{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["# Manipulation de s\u00e9ries financi\u00e8res avec la classe StockPrices\n", "\n", "La classe [StockPrices](http://www.xavierdupre.fr/app/pyensae/helpsphinx/notebooks/pyensae%20StockPrices.html?highlight=stockprices) facilite la r\u00e9cup\u00e9ration de donn\u00e9es financi\u00e8res via diff\u00e9rents sites. Le site [Yahoo Finance](http://finance.yahoo.com/) requiet maintenant un cookie (depuis Mai 2017) et il est pr\u00e9f\u00e9rable de choisir [Google](https://www.google.com/finance?q=apple&ei=bPghWZnLDoKVULfBk-gC) ou [Quandl](https://www.quandl.com/tools/python). Google ne fonctionne que les march\u00e9s am\u00e9ricains, [Quandl](https://www.quandl.com/tools/python) a des historiques plus courts."]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [{"data": {"text/html": ["<div id=\"my_id_menu_nb\">run previous cell, wait for 2 seconds</div>\n", "<script>\n", "function repeat_indent_string(n){\n", "    var a = \"\" ;\n", "    for ( ; n > 0 ; --n)\n", "        a += \"    \";\n", "    return a;\n", "}\n", "// look up into all sections and builds an automated menu //\n", "var update_menu_string = function(begin, lfirst, llast, sformat, send, keep_item, begin_format, end_format) {\n", "    var anchors = document.getElementsByClassName(\"section\");\n", "    if (anchors.length == 0) {\n", "        anchors = document.getElementsByClassName(\"text_cell_render rendered_html\");\n", "    }\n", "    var i,t;\n", "    var text_menu = begin;\n", "    var text_memo = \"<pre>\\nlength:\" + anchors.length + \"\\n\";\n", "    var ind = \"\";\n", "    var memo_level = 1;\n", "    var href;\n", "    var tags = [];\n", "    var main_item = 0;\n", "    var format_open = 0;\n", "    for (i = 0; i <= llast; i++)\n", "        tags.push(\"h\" + i);\n", "\n", "    for (i = 0; i < anchors.length; i++) {\n", "        text_memo += \"**\" + anchors[i].id + \"--\\n\";\n", "\n", "        var child = null;\n", "        for(t = 0; t < tags.length; t++) {\n", "            var r = anchors[i].getElementsByTagName(tags[t]);\n", "            if (r.length > 0) {\n", "child = r[0];\n", "break;\n", "            }\n", "        }\n", "        if (child == null) {\n", "            text_memo += \"null\\n\";\n", "            continue;\n", "        }\n", "        if (anchors[i].hasAttribute(\"id\")) {\n", "            // when converted in RST\n", "            href = anchors[i].id;\n", "            text_memo += \"#1-\" + href;\n", "            // passer \u00e0 child suivant (le chercher)\n", "        }\n", "        else if (child.hasAttribute(\"id\")) {\n", "            // in a notebook\n", "            href = child.id;\n", "            text_memo += \"#2-\" + href;\n", "        }\n", "        else {\n", "            text_memo += \"#3-\" + \"*\" + \"\\n\";\n", "            continue;\n", "        }\n", "        var title = child.textContent;\n", "        var level = parseInt(child.tagName.substring(1,2));\n", "\n", "        text_memo += \"--\" + level + \"?\" + lfirst + \"--\" + title + \"\\n\";\n", "\n", "        if ((level < lfirst) || (level > llast)) {\n", "            continue ;\n", "        }\n", "        if (title.endsWith('\u00b6')) {\n", "            title = title.substring(0,title.length-1).replace(\"<\", \"&lt;\")\n", "         .replace(\">\", \"&gt;\").replace(\"&\", \"&amp;\");\n", "        }\n", "        if (title.length == 0) {\n", "            continue;\n", "        }\n", "\n", "        while (level < memo_level) {\n", "            text_menu += end_format + \"</ul>\\n\";\n", "            format_open -= 1;\n", "            memo_level -= 1;\n", "        }\n", "        if (level == lfirst) {\n", "            main_item += 1;\n", "        }\n", "        if (keep_item != -1 && main_item != keep_item + 1) {\n", "            // alert(main_item + \" - \" + level + \" - \" + keep_item);\n", "            continue;\n", "        }\n", "        while (level > memo_level) {\n", "            text_menu += \"<ul>\\n\";\n", "            memo_level += 1;\n", "        }\n", "        text_menu += repeat_indent_string(level-2);\n", "        text_menu += begin_format + sformat.replace(\"__HREF__\", href).replace(\"__TITLE__\", title);\n", "        format_open += 1;\n", "    }\n", "    while (1 < memo_level) {\n", "        text_menu += end_format + \"</ul>\\n\";\n", "        memo_level -= 1;\n", "        format_open -= 1;\n", "    }\n", "    text_menu += send;\n", "    //text_menu += \"\\n\" + text_memo;\n", "\n", "    while (format_open > 0) {\n", "        text_menu += end_format;\n", "        format_open -= 1;\n", "    }\n", "    return text_menu;\n", "};\n", "var update_menu = function() {\n", "    var sbegin = \"\";\n", "    var sformat = '<a href=\"#__HREF__\">__TITLE__</a>';\n", "    var send = \"\";\n", "    var begin_format = '<li>';\n", "    var end_format = '</li>';\n", "    var keep_item = -1;\n", "    var text_menu = update_menu_string(sbegin, 2, 4, sformat, send, keep_item,\n", "       begin_format, end_format);\n", "    var menu = document.getElementById(\"my_id_menu_nb\");\n", "    menu.innerHTML=text_menu;\n", "};\n", "window.setTimeout(update_menu,2000);\n", "            </script>"], "text/plain": ["<IPython.core.display.HTML object>"]}, "execution_count": 2, "metadata": {}, "output_type": "execute_result"}], "source": ["import pyensae\n", "from jyquickhelper import add_notebook_menu\n", "add_notebook_menu()"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "plt.style.use('ggplot')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Initialisation"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["import pyensae\n", "import os\n", "from pyensae.finance import StockPrices\n", "cache = os.path.abspath(\"cache\")\n", "if not os.path.exists(cache):\n", "    os.mkdir(cache)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Cr\u00e9er un objet StockPrices"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Le plus est d'utiliser le tick de la s\u00e9rie financi\u00e8re utilis\u00e9 par le site [Yahoo Finance](https://fr.finance.yahoo.com) ou [Google Finance](https://www.google.com/search?q=finance) qui fait maintenant partie du moteur de recherche ou [quandl](https://www.quandl.com/tools/python)."]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Date</th>\n", "      <th>Open</th>\n", "      <th>High</th>\n", "      <th>Low</th>\n", "      <th>Close</th>\n", "      <th>Adj Close</th>\n", "      <th>Volume</th>\n", "    </tr>\n", "    <tr>\n", "      <th>Date</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>2000-01-03</th>\n", "      <td>2000-01-03</td>\n", "      <td>58.68750</td>\n", "      <td>59.3125</td>\n", "      <td>56.00000</td>\n", "      <td>58.28125</td>\n", "      <td>42.295185</td>\n", "      <td>53228400</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-04</th>\n", "      <td>2000-01-04</td>\n", "      <td>56.78125</td>\n", "      <td>58.5625</td>\n", "      <td>56.12500</td>\n", "      <td>56.31250</td>\n", "      <td>40.866425</td>\n", "      <td>54119000</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-05</th>\n", "      <td>2000-01-05</td>\n", "      <td>55.56250</td>\n", "      <td>58.1875</td>\n", "      <td>54.68750</td>\n", "      <td>56.90625</td>\n", "      <td>41.297348</td>\n", "      <td>64059600</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-06</th>\n", "      <td>2000-01-06</td>\n", "      <td>56.09375</td>\n", "      <td>56.9375</td>\n", "      <td>54.18750</td>\n", "      <td>55.00000</td>\n", "      <td>39.913952</td>\n", "      <td>54976600</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-07</th>\n", "      <td>2000-01-07</td>\n", "      <td>54.31250</td>\n", "      <td>56.1250</td>\n", "      <td>53.65625</td>\n", "      <td>55.71875</td>\n", "      <td>40.435547</td>\n", "      <td>62013600</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["                  Date      Open     High       Low     Close  Adj Close  \\\n", "Date                                                                       \n", "2000-01-03  2000-01-03  58.68750  59.3125  56.00000  58.28125  42.295185   \n", "2000-01-04  2000-01-04  56.78125  58.5625  56.12500  56.31250  40.866425   \n", "2000-01-05  2000-01-05  55.56250  58.1875  54.68750  56.90625  41.297348   \n", "2000-01-06  2000-01-06  56.09375  56.9375  54.18750  55.00000  39.913952   \n", "2000-01-07  2000-01-07  54.31250  56.1250  53.65625  55.71875  40.435547   \n", "\n", "              Volume  \n", "Date                  \n", "2000-01-03  53228400  \n", "2000-01-04  54119000  \n", "2000-01-05  64059600  \n", "2000-01-06  54976600  \n", "2000-01-07  62013600  "]}, "execution_count": 5, "metadata": {}, "output_type": "execute_result"}], "source": ["source = 'yahoo_new'\n", "tick = 'MSFT'\n", "stock = StockPrices(tick, folder=cache, url=source)\n", "stock.head()"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Date</th>\n", "      <th>Open</th>\n", "      <th>High</th>\n", "      <th>Low</th>\n", "      <th>Close</th>\n", "      <th>Adj Close</th>\n", "      <th>Volume</th>\n", "    </tr>\n", "    <tr>\n", "      <th>Date</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>2019-01-25</th>\n", "      <td>2019-01-25</td>\n", "      <td>107.239998</td>\n", "      <td>107.879997</td>\n", "      <td>106.199997</td>\n", "      <td>107.169998</td>\n", "      <td>107.169998</td>\n", "      <td>31225600</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-28</th>\n", "      <td>2019-01-28</td>\n", "      <td>106.260002</td>\n", "      <td>106.480003</td>\n", "      <td>104.660004</td>\n", "      <td>105.080002</td>\n", "      <td>105.080002</td>\n", "      <td>29476700</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-29</th>\n", "      <td>2019-01-29</td>\n", "      <td>104.879997</td>\n", "      <td>104.970001</td>\n", "      <td>102.169998</td>\n", "      <td>102.940002</td>\n", "      <td>102.940002</td>\n", "      <td>31490500</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-30</th>\n", "      <td>2019-01-30</td>\n", "      <td>104.620003</td>\n", "      <td>106.379997</td>\n", "      <td>104.330002</td>\n", "      <td>106.379997</td>\n", "      <td>106.379997</td>\n", "      <td>49471900</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-31</th>\n", "      <td>2019-01-31</td>\n", "      <td>103.800003</td>\n", "      <td>105.220001</td>\n", "      <td>103.180000</td>\n", "      <td>104.430000</td>\n", "      <td>104.430000</td>\n", "      <td>55636400</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["                  Date        Open        High         Low       Close  \\\n", "Date                                                                     \n", "2019-01-25  2019-01-25  107.239998  107.879997  106.199997  107.169998   \n", "2019-01-28  2019-01-28  106.260002  106.480003  104.660004  105.080002   \n", "2019-01-29  2019-01-29  104.879997  104.970001  102.169998  102.940002   \n", "2019-01-30  2019-01-30  104.620003  106.379997  104.330002  106.379997   \n", "2019-01-31  2019-01-31  103.800003  105.220001  103.180000  104.430000   \n", "\n", "             Adj Close    Volume  \n", "Date                              \n", "2019-01-25  107.169998  31225600  \n", "2019-01-28  105.080002  29476700  \n", "2019-01-29  102.940002  31490500  \n", "2019-01-30  106.379997  49471900  \n", "2019-01-31  104.430000  55636400  "]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["stock.tail()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["La classe <tt>StockPrices</tt> contient un objet <a href=\"http://pandas.pydata.org/pandas-docs/version/0.13.1/generated/pandas.DataFrame.html\">pandas.DataFrame</a> auquel on acc\u00e8de en \u00e9crivant <tt>stock.dataframe</tt> ou <tt>stock.df</tt> :"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [{"data": {"text/plain": ["Index(['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume'], dtype='object')"]}, "execution_count": 7, "metadata": {}, "output_type": "execute_result"}], "source": ["stock.dataframe.columns"]}, {"cell_type": "markdown", "metadata": {}, "source": ["De la m\u00eame mani\u00e8re, on peut cr\u00e9er un objet <tt>StockPrices</tt> \u00e0 partir d'un DataFrame :"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Close</th>\n", "      <th>Date</th>\n", "    </tr>\n", "    <tr>\n", "      <th>Date</th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>2014-04-01</th>\n", "      <td>105.6</td>\n", "      <td>2014-04-01</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2014-04-02</th>\n", "      <td>104.6</td>\n", "      <td>2014-04-02</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2014-04-03</th>\n", "      <td>105.8</td>\n", "      <td>2014-04-03</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["            Close        Date\n", "Date                         \n", "2014-04-01  105.6  2014-04-01\n", "2014-04-02  104.6  2014-04-02\n", "2014-04-03  105.8  2014-04-03"]}, "execution_count": 8, "metadata": {}, "output_type": "execute_result"}], "source": ["import pandas\n", "data = [{\"Date\":\"2014-04-01\", \"Close\":105.6}, {\"Date\":\"2014-04-02\", \"Close\":104.6}, \n", "        {\"Date\":\"2014-04-03\", \"Close\":105.8}, ]\n", "df = pandas.DataFrame(data)\n", "stock = StockPrices(\"donnees\",df)\n", "stock.head()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Quelques graphes"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Premier dessin, on t\u00e9l\u00e9charge les donn\u00e9es de BNP puis on dessine le cours de l'action."]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["<Figure size 864x432 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["import datetime\n", "stock = StockPrices(tick, folder=cache, url=source)\n", "ax = StockPrices.draw(stock, figsize=(12,6))"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["<Figure size 864x432 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["stock = StockPrices(tick, folder=cache, url=source)\n", "StockPrices.draw(stock, figsize=(12,6));"]}, {"cell_type": "markdown", "metadata": {}, "source": ["La m\u00eame chose se produit sur une autre s\u00e9rie financi\u00e8re mais pas \u00e0 la m\u00eame date. On trace maintenant la s\u00e9rie *Open* (*Adj Close* d\u00e9fini\n", "sur cette page [View and download historical price, dividend, or split data](https://help.yahoo.com/kb/finance/historical-prices-sln2311.html?impressions=true) n'est disponible qu'avec Yahoo)."]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["<Figure size 864x432 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["stock = StockPrices(\"MSFT\", folder=cache, url='yahoo')\n", "StockPrices.draw(stock, field=[\"Open\", \"Close\"], figsize=(12,6));"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Ce type de s\u00e9rie ne fait pas toujours appara\u00eetre les saut de prix qui survient comme par exemple le <a href=\"http://invest.bnpparibas.com/fr/pid5900/en-bref.html\">20 f\u00e9vrier 2002</a> lorsque le cours nominal de l'action de la BNP a \u00e9t\u00e9 divis\u00e9 par deux pour augmenter la liquidit\u00e9. Le nombre d'actions a \u00e9t\u00e9 multipli\u00e9 par deux. Les donn\u00e9es sont le plus souvent corrig\u00e9es [BNP f\u00e9vrier 2002](http://www.google.com/finance/historical?cid=667923&startdate=Feb+15%2C+2002&enddate=Feb+28%2C+2002&num=30&ei=AP8hWaDXF4WNUNuujYgK)."]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Ajouter une seconde s\u00e9rie sur un graphe"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Dans l'exemple suivant, on trace une s\u00e9rie financi\u00e8re puis on ajoute la s\u00e9rie des rendements sur un second axe."]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Date</th>\n", "      <th>Open</th>\n", "      <th>High</th>\n", "      <th>Low</th>\n", "      <th>Close</th>\n", "      <th>Adj Close</th>\n", "      <th>Volume</th>\n", "    </tr>\n", "    <tr>\n", "      <th>Date</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>2000-01-03</th>\n", "      <td>2000-01-03</td>\n", "      <td>58.68750</td>\n", "      <td>59.3125</td>\n", "      <td>56.00000</td>\n", "      <td>58.28125</td>\n", "      <td>42.295185</td>\n", "      <td>53228400</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-04</th>\n", "      <td>2000-01-04</td>\n", "      <td>56.78125</td>\n", "      <td>58.5625</td>\n", "      <td>56.12500</td>\n", "      <td>56.31250</td>\n", "      <td>40.866425</td>\n", "      <td>54119000</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-05</th>\n", "      <td>2000-01-05</td>\n", "      <td>55.56250</td>\n", "      <td>58.1875</td>\n", "      <td>54.68750</td>\n", "      <td>56.90625</td>\n", "      <td>41.297348</td>\n", "      <td>64059600</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-06</th>\n", "      <td>2000-01-06</td>\n", "      <td>56.09375</td>\n", "      <td>56.9375</td>\n", "      <td>54.18750</td>\n", "      <td>55.00000</td>\n", "      <td>39.913952</td>\n", "      <td>54976600</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2000-01-07</th>\n", "      <td>2000-01-07</td>\n", "      <td>54.31250</td>\n", "      <td>56.1250</td>\n", "      <td>53.65625</td>\n", "      <td>55.71875</td>\n", "      <td>40.435547</td>\n", "      <td>62013600</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["                  Date      Open     High       Low     Close  Adj Close  \\\n", "Date                                                                       \n", "2000-01-03  2000-01-03  58.68750  59.3125  56.00000  58.28125  42.295185   \n", "2000-01-04  2000-01-04  56.78125  58.5625  56.12500  56.31250  40.866425   \n", "2000-01-05  2000-01-05  55.56250  58.1875  54.68750  56.90625  41.297348   \n", "2000-01-06  2000-01-06  56.09375  56.9375  54.18750  55.00000  39.913952   \n", "2000-01-07  2000-01-07  54.31250  56.1250  53.65625  55.71875  40.435547   \n", "\n", "              Volume  \n", "Date                  \n", "2000-01-03  53228400  \n", "2000-01-04  54119000  \n", "2000-01-05  64059600  \n", "2000-01-06  54976600  \n", "2000-01-07  62013600  "]}, "execution_count": 12, "metadata": {}, "output_type": "execute_result"}], "source": ["stock.head()"]}, {"cell_type": "code", "execution_count": 12, "metadata": {"scrolled": false}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["<Figure size 1152x360 with 2 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["stock = StockPrices(tick)\n", "ret = stock.returns()[\"2019-01-04\":\"2019-02-02\"]\n", "ret.dataframe.loc[\"2019-01-11\":\"2019-01-18\",\"Close\"] = 0  # on annule certains valeurs\n", "ax = stock.plot(figsize=(16, 5))\n", "ret.plot(axis=2, ax=ax, label_prefix=\"r\", color='blue');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Quelques op\u00e9rations"]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [{"data": {"text/plain": ["['GOOGL.2000-01-03.2018-03-15.txt',\n", " 'GOOGL.2000-01-03.2018-05-13.txt',\n", " 'GOOGL.2000-01-03.2019-02-01.txt',\n", " 'MSFT.2000-01-03.2018-03-15.txt',\n", " 'MSFT.2000-01-03.2018-05-13.txt',\n", " 'MSFT.2000-01-03.2019-02-01.txt']"]}, "execution_count": 14, "metadata": {}, "output_type": "execute_result"}], "source": ["os.listdir(cache)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On affiche les derni\u00e8res lignes."]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Date</th>\n", "      <th>Open</th>\n", "      <th>High</th>\n", "      <th>Low</th>\n", "      <th>Close</th>\n", "      <th>Adj Close</th>\n", "      <th>Volume</th>\n", "    </tr>\n", "    <tr>\n", "      <th>Date</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>2019-01-25</th>\n", "      <td>2019-01-25</td>\n", "      <td>107.239998</td>\n", "      <td>107.879997</td>\n", "      <td>106.199997</td>\n", "      <td>107.169998</td>\n", "      <td>107.169998</td>\n", "      <td>31225600</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-28</th>\n", "      <td>2019-01-28</td>\n", "      <td>106.260002</td>\n", "      <td>106.480003</td>\n", "      <td>104.660004</td>\n", "      <td>105.080002</td>\n", "      <td>105.080002</td>\n", "      <td>29476700</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-29</th>\n", "      <td>2019-01-29</td>\n", "      <td>104.879997</td>\n", "      <td>104.970001</td>\n", "      <td>102.169998</td>\n", "      <td>102.940002</td>\n", "      <td>102.940002</td>\n", "      <td>31490500</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-30</th>\n", "      <td>2019-01-30</td>\n", "      <td>104.620003</td>\n", "      <td>106.379997</td>\n", "      <td>104.330002</td>\n", "      <td>106.379997</td>\n", "      <td>106.379997</td>\n", "      <td>49471900</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-31</th>\n", "      <td>2019-01-31</td>\n", "      <td>103.800003</td>\n", "      <td>105.220001</td>\n", "      <td>103.180000</td>\n", "      <td>104.430000</td>\n", "      <td>104.430000</td>\n", "      <td>55636400</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["                  Date        Open        High         Low       Close  \\\n", "Date                                                                     \n", "2019-01-25  2019-01-25  107.239998  107.879997  106.199997  107.169998   \n", "2019-01-28  2019-01-28  106.260002  106.480003  104.660004  105.080002   \n", "2019-01-29  2019-01-29  104.879997  104.970001  102.169998  102.940002   \n", "2019-01-30  2019-01-30  104.620003  106.379997  104.330002  106.379997   \n", "2019-01-31  2019-01-31  103.800003  105.220001  103.180000  104.430000   \n", "\n", "             Adj Close    Volume  \n", "Date                              \n", "2019-01-25  107.169998  31225600  \n", "2019-01-28  105.080002  29476700  \n", "2019-01-29  102.940002  31490500  \n", "2019-01-30  106.379997  49471900  \n", "2019-01-31  104.430000  55636400  "]}, "execution_count": 15, "metadata": {}, "output_type": "execute_result"}], "source": ["stock.tail()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On r\u00e9cup\u00e8re la s\u00e9rie des rendements."]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Date</th>\n", "      <th>Volume</th>\n", "      <th>Open</th>\n", "      <th>High</th>\n", "      <th>Low</th>\n", "      <th>Close</th>\n", "      <th>Adj Close</th>\n", "    </tr>\n", "    <tr>\n", "      <th>Date</th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "      <th></th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>2019-01-25</th>\n", "      <td>2019-01-25</td>\n", "      <td>31225600</td>\n", "      <td>0.003556</td>\n", "      <td>0.008224</td>\n", "      <td>0.008164</td>\n", "      <td>0.009134</td>\n", "      <td>0.009134</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-28</th>\n", "      <td>2019-01-28</td>\n", "      <td>29476700</td>\n", "      <td>-0.009138</td>\n", "      <td>-0.012977</td>\n", "      <td>-0.014501</td>\n", "      <td>-0.019502</td>\n", "      <td>-0.019502</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-29</th>\n", "      <td>2019-01-29</td>\n", "      <td>31490500</td>\n", "      <td>-0.012987</td>\n", "      <td>-0.014181</td>\n", "      <td>-0.023791</td>\n", "      <td>-0.020365</td>\n", "      <td>-0.020365</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-30</th>\n", "      <td>2019-01-30</td>\n", "      <td>49471900</td>\n", "      <td>-0.002479</td>\n", "      <td>0.013432</td>\n", "      <td>0.021141</td>\n", "      <td>0.033417</td>\n", "      <td>0.033417</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2019-01-31</th>\n", "      <td>2019-01-31</td>\n", "      <td>55636400</td>\n", "      <td>-0.007838</td>\n", "      <td>-0.010904</td>\n", "      <td>-0.011023</td>\n", "      <td>-0.018330</td>\n", "      <td>-0.018330</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["                  Date    Volume      Open      High       Low     Close  \\\n", "Date                                                                       \n", "2019-01-25  2019-01-25  31225600  0.003556  0.008224  0.008164  0.009134   \n", "2019-01-28  2019-01-28  29476700 -0.009138 -0.012977 -0.014501 -0.019502   \n", "2019-01-29  2019-01-29  31490500 -0.012987 -0.014181 -0.023791 -0.020365   \n", "2019-01-30  2019-01-30  49471900 -0.002479  0.013432  0.021141  0.033417   \n", "2019-01-31  2019-01-31  55636400 -0.007838 -0.010904 -0.011023 -0.018330   \n", "\n", "            Adj Close  \n", "Date                   \n", "2019-01-25   0.009134  \n", "2019-01-28  -0.019502  \n", "2019-01-29  -0.020365  \n", "2019-01-30   0.033417  \n", "2019-01-31  -0.018330  "]}, "execution_count": 16, "metadata": {}, "output_type": "execute_result"}], "source": ["ret = stock.returns()\n", "ret.tail()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On trace la s\u00e9rie des rendements pour les derniers mois."]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"data": {"image/png": "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\n", "text/plain": ["<Figure size 864x432 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["StockPrices.draw(ret, figsize=(12,6), begin=\"2013-12-01\", date_format=\"%Y-%m\");"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Quelques notions sur les dates"]}, {"cell_type": "markdown", "metadata": {}, "source": ["La classe <i>StockPrices</i> utilise les dates sous forme de cha\u00eenes de caract\u00e8res. De cette fa\u00e7on, il n'est pas possible de faire des op\u00e9rations dessus. Pour ce faire, il faut les convertir en un objet appel\u00e9 <a href=\"https://docs.python.org/2/library/datetime.html\">datetime</a>."]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"data": {"text/plain": ["datetime.datetime(2014, 3, 31, 0, 0)"]}, "execution_count": 18, "metadata": {}, "output_type": "execute_result"}], "source": ["from datetime import datetime, timedelta\n", "dt = datetime.strptime(\"2014-03-31\",\"%Y-%m-%d\")\n", "dt"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On ajoute un jour :"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [{"data": {"text/plain": ["datetime.datetime(2014, 4, 1, 0, 0)"]}, "execution_count": 19, "metadata": {}, "output_type": "execute_result"}], "source": ["delta = timedelta(1)\n", "dt = dt + delta\n", "dt"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Puis on convertit dans l'autre sens :"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [{"data": {"text/plain": ["'2014-04-01'"]}, "execution_count": 20, "metadata": {}, "output_type": "execute_result"}], "source": ["s = dt.strftime(\"%Y-%m-%d\")\n", "s"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Promenade dans l'index"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Il est facile de r\u00e9cup\u00e9rer les valeurs correspondant \u00e0 une date pr\u00e9cise. Mais comment r\u00e9cup\u00e9rer la valeur du jour d'apr\u00e8s ?"]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["A                   Date        Open        High        Low      Close  \\\n", "Date                                                                   \n", "2005-01-04  2005-01-04  100.800804  101.566566  96.836838  97.347351   \n", "2005-01-05  2005-01-05   96.821823   98.548546  96.211212  96.851852   \n", "2005-01-06  2005-01-06   97.637634   98.048050  93.953957  94.369370   \n", "\n", "            Adj Close    Volume  \n", "Date                             \n", "2005-01-04  97.347351  27484200  \n", "2005-01-05  96.851852  16456700  \n", "2005-01-06  94.369370  20753400  \n", "D 97.347351\n", "G 97\n"]}], "source": ["tick2 = 'GOOGL'\n", "stock = StockPrices(tick2, folder=cache, url=source)\n", "df = stock.dataframe\n", "print(\"A\", df[\"2005-01-04\":\"2005-01-06\"])\n", "print(\"D\", df.loc[\"2005-01-04\",\"Close\"])\n", "print(\"G\", df.index.get_loc(\"2005-01-06\"))  # retourne la position de cette date"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Sauver les tables"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On peut conserver les donn\u00e9es sous forme de fichiers pour les r\u00e9cup\u00e9rer plus tard."]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"data": {"text/plain": ["['donnees.txt']"]}, "execution_count": 22, "metadata": {}, "output_type": "execute_result"}], "source": ["stock = StockPrices(tick2, folder=cache, url=source)\n", "stock.dataframe.to_csv(\"donnees.txt\", sep=\"\\t\")\n", "[_ for _ in os.listdir(\".\") if \"donnees\" in _]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Le fichier est sauv\u00e9. Pour le r\u00e9cup\u00e9rer avec pandas :"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Date</th>\n", "      <th>Date.1</th>\n", "      <th>Open</th>\n", "      <th>High</th>\n", "      <th>Low</th>\n", "      <th>Close</th>\n", "      <th>Adj Close</th>\n", "      <th>Volume</th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>0</th>\n", "      <td>2004-08-19</td>\n", "      <td>2004-08-19</td>\n", "      <td>50.050049</td>\n", "      <td>52.082081</td>\n", "      <td>48.028027</td>\n", "      <td>50.220219</td>\n", "      <td>50.220219</td>\n", "      <td>44659000</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1</th>\n", "      <td>2004-08-20</td>\n", "      <td>2004-08-20</td>\n", "      <td>50.555557</td>\n", "      <td>54.594593</td>\n", "      <td>50.300301</td>\n", "      <td>54.209209</td>\n", "      <td>54.209209</td>\n", "      <td>22834300</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2</th>\n", "      <td>2004-08-23</td>\n", "      <td>2004-08-23</td>\n", "      <td>55.430431</td>\n", "      <td>56.796795</td>\n", "      <td>54.579578</td>\n", "      <td>54.754753</td>\n", "      <td>54.754753</td>\n", "      <td>18256100</td>\n", "    </tr>\n", "    <tr>\n", "      <th>3</th>\n", "      <td>2004-08-24</td>\n", "      <td>2004-08-24</td>\n", "      <td>55.675674</td>\n", "      <td>55.855854</td>\n", "      <td>51.836838</td>\n", "      <td>52.487488</td>\n", "      <td>52.487488</td>\n", "      <td>15247300</td>\n", "    </tr>\n", "    <tr>\n", "      <th>4</th>\n", "      <td>2004-08-25</td>\n", "      <td>2004-08-25</td>\n", "      <td>52.532532</td>\n", "      <td>54.054054</td>\n", "      <td>51.991993</td>\n", "      <td>53.053055</td>\n", "      <td>53.053055</td>\n", "      <td>9188600</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["         Date      Date.1       Open       High        Low      Close  \\\n", "0  2004-08-19  2004-08-19  50.050049  52.082081  48.028027  50.220219   \n", "1  2004-08-20  2004-08-20  50.555557  54.594593  50.300301  54.209209   \n", "2  2004-08-23  2004-08-23  55.430431  56.796795  54.579578  54.754753   \n", "3  2004-08-24  2004-08-24  55.675674  55.855854  51.836838  52.487488   \n", "4  2004-08-25  2004-08-25  52.532532  54.054054  51.991993  53.053055   \n", "\n", "   Adj Close    Volume  \n", "0  50.220219  44659000  \n", "1  54.209209  22834300  \n", "2  54.754753  18256100  \n", "3  52.487488  15247300  \n", "4  53.053055   9188600  "]}, "execution_count": 23, "metadata": {}, "output_type": "execute_result"}], "source": ["import pandas\n", "df = pandas.read_csv(\"donnees.txt\", sep=\"\\t\")\n", "df.head()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Les dates apparaissent deux fois."]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Date\tDate\tOpen\tHigh\tLow\tClose\tAdj Close\tVolume\n", "2004-08-19\t2004-08-19\t50.050049\t52.082081\t48.028027\t50.220219\t50.220219\t44659000\n", "2004-08-20\t2004-08-20\t50.555557\t54.594593\t50.300301\t54.209209\t54.209209\t22834300\n", "2004-08-23\t2004-08-23\t55.43043100000001\t56.796795\t54.57957800000001\t54.754753\t54.754753\t18256100\n", "2004-08-24\t2004-08-24\t55.675674\t55.855854\t51.836838\t52.487488\t52.487488\t15247300\n", "2004-08-25\t20\n"]}], "source": ["with open(\"donnees.txt\",\"r\") as f: \n", "    text = f.read()\n", "print(text[:400])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Cela est d\u00fb au fait que les dates sont \u00e0 la fois une colonne et servent d'index. Pour \u00e9viter de les conserver deux fois, on demande explicitement \u00e0 ce que l'index ne soit pas ajout\u00e9 au fichier : "]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": ["stock = StockPrices(tick2, folder=cache, url=source)\n", "stock.dataframe.to_csv(\"donnees.txt\", sep=\"\\t\", index=False)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Puis on r\u00e9cup\u00e8re les donn\u00e9es :"]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [{"data": {"text/html": ["<div>\n", "<style scoped>\n", "    .dataframe tbody tr th:only-of-type {\n", "        vertical-align: middle;\n", "    }\n", "\n", "    .dataframe tbody tr th {\n", "        vertical-align: top;\n", "    }\n", "\n", "    .dataframe thead th {\n", "        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>Date</th>\n", "      <th>Open</th>\n", "      <th>High</th>\n", "      <th>Low</th>\n", "      <th>Close</th>\n", "      <th>Adj Close</th>\n", "      <th>Volume</th>\n", "    </tr>\n", "  </thead>\n", "  <tbody>\n", "    <tr>\n", "      <th>0</th>\n", "      <td>2004-08-19</td>\n", "      <td>50.050049</td>\n", "      <td>52.082081</td>\n", "      <td>48.028027</td>\n", "      <td>50.220219</td>\n", "      <td>50.220219</td>\n", "      <td>44659000</td>\n", "    </tr>\n", "    <tr>\n", "      <th>1</th>\n", "      <td>2004-08-20</td>\n", "      <td>50.555557</td>\n", "      <td>54.594593</td>\n", "      <td>50.300301</td>\n", "      <td>54.209209</td>\n", "      <td>54.209209</td>\n", "      <td>22834300</td>\n", "    </tr>\n", "    <tr>\n", "      <th>2</th>\n", "      <td>2004-08-23</td>\n", "      <td>55.430431</td>\n", "      <td>56.796795</td>\n", "      <td>54.579578</td>\n", "      <td>54.754753</td>\n", "      <td>54.754753</td>\n", "      <td>18256100</td>\n", "    </tr>\n", "    <tr>\n", "      <th>3</th>\n", "      <td>2004-08-24</td>\n", "      <td>55.675674</td>\n", "      <td>55.855854</td>\n", "      <td>51.836838</td>\n", "      <td>52.487488</td>\n", "      <td>52.487488</td>\n", "      <td>15247300</td>\n", "    </tr>\n", "    <tr>\n", "      <th>4</th>\n", "      <td>2004-08-25</td>\n", "      <td>52.532532</td>\n", "      <td>54.054054</td>\n", "      <td>51.991993</td>\n", "      <td>53.053055</td>\n", "      <td>53.053055</td>\n", "      <td>9188600</td>\n", "    </tr>\n", "  </tbody>\n", "</table>\n", "</div>"], "text/plain": ["         Date       Open       High        Low      Close  Adj Close    Volume\n", "0  2004-08-19  50.050049  52.082081  48.028027  50.220219  50.220219  44659000\n", "1  2004-08-20  50.555557  54.594593  50.300301  54.209209  54.209209  22834300\n", "2  2004-08-23  55.430431  56.796795  54.579578  54.754753  54.754753  18256100\n", "3  2004-08-24  55.675674  55.855854  51.836838  52.487488  52.487488  15247300\n", "4  2004-08-25  52.532532  54.054054  51.991993  53.053055  53.053055   9188600"]}, "execution_count": 26, "metadata": {}, "output_type": "execute_result"}], "source": ["df = pandas.read_csv(\"donnees.txt\",sep=\"\\t\")\n", "df.head()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On v\u00e9rifie le fichier sur disque dur :"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Date\tOpen\tHigh\tLow\tClose\tAdj Close\tVolume\n", "2004-08-19\t50.050049\t52.082081\t48.028027\t50.220219\t50.220219\t44659000\n", "2004-08-20\t50.555557\t54.594593\t50.300301\t54.209209\t54.209209\t22834300\n", "2004-08-23\t55.43043100000001\t56.796795\t54.57957800000001\t54.754753\t54.754753\t18256100\n", "2004-08-24\t55.675674\t55.855854\t51.836838\t52.487488\t52.487488\t15247300\n", "2004-08-25\t52.532532\t54.054054\t51.991993\t53.05305500000001\t53.\n"]}], "source": ["with open(\"donnees.txt\", \"r\") as f:\n", "    text = f.read()\n", "print(text[:400])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["C'est mieux."]}, {"cell_type": "code", "execution_count": 27, "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": "3.7.0"}}, "nbformat": 4, "nbformat_minor": 2}