diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index d550766ef4b34fb959ffd60c85860e1165fcfe65..fe6f3d542b23d746f3eb291765a7797388d7036f 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -30,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -39,17 +39,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Aucun fichier local avec les données étudiées n'est disponible. Un nouveau fichier est fabriqué à partir du lien donné\n" - ] - } - ], + "outputs": [], "source": [ "import os\n", "import urllib.request\n", @@ -64,12 +56,12 @@ "metadata": {}, "source": [ "Nous pouvons à présent ouvrir le fichier local et travailler avec celui-ci tout au long de l'étude.\n", - "La première colonne correspond à l'ID. Nous avons dès lors décidé de passer cette colonne comme index (au moins dans un premier temps)" + "La première colonne correspond à l'ID. Nous avons dès lors décidé de passer cette colonne comme index :`index_col=0`" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -478,7 +470,7 @@ "53 1821 54.0 NaN" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -505,64 +497,171 @@ "* Les salaires sont donnés en shillings par semaine." ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 2. Pré-Analyse des données" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous recherchons dans un premier temps le type de données présentes dans chaque colonne" + ] + }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 7, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "numpy.int64" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + " \n" + ] } ], "source": [ - "type(raw_data['Year'][1])" + "print (type(raw_data['Year'][1]),type(raw_data['Wheat'][1]),type(raw_data['Wages'][1]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Afin de pouvoir réaliser des graphique numérique des données, nous convertissons les date en format datetime compatible avec les graphique matplotlib\n" + "Le premier (date)est un nombre entier, les deux autres sont des nombres réels. Afin de traiter les dates comme des dates dans les graphiques, nous avons décider de convertir les dates en `datetime`, format de date supporter par Matplotlib. Pour ce faire, nous avons choisi de mettre chaque date comme étant le 1er janvier de l'année en cours `datetime.date(année,mois (=1),jours (=1))`. " ] }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "import datetime\n", - "year=[]\n", - "year=[datetime.date(raw_data['Year'][i+1],1,1)for i in range(0,len(raw_data['Year'])-1)]\n", - "width=[(year[j+1]-year[j]).days for j in range(0,len(year)-1)]\n", - "width.append(365)" + "year=[datetime.date(raw_data['Year'][i],1,1)for i in range(1,len(raw_data['Year'])+1)]# car l'index choisi commence à 1 et pas 0" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Calculer la durée entre chaque date est necessaire et variera pour 5 ans de $4*365+366 = 1826 $ à $3*365+2*366 = 1827$ " + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "width=[(year[j+1]-year[j]).days for j in range(0,len(year)-1)]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Entre 1565 et 1821, il y a n-1 periode de temps (n= nombre d'année) ! Nous ajoutons donc à width, une période de temps = 0 pour l'année 1821 !" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "width.append(0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nous choisissons à présent de remettre l'ensemble des données dans un seul dataframe avec 2 nouvelles colonnes : \"Year_date\" et \"period_width\"" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "data = raw_data.assign(Year_date=year,period_width=width)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Dernière verification des types d'objects pour les deux colonnes ajoutées. La colonne date est maintenant bien den datetime !" ] }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \n" + ] + } + ], + "source": [ + "print (type(data['Year_date'][1]),type(data['period_width'][1]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 3. Plot" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## A. Plot séparé des deux parties du graph\n", + "Dans un premier temps, nous réalisons le graphique en batonnet pour le prix du blé au cours du temps. celui-ci est réalisé avec `matplotlib.pyplot.bar` dans lequel, nous assignons `x=` dates; `y=`prix du blé ; `align='edge'`pour faire partir le batonnet depuis la limite gauche (et non centrale vu que nous avons choisi le 1 janvier comme date), `width=` le temps entre deux dates calculée ci-dessus.\n", + "\n", + "Nous limitons également le graphique en x: depuis la date du 1565 à 1821.\n", + "\n", + "Nous limitons aussi l'axe des y entre le minimum -5 (pour voir cette donnée malgrès tout) et le maximum +5 (pour les même raisons que pour le minimum) des données plotées" + ] + }, + { + "cell_type": "code", + "execution_count": 94, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(21.0, 100)" + "(571240.0, 664742.0)" ] }, - "execution_count": 93, + "execution_count": 94, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -575,10 +674,237 @@ ], "source": [ "import matplotlib.pyplot as plt\n", - "ax = plt.subplot(111)\n", - "plt.bar(year[48:52],raw_data['Wheat'][48:52],align='edge',width=width[48:52])\n", - "ax.xaxis_date()\n", - "plt.ylim(raw_data['Wheat'].min()-5,100)" + "import numpy as np\n", + "ax1 = plt.subplot(111)\n", + "ax1.bar(data['Year_date'].values,data['Wheat'],align='edge',width=data['period_width'])\n", + "ax1.xaxis_date()\n", + "ax1.set_ylim(data['Wheat'].min()-5,data['Wheat'].max()+5)\n", + "ax1.set_xlim(data['Year_date'][1],data['Year_date'][len(data)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Deuxièmement, nous faisons le graphique des salaires des ouvrirers \n", + "\n", + "En rouge : la courbe obtenue en représentant le salaire au cours du temps\n", + "\n", + "En bleu: la surface située en dessous de cette courbe (comme dans le graphique initial)" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(571240.0, 664742.0)" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ax2 = plt.subplot(111)\n", + "ax2.fill_between(data['Year_date'].values,data['Wages'],facecolor='lightblue')\n", + "ax2.plot(data['Year_date'].values,data['Wages'],'r')\n", + "ax2.xaxis_date()\n", + "ax2.set_xlim(data['Year_date'][1],data['Year_date'][len(data['Year_date'])])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Notons que pour ce graphique, les dernières valeurs du tableaux sont absente `NaN`, ce qui ne pose pas de problème dans le graphique, ces valeurs ne sont simplement pas plotée." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## B. mettre les deux graphique ensemble" + ] + }, + { + "cell_type": "code", + "execution_count": 286, + "metadata": {}, + "outputs": [], + "source": [ + "def gradientbars(bars,zorder):\n", + " grad = np.atleast_2d(np.linspace(0,1,300)).T\n", + " ax = bars[0].axes\n", + " lim = ax.get_xlim()+ax.get_ylim()\n", + " for bar in bars:\n", + " bar.set_zorder(1)\n", + " bar.set_facecolor('none')\n", + " x,y = bar.get_xy()\n", + " w, h = bar.get_width(), bar.get_height()\n", + " ax.imshow(grad, extent=[x,x+w,y,y+h], aspect='auto', zorder=zorder,cmap=cm.gray,alpha=0.75)\n", + " ax.axis(lim)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "cas avec un seul axe pour Y1 et Y2" + ] + }, + { + "cell_type": "code", + "execution_count": 287, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n", + " warnings.warn(message, mplDeprecation, stacklevel=1)\n", + "/opt/conda/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n", + " warnings.warn(message, mplDeprecation, stacklevel=1)\n", + "/opt/conda/lib/python3.6/site-packages/matplotlib/axes/_base.py:3152: UserWarning: Attempting to set identical left==right results\n", + "in singular transformations; automatically expanding.\n", + "left=664742.0, right=664742.0\n", + " 'left=%s, right=%s') % (left, right))\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib.ticker import MultipleLocator\n", + "from matplotlib.dates import HourLocator, MonthLocator, YearLocator\n", + "import matplotlib.cm as cm\n", + "\n", + "fig, ax1 = plt.subplots()\n", + "# paramètre des axes - avoir des données écrite à gauche et à droite\n", + "ax1.tick_params(axis='y', which='both', labelleft='on', labelright='on')\n", + "\n", + "# paramètre des grilles\n", + "ax1.grid(which='minor',axis='x',linestyle='--',color='k')\n", + "ax1.grid(which='major',axis='x',linestyle='-',color='k')\n", + "ax1.grid(which='major',axis='y',linestyle='--',color='k')\n", + "\n", + "# données en batonnet\n", + "bar=ax1.bar(data['Year_date'].values,data['Wheat'],color='dimgray',align='edge',width=data['period_width'])\n", + "gradientbars(bar,zorder=0)# gradiant de couleur\n", + "\n", + "#données en ligne et plage\n", + "ax1.fill_between(data['Year_date'].values,data['Wages'],facecolor='lightblue',zorder=0.5)\n", + "ax1.plot(data['Year_date'].values,data['Wages'],'r')\n", + "\n", + "# définitions des axes\n", + "#X\n", + "ax1.xaxis_date()\n", + "ax1.set_xlim(data['Year_date'][1],datetime.date(1830,1,1))\n", + "ax1.set_xlabel('5 years each division')\n", + "\n", + "#Y\n", + "ax1.set_ylim(0,100)\n", + "ax1.yaxis.set_major_locator(MultipleLocator(5))\n", + "ax1.xaxis.set_major_locator(YearLocator(50))\n", + "ax1.xaxis.set_minor_locator(YearLocator(5))\n", + "ax1.set_ylabel('Prize of the Quarter of Wheat in Shillings', color='k')\n", + "ax1.yaxis.set_label_position(\"right\")\n", + "\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Cas avec deux axes différents Y1 et Y2" + ] + }, + { + "cell_type": "code", + "execution_count": 290, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.6/site-packages/matplotlib/axes/_base.py:3152: UserWarning: Attempting to set identical left==right results\n", + "in singular transformations; automatically expanding.\n", + "left=664742.0, right=664742.0\n", + " 'left=%s, right=%s') % (left, right))\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax1 = plt.subplots()\n", + "ax2 = ax1.twinx() # deux axes Y différents pour un même X\n", + "\n", + "#Grille\n", + "ax1.grid(which='minor',axis='x',linestyle='--',color='k')\n", + "ax1.grid(which='major',axis='x',linestyle='-',color='k')\n", + "ax1.grid(which='major',axis='y',linestyle='--',color='k')\n", + "ax2.grid(which='major',axis='y',linestyle='--',color='k')\n", + "\n", + "# batonnet Y1\n", + "bar=ax1.bar(data['Year_date'].values,data['Wheat'],color='dimgray',align='edge',width=data['period_width'])\n", + "gradientbars(bar,zorder=1)\n", + "#ligne et surface Y2\n", + "ax2.fill_between(data['Year_date'].values,data['Wages'],facecolor='lightblue',alpha=0.8)\n", + "ax2.plot(data['Year_date'].values,data['Wages'],'r')\n", + "\n", + "# définitions des axes\n", + "# X\n", + "ax1.xaxis_date()\n", + "ax1.set_xlim(data['Year_date'][1],datetime.date(1830,1,1))\n", + "ax1.set_xlabel('Years')\n", + "ax1.xaxis.set_major_locator(YearLocator(50))\n", + "ax1.xaxis.set_minor_locator(YearLocator(5))\n", + "\n", + "#Y\n", + "ax1.set_ylim(0,100)\n", + "ax2.set_ylim(0,100)\n", + "ax1.yaxis.set_major_locator(MultipleLocator(5))\n", + "ax2.yaxis.set_major_locator(MultipleLocator(5))\n", + "ax1.set_ylabel('Wheat prices(shillings per quarter)', color='k')\n", + "ax2.set_ylabel('Weekly Wages(shillings per week)', color='k')\n", + "\n", + "plt.show()\n" ] }, {