMffY10gIbjD3KMnBleSmQuIXxn+m5E3GKoX2Fxu9iW7XgLcLXpAjhIvYmbGT2fGzWXloJYFegdzZ405u7XorAV71s7oHMFYt7v3J+Bve9a2xajGsw4mqCm60alGSg6tK22P0JhIWQ9ZB8PQ1EkT0zdDhEqeubxbCnezO3M2c+Dms+HsFgdZAbutxG2O6jam/q5u1Nhpz5dc7pTuud/qH43qnOLe83kmSg6vTGg794fiP94XjyshwY8gpeiS06u2W//GEOFd7MvcwZ8sclh9cToA1gDHdx3Bb99sI8gqqnwAy9kGCo1JCxl9GpYSuVxkJoeMQt6+UIMnBnZQWwZ7ljpoq31eoqTISokZCaDuzIxTC6fZl7WPOljn8cOAH/Kx+jO42mtu7306wd7Dzd56fYQz9blkMSesBBZEDjYTQfTj41EMM9eSck4NSygtoq7XeW9fB1YUGlRwqKsg0VjolfAoH1xjb2vZ3THZdf07VGIVwRfuz9/P2lrf5bv93+Hj6MLrbaO7ofgchPk4uellSaDTGEj41Ct7ZSyC8m7FoJGoEBEc4d/8mOafkoJS6GngN8NJat1dKxQDPaK1vqPtQa6fBJoeKMg+eKARYVse98xVGa6bTUPB0oxuVCHGKgzkHmbtlLsv2L8Pbw5tRXUdxZ487CfVxYgPIbjdKYCcshsSvoSgbAlqcKHTXIqrBD+eea3LYBAwBVmqtezu2bdVaR9V5pLXUKJJDGa3hSLzRwtm6BPJSwScEetxgXGQTEScrnoTbOJRziLcT3mbZvmVYLVZu6XoLd/a4kya+TloCWlpkXKC2c5nx95N9CKz+jgtVRxorBy0eztm3C6opOZzJcpgSrXXWKTfDcP+JCnellDFB3ao3XP487PvlREXHTQsBZVySHxEHreOMek/hXRrVf3jh+pKOJzEvYR5L/1qKp8WTW7vdyt0976apb9O624nWxirApI2Orw1wNMGYx1Me0PFSGPKMMcHsVc/XR7iBM0kOO5RSIwGLUqo98B9gnXPDEmfEwxM6XWZ8FeUateCTNkDyRti+FDa/b7zOK8BIJhHnn0gagc3NjV00SodzDzMvYR5f7/0ai7Iwquso7u55N+F+4ef+4YXZRnn95I0nEkJ+mvGcp6/xN3DBv4y/g7b9jdtrimqdybCSP/A0MNSx6Qdgita6wMmxnbFGNax0prSG9L8cfygbjD+UlG1gLzWeD25rJIqyZNGyF1hNKk4mGrwjuUeYv3U+X+79EoXips438c+e/6S5fy0bKbZSSN1xIgkkbzTuCV82qNG0s6Pn7Phq1h08rHV2PA3Fuc453Ki1/uJ028wkyeEMlRTAkS0nutjJm4wxVwCLFVr0NFpVZX9UYR0a/ISccK6jeUd5Z+s7fL7ncwD+0ekf3BN1Dy38z7I8dc6Rk3sEh/+EkjzjOd8wRxI4H1r3gdaxDWIln9aa40WlZOeXkJlfTJbje3ZBCZl5JWQVGNsGdwnnupjWtdrHuc45TAZOTQSTqtgmXJ3VF9r2M77KHD96ouWVtBH+/C+sn2c85xtm/LFFnA8RfYyfG8AfnXC+Y/nHeHfruyzZvQStNTd0uoF7o+6lZcAZ1BErzjcaMeW93k2Qk2Q8Z7Eaq4h6jz6RDFy8EaO1Jr/YVn6Cz8o3TuyZ+SVk5xvfje3FZBU4EkB+CVkFJdjs1TfeA709Cfaz0q2lcxagVJsclFJXAFcCrZVSr1V4KgiwOyUaUf8CWxglO7pdYzy22+DYjpP/MPeuoLy73qTTycNRzXtId12USytIK08KNruN6867jnuj76V1QDUtW7vduPK4vDe7EVISTwx/hrSFNn0h4kHj/1yLaFOHPwuKbcaJvULLvWKLPiu/7KTvaO0XGD8X26o/Zfp5eRDq50Wwr5VQfyvdWgQR4mclxM9avj3Ez4tQx7YQxzarh3PLftfUczgGbAMKgcQK248DE50ZlDCRxcMYXmrRE/rcaWwrzDFuZVjWpd+7ArZ8bDzn6QutYk5eHRVcuy6ucF9pBWks3LaQxbsWU2ovZXjH4dwbfS9tAtuc/ML8DGM4s2weLHmTUS4GwCsQWveGAf85MbQZ0Mwp8RaV2hwn8Aon9IJTWvEVh3Ecj4tKqz/Je3taCPXzKj+xdwwPINTfSrDvySf2EF8rof7G92A/K96errmSsMY5B6WUB/Cx1npk/YV09mTOoZ5pbdwIvWzeImmDMQxgKzaeD2xZYTgqzlglIksFG6SMwgwWblvIJzs/odhezDUdruFf0f+ibVBbKC02FkFUTAYZfxlvVBbjCuSyXmjE+cYk8lkuuS6x2ck65cReNixT1nI/caI3hnGyCkrIL7ZV+5lWD3Wipe7rdXIr3vE9xNGaL9se4mfFx+qaJ/ma1HrOQWttU0oFK6WsWusS54Qn3I5SRo2n0HbG1aTgOBFsPXlN+c7/OV7vYawWqTgc1bSzy9wNS5y9zMJM3kt8j493fkyRrYir21/Fv9oPp13WEVj7tjE8dGSLUc4aIKC5kQB6jznRYKhwsWapzU5OQSmZ+QU1ttzLxuvLfs4tKq02Rk+LIsTPagzX+HnROsSHHq2CHCf2k0/uwRVa835eHigXnsOoL2eyWultIAb4Gsgr2661fsO5oZ056Tm4qLw0R6uxbMJ7k1GiAIzbJraOPXl1lH8dXgAlnCK7KJtFiYv4747/UlBawLCA9txX5En7w1shNwUA7elDUXgUOWG9OBYSTZJfN47opmQWlJa33E+ejC0mp7D6k7xFUX6Cr9hyD67Qai8frqkwrBPg7Skn+dM416Wsz1e1XWv9VB3EVickObgJux3S956YeExyTD5qRxc/NPLEvEVYB2NllF+Y8d0nWK7yrkd2m42jGUkcST3Ascy/yTh+hO1ZW1lemEAhdobm5XN/VhYdS0pJ9mhNourERtt5/F4UyQ57W0qrGZQILmu1+1bRcq/Qmq84rBPo44nFIid5Z6iTkt1KKW+tdVGdRlZHJDm4seI8x7UXG04MSR0/XMULlZEgypKFb9jJyaPssW8o+IWe2OYd1KiHr+w2G+k5KSQf28exjEOk5RwmO+8Y2YVp5BZnkVd6nMHvTj4AABkdSURBVAJ7Pvm6kHxVQp7FRq5Fc9yisFXR6h6cW8SFGeFklXblL+9uHPbvgWdAWIWWu5VgvyomYP28CPK14iEneZdyTtc5KKX6Au8CwUBbpVQv4B6t9b/rNsxK+70SeB3wAN7RWk915v6ESbz8oV1/46tMzmHjKz/DKFte4Phe8XF+mlGdtiDrxFBVVZQH+IbUkFBCqk4w3oEut3Y+MzuV5NR9HE3/m/ScZLJyU8guTCe3OJO8kuPk2/PI14UUqBJyVSl5Fs1xD0VJdcehwNfDTqACf7sFf+1JS5svftoXP/wJsAYT4BVKiF8zwgKa0yq8Mx3aXUiwn5fTl1EK853JRXBvANcAXwForbcopS5xZlCOVVKzgMuBJGCDUmqp1nq7M/crXERQK+PrTNlKjeWQpyaQqh4fP2Jcx1GQAcW51X+mxbOahBJadY+l7LHV77RJ5XheFkkpf5GS8TepWclk5qWQU5BKblEWeaU55NnyKNCF5Kki8pWNXIudXIuiqIZWt7eHJlBpAuwW/LQnze3++OGDHwEEWAMJ8Aol2C+cEP/mhIdE0CKsLa2atSfQ38n3SRBu60ySg0VrffCUiZ3q14HVjb7AXq31PgCl1CfAdYAkB1GZh6cxmX22E9qlxY7EUVUyOWVb1iFj+KsgE0ryASgBsi0Wsj0sZFs8yPKwkOnhRbrVl3QPbzI8vMhQijxVanxZ7By3KAprOMlbPTRBaEdL3oOmdl/aaG/8dQB+lkACvUIJ8m1CqH8Lmga3onmTSFo3iyQkUCbzRd06k+RwyDG0pB0t+n8Du50bFq2BQxUeJwEXVHyBUmosMBagbdu2Tg5HNEieXhDYnEKfUJI9Qki2p3OkOIgUFUQqQaQTRLZHKDneTcizHKfAJ4fikFxKdS7akoe2FFf70RatCbAXE2g3WvOh2ofWNh/8tB/+KogAr2CCfMMJ9Q+nSVBrmoe1oXWzDoQGhmPxkIl3Yb4zSQ73YwwttQVSgBWObc5UVdPqpJlzrfU8YB4YE9JOjke4gVKbjcPHM0jKTudwTjopeRmk5meSXpBFVmEWOcXZ5JbmUGDLpch+nFKdi13lgUdhtZ+ptULZffHQAXgqf3wtofh5tCXAGkyQdxBhPiGE+YbSzD+U5v5htA5qQkRwE5r5B2NpxBPhwv3VVFspSGudo7U+BtxSjzGB0VOoeN19BFDVEhbRANntdo7mZnEoK50juekcyc0gNS/DcZLPJrs4y5iAteVQZM+lxHGS15YClKq6nWCc5H2waH+sKgAfSyB+Hq3xtwYR5BVMiHcwTf1CaeoXQouAJrQKDCMiKJwWgcF4SkteNEI19Rz2KaWSgbXAGmBt2RxAPdgAdHLcXCgZIzndWk/7FnVEa01esa38atesiiUN8spKG5yoRpmRn0emZQ0lgSuwWGtYgWT3wWL3x1P5460CCbY2J8AziECvIEK8Q2jiG0JTR0u+VWATIoKa0CooDC/PM+koCyGghuSgtW6qlOoO9AcuBSYrpYKA34E1WuvXqnvvudJalyqlHsK4sZAHsEBrnXiatwkn0VpTWGKvUMLgRGlho65NCZl5VdSxKSimxFb9iJ+/l4dRYdJPYfffwHG/ZdjIoLm1C10DbyTMN5SmfqE09w+lZWATWgc1oXVwGH5W73o8eiEap7O5CK4dcC3wCBChtXaZ24bJRXBnrrDEVrlWzSl15KuqO19cQzVKH6ulUoGyUy+AOrnUgVHvxmKxs3TvUuYlzONw3mGiw6N5sNeDXNjqQil7IEQ9qNVFcI4VSv0dX5HA3xj3jr4TkDOxyYpL7eX147NqaLkbdedPbC8oqX4VspeHpfzkHeLnRbsmfsT4hZxSpMxRgtj/RMXKs61GWWov5Zu/ljI3YS7Jucn0bNKTpy58igGtBkhSEMJF1DQIuw7YDMwAPnPV0hnurtTmOMmfcmIvH6cvOOXmIY7n8mooOVxWjbKs5d46xJcerYJOrl3jqDEfXKGOja/VudUoS+2lLNu3jLkJczl0/BDdm3TnyQue5KLWF0lSEMLF1JQc2gADMHoODyhjGchGjDmH37XWf9dDfG7DbtfkFFZxYne03MsrUBacXI74+GmqUYaU14630jzIhy4tAstb7CfVsfF13WqUNruNb/d/y9yEuRzMOUi3sG68cckbDG4z2KXiFEKcUNOEdDLwqeMLpZQ/cBfwItAeY6K4wSm7qXdW3olW+6mrbU4es3fcCrCghOqmb5SCIB9rhWqTXnRo6l+hFW/Ukg/2PXm8PtDbvatR2uw2fjjwA28nvM3+7P10Ce3CzEtmcmmbSyUpCOHiappzCAD6cWLeIQ44CHyHsbTV7a3fn8HcX/+qcMco4yR/upt6h1QYb28T5udouZ9SgrhC3fnGVo3Sru38eOBH5myZw77sfZwXch6vDX6NIW2HYFFyYZgQ7qCmYaWDwHqM6xxeAdZprfNqeL3bKS61czSnkBA/Ky1DfE+6WciprfiybVKNsnp2bWfFwRXM2TKHvVl76RjckVcufoWh7YZKUhDCzdSUHJrqU9a5KqWaaq3TnBxTvRnYqSnLOl1kdhhuz67t/Pz3z8zZMofdmbtpH9ye6YOmM7TdUDzkBj1CuKWa5hyqGlv5EYh1XjjCnWitWXloJXO2zGFnxk4igyJ5+aKXGRY5TJKCEG7ubOsJNJ6Bc1EtrTWrklYxe8tstqdvp21gW14a+BLD2g/D0yIlKoRoCGqakP4WeEBrfaDC5gVOj0i4LK01q5NXMyd+DtvStxEREMHzA57nmg7XSFIQooGp6S/6PeBHpdQiYLrWukRr/Wb9hCVcidaatYfXMjt+NglpCbQOaM2U/lO4tuO1WC1Ws8MTQjhBTXMOnyqllgFPAxuVUh8A9grPO63wnnANWmvWHVnHrPhZbEndQkv/ljxz4TNc1/E6rB6SFIRoyE43FlAC5AHeQCAVkoNo2NYfWc+s+FlsPraZ5n7NearfU9xw3g2SFIRoJGqac7gSeA1YCsRqrfPrLSphmg1HNzA7fjYbUzbSzLcZky6YxI2dbsTLw8vs0IQQ9aimnsMkYITcR6Fx2JSyidnxs1l/dD1NfZsyse9Ebup8E94ecu8EIRqjmuYc5OqwRiD+WDyz4mex7sg6mvg0Yfz54xnReQQ+ni5zuw4hhAlk/WEjlZCawOz42aw5vIYwnzAej3uckV1G4uvpa3ZoQggXIMmhkdmWto1Z8bP4Lfk3Qr1DebTPo9zc5Wb8rH5mhyaEcCGSHBqJxPRE5sTP4dekXwn2DuY/sf/h1q63SlIQQlRJkkMDtyN9B7O3zOaXQ78Q5BXEv3v/m1u73kqAV4DZoQkhXJgkhwZqV8Yu5myZw09//0SgVyAPxjzI6G6jCfQKNDs0IYQbkOTQwOzJ3MOcLXNYfnA5AdYA7u91P2O6jyHIK8js0IQQbkSSQwORnJvMzE0z+eHAD/hZ/fhX9L+4rfttBHsHmx2aEMINSXJoAPJL8rlv+X2k5KdwT9Q93N79dkJ8QswOSwjhxiQ5NABT10/lYM5B3hn6Dn1b9jU7HCFEAyA39nVz3+3/ji/3fsk9UfdIYhBC1BlJDm7s0PFDTPl9Cr3Ce/FAzANmhyOEaEAkObipEnsJE1ZNwIKFaYOmyZ3YhBB1ypTkoJQaoZRKVErZlVJxpzz3hFJqr1Jql1LqCjPicwdv/fkWW9O28mz/Z2kd0NrscIQQDYxZzc1twI3A3IoblVLdgVuAHkArYIVSqrPW2lb/IbqutYfXsmDbAm7qfBNDI4eaHY4QogEypeegtd6htd5VxVPXAZ9orYu01vuBvYDMslaQVpDGk6ufpGNwR8afP97scIQQDZSrzTm0Bg5VeJzk2FaJUmqsUmqjUmpjampqvQRnNru2M3nNZHJLcpl+8XQpry2EcBqnJQel1Aql1LYqvq6r6W1VbNNVvVBrPU9rHae1jgsPD6+boF3cB9s/YE3yGsbFjaNzaGezwxFCNGBOm3PQWl9Wi7clAW0qPI4ADtdNRO4tMS2RmZtnMqTtEEZ2GWl2OEKIBs7VhpWWArcopbyVUu2BTsB6k2MyXW5xLuNWjaOpb1Om9J+CUlV1sIQQou6YslpJKXUD8CYQDixTSsVrra/QWicqpT4FtgOlwIOyUgle/ONFknOTWXDFAimkJ4SoF6YkB631l8CX1Tz3IvBi/Ubkupb+tZT/7fsfD8Q8QJ/mfcwORwjRSLjasJKo4ED2AV5Y9wJ9mvdhbNRYs8MRQjQikhxcVLGtmPGrxuPl4cXUi6biYfEwOyQhRCMiBXlc1MzNM9mRsYPXL3mdFv4tzA5HCNHISM/BBa1KWsUH2z9gVNdRXNr2UrPDEUI0QpIcXExqfiqTf5tM59DOPBb3mNnhCCEaKUkOLsSu7Tzx2xMU2gp5ZdAreHt4mx2SEKKRkuTgQhZsW8AfR/5gYt+JdAjpYHY4QohGTJKDi4g/Fs9bf77FFZFXcMN5N5gdjhCikZPk4AJyinOYsGoCLfxb8MyFz0h5DCGE6WQpq8m01jz3+3Ok5KewaNgiAr0CzQ5JCCGk52C2L/Z8wQ8HfuCh3g/RK7yX2eEIIQQgycFU+7L2MXX9VC5oeQF397zb7HCEEKKcJAeTFNmKGLdqHH5WP14e+DIWJb8KIYTrkDkHk7y64VV2Z+5m1pBZhPs1jjvZCSHchzRXTfDz3z/zya5PuK37bQyKGGR2OEIIUYkkh3p2NO8oT699mm5h3Xgk9hGzwxFCiCpJcqhHNruNiasnUmIr4ZWLX8HLw8vskIQQokqSHOrRvIR5bErZxOR+k2kX1M7scIQQolqSHOrJppRNvJ3wNtd0uIZrO15rdjhCCFEjSQ71ILsom4mrJxIREMHkfpPNDkcIIU5LlrI6mdaap9c8TVpBGh9e9SH+Vn+zQxJCiNOSnoOTfbrrU34+9DOPxD5CjyY9zA5HCCHOiCQHJ9qduZvpG6YzoPUAbut+m9nhCCHEGZPk4CQFpQWM+3UcQd5BvDjgRSmPIYRwKzLn4CTTN0xnf/Z+5l4+lya+TcwORwghzoo0Z53ghwM/8Nnuz7ir511c2OpCs8MRQoizJsmhjiXnJjNl7RSim0bzUO+HzA5HCCFqxZTkoJR6RSm1UymVoJT6UikVUuG5J5RSe5VSu5RSV5gRX22V2EuYsGoCGs20QdOwWqxmhySEELViVs9hOdBTax0N7AaeAFBKdQduAXoAVwKzlVIeJsV41ubEz2FL6haevvBpIgIjzA5HCCFqzZTkoLX+UWtd6ni4Dig7k14HfKK1LtJa7wf2An3NiPFs/XHkD97Z+g43nHcDw9oPMzscIYQ4J64w53A38J3j59bAoQrPJTm2VaKUGquU2qiU2piamurkEGuWUZjBE6ufIDI4kol9J5oaixBC1AWnLWVVSq0AWlTx1CSt9deO10wCSoH/lr2titfrqj5faz0PmAcQFxdX5Wvqg9aap9Y8RVZRFnMum4Of1c+sUIQQos44LTlorS+r6Xml1B3ANcAQrXXZyT0JaFPhZRHAYedEWDf+u+O/rEpaxcS+E+kS1sXscIQQok6YtVrpSmACMFxrnV/hqaXALUopb6VUe6ATsN6MGM/EjvQdvLbpNQa3GcytXW81OxwhhKgzZl0h/RbgDSxXSgGs01rfp7VOVEp9CmzHGG56UGttMynGGuWX5DN+1XhCfUJ5vv/zOI5DCCEaBFOSg9b6vBqeexF4sR7DqZWX/niJgzkHefeKdwnxCTn9G4QQwo24wmolt7Ns3zK+/utrxkaP5fwW55sdjhBC1DlJDmfpUM4hnl/3PLHNYrmv131mhyOEEE4hyeEslNhKGL9qPBZlYepFU/G0SFFbIUTDJGe3s/Dmn2+yLX0bMwbPoGVAS7PDEUIIp5Gewxlak7yGhYkLGdl5JJe1q/ESDiGEcHuSHM5AWkEaT/72JOeFnMe488eZHY4QQjidDCudhl3bmfTbJPJK8nh36Lv4ePqYHZIQQjid9BxOY1HiItYeXsv488dzXmi1l2cIIUSDIsmhBtvStvHG5je4vN3ljOg8wuxwhBCi3khyqEZucS7jfh1HuF84z1z4jJTHEEI0KjLnUAWtNc+ve54jeUdYeOVCgr2DzQ5JCCHqlfQcqvD1X1/z7f5vub/X/fRu1tvscIQQot5JcjjF/uz9vPTHS5zf4nzuibrH7HCEEMIUkhwqKLYVM2HVBLw9vHl54Mt4WDzMDkkIIUwhcw4VzNg0gx0ZO3jz0jdp7t/c7HCEEMI00nNw+PXQr3y440NGdxvN4DaDzQ5HCCFMJckBOJZ/jKfWPEXXsK482udRs8MRQgjTNfrkYLPbeGL1ExTaCpk+aDpeHl5mhySEEKZr9MlhwbYFrD+6nif6PkH74PZmhyOEEC6hUSeH+GPxzIqfxbD2w7j+vOvNDkcIIVxGo04OXh5eXNDyAp7q95SUxxBCiAoa9VLW7k26M/fyuWaHIYQQLqdR9xyEEEJUTZKDEEKISiQ5CCGEqESSgxBCiEokOQghhKhEkoMQQohKJDkIIYSoRJKDEEKISpTW2uwYzplSKhU4WMu3NwXS6jAcM8mxuKaGciwN5ThAjqVMO611eFVPNIjkcC6UUhu11nFmx1EX5FhcU0M5loZyHCDHciZkWEkIIUQlkhyEEEJUIskB5pkdQB2SY3FNDeVYGspxgBzLaTX6OQchhBCVSc9BCCFEJZIchBBCVCLJAVBKPa+USlBKxSulflRKtTI7ptpSSr2ilNrpOJ4vlVIhZsdUW0qpEUqpRKWUXSnldssOlVJXKqV2KaX2KqUmmh1PbSmlFiiljimltpkdy7lSSrVRSq1USu1w/N/6j9kx1YZSykcptV4ptcVxHFPqfB8y5wBKqSCtdY7j54eB7lrr+0wOq1aUUkOBn7XWpUqpaQBa6wkmh1UrSqlugB2YCzyutd5ockhnTCnlAewGLgeSgA3AKK31dlMDqwWl1CAgF3hfa93T7HjOhVKqJdBSa71ZKRUIbAKud7ffizLua+yvtc5VSlmB34D/aK3X1dU+pOcAlCUGB3/AbTOm1vpHrXWp4+E6IMLMeM6F1nqH1nqX2XHUUl9gr9Z6n9a6GPgEuM7kmGpFa70KyDA7jrqgtT6itd7s+Pk4sANobW5UZ08bch0PrY6vOj1vSXJwUEq9qJQ6BIwGnjY7njpyN/Cd2UE0Uq2BQxUeJ+GGJ6GGTCkVCfQG/jA3ktpRSnkopeKBY8ByrXWdHkejSQ5KqRVKqW1VfF0HoLWepLVuA/wXeMjcaGt2umNxvGYSUIpxPC7rTI7FTakqtrltj7ShUUoFAJ8Dj5wycuA2tNY2rXUMxuhAX6VUnQ75edblh7kyrfVlZ/jSj4BlwDNODOecnO5YlFJ3ANcAQ7SLTyqdxe/F3SQBbSo8jgAOmxSLqMAxRv858F+t9Rdmx3OutNZZSqlfgCuBOls00Gh6DjVRSnWq8HA4sNOsWM6VUupKYAIwXGudb3Y8jdgGoJNSqr1Sygu4BVhqckyNnmMi911gh9b6NbPjqS2lVHjZSkSllC9wGXV83pLVSoBS6nOgC8bKmIPAfVrrZHOjqh2l1F7AG0h3bFrnxiuvbgDeBMKBLCBea32FuVGdOaXUVcBMwANYoLV+0eSQakUp9TEwGKM0dArwjNb6XVODqiWl1EBgNbAV4+8d4Emt9bfmRXX2lFLRwCKM/1sW4FOt9XN1ug9JDkIIIU4lw0pCCCEqkeQghBCiEkkOQgghKpHkIIQQohJJDkIIISqR5CDEKRyVO/crpcIcj0Mdj9tVeE2IUirdsW4epdSFSimtlIpwPA5WSmUopc74b0wpNVgp1b+uj0eI2pDkIMQptNaHgDnAVMemqcA8rfXBCq/JAo4C3Ryb+gN/Or4D9AP+0FqXraWvkVLKE+NaAkkOwiU0mvIZQpylGcAmpdQjwEDg31W8Zg3GyXy74/sMx/dPHd/XAiilOgKzMC7mywfu1VrvVEq9h1HttLfj+wDAppQa49jfTuBtoK1jf49ordfU+ZEKUQVJDkJUQWtdopQaB3wPDHWU3T7VWmAQ8A7QAVgC/MvxXH/gZcfP8zCuut+jlLoAmA1c6niuM3CZ1tqmlHoWyNVavwqglPoImKG1/k0p1Rb4gRM9FSGcSpKDENUbBhwBegLLq3h+DTBRKdUeOKC1LlSGAKAPsN7xc39giWN6AozyJmWWaK1t1ez/MqB7hfcFKaUCHfchEMKpJDkIUQWlVAzGXdz6Ab8ppT7BKOV+NYDWOsbREwgFrgV+d7x1E3AXsN9xl64gIMtRWrkqeTWEYQEu1FoXnPsRCXF2ZEJaiFM4ViDNwRjj/xt4BXjVcc+PmFNO9L8D/+FEcvgdeATHfIPjXgH7lVIjyj5bKdWrml0fBwIrPP6RCvcWcSQsIeqFJAchKrsX+FtrXTaUNBvoqpS6uIrXrsG4b0PZ/a1/x5h/WFvhNaOBfyqltgCJVH+70G+AG5RS8Uqpi4CHgTilVIJSajvgltV1hXuSqqxCCCEqkZ6DEEKISiQ5CCGEqESSgxBCiEokOQghhKhEkoMQQohKJDkIIYSoRJKDEEKISv4/Kn4UOUEwLLcAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "xdaten = [-3, -2, -1, 0, 1, 2, 3]\n",
     "ydaten1 = xdaten\n",
@@ -1943,27 +1150,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 168,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:14.475608Z",
-     "start_time": "2019-10-27T12:26:14.114103Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "def cubic(x):\n",
     "    '''\n",
@@ -1998,27 +1187,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 169,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:14.843403Z",
-     "start_time": "2019-10-27T12:26:14.481761Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "spannung = [0.9, 2.0, 3.0, 4.1, 4.9, 6.2] # [V]\n",
     "strom = [105, 204, 298, 391, 506, 601] # [mA]\n",
@@ -2061,27 +1232,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 170,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:15.158961Z",
-     "start_time": "2019-10-27T12:26:14.848218Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "#plt.errorbar(, \n",
     "#             ,\n",
@@ -2120,27 +1273,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 171,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:15.459775Z",
-     "start_time": "2019-10-27T12:26:15.162948Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "plt.errorbar(strom, \n",
     "             spannung,\n",
@@ -2174,13 +1309,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 172,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:15.475426Z",
-     "start_time": "2019-10-27T12:26:15.464767Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import numpy as np"
@@ -2188,13 +1318,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 173,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:15.491024Z",
-     "start_time": "2019-10-27T12:26:15.481421Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "rnd_numbers = np.random.normal(0,1,1000)  # <-- Hier werden 1000 gausförmig verteile Zufallszahlen\n",
@@ -2211,27 +1336,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 174,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:15.859118Z",
-     "start_time": "2019-10-27T12:26:15.497216Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "plt.hist(rnd_numbers)\n",
     "\n",
@@ -2249,27 +1356,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 175,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:16.259231Z",
-     "start_time": "2019-10-27T12:26:15.864179Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "rnd_numbers2 = np.random.normal(1,2,1000)\n",
     "\n",
@@ -2305,39 +1394,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 176,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:17.423642Z",
-     "start_time": "2019-10-27T12:26:16.263266Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "plt.hist(rnd_numbers, \n",
     "         bins=100, \n",
@@ -2477,13 +1536,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 177,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:17.441661Z",
-     "start_time": "2019-10-27T12:26:17.429226Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from scipy.optimize import curve_fit"
@@ -2498,23 +1552,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 178,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:17.473756Z",
-     "start_time": "2019-10-27T12:26:17.447575Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[10.0982598]\n",
-      "[[0.02490203]]\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# Und jetzt fitten wir:\n",
     "para, pcov = curve_fit(Spannung,   # <-- Funktion die an die Messdaten gefittet werden soll\n",
@@ -2541,27 +1581,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 179,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:17.858275Z",
-     "start_time": "2019-10-27T12:26:17.478277Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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NsrhVrFixwOVX13+5HllZWZKZmenUulfXinGFTp06ycaNG/Nc1q9fP5k3b56IiCxfvlwaNGhQLMf83//+JwsWLMh1bg888IDMmTNHREQGDRok06ZNy7Xt+fPnZfXq1TJ9+nR55plnciyLjo6WtWvXSlZWlvTs2VMWLVpUYBydOnXKs6ttamqqREdHF7htRkaG1K9fX/bv3y+XLl2SsLAw+fnnn3Otl5ycLFu2bJHHH3/c8b3MfvylS5eKiMi5c+fkwoULBR7z6m3z+7kVlSf8DXqUrCyR1Q9a9a4WNhc5utqt4eCmbpI+7crVs81my1XBcf/+/bRt25bo6GjGjBmTox74uHHjiI6OJiwszFHX22az0bRpU4YMGUJkZCS//vorgwcPJioqiubNm+eo/7148WKaNGlC+/btc9RWya+i5dUxd+rUiQcffJBGjRrx0ksvMXv2bFq3bk1oaCj79+8H/qhTPn/+fBISEnj00UeJiIhwlEvOS0xMTKFXtM7q1q1bjlo5YF2ILF++3FGat1+/fvznP//JtW3FihVp3759rqeXjxw5wtmzZ4mJicEYQ9++ffPc3hkrV66kc+fOBa6zYcMGGjRoQP369SlXrhwPPfRQnj+T4OBgwsLC8PPL+ae4Y8cOMjIyuOOOOwCrpnxgYO5KH0lJSbRt25awsDD+8pe/cPr0aceyefPm0bp1axo1asTq1asB6xPZPffcw1133UVISAhTp07lvffeo2XLlrRt25ZTp04V9dtRemTZS0wYAze0goh3IXYz1Grv3rgK4H0J/n+dc7/2TLOWZaTmvfzATGt52oncy5xw8eJFR/PMX/7ylxzLgoODefrpp3nuuedISkqiQ4cODBs2jGHDhrFx40ZHbRWwipLt3buXDRs2kJSURGJiomPQit27d9O3b182b95MvXr1ePPNN0lISGDr1q388MMPbN26lbS0NJ588kn++9//snr1an7//XfHvt988026du3Kxo0bWbFiBaNGjeLChQu5zmXLli3885//ZNu2bXz++efs2bOHDRs28MQTTzBlypQc695///1ERUU5ap8XVP9k8eLF3HPPPXkuGzduXI4mriuvK01czjh58iTVqlWjTBmrX0BQUFCR/qH89ttvBAX98RG6qNtnFx8fn6NccX7Hq1u37jUfb8+ePVSrVo17772Xli1bMmrUqDxLF/ft25d33nmHrVu3Ehoayuuvv+5YlpGRwYYNG5g0aVKO+du3b+fLL79kw4YNvPzyywQGBrJ582ZiYmIcTXPqKsdWQXy41SwDVjt7s1HgV9a9cRXC1d0kfcKVQSic9dNPPzmuDh955BFHvfSlS5eydOlSxyP/58+fZ+/evdxyyy3Uq1cvx6P9//d//8eMGTPIyMjgyJEj7Nixg6ysLEJCQmjYsCEAjz32GDNmzHDsO6+Klk2bNs0RW3R0NHXq1AHg1ltvpXv37gCEhoayYsWKIn9vRo0axQsvvMCxY8dYt25dvuuMGjWqyPvOTvJoLy/KgNDObv/pp5/yz3/+E4B9+/Zx5513Uq5cOUJCQvjmm28A+PHHHwsdiel6483IyGD16tVs3ryZW265hT59+jBz5kwGDhzoWCclJYUzZ844au/069cvR0XK7JU0s7ffd+nShcqVK1O5cmWqVq3KXXfdBVi/A1u3bnU6xlIh7ThsHgXJs6BiPfD3riJv3pfgb1+Z/7IygQUvD6hR8HIXExFGjx7NoEE5x4q12Ww5KgYmJyczfvx4Nm7cSPXq1enfv7+jemJ+SULyqWh5texVFP38/BzTfn5+uaocOmPcuHHce++9TJ48mX79+pGYmJjnOrNnz841v2PHjjkG2yhIjRo1OHPmDBkZGZQpU4ZDhw7l+HRUmKCgIA4dOuSYzm/7v/71r/z1r9bjGp07d2bmzJk5nog+cOAAdevWpVy5cqxfv97xs/zb3/6WY4jBoKAgfv3110KPV1C8LVu2dAz4cs8997Bu3bocCb4wzlTSLI7fAZ9l+xIShkL6OWg2Glq8YuUYL+J9TTQe6OoKjm3btuXrr78GyFFBsUePHnzyySecP38esD7GX6k+mN3Zs2epWLEiVatW5ejRo45xZZs0aUJycrKjrXzOnDk59p1XRcviPre8+Pn5MWzYMLKysliyZEmu5aNGjXIMb5f95WxyB+sfW5cuXRw9TWbNmsWf//xnp7evU6cOlStXZt26dYgIn332WZG2vyJ780ybNm0c53L1+LHR0dHs3buX5ORkLl++zNy5cwscY/Zq0dHRnD59misF+JYvX56r8FrVqlWpXr26o339eippqjxkpUO1MLhzC0T8w+uSO2iCLxZXV3CcNGkS7733Hq1bt+bIkSNUrVoVsEr3PvLII8TExBAaGsr999+fZ/IMDw+nZcuWNG/enAEDBtCuXTvAqpw4Y8YMevXqRfv27alXr55jm/wqWl6v/v378/TTTxd6k9UYwyuvvMK777573cfs0KEDDzzwAMuWLSMoKMjxT+Odd97hvffeo0GDBpw8edJxNXt1dcrg4GCef/55Zs6cSVBQkGPAk+nTp/PEE0/QoEEDbr311muqNLp48eJC29/Bqpk/depUevToQdOmTXnwwQdp3rw5AGPGjHGMN7tx40aCgoKYN28egwYNcqzj7+/P+PHj6datG6GhoYgITz75ZK7jzJo1i1GjRhEWFkZSUlKeVTqVk9LPQeLzf9zTC+kL3VZA1dwVTb2Fyaut0F2ioqLk6r67O3fuzNWO7OlSU1OpUKECxhjmzp3LnDlzCiz/qrzDpUuXaNeuXanrX+6Nf4NFIgK/fg2Jw+HiYWg6AlqOc3dUTjPGJIpInhUDvK8N3gskJiYydOhQRIRq1arxySefuDskVQzKly9f6pK7zzt/ADYOhSPxUD0COsyHGm0L385LaIJ3gQ4dOhQ4Io9SykNcOAjH10DkRGg0FPx8KyV6xdmISJG6mCmliocnNeEWm9+Xw+nNVlNM7c5wz0EoV83dUbmEx99kDQgI4OTJk775i6aUBxMRTp48WWxjGrvdxd/hx0dheTfYNwMyra7HvprcwQuu4K/0Xy6O8VqVUkUTEBCQ4wlgr5SVCfs+gC0vQ+ZFaDEGmr0E/j7yj6sAHp/gy5YtS0hIiLvDUEp5q9RfYNPzULMDRE+DKo3cHVGJ8fgEr5RSRXY5BQ7+HzR4EirVh56JULW5VSisFNEEr5TyHSLwy1zriv3SMahxG1RrDtVauDsyt/D4m6xKKeWUs3tg+R2w9hFr8I0eG6zkXorpFbxSyvtlpcOyrpBxHqLehwaDwM/f3VG5nSZ4pZT3OvoD1Gxv1WW/bTZUaQwV/uTuqDyGNtEopbxP6m+w5kFY1tmq1Q5Qu5Mm96voFbxSyntkZcCe92HrKyAZEPZ3CH7U3VF5LE3wSinvsfYxOPgV1ImF6KlWF0iVL03wSinPdukU+JWDspWsgmC3PAB17y11fdqvhbbBK6U8kwgc+AwWNoFtr1nzarWHW+7T5O4kvYJXSnmelB2wcQgc+wFqxFijK6ki0wSvlPIsB2bB+iegbGVoPQNuHQhGGxuuhUsTvDHGBpwDMoGM/IaVUkopMtOsCo81YqB+Pwh/CwJqujsqr1YSV/BdRORECRxHKeWNLhyExGGAgY7/tqo9tvnI3VH5BP3co5Ryj6x02DEOFjaFI0uhRhvrxqqdzWajc4c22Gw298Xo5Vyd4AVYaoxJNMY8ldcKxpinjDEJxpgEHdRDqVIiZSfER0LSC/Cn26H3Dmj2Yo7eMcOHPsmx5ASee3aQGwP1bq5O8O1EJBKIBZ4xxnS8egURmSEiUSISVbOmtrcpVSoE1AL/8tDxW+j0LVSsl2PxokWL+DlpLevGZrFt0xri4+PdFKh3c2mCF5HD9q/HgG+A1q48nlLKQ0kW7PsIlvewhtArfyP02AhBd+daNS0tjbghA5nyaCpVAmHKo6nEDRlIWlqaGwL3bi5L8MaYisaYylfeA92B7a46nlLKQ53eCt+3hw1PQlYaXD5lzc/nYaVx77xFWJ2z9Ay3pmMjoEXtFMa/+3YJBew7XHkFXxtYY4zZAmwAvhORxS48nlLKk2SkwqYRsDgSzu2FtjOh28pCuz5OnzaZEd1Tc8wb0SOV6dMmuy5WH+WybpIicgAId9X+lVIezvjD4XioPwAi3rKaZZwweEgcExaPp13jP5L8hCWBDB4S56pIfZZ2k1RKFZ/zB2DdXyH9vHUTtWcCtJnhdHIHGPXiaLYeqUJ8kjW9KAm2H63KyBdeclHQvksTvFLq+mVegu1vwnfN4eB8OL3Jml8msMi7CggIYMr0T4j7MpCUVIibHcjkaR8TEBBQzEH7Pq1Fo5S6PkdXwMbBcHY31L0fWk20Br2+DrGxsTSPuI2YscsJjWxPbGxsMQVbuugVvFLq2olYV+5Z6dB5EXSYd93J/YpJUz+kVkgUE6f8q1j2VxrpFbxSqmiyMmH/h3BTL6hYF277HMpWgzIVivUwwcHBrFy9vlj3WdroFbxSynmnNsHSGKtJ5sAn1rwKdYo9uavioVfwSqnCXU6Bra/C3vehfE2I+QKCH3F3VKoQmuCVUoXbNhb2TIWGQyD8DShXzd0RKSdogldK5e3sXsi6DNWaQ/OXrSv2G6PdHZUqAm2DV0rllJkGW1+DRS3sA3EAATU0uXshvYJXSv3hyFLY+Ayc3wf1HobICe6OSF0HTfBKKcvB+bDmAajcELp+bw3EobyaJnilSrOsDLhgg8oN4Oa7IHIiNHzaGvxaeT1tg1eqtDqxAZa0hmVdrNK+/uWhyXBN7j5EE7xSpc3l07BhMCxtC2lHIfI98NcHlXyRNtEoVZqct8HSNnDpBDQeBmGvQ9kq7o5KuUi+Cd4Y48zwKWdF5JVijEcp5Qrp56BsZWtw63qPQP1+UD3C3VEpFyvoCv7PwJhCtn8J0ASvlKfKSIXtb8C+f8GdW6xKj60mujsqVUIKSvATRWRWQRsbY6oXczxKqeLy20JIeNbqJRPSF/zKuzsiVcIKSvBrCttYRCYVYyxKqeKQlQFrHoRD30CVptZA17U7uTsq5QYFJfgPjTGVgDnAXBHZUUIxKaWuhQgYA35loMJNEP4WNHke/Mu5OzLlJvl2kxSRlkBvIBOYb4xJMsa8aIypV2LRKaWcc/xHWBxp1WsHiJ4KzV/S5F7KFdgPXkR2i8jrItIM6AdUA5YbY34skeiUUgVLOwHrn4Dv28Olk5Ce4u6IlAdx6kEnY4wfUAuoDVQEjrsyKKVKC5vNRucObbDZbEXfOPlz+K4JHJgFTV+A3juhdpdij1F5rwITvDGmgzFmGnAIGIV147WxiNxTEsEp5euGD32SY8kJPPfsoKJvfN5m3USN3Qwt34EyFYs9PuXd8k3wxphfgbeBnUBLEekuIp+IiH4GVKoYLFq0iJ+T1rJubBbbNq0hPj6+4A3Sz8PmUXBogTXdfDTc/gNUa+H6YJVXKqgXTXsR+aXEIlGqFElLSyNuyECmPppKlUCY8mgqcUMGsm3nAQICrir2JQKH/gOJcZB6CPwCIOhuq7eMUgUoqInmr4VtbIwZW3yhKFV6jHvnLcLqnKVnuDUdGwEtaqcw/t23c654Phl+uAtW3wvlqsMdayD87yUfsPJKRkTyXmDMIeC9grYFnhSRJgUewBh/IAH4TUR6F7RuVFSUJCQkFByxUj7gptrVmff0Gdo1/mPemt3Q51/V+e33U3/MPPAZJAyB0NehcRz4lS35YJVHM8YkikhUXssKuoL/EKhcwKuSfZ3CDMNqx1dK2Q0eEseEpYE55k1YEsjgIXFwdCUkz7ZmhjwOd+2DpiM0uasiy7cRT0Rev96dG2OCgF7Am8Dz17s/pXzFqBdH0+LTGcQnpRIbAYuS4PD5SszvuheWvQ7VwiD4YTB+UOFP7g5XeSlXD/gxCXgByMpvBWPMU8aYBGNMwvHj2r1elQ4BAQFMmf4JcV8GkpIKP+0vy5qXU/E/NA+a/z/o/pOV3JW6Di77DTLG9AaOiUhiQeuJyAwRiRKRqJo1a7oqHKU8TmxsLM0jbuPJjwx/vy+dsjWjIHYLhL8JZQIL34FShXDlJUI74G5jjA2YC3Q1xnzhwuMp5T3Sz8Kv3z6BVvMAABgLSURBVDBp6occKxvNkRbzoNtyqNrU3ZEpH5JvLxrHCnmP7JQCJIjIt04dxJjOwEjtRaNKPRE4OA82PQeXjsPdyRB4s7ujUl7sWnvRXBEARAB77a8w4AZgoDFG68Er5axz+2BFT/ixDwT8CW5fo8lduZQzj8I1ALqKSAaAMWY6sBS4A9jmzEFEZCWw8tpCVMoHpJ+DxVEgWdBqMjQcAn7+7o5K+ThnEvzNWBUkr9SgqQjcJCKZxphLLotMKV9wahPcEGkNeN32E7ixLQTe5O6oVCnhTBPNu0CSMeZTY8xMYDMw3hhTEfifK4NTymtdPAI/PgyLW8FhexGxuvdqclclqtAreBH52BizCGiNVZ7g/4nIYfviUa4MTimvk5UJe6fD1pch8xKEjtUa7cptnC1H54c1yEcZoIExpoGIrHJdWEp5qR/ugiPx8KfuEDUVqjR0d0SqFCs0wRtj3gH6AD/zxxOpAmiCVwrg8hkoU8kq33vrQKjfD2550BoAWyk3cuYK/h6sUZz0hqpS2YmAbTZsHgHNX7aqPd5yn7ujUsrBmZusBwAtY6dUdim7YHk3+OlxqBgMNTu4OyKlcnHmCj4VqxfNMsBxFS8icS6LSilPtnc6JA4D/4oQPR1ufVL7tCuP5EyCX2B/KVW6ZWVaibxKM7jlIWg5DirUdndUSuXLmW6Ss0oiEKU8VuohSBwOgbdAq/egdifrpZSHc6YXTTJWr5kcRKS+SyJSylNkZcDuybDtNZAMa9g8pbyIM0002auUBQAPYBUbU8p3nd4CP/WFM1vhpl4QNQUqhbg7KqWKxJkmmpNXzZpkjFkDjHFNSEp5AP8KkJEKHf4NQfdon3bllZxpoonMNumHdUVf2WURKeUOkgUHZsGJH6HNR1ClEfTepb1jlFdzpolmQrb3GYANeNAl0SjlDme2w8bBcHwN1GwH6eehbCVN7srrOdNEo5WSlG/KuADbXoddE6FsFWjzMdTvr4NdK5/hTBNNeeA+IDj7+iLyN9eFpVQJyLwEB2ZCSF+IeAcCarg7IqWKlTNNNN9iDfaRSLYnWZXySudtsGcKRLwL5W+w2tnLa6cw5ZucSfBBItLT5ZEo5UqZl2HXe7D9b1YTTPBjcENLTe7KpznT2LjWGBPq8kiUcpWjP8DilrBlNNTpCb12WsldKR/nzBV8e6C//YnWS1ijOomIhLk0MqWKQ1am1UMm8yJ0+i/c3NvdESlVYpxJ8LEuj0Kp4nSlT/st91uDXXf8FgJvhjKB7o5MqRLlTDfJX4wx/kBtZ9ZXyq1OJ8GGwXByHWSch8bP6rB5qtRyppvks8BrwFFyDtmnTTTKc6Sfg61jYM9kKHcjtJ0FIY+7Oyql3MqZK/JhWEP2XV2TRinPseFp+GUONHgKIt6CctXdHZFSbudMgv8Vqx+8Up7l3H7wD7Da18Net8ZErdHG3VEp5TGcSfAHgJXGmO/IOWTfey6LSqmCZF6CHe/Az/+AuvdBu9lQuYH1Uko5ONMP/iDwPVAOq4rklZdSLmWz2ejcoQ02m+2Pmb8vg0Vh1iAcQX+2hs1TSuXJmV401zSMjTEmAFgFlLcfZ76IvHYt+1Kl0/ChT3IsOYHnnh3EN/9dAvs+gg1PQqVbocsSqNPd3SEq5dGc6UVTE3gBaI41ohMAItK1kE0vAV1F5LwxpiywxhgTLyLrridgVTosWrSIn5PWkjg2i+7jVxMfH09s179A2lFo8jyUqeDuEJXyeM400cwGdgEhwOtY9eA3FraRWM7bJ8vaX7nGdlXqamlpacQNGcisJ1KpEghLRl5k+DMDSJOK0OJlTe5KOcmZBH+jiHwMpIvIDyIyAGjrzM6NMf7GmCTgGPC9iKy/jlhVKTF53GtMfugEtzWypqsGQrNaKYx/9233BqaUl3Emwafbvx4xxvQyxrQEgpzZuYhkikiEff3WxpgWV69jjHnKGJNgjEk4fvy404ErH3VmO/1rjiM2NCPH7BE9LjJ92mQ3BaWUd3Imwb9hjKkKjABGAh8BzxXlICJyBlgJ5Co7LCIzRCRKRKJq1qxZlN0qX5J52fpauSHHTHNGfRWQY/GEJYEMHhLnhsCU8l6FJngRWSgiKSKyXUS6iEgrEVlQ2HbGmJrGmGr29xWA27Ha8pX6Q8ZF2PIqfNfMGgvVvzwN+m3kP1urEZ9krbIoCbYfrcrIF15yb6xKeZlCE7wxpr4x5r/GmBPGmGPGmG+NMfWd2HcdYIUxZivWTdnvRWTh9QasfMjheFjUAn5+A2q0hSzrKj4gIIAp0z8h7stAUlIhbnYgk6d9TEBAQCE7VEpl58yTrF8C7wN/sU8/BMwBCnwmXES2Ajqqgsot4wL81A9+/RqqNIauy+BPOXvdxsbG0jziNmLGLic0sj2xsVq1WqmicqYN3ojI5yKSYX99gXZ3VNfDPxAy0yDsDYjdkiu5XzFp6ofUColi4pR/lXCASvkGI1JwrjbGvA2cAeZiJfY+WE+nvg8gIqeKK5ioqChJSEgort0pT3JiHWweBbd9CRXrgggY4+6olPJ6xphEEYnKa5kzTTR97F8HXTV/AFbCd6Y9XpVWl05ZY6Hu+xAq3ASpB60Er8ldKZdzphZNSEkEonzQgc9g80i4fAqaPAehY60h9JRSJSLfBG+MiQZ+FZHf7dN9gfuAX4Cxxdk0o3zU8VVWCd/oD6C6DgCmVEkr6Cbrv4DLAMaYjsDbwGdYg3/McH1oyutkXICkl+Ck/T5Kq8lwxxpN7kq5SUFNNP7ZrtL7ADNE5Gvga3t9GaX+cGgBJDxrtbGXrQo3RkGZQHdHpVSpVmCCN8aUEZEMoBvwlJPbqdLkwkFIjIND30LV5nD7KqjVwd1RKaUoOFHPAX4wxpwALgKrAYwxDdAxWtUVti/gyPcQ8Y51I9WvrLsjUkrZ5ZvgReRNY8wyrJIDS+WPDvN+wLMlEZzyUMdWQ9Yl+NPt0GQEBD8GFW9xd1RKqasU2NSS1+hLIrLHdeEoj5Z2HJJegAMzoWYHK8H7l9fkrpSH0rZ0VTjJgv0fWz1k0s9Cs5egxSvujkopVQhN8Kpwh+Nhw1NQqyNETYNqzd0dkVLKCZrgVd7Sz8GpTVC7E9x0J3RaaH3VEgNKeQ1nqkmq0kQEDn4NC5vCqrvhcoqV1G/upcldKS+jCV794fwBWNkL1twP5WtAlyVQrqq7o1JKXSNtolGWi0fguxZg/CFyIjQaCn7666GUN9O/4NLu3D6rIFiFOlZiv7k3BN7s7qiUUsVAm2hKq4tHYe1jsLAxnNpszWs4SJO7Uj5Er+BLm6xM2D8DkkZD5kVo/jJUaeLuqJRSLqAJvjSRLFjeFY6tgtrdIPp9a9BrpZRP0gRfGmRcsAa6Nn5Q935oMAjqPazdHpXycdoG78tEwDYXFjSwyvkCNH4Wgh/R5K5UKaAJ3led3QMrusPah60bp1oQTKlSR5tofNGuiVZhMP8AiJoKDZ4GP393R6WUKmGa4H2JiNX0Ur6m1dYeOQEq/MndUSml3ESbaHxB6mFY0wd2T7amQx6DdrM1uStVymmC91I2m41uHVtzcu1rsLCJdRNVMtwdllLKg2gTjZea/Gofpty1kRttG6FOT6utvfKt7g5LKeVBXHYFb4ypa4xZYYzZaYz52RgzzFXHKm0WLVrEkeQtNKkDQz8rR/zFZzW5K6VycWUTTQYwQkSaAm2BZ4wxzVx4PN8mAgc+I33zq8QNGUi/dpfw84NeYZeJe+YJ0tLS3B2hUsrDuCzBi8gREdlkf38O2AloJatrkbIDlnWBdf04smkWLW9OoWe4tSg2AlrUTmH8u2+7N0allMcpkZusxphgoCWwPo9lTxljEowxCcePHy+JcLxHRqpVFGxROJzZCq1nEPPyWYbffjHHaiN6pDJ92mQ3BamU8lQuT/DGmErA18BwETl79XIRmSEiUSISVbNmTVeH410uHobdkyD4Uei9Cxo8ydODhzFhaWCO1SYsCWTwkDg3BamU8lQuTfDGmLJYyX22iPzblcfyGRcOwo53rfeVG8BdeyFmJgTUAmDUi6PZeqQK8UnWKouSYPvRqox84SX3xKuU8liu7EVjgI+BnSLynquO4zOy0mHHOGuw621jrfFRAQKDcqwWEBDAlOmfEPdlICmpEDc7kMnTPiYgIKDkY1ZKeTRXXsG3Ax4HuhpjkuyvO114PO91bA3ER0LSC/Cn26H3TqhUP9/VY2NjaR5xGzFj/QiNbE9sbGwJBquU8hYue9BJRNYAWpO2MBkXYc194BcAHb+FoLud2mzS1A/p/3gfJk75l4sDVEp5K32S1R0kCw7Oh7r3QpkK0Ok7qNoUylR0ehfBwcGsXJ2rU5JSSjloLZqSdmYbfN8BfuwDB+dZ826MKlJyV0opZ2iCLynp52HTSIhvCed2Q5tPoF4fd0ellPJh2kRTUtbcD0eWwK1PQMTbUP5Gd0eklPJxmuBd6XyylcjLVoHQ16HFGKh5m7ujUkqVEtpE4wqZl+Hnf8B3zWD73615NdpocldKlSi9gi9uR1fAxiFwdhfUvQ8aa5VkpZR7aIIvTjvfg80jrIeUOi+Cm/QBJKWU+2iCv16SBennoFxVuPkuSD8DzUZb/duVUsqNtA3+epzaDEtjYF0/a7pKQwj7myZ3pZRH0AR/LdLPQsIwWBIFF2xQ935rxCWllPIg2kRTVCc2wOp74OLv0HAwhL8B5aq7OyqllMpFE7yzJAuMn1WjvVqYVRjsxmh3R6WUUvnSJprCZKbB1rHwfXvIyoDyN0CXxZrclVIeTxN8QY4she9CYfvrUDEYMlPdHZFSSjlNm2jycvkMbHgaDn4FlRtC1++tgTiUUsqLaILPi38gnNtj1Y9p9gL463B4Sinvown+ipMbYdvfoN2XULYy9NgIfv7ujkoppa6ZtsFfPmPVjlnSBk5vgnN7rfma3JVSXq70XsGLgG22VTvm0gloHGc9hVq2irsjU0qpYlF6EzxA8iyoGAKdF8MNLd0djVJKFavSleAzUmHH29aoShVvgXZfQblq1gNMSinlY0pPgv/tO0gYatWOKV8LGg+1HlpSSikf5fsJ/sKvsGk4/PpvqNIUuq2A2p3dHZVSSrmc7yf4HW/D4XgI/wc0GQH+5dwdkVJKlQjfTPDH10KZQKgeAWF/h6YjoVKIu6NSSqkS5Vt3Fy+dhPVPwPftYNtYa175GzS5K6VKJd+4gpcsODATkl6AyynQdBS0GOPuqJRSyq1cdgVvjPnEGHPMGLPdVcdwODAL1g+0bqLGboaW70LZSi4/rFJKeTJXXsHPBKYCn7nwGJbgR6yCYPX6aJ92pZSyc1k2FJFVwClX7T87269H6Pz4JGy/HCyJwymllFdw++WuMeYpY0yCMSbh+PHj17SP4UOf5FhyAs89O6iYo1NKKe/l9gQvIjNEJEpEomrWrFnk7RctWsTPSWtZNzaLbZvWEB8f74IolVLK+7g9wV+PtLQ04oYMZMqjqVQJhCmPphI3ZCBpaWnuDk0ppdzOqxP8uHfeIqzOWXqGW9OxEdCidgrj333bvYEppZQHcGU3yTnAT0BjY8whY8zA4j7G9GmTGdE950DYI3qkMn3a5OI+lFJKeR1X9qJ5WETqiEhZEQkSkY+L+xiDh8QxYWlgjnkTlgQyeEhccR9KKaW8jlc30Yx6cTRbj1QhPsmaXpQE249WZeQLL7k3MKWU8gBeneADAgKYMv0T4r4MJCUV4mYHMnnaxwQEBLg7NKWUcjuvTvAAsbGxNI+4jZixfoRGtic2NtbdISmllEfw+gQPMGnqh9QKiWLilH+5OxSllPIYPlFNMjg4mJWr17s7DKWU8ig+cQWvlFIqN03wSinlozTBK6WUjzIi4u4YHIwxx4FfirBJDeCEi8LxVHrOpUdpPO/SeM5wfeddT0TyrNToUQm+qIwxCSIS5e44SpKec+lRGs+7NJ4zuO68tYlGKaV8lCZ4pZTyUd6e4Ge4OwA30HMuPUrjeZfGcwYXnbdXt8ErpZTKn7dfwSullMqHJnillPJRHpvgjTGfGGOOGWO2Z5t3gzHme2PMXvvX6vb5xhgz2Rizzxiz1RgT6b7Ir50xpq4xZoUxZqcx5mdjzDD7fF8/7wBjzAZjzBb7eb9unx9ijFlvP++vjDHl7PPL26f32ZcHuzP+62GM8TfGbDbGLLRPl4ZzthljthljkowxCfZ5vv47Xs0YM98Ys8v+9x1TEufssQkemAn0vGreS8AyEWkILLNPA8QCDe2vp4DpJRRjccsARohIU6At8Iwxphm+f96XgK4iEg5EAD2NMW2Bd4CJ9vM+DVwZ9nEgcFpEGgAT7et5q2HAzmzTpeGcAbqISES2vt++/jv+T2CxiDQBwrF+5q4/ZxHx2BcQDGzPNr0bqGN/XwfYbX//L+DhvNbz5hfwLXBHaTpvIBDYBLTBerKvjH1+DLDE/n4JEGN/X8a+nnF37NdwrkH2P+yuwELA+Po52+O3ATWumuezv+NAFSD56p9XSZyzJ1/B56W2iBwBsH+tZZ9/M/BrtvUO2ed5LftH8JbAekrBedubKpKAY8D3wH7gjIhk2FfJfm6O87YvTwFuLNmIi8Uk4AUgyz59I75/zgACLDXGJBpjnrLP8+Xf8frAceBTe3PcR8aYipTAOXtbgs+PyWOe1/b/NMZUAr4GhovI2YJWzWOeV563iGSKSATWVW1roGleq9m/ev15G2N6A8dEJDH77DxW9ZlzzqadiERiNUU8Y4zpWMC6vnDeZYBIYLqItAQu8EdzTF6K7Zy9LcEfNcbUAbB/PWaffwiom229IOBwCcdWLIwxZbGS+2wR+bd9ts+f9xUicgZYiXUPopox5sqgNNnPzXHe9uVVgVMlG+l1awfcbYyxAXOxmmkm4dvnDICIHLZ/PQZ8g/UP3Zd/xw8Bh0TkyqhE87ESvsvP2dsS/AKgn/19P6w26ivz+9rvPrcFUq589PEmxhgDfAzsFJH3si3y9fOuaYypZn9fAbgd6ybUCuB++2pXn/eV78f9wHKxN1Z6CxEZLSJBIhIMPIR1Do/iw+cMYIypaIypfOU90B3Yjg//jovI78CvxpjG9lndgB2UxDm7+wZEATcm5gBHgHSs/2gDsdoclwF77V9vsK9rgPex2m23AVHujv8az7k91kexrUCS/XVnKTjvMGCz/by3A2Ps8+sDG4B9wDygvH1+gH16n315fXefw3Wef2dgYWk4Z/v5bbG/fgZets/39d/xCCDB/jv+H6B6SZyzlipQSikf5W1NNEoppZykCV4ppXyUJnillPJRmuCVUspHaYJXSikfpQleKaV8lCZ45ZWMMS/bSwtvtZedbWOfP9wYE1gCxw82xly018+5lu2/Ncb8dNW854wxB40xU4snSlXalSl8FaU8izEmBugNRIrIJWNMDaCcffFw4AsgNY/t/EUksxhD2S9W/ZwisT+1GwmcN8aEiEgygIhMNMacBqIK3IFSTtIreOWN6gAnROQSgIicEJHDxpg44CZghTFmBYAx5rwx5m/GmPVAjDGmm72i3zZjDSpT3r6ezRjzD2PMT8aYBGNMpDFmiTFmvzHm6cICsl/R77JXCtxujJltjLndGPOjfUCH1tlWvw/4L1YNmoeK91uj1B80wStvtBSoa4zZY4yZZozpBCAik7GKMnURkS72dStijSnQButR8ZlAHxEJxfoEOzjbfn8VkRhgtX29+7GKnv3NybgaYA3sEAY0AR7BKj8xEvh/2dZ7GKsUxxz7e6VcQhO88joich5ohTXazXHgK2NM/3xWz8SqzgnQGEgWkT326VlA9lK1C+xftwHrReSciBwH0q4UQytEsohsE5EsrDory8SqBbINa/AajDG1sf4RrLHHkWGMaeHEvpUqMk3wyiuJVT9+pYi8BgzFavbIS1q2dve86mxnd8n+NSvb+yvTztyvunqb7Pu7sn0frEJTyfZSwcFoM41yEU3wyusYYxobYxpmmxUB/GJ/fw6onM+mu4BgY0wD+/TjwA+uiTJfDwM9RSRYrFLBrdAEr1xEE7zyRpWAWcaYHcaYrUAzYKx92Qwg/spN1uxEJA34KzDPGLMN68r6g5IJ2TEM4y3AumwxJQNnr3TzVKo4ablgpa6BPVkvFJFibT+330uIEpGhxblfVTrpFbxS1yYTqHqtDzrlxRjzHDAaKGgcXqWcplfwSinlo/QKXimlfJQmeKWU8lGa4JVSykdpgldKKR/1/wEkNyigl4SHqwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "plt.plot(strom, \n",
     "             spannung,    \n",
@@ -2594,27 +1616,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 180,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:18.407014Z",
-     "start_time": "2019-10-27T12:26:17.859663Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "para2, pcov2 = curve_fit(Spannung,   \n",
     "                       strom,      \n",
@@ -2674,22 +1678,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 181,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:18.422614Z",
-     "start_time": "2019-10-27T12:26:18.408933Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Das chi-qudrat ist 506\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "chi_2 = [ (u - Spannung(I, para2[0])/du)**2 for I,u,du in zip(strom, spannung, spannung_error)]\n",
     "chi_2 = sum(chi_2)\n",
@@ -2709,23 +1700,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 182,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2019-10-27T12:26:18.437793Z",
-     "start_time": "2019-10-27T12:26:18.427118Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Chi-qudrat nach URI:  506\n",
-      "Chi-qudrat nach URIC: 506\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "def Spannung2(I, R, C):\n",
     "    return R * I + C \n",