diff --git a/_doc/notebooks/td2a/Python-Logique-SQL.ipynb b/_doc/notebooks/td2a/Python-Logique-SQL.ipynb
index 54948e5ae..6be8f029d 100644
--- a/_doc/notebooks/td2a/Python-Logique-SQL.ipynb
+++ b/_doc/notebooks/td2a/Python-Logique-SQL.ipynb
@@ -1,375 +1,375 @@
{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Python et la logique SQL"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Python et la logique SQL"
+ ]
+ },
{
- "data": {
- "text/html": [
- "\n",
- ""
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ ""
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
],
- "text/plain": [
- ""
+ "source": [
+ "from pyquickhelper.ipythonhelper import add_notebook_menu\n",
+ "add_notebook_menu()"
]
- },
- "execution_count": 2,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "from pyquickhelper.ipythonhelper import add_notebook_menu\n",
- "add_notebook_menu()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "SQL vous avez tous ça dans le sang. \n",
- "\n",
- "SQL permet de créer des tables, de rechercher, d'ajouter, de modifier ou de supprimer des données dans les bases de données. Un peu ce que vous faites tous les jours. \n",
- "\n",
- "Sauf que SQL, c'est un langage pas un logiciel. \n",
- "\n",
- "Les instructions SQL s'écrivent d'une manière qui ressemble à celle de phrases ordinaires en anglais. Cette ressemblance voulue vise à faciliter l'apprentissage et la lecture. \n",
- "\n",
- "Comme avec STATA, on donne des ordres dans le programme, on ne parle plus de méthode ou d'objet comme dans Python. \n",
- "\n",
- "Là le tric, c'est d'utiliser le langage SQL dans le framework Python : mal à la tête ? ça va bien se passer..."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Exemple"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "#Exemple d'utilisation d'un langage type SQL \n",
- "# site avec des exemples http://www.w3schools.com/sql/sql_insert_into_select.asp\n",
- "\n",
- "import sqlite3\n",
- "\n",
- "# on crée une base de données SQL vide\n",
- "CreateDataBase = sqlite3.connect('MyDataBase.db')\n",
- "\n",
- "QueryCurs = CreateDataBase.cursor()\n",
- "\n",
- "# on va créer une table qui contient plusieurs variables de format différents\n",
- "# id sera la clé primaire de la base\n",
- "# Nom, Rue, Ville, Region seront du text\n",
- "# Note sera un réel\n",
- "\n",
- "def CreateTable(nom_bdd):\n",
- " QueryCurs.execute('''CREATE TABLE ''' + nom_bdd + '''\n",
- " (id INTEGER PRIMARY KEY, Name TEXT,City TEXT, Country TEXT, Price REAL)''')\n",
- "\n",
- " \n",
- "def AddEntry(nom_bdd, Nom,Ville,Region,Note):\n",
- " QueryCurs.execute('''INSERT INTO ''' + nom_bdd + ''' \n",
- " (Name,City,Country,Price) VALUES (?,?,?,?)''',(Nom,Ville,Region,Note))\n",
- "\n",
- "CreateTable('Clients')\n",
- "\n",
- "AddEntry('Clients','Toto','Munich','Germany',5.2)\n",
- "AddEntry('Clients','Bill','Berlin','Germany',2.3)\n",
- "AddEntry('Clients','Tom','Lille','France',7.8)\n",
- "AddEntry('Clients','Marvin','Miami','USA',15.2)\n",
- "\n",
- "# on va \"commit\" c'est à dire qu'on va valider la transaction. \n",
- "# on va envoyer ses modifications locales vers le référentiel central - la base de données SQL\n",
- "\n",
- "CreateDataBase.commit()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "collapsed": false,
- "scrolled": true
- },
- "outputs": [
+ },
{
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "[(2, 'Bill', 'Berlin', 'Germany', 2.3)]\n",
- " \n"
- ]
- }
- ],
- "source": [
- "QueryCurs.execute('SELECT * FROM Clients WHERE City==\"Berlin\"')\n",
- "Values = QueryCurs.fetchall()\n",
- "print(Values)\n",
- "print(type(Values),type(Values[0]))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Les commandes les plus fréquentes : \n",
- "\n",
- "Parmi les commandes SQL les plus utilisées, il y a : \n",
- "\n",
- "- SELECT - extraction d'une sélection dans une table\n",
- "- UPDATE \n",
- "- DELETE \n",
- "- INSERT INTO \n",
- "- CREATE DATABASE\n",
- "- ALTER DATABASE\n",
- "- CREATE TABLE\n",
- "- DROP TABLE \n",
- "- CREATE INDEX - créer une clé\n",
- "- DROP INDEX \n",
- "- JOIN\n",
- " \n",
- "Pour écrire des conditions : \n",
- "\n",
- "- on utilise AND et OR comme dans STATA\n",
- "- BETWEEN value1 and value 2\n",
- " \n",
- " "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "SQL vous avez tous \u00e7a dans le sang. \n",
+ "\n",
+ "SQL permet de cr\u00e9er des tables, de rechercher, d'ajouter, de modifier ou de supprimer des donn\u00e9es dans les bases de donn\u00e9es. Un peu ce que vous faites tous les jours. \n",
+ "\n",
+ "Sauf que SQL, c'est un langage pas un logiciel. \n",
+ "\n",
+ "Les instructions SQL s'\u00e9crivent d'une mani\u00e8re qui ressemble \u00e0 celle de phrases ordinaires en anglais. Cette ressemblance voulue vise \u00e0 faciliter l'apprentissage et la lecture. \n",
+ "\n",
+ "Comme avec STATA, on donne des ordres dans le programme, on ne parle plus de m\u00e9thode ou d'objet comme dans Python. \n",
+ "\n",
+ "L\u00e0 le tric, c'est d'utiliser le langage SQL dans le framework Python : mal \u00e0 la t\u00eate ? \u00e7a va bien se passer..."
+ ]
+ },
{
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "[(1, 'Toto', 'Munich', 'Germany', 5.2), (2, 'Bill', 'Berlin', 'Germany', 2.3)]\n",
- "[(2, 'Bill', 'Berlin', 'Germany', 2.3)]\n",
- "[(3, 'Tom', 'Lille', 'France', 7.8), (4, 'Marvin', 'Miami', 'USA', 15.2)]\n"
- ]
- }
- ],
- "source": [
- "QueryCurs.execute('SELECT * FROM Clients WHERE Country == \"Germany\"')\n",
- "print(QueryCurs.fetchall())\n",
- "QueryCurs.execute('SELECT * FROM Clients WHERE City==\"Berlin\" AND Country == \"Germany\"')\n",
- "print(QueryCurs.fetchall())\n",
- "QueryCurs.execute('SELECT * FROM Clients WHERE Price BETWEEN 7 AND 20')\n",
- "print(QueryCurs.fetchall())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Enregistrer une table SQL sous un autre format \n",
- "\n",
- "On utilise le package csv, l'option 'w' pour 'write'. \n",
- "\n",
- "On crée l'objet \"writer\", qui vient du package csv.\n",
- "\n",
- "Cet objet a deux méthodes : \n",
- "- writerow pour les noms de colonnes : une liste\n",
- "- writerows pour les lignes : un ensemble de liste\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {
- "collapsed": false
- },
- "outputs": [],
- "source": [
- "data = QueryCurs.execute('SELECT * FROM Clients')\n",
- "\n",
- "import csv\n",
- "\n",
- "file = open('output.csv', 'w')\n",
- "writer = csv.writer(file)\n",
- "writer.writerow(['id','Name','City','Country','Price'])\n",
- "writer.writerows(data)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Suppression d'une table"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "collapsed": false
- },
- "outputs": [
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Exemple"
+ ]
+ },
{
- "data": {
- "text/plain": [
- ""
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "#Exemple d'utilisation d'un langage type SQL \n",
+ "# site avec des exemples http://www.w3schools.com/sql/sql_insert_into_select.asp\n",
+ "\n",
+ "import sqlite3\n",
+ "\n",
+ "# on cr\u00e9e une base de donn\u00e9es SQL vide\n",
+ "CreateDataBase = sqlite3.connect('MyDataBase.db')\n",
+ "\n",
+ "QueryCurs = CreateDataBase.cursor()\n",
+ "\n",
+ "# on va cr\u00e9er une table qui contient plusieurs variables de format diff\u00e9rents\n",
+ "# id sera la cl\u00e9 primaire de la base\n",
+ "# Nom, Rue, Ville, Region seront du text\n",
+ "# Note sera un r\u00e9el\n",
+ "\n",
+ "def CreateTable(nom_bdd):\n",
+ " QueryCurs.execute('''CREATE TABLE ''' + nom_bdd + '''\n",
+ " (id INTEGER PRIMARY KEY, Name TEXT,City TEXT, Country TEXT, Price REAL)''')\n",
+ "\n",
+ " \n",
+ "def AddEntry(nom_bdd, Nom,Ville,Region,Note):\n",
+ " QueryCurs.execute('''INSERT INTO ''' + nom_bdd + ''' \n",
+ " (Name,City,Country,Price) VALUES (?,?,?,?)''',(Nom,Ville,Region,Note))\n",
+ "\n",
+ "CreateTable('Clients')\n",
+ "\n",
+ "AddEntry('Clients','Toto','Munich','Germany',5.2)\n",
+ "AddEntry('Clients','Bill','Berlin','Germany',2.3)\n",
+ "AddEntry('Clients','Tom','Lille','France',7.8)\n",
+ "AddEntry('Clients','Marvin','Miami','USA',15.2)\n",
+ "\n",
+ "# on va \"commit\" c'est \u00e0 dire qu'on va valider la transaction. \n",
+ "# on va envoyer ses modifications locales vers le r\u00e9f\u00e9rentiel central - la base de donn\u00e9es SQL\n",
+ "\n",
+ "CreateDataBase.commit()"
]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[(2, 'Bill', 'Berlin', 'Germany', 2.3)]\n",
+ " \n"
+ ]
+ }
+ ],
+ "source": [
+ "QueryCurs.execute('SELECT * FROM Clients WHERE City==\"Berlin\"')\n",
+ "Values = QueryCurs.fetchall()\n",
+ "print(Values)\n",
+ "print(type(Values),type(Values[0]))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Les commandes les plus fr\u00e9quentes : \n",
+ "\n",
+ "Parmi les commandes SQL les plus utilis\u00e9es, il y a : \n",
+ "\n",
+ "- SELECT - extraction d'une s\u00e9lection dans une table\n",
+ "- UPDATE \n",
+ "- DELETE \n",
+ "- INSERT INTO \n",
+ "- CREATE DATABASE\n",
+ "- ALTER DATABASE\n",
+ "- CREATE TABLE\n",
+ "- DROP TABLE \n",
+ "- CREATE INDEX - cr\u00e9er une cl\u00e9\n",
+ "- DROP INDEX \n",
+ "- JOIN\n",
+ " \n",
+ "Pour \u00e9crire des conditions : \n",
+ "\n",
+ "- on utilise AND et OR comme dans STATA\n",
+ "- BETWEEN value1 and value 2\n",
+ " \n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[(1, 'Toto', 'Munich', 'Germany', 5.2), (2, 'Bill', 'Berlin', 'Germany', 2.3)]\n",
+ "[(2, 'Bill', 'Berlin', 'Germany', 2.3)]\n",
+ "[(3, 'Tom', 'Lille', 'France', 7.8), (4, 'Marvin', 'Miami', 'USA', 15.2)]\n"
+ ]
+ }
+ ],
+ "source": [
+ "QueryCurs.execute('SELECT * FROM Clients WHERE Country == \"Germany\"')\n",
+ "print(QueryCurs.fetchall())\n",
+ "QueryCurs.execute('SELECT * FROM Clients WHERE City==\"Berlin\" AND Country == \"Germany\"')\n",
+ "print(QueryCurs.fetchall())\n",
+ "QueryCurs.execute('SELECT * FROM Clients WHERE Price BETWEEN 7 AND 20')\n",
+ "print(QueryCurs.fetchall())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Enregistrer une table SQL sous un autre format \n",
+ "\n",
+ "On utilise le package csv, l'option 'w' pour 'write'. \n",
+ "\n",
+ "On cr\u00e9e l'objet \"writer\", qui vient du package csv.\n",
+ "\n",
+ "Cet objet a deux m\u00e9thodes : \n",
+ "- writerow pour les noms de colonnes : une liste\n",
+ "- writerows pour les lignes : un ensemble de liste\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "data = QueryCurs.execute('SELECT * FROM Clients')\n",
+ "\n",
+ "import csv\n",
+ "\n",
+ "file = open('output.csv', 'w')\n",
+ "writer = csv.writer(file)\n",
+ "writer.writerow(['id','Name','City','Country','Price'])\n",
+ "writer.writerows(data)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Suppression d'une table"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "QueryCurs.execute('''DROP TABLE Clients''')\n",
+ "#QueryCurs.close()"
+ ]
+ }
+ ],
+ "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": "3.5.0"
}
- ],
- "source": [
- "QueryCurs.execute('''DROP TABLE Clients''')\n",
- "#QueryCurs.close()"
- ]
- }
- ],
- "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": "3.5.0"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
\ No newline at end of file
diff --git a/_doc/notebooks/td2a/ml_timeseries_base.ipynb b/_doc/notebooks/td2a/ml_timeseries_base.ipynb
new file mode 100644
index 000000000..7a5a5a5b4
--- /dev/null
+++ b/_doc/notebooks/td2a/ml_timeseries_base.ipynb
@@ -0,0 +1,1395 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Timeseries et machine learning"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import matplotlib.pyplot as plt\n",
+ "plt.style.use('ggplot')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Les s\u00e9ries temporelles diff\u00e8rent des probl\u00e8mes de machine learning classique car les observations ne sont pas ind\u00e9pendantes. Ce notebook pr\u00e9sente quelques traitements classiques et une fa\u00e7on assez simple d'appliquer un traitement de machine learning."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ ""
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from pyquickhelper.ipythonhelper import add_notebook_menu\n",
+ "add_notebook_menu()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Je ne vais pas refaire ici un cours sur les s\u00e9ries temporelles. Quelques r\u00e9f\u00e9rences pour approfondir :\n",
+ " \n",
+ "* [Diff\u00e9rencier (ind\u00e9finiment) les s\u00e9ries temporelles ?](https://freakonometrics.hypotheses.org/1876)\n",
+ "* [Cours de S\u00e9ries Temporelles - Arthur Charpentier](http://cours.mido.dauphine.fr/st/cours.html)\n",
+ "* [Mod\u00e8les de pr\u00e9vision S\u00e9ries temporelles](http://freakonometrics.free.fr/M1_TS_2015.pdf)\n",
+ "* [COURS DE SERIES TEMPORELLES THEORIE ET APPLICATIONS](https://perso.univ-rennes1.fr/arthur.charpentier/TS1.pdf)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Donn\u00e9es"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Prenons comme exemple une s\u00e9rie venant de [Google Trend](https://www.google.com/trends/), par exemple le terme [macron](https://www.google.com/trends/explore?geo=FR&q=macron) pris sur la France."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Week | \n",
+ " macron | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 256 | \n",
+ " 2016-08-21 | \n",
+ " 9 | \n",
+ "
\n",
+ " \n",
+ " | 257 | \n",
+ " 2016-08-28 | \n",
+ " 98 | \n",
+ "
\n",
+ " \n",
+ " | 258 | \n",
+ " 2016-09-04 | \n",
+ " 34 | \n",
+ "
\n",
+ " \n",
+ " | 259 | \n",
+ " 2016-09-11 | \n",
+ " 17 | \n",
+ "
\n",
+ " \n",
+ " | 260 | \n",
+ " 2016-09-18 | \n",
+ " 13 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Week | \n",
+ " chocolat | \n",
+ " diff | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " 2011-09-25 | \n",
+ " 31 | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " 2011-10-02 | \n",
+ " 34 | \n",
+ " 3.0 | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " 2011-10-09 | \n",
+ " 38 | \n",
+ " 4.0 | \n",
+ "
\n",
+ " \n",
+ " | 258 | \n",
+ " 2016-09-04 | \n",
+ " 32 | \n",
+ " 1.0 | \n",
+ "
\n",
+ " \n",
+ " | 259 | \n",
+ " 2016-09-11 | \n",
+ " 35 | \n",
+ " 3.0 | \n",
+ "
\n",
+ " \n",
+ " | 260 | \n",
+ " 2016-09-18 | \n",
+ " 36 | \n",
+ " 1.0 | \n",
+ "
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+ " \n",
+ "
\n",
+ "
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+ "
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+ " \n",
+ " \n",
+ " | \n",
+ " Week | \n",
+ " chocolat | \n",
+ " diff | \n",
+ " lag1 | \n",
+ " lag2 | \n",
+ " lag3 | \n",
+ " lag4 | \n",
+ " lag5 | \n",
+ " lag6 | \n",
+ " lag7 | \n",
+ " lag8 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " 2011-09-25 | \n",
+ " 31 | \n",
+ " NaN | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " 2011-10-02 | \n",
+ " 34 | \n",
+ " 3.0 | \n",
+ " NaN | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " 2011-10-09 | \n",
+ " 38 | \n",
+ " 4.0 | \n",
+ " 3.0 | \n",
+ " NaN | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ "
\n",
+ " \n",
+ " | 3 | \n",
+ " 2011-10-16 | \n",
+ " 45 | \n",
+ " 7.0 | \n",
+ " 4.0 | \n",
+ " 3.0 | \n",
+ " NaN | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ "
\n",
+ " \n",
+ " | 4 | \n",
+ " 2011-10-23 | \n",
+ " 44 | \n",
+ " -1.0 | \n",
+ " 7.0 | \n",
+ " 4.0 | \n",
+ " 3.0 | \n",
+ " NaN | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ " 0.0 | \n",
+ "
\n",
+ " \n",
+ " | 256 | \n",
+ " 2016-08-21 | \n",
+ " 33 | \n",
+ " -2.0 | \n",
+ " 0.0 | \n",
+ " 1.0 | \n",
+ " 1.0 | \n",
+ " 3.0 | \n",
+ " -4.0 | \n",
+ " -1.0 | \n",
+ " -4.0 | \n",
+ " 1.0 | \n",
+ "
\n",
+ " \n",
+ " | 257 | \n",
+ " 2016-08-28 | \n",
+ " 31 | \n",
+ " -2.0 | \n",
+ " -2.0 | \n",
+ " 0.0 | \n",
+ " 1.0 | \n",
+ " 1.0 | \n",
+ " 3.0 | \n",
+ " -4.0 | \n",
+ " -1.0 | \n",
+ " -4.0 | \n",
+ "
\n",
+ " \n",
+ " | 258 | \n",
+ " 2016-09-04 | \n",
+ " 32 | \n",
+ " 1.0 | \n",
+ " -2.0 | \n",
+ " -2.0 | \n",
+ " 0.0 | \n",
+ " 1.0 | \n",
+ " 1.0 | \n",
+ " 3.0 | \n",
+ " -4.0 | \n",
+ " -1.0 | \n",
+ "
\n",
+ " \n",
+ " | 259 | \n",
+ " 2016-09-11 | \n",
+ " 35 | \n",
+ " 3.0 | \n",
+ " 1.0 | \n",
+ " -2.0 | \n",
+ " -2.0 | \n",
+ " 0.0 | \n",
+ " 1.0 | \n",
+ " 1.0 | \n",
+ " 3.0 | \n",
+ " -4.0 | \n",
+ "
\n",
+ " \n",
+ " | 260 | \n",
+ " 2016-09-18 | \n",
+ " 36 | \n",
+ " 1.0 | \n",
+ " 3.0 | \n",
+ " 1.0 | \n",
+ " -2.0 | \n",
+ " -2.0 | \n",
+ " 0.0 | \n",
+ " 1.0 | \n",
+ " 1.0 | \n",
+ " 3.0 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "