diff --git a/pandas_ta/Untitled.ipynb b/pandas_ta/Untitled.ipynb
deleted file mode 100644
index 78587a3..0000000
--- a/pandas_ta/Untitled.ipynb
+++ /dev/null
@@ -1,667 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas_ta as ta"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = pd.read_csv('/virt/admin/Fic_entree/Dwx-NDXH8.csv', sep=',', header=None)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "      <th></th>\n",
-       "      <th>0</th>\n",
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-       "      <th>0</th>\n",
-       "      <td>2017.04.20</td>\n",
-       "      <td>00:00</td>\n",
-       "      <td>5395.3</td>\n",
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-       "      <th>1</th>\n",
-       "      <td>2017.04.20</td>\n",
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-       "      <th>4</th>\n",
-       "      <td>2017.04.21</td>\n",
-       "      <td>08:00</td>\n",
-       "      <td>5448.4</td>\n",
-       "      <td>5455.3</td>\n",
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-       "<p>2392 rows × 7 columns</p>\n",
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-      ],
-      "text/plain": [
-       "               0      1       2       3       4       5      6\n",
-       "0     2017.04.20  00:00  5395.3  5455.3  5393.3  5401.5  34502\n",
-       "1     2017.04.20  08:00  5401.8  5421.5  5399.8  5418.8   7241\n",
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-       "3     2017.04.21  00:00  5442.8  5450.0  5442.5  5448.5   2181\n",
-       "4     2017.04.21  08:00  5448.4  5455.3  5447.8  5448.5   7406\n",
-       "...          ...    ...     ...     ...     ...     ...    ...\n",
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-       "2390  2020.05.27  00:00  9413.5  9500.5  9380.7  9487.5  20104\n",
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-       "\n",
-       "[2392 rows x 7 columns]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.columns=['date', 'time', 'open', 'high', 'low', 'close', 'ticks']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "<p>2392 rows × 4 columns</p>\n",
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-      ],
-      "text/plain": [
-       "      STOCHFk_14  STOCHFd_3   STOCHk_3   STOCHd_3\n",
-       "0            NaN        NaN        NaN        NaN\n",
-       "1            NaN        NaN        NaN        NaN\n",
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-       "4      84.295612  84.767141  84.767141        NaN\n",
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-       "\n",
-       "[2392 rows x 4 columns]"
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-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
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-    "df.ta.stoch(df['high'], df['low'], df['close'], 14,3,3, append = True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
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-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['date', 'time', 'open', 'high', 'low', 'close', 'ticks', 'STOCHFk_14',\n",
-       "       'STOCHFd_3', 'STOCHk_3', 'STOCHd_3'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
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-   "source": [
-    "df.columns"
-   ]
-  },
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-   "execution_count": 20,
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-       "      <td>2020.05.27</td>\n",
-       "      <td>00:00</td>\n",
-       "      <td>9413.5</td>\n",
-       "      <td>9500.5</td>\n",
-       "      <td>9380.7</td>\n",
-       "      <td>9487.5</td>\n",
-       "      <td>20104</td>\n",
-       "      <td>47.359307</td>\n",
-       "      <td>36.817288</td>\n",
-       "      <td>36.817288</td>\n",
-       "      <td>55.785458</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2391</th>\n",
-       "      <td>2020.05.27</td>\n",
-       "      <td>08:00</td>\n",
-       "      <td>9487.2</td>\n",
-       "      <td>9513.0</td>\n",
-       "      <td>9391.7</td>\n",
-       "      <td>9395.5</td>\n",
-       "      <td>33445</td>\n",
-       "      <td>8.845958</td>\n",
-       "      <td>24.391654</td>\n",
-       "      <td>24.391654</td>\n",
-       "      <td>37.757574</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>2392 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            date   time    open    high     low   close  ticks  STOCHFk_14  \\\n",
-       "0     2017.04.20  00:00  5395.3  5455.3  5393.3  5401.5  34502         NaN   \n",
-       "1     2017.04.20  08:00  5401.8  5421.5  5399.8  5418.8   7241         NaN   \n",
-       "2     2017.04.20  16:00  5418.5  5455.3  5412.0  5444.3  21038   82.258065   \n",
-       "3     2017.04.21  00:00  5442.8  5450.0  5442.5  5448.5   2181   87.747748   \n",
-       "4     2017.04.21  08:00  5448.4  5455.3  5447.8  5448.5   7406   84.295612   \n",
-       "...          ...    ...     ...     ...     ...     ...    ...         ...   \n",
-       "2387  2020.05.26  00:00  9532.4  9597.8  9509.8  9587.6  15120   93.098782   \n",
-       "2388  2020.05.26  08:00  9587.8  9609.1  9542.5  9555.6  31628   46.122860   \n",
-       "2389  2020.05.26  16:00  9556.1  9574.8  9378.1  9417.3  73867   16.969697   \n",
-       "2390  2020.05.27  00:00  9413.5  9500.5  9380.7  9487.5  20104   47.359307   \n",
-       "2391  2020.05.27  08:00  9487.2  9513.0  9391.7  9395.5  33445    8.845958   \n",
-       "\n",
-       "      STOCHFd_3   STOCHk_3   STOCHd_3  \n",
-       "0           NaN        NaN        NaN  \n",
-       "1           NaN        NaN        NaN  \n",
-       "2           NaN        NaN        NaN  \n",
-       "3           NaN        NaN        NaN  \n",
-       "4     84.767141  84.767141        NaN  \n",
-       "...         ...        ...        ...  \n",
-       "2387  95.820450  95.820450  96.319133  \n",
-       "2388  78.475307  78.475307  90.117018  \n",
-       "2389  52.063780  52.063780  75.453179  \n",
-       "2390  36.817288  36.817288  55.785458  \n",
-       "2391  24.391654  24.391654  37.757574  \n",
-       "\n",
-       "[2392 rows x 11 columns]"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "AttributeError",
-     "evalue": "module 'pandas_ta' has no attribute 'ha'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-24-c6639b8e7a6b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhelp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mta\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mha\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mAttributeError\u001b[0m: module 'pandas_ta' has no attribute 'ha'"
-     ]
-    }
-   ],
-   "source": [
-    "help(ta.ha)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}