05_03_pandas_assigning_data_append_new_row_from_dict.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](./pic/zuweisen/dict/1_title.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Kelly, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td>34.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330911</td>\n",
       "      <td>7.8292</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>893</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Wilkes, Mrs. James (Ellen Needs)</td>\n",
       "      <td>female</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>363272</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>894</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Myles, Mr. Thomas Francis</td>\n",
       "      <td>male</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>240276</td>\n",
       "      <td>9.6875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>895</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Wirz, Mr. Albert</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>315154</td>\n",
       "      <td>8.6625</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>896</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Hirvonen, Mrs. Alexander (Helga E Lindqvist)</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3101298</td>\n",
       "      <td>12.2875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0          892         0       3   \n",
       "1          893         1       3   \n",
       "2          894         0       2   \n",
       "3          895         0       3   \n",
       "4          896         1       3   \n",
       "\n",
       "                                           Name     Sex   Age  SibSp  Parch  \\\n",
       "0                              Kelly, Mr. James    male  34.5      0      0   \n",
       "1              Wilkes, Mrs. James (Ellen Needs)  female  47.0      1      0   \n",
       "2                     Myles, Mr. Thomas Francis    male  62.0      0      0   \n",
       "3                              Wirz, Mr. Albert    male  27.0      0      0   \n",
       "4  Hirvonen, Mrs. Alexander (Helga E Lindqvist)  female  22.0      1      1   \n",
       "\n",
       "    Ticket     Fare Cabin Embarked  \n",
       "0   330911   7.8292   NaN        Q  \n",
       "1   363272   7.0000   NaN        S  \n",
       "2   240276   9.6875   NaN        Q  \n",
       "3   315154   8.6625   NaN        S  \n",
       "4  3101298  12.2875   NaN        S  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('./csv/titanic.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Neue Zeile aus einem `dictionary` hinzufügen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wie wir bereits wissen, besteht ein `DataFrame` aus einer Reihe von `Series`. Eine solche `Serie` kann mittels einem Python-`Dictionary` dargestellt werden. Willst du also neue Daten (also z.B. eine komplette Zeile) an ein bestehendes `DataFrame` anhängen, kannst du das mittels einem `Dictionary` machen."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](./pic/zuweisen/dict/2_dict.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<video width=\"1000\" controls src=\"./pic/zuweisen/dict/4_dict_video.mp4\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hierzu definieren wir uns zuerst einen neuen Passagier, mittel dem `Key-Value` Prinzip:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = {\n",
    "    'Name': 'Stefan, Mr. Lippl',\n",
    "    'Sex': 'male',\n",
    "    'Pclass': 2.0,\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Anschließend kann einfach die Funktion **`.append()`** benutzt werden, und die neu erstellte Row, an das bestehende DataFrame angehängt werden. Bei dieser funktion muss zudem der Parameter `ignore_index=True` gesetzt werden."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
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       "      <th>Name</th>\n",
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       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
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       "      <th>3</th>\n",
       "      <td>895.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Wirz, Mr. Albert</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>315154</td>\n",
       "      <td>8.6625</td>\n",
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       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>896.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Hirvonen, Mrs. Alexander (Helga E Lindqvist)</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3101298</td>\n",
       "      <td>12.2875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>1306.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Oliva y Ocana, Dona. Fermina</td>\n",
       "      <td>female</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>PC 17758</td>\n",
       "      <td>108.9000</td>\n",
       "      <td>C105</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>1307.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Saether, Mr. Simon Sivertsen</td>\n",
       "      <td>male</td>\n",
       "      <td>38.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>SOTON/O.Q. 3101262</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>1308.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Ware, Mr. Frederick</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>359309</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>1309.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Peter, Master. Michael J</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2668</td>\n",
       "      <td>22.3583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
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       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Stefan, Mr. Lippl</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>419 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0          892.0       0.0     3.0   \n",
       "1          893.0       1.0     3.0   \n",
       "2          894.0       0.0     2.0   \n",
       "3          895.0       0.0     3.0   \n",
       "4          896.0       1.0     3.0   \n",
       "..           ...       ...     ...   \n",
       "414       1306.0       1.0     1.0   \n",
       "415       1307.0       0.0     3.0   \n",
       "416       1308.0       0.0     3.0   \n",
       "417       1309.0       0.0     3.0   \n",
       "418          NaN       NaN     2.0   \n",
       "\n",
       "                                             Name     Sex   Age  SibSp  Parch  \\\n",
       "0                                Kelly, Mr. James    male  34.5    0.0    0.0   \n",
       "1                Wilkes, Mrs. James (Ellen Needs)  female  47.0    1.0    0.0   \n",
       "2                       Myles, Mr. Thomas Francis    male  62.0    0.0    0.0   \n",
       "3                                Wirz, Mr. Albert    male  27.0    0.0    0.0   \n",
       "4    Hirvonen, Mrs. Alexander (Helga E Lindqvist)  female  22.0    1.0    1.0   \n",
       "..                                            ...     ...   ...    ...    ...   \n",
       "414                  Oliva y Ocana, Dona. Fermina  female  39.0    0.0    0.0   \n",
       "415                  Saether, Mr. Simon Sivertsen    male  38.5    0.0    0.0   \n",
       "416                           Ware, Mr. Frederick    male   NaN    0.0    0.0   \n",
       "417                      Peter, Master. Michael J    male   NaN    1.0    1.0   \n",
       "418                             Stefan, Mr. Lippl    male   NaN    NaN    NaN   \n",
       "\n",
       "                 Ticket      Fare Cabin Embarked  \n",
       "0                330911    7.8292   NaN        Q  \n",
       "1                363272    7.0000   NaN        S  \n",
       "2                240276    9.6875   NaN        Q  \n",
       "3                315154    8.6625   NaN        S  \n",
       "4               3101298   12.2875   NaN        S  \n",
       "..                  ...       ...   ...      ...  \n",
       "414            PC 17758  108.9000  C105        C  \n",
       "415  SOTON/O.Q. 3101262    7.2500   NaN        S  \n",
       "416              359309    8.0500   NaN        S  \n",
       "417                2668   22.3583   NaN        C  \n",
       "418                 NaN       NaN   NaN      NaN  \n",
       "\n",
       "[419 rows x 12 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.append(result, ignore_index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wie du also sehen kannst, müssen nicht einmal alle Features der Zeile Befüllt werden. `Pandas` erkennt fehlende Werte und hinterlegt diese mit einem `Nan`-Value.\n",
    "\n",
    "Außerdem erkennt `Pandas` neue Features. Wird ein Objekt mit einem Feature übergeben, das nicht im `DataFrame` vorkommt, erstellt `Pandas` diese Spalte automatisch von alleine und fügt sie dem `DataFrame` an."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = {\n",
    "    'Name': 'Ludwig, Mr. Hahn',\n",
    "    'Sex': 'male',\n",
    "    'Pclass': 3.0,\n",
    "    'Vegan': True\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
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       "      <th>Cabin</th>\n",
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       "      <th>0</th>\n",
       "      <td>892.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Kelly, Mr. James</td>\n",
       "      <td>male</td>\n",
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       "      <th>1</th>\n",
       "      <td>893.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Wilkes, Mrs. James (Ellen Needs)</td>\n",
       "      <td>female</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>894.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Myles, Mr. Thomas Francis</td>\n",
       "      <td>male</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>240276</td>\n",
       "      <td>9.6875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>895.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Wirz, Mr. Albert</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>315154</td>\n",
       "      <td>8.6625</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>896.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Hirvonen, Mrs. Alexander (Helga E Lindqvist)</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3101298</td>\n",
       "      <td>12.2875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>1306.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Oliva y Ocana, Dona. Fermina</td>\n",
       "      <td>female</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>PC 17758</td>\n",
       "      <td>108.9000</td>\n",
       "      <td>C105</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>1307.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Saether, Mr. Simon Sivertsen</td>\n",
       "      <td>male</td>\n",
       "      <td>38.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>SOTON/O.Q. 3101262</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>1308.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Ware, Mr. Frederick</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>359309</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>1309.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Peter, Master. Michael J</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2668</td>\n",
       "      <td>22.3583</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Ludwig, Mr. Hahn</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>419 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass  \\\n",
       "0          892.0       0.0     3.0   \n",
       "1          893.0       1.0     3.0   \n",
       "2          894.0       0.0     2.0   \n",
       "3          895.0       0.0     3.0   \n",
       "4          896.0       1.0     3.0   \n",
       "..           ...       ...     ...   \n",
       "414       1306.0       1.0     1.0   \n",
       "415       1307.0       0.0     3.0   \n",
       "416       1308.0       0.0     3.0   \n",
       "417       1309.0       0.0     3.0   \n",
       "418          NaN       NaN     3.0   \n",
       "\n",
       "                                             Name     Sex   Age  SibSp  Parch  \\\n",
       "0                                Kelly, Mr. James    male  34.5    0.0    0.0   \n",
       "1                Wilkes, Mrs. James (Ellen Needs)  female  47.0    1.0    0.0   \n",
       "2                       Myles, Mr. Thomas Francis    male  62.0    0.0    0.0   \n",
       "3                                Wirz, Mr. Albert    male  27.0    0.0    0.0   \n",
       "4    Hirvonen, Mrs. Alexander (Helga E Lindqvist)  female  22.0    1.0    1.0   \n",
       "..                                            ...     ...   ...    ...    ...   \n",
       "414                  Oliva y Ocana, Dona. Fermina  female  39.0    0.0    0.0   \n",
       "415                  Saether, Mr. Simon Sivertsen    male  38.5    0.0    0.0   \n",
       "416                           Ware, Mr. Frederick    male   NaN    0.0    0.0   \n",
       "417                      Peter, Master. Michael J    male   NaN    1.0    1.0   \n",
       "418                              Ludwig, Mr. Hahn    male   NaN    NaN    NaN   \n",
       "\n",
       "                 Ticket      Fare Cabin Embarked  Vegan  \n",
       "0                330911    7.8292   NaN        Q    NaN  \n",
       "1                363272    7.0000   NaN        S    NaN  \n",
       "2                240276    9.6875   NaN        Q    NaN  \n",
       "3                315154    8.6625   NaN        S    NaN  \n",
       "4               3101298   12.2875   NaN        S    NaN  \n",
       "..                  ...       ...   ...      ...    ...  \n",
       "414            PC 17758  108.9000  C105        C    NaN  \n",
       "415  SOTON/O.Q. 3101262    7.2500   NaN        S    NaN  \n",
       "416              359309    8.0500   NaN        S    NaN  \n",
       "417                2668   22.3583   NaN        C    NaN  \n",
       "418                 NaN       NaN   NaN      NaN    1.0  \n",
       "\n",
       "[419 rows x 13 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.append(result, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# NOTE: Zeigen wieso Stefan nicht mehr drin steht -> keine Zuweisung zum DF sondern nur RAM"
   ]
  }
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