495 lines
278 KiB
Plaintext
495 lines
278 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Quandl\n",
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"Plus d'infos:\n",
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"https://www.quandl.com/tools/python"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import quandl"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Les bases de QUANDL\n",
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"Cette requête obtient le prix du pétrole brut WTI du ministère américain de l'énergie:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"mydata = quandl.get(\"EIA/PET_RWTC_D\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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" Value\n",
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"Date \n",
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"1986-01-02 25.56\n",
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"1986-01-03 26.00\n",
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"1986-01-06 26.53\n",
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"1986-01-07 25.85\n",
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"1986-01-08 25.87"
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],
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"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>Value</th>\n </tr>\n <tr>\n <th>Date</th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1986-01-02</th>\n <td>25.56</td>\n </tr>\n <tr>\n <th>1986-01-03</th>\n <td>26.00</td>\n </tr>\n <tr>\n <th>1986-01-06</th>\n <td>26.53</td>\n </tr>\n <tr>\n <th>1986-01-07</th>\n <td>25.85</td>\n </tr>\n <tr>\n <th>1986-01-08</th>\n <td>25.87</td>\n </tr>\n </tbody>\n</table>\n</div>"
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},
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"metadata": {},
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"execution_count": 4
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}
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],
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"source": [
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"mydata.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"<AxesSubplot:xlabel='Date'>"
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]
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},
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"metadata": {},
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"execution_count": 5
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},
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{
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"output_type": "display_data",
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"data": {
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"text/plain": "<Figure size 864x432 with 1 Axes>",
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},
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"metadata": {
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"needs_background": "light"
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}
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}
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],
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"source": [
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"mydata.plot(figsize=(12,6))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Notez que vous devez connaître le \"code Quandl\" de chaque ensemble de données que vous téléchargez. Dans l'exemple ci-dessus, il s'agit de \"EIA/PET_RWTC_D\"."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Modifier les formats\n",
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"Vous pouvez obtenir les mêmes données dans un tableau NumPy:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"mydata = quandl.get(\"EIA/PET_RWTC_D\", returns=\"numpy\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Spécification des données\n",
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"\n",
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"Pour définir les dates de début et de fin:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"mydata = quandl.get(\"FRED/GDP\", start_date=\"2001-12-31\", end_date=\"2005-12-31\")"
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]
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|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" Value\n",
|
||
|
|
"Date \n",
|
||
|
|
"2002-01-01 10788.952\n",
|
||
|
|
"2002-04-01 10893.207\n",
|
||
|
|
"2002-07-01 10992.051\n",
|
||
|
|
"2002-10-01 11071.463\n",
|
||
|
|
"2003-01-01 11183.507"
|
||
|
|
],
|
||
|
|
"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>Value</th>\n </tr>\n <tr>\n <th>Date</th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>2002-01-01</th>\n <td>10788.952</td>\n </tr>\n <tr>\n <th>2002-04-01</th>\n <td>10893.207</td>\n </tr>\n <tr>\n <th>2002-07-01</th>\n <td>10992.051</td>\n </tr>\n <tr>\n <th>2002-10-01</th>\n <td>11071.463</td>\n </tr>\n <tr>\n <th>2003-01-01</th>\n <td>11183.507</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 8
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"mydata.head()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"mydata = quandl.get([\"NSE/OIL.1\", \"WIKI/AAPL.4\"])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" NSE/OIL - Open WIKI/AAPL - Close\n",
|
||
|
|
"Date \n",
|
||
|
|
"1980-12-12 NaN 28.75\n",
|
||
|
|
"1980-12-15 NaN 27.25\n",
|
||
|
|
"1980-12-16 NaN 25.25\n",
|
||
|
|
"1980-12-17 NaN 25.87\n",
|
||
|
|
"1980-12-18 NaN 26.63"
|
||
|
|
],
|
||
|
|
"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>NSE/OIL - Open</th>\n <th>WIKI/AAPL - Close</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>1980-12-12</th>\n <td>NaN</td>\n <td>28.75</td>\n </tr>\n <tr>\n <th>1980-12-15</th>\n <td>NaN</td>\n <td>27.25</td>\n </tr>\n <tr>\n <th>1980-12-16</th>\n <td>NaN</td>\n <td>25.25</td>\n </tr>\n <tr>\n <th>1980-12-17</th>\n <td>NaN</td>\n <td>25.87</td>\n </tr>\n <tr>\n <th>1980-12-18</th>\n <td>NaN</td>\n <td>26.63</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 10
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"mydata.head()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"### Limites d'utilisation\n",
|
||
|
|
"Le module Quandl Python est gratuit. Si vous souhaitez passer plus de 50 requêtes par jour, vous devrez créer un compte Quandl gratuit et définir votre clé API:"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# EXEMPLE\n",
|
||
|
|
"quandl.ApiConfig.api_key = \"A remplacer par votre clé API (API KEY)\"\n",
|
||
|
|
"mydata = quandl.get(\"FRED/GDP\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Codes de base de données\n",
|
||
|
|
"\n",
|
||
|
|
"Chaque base de données sur Quandl a un ID de base de données court (3 à 6 caractères). Par exemple :\n",
|
||
|
|
"\n",
|
||
|
|
"* CFTC Commitment of Traders Data: CFTC\n",
|
||
|
|
"* Actions américaines (Core US Stock Fundamentals): SF1\n",
|
||
|
|
"* Données économiques de la Réserve fédérale américaine (Federal Reserve Economic Data): FRED\n",
|
||
|
|
"\n",
|
||
|
|
"Chaque base de données contient de nombreux ensembles de données. Les ensembles de données ont leurs propres ID qui sont ajoutés à l'ID de leur base de données mère, comme ceci :\n",
|
||
|
|
"\n",
|
||
|
|
"* CFTC pour le blé: CFTC/W_F_ALL\n",
|
||
|
|
"* Capitalisation d'Apple: SF1/AAPL_MARKETCAP\n",
|
||
|
|
"* Taux de chômage américain: FRED/UNRATE\n",
|
||
|
|
"\n",
|
||
|
|
"Vous pouvez télécharger tous les codes d'un ensemble de données dans une base de données en ue seule requête API, en ajoutant '/codes' à votre demande de base de données. La requête retourne un fichier ZIP contenant un CSV.\n",
|
||
|
|
"\n",
|
||
|
|
"### Bases de Données\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"Chaque code Quandl comporte 2 parties: le code de la base de données (\"WIKI\") qui spécifie d'où proviennent les données, et le code du jeu de données (\"FB\") qui identifie la série temporelle spécifique que vous voulez.\n",
|
||
|
|
"\n",
|
||
|
|
"Vous pouvez trouver les codes Quandl sur leur site Web, en utilisant leur navigateur de données.\n",
|
||
|
|
"\n",
|
||
|
|
"https://www.quandl.com/search"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"source": [
|
||
|
|
"# POUR LES ACTIONS (STOCKS)"
|
||
|
|
],
|
||
|
|
"cell_type": "code",
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 12,
|
||
|
|
"outputs": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"mydata = quandl.get('WIKI/FB',start_date='2015-01-01',end_date='2017-01-01')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" Open High Low Close Volume Ex-Dividend \\\n",
|
||
|
|
"Date \n",
|
||
|
|
"2015-01-02 78.58 78.9300 77.700 78.450 18177475.0 0.0 \n",
|
||
|
|
"2015-01-05 77.98 79.2455 76.860 77.190 26452191.0 0.0 \n",
|
||
|
|
"2015-01-06 77.23 77.5900 75.365 76.150 27399288.0 0.0 \n",
|
||
|
|
"2015-01-07 76.76 77.3600 75.820 76.150 22045333.0 0.0 \n",
|
||
|
|
"2015-01-08 76.74 78.2300 76.080 78.175 23960953.0 0.0 \n",
|
||
|
|
"\n",
|
||
|
|
" Split Ratio Adj. Open Adj. High Adj. Low Adj. Close \\\n",
|
||
|
|
"Date \n",
|
||
|
|
"2015-01-02 1.0 78.58 78.9300 77.700 78.450 \n",
|
||
|
|
"2015-01-05 1.0 77.98 79.2455 76.860 77.190 \n",
|
||
|
|
"2015-01-06 1.0 77.23 77.5900 75.365 76.150 \n",
|
||
|
|
"2015-01-07 1.0 76.76 77.3600 75.820 76.150 \n",
|
||
|
|
"2015-01-08 1.0 76.74 78.2300 76.080 78.175 \n",
|
||
|
|
"\n",
|
||
|
|
" Adj. Volume \n",
|
||
|
|
"Date \n",
|
||
|
|
"2015-01-02 18177475.0 \n",
|
||
|
|
"2015-01-05 26452191.0 \n",
|
||
|
|
"2015-01-06 27399288.0 \n",
|
||
|
|
"2015-01-07 22045333.0 \n",
|
||
|
|
"2015-01-08 23960953.0 "
|
||
|
|
],
|
||
|
|
"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>Open</th>\n <th>High</th>\n <th>Low</th>\n <th>Close</th>\n <th>Volume</th>\n <th>Ex-Dividend</th>\n <th>Split Ratio</th>\n <th>Adj. Open</th>\n <th>Adj. High</th>\n <th>Adj. Low</th>\n <th>Adj. Close</th>\n <th>Adj. 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 <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>2015-01-02</th>\n <td>78.58</td>\n <td>78.9300</td>\n <td>77.700</td>\n <td>78.450</td>\n <td>18177475.0</td>\n <td>0.0</td>\n <td>1.0</td>\n <td>78.58</td>\n <td>78.9300</td>\n <td>77.700</td>\n <td>78.450</td>\n <td>18177475.0</td>\n </tr>\n <tr>\n <th>2015-01-05</th>\n <td>77.98</td>\n <td>79.2455</td>\n <td>76.860</td>\n <td>77.190</td>\n <td>26452191.0</td>\n <td>0.0</td>\n <td>1.0</td>\n <td>77.98</td>\n <td>79.2455</td>\n <td>76.860</td>\n <td>77.190</td>\n <td>26452191.0</td>\n </tr>\n <tr>\n <th>2015-01-06</th>\n <td>77.23</td>\n <td>77.5900</td>\n <td>75.365</td>\n <td>76.150</td>\n <td>27399288.0</td>\n <td>0.0</td>\n <td>1.0</td>\n <td>77.23</td>\n <td>77.5900</td>\n <td>75.365</td>\n <td>76.150</td>\n <td>27399288.0</td>\n </tr>\n <tr>\n <th>2015-01-07</th>\n <td>76.76</td>\n <td>77.3600</td>\n <td>75.820</td>\n <td>76.150</td>\n <td>22045333.0</td>\n <td>0.0</td>\n <td>1.0</td>\n <td>76.76</td>\n <td>77.3600</td>\n <td>75.820</td>\n <td>76.150</td>\n <td>22045333.0</td>\n </tr>\n <tr>\n <th>2015-01-08</th>\n <td>76.74</td>\n <td>78.2300</td>\n <td>76.080</td>\n <td>78.175</td>\n <td>23960953.0</td>\n <td>0.0</td>\n <td>1.0</td>\n <td>76.74</td>\n <td>78.2300</td>\n <td>76.080</td>\n <td>78.175</td>\n <td>23960953.0</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 14
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"mydata.head()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"mydata = quandl.get('WIKI/FB.1',start_date='2015-01-01',end_date='2017-01-01')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 16,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" Open\n",
|
||
|
|
"Date \n",
|
||
|
|
"2015-01-02 78.58\n",
|
||
|
|
"2015-01-05 77.98\n",
|
||
|
|
"2015-01-06 77.23\n",
|
||
|
|
"2015-01-07 76.76\n",
|
||
|
|
"2015-01-08 76.74"
|
||
|
|
],
|
||
|
|
"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>Open</th>\n </tr>\n <tr>\n <th>Date</th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>2015-01-02</th>\n <td>78.58</td>\n </tr>\n <tr>\n <th>2015-01-05</th>\n <td>77.98</td>\n </tr>\n <tr>\n <th>2015-01-06</th>\n <td>77.23</td>\n </tr>\n <tr>\n <th>2015-01-07</th>\n <td>76.76</td>\n </tr>\n <tr>\n <th>2015-01-08</th>\n <td>76.74</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 16
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"mydata.head()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"mydata = quandl.get('WIKI/FB.7',start_date='2015-01-01',end_date='2017-01-01')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" Split Ratio\n",
|
||
|
|
"Date \n",
|
||
|
|
"2015-01-02 1.0\n",
|
||
|
|
"2015-01-05 1.0\n",
|
||
|
|
"2015-01-06 1.0\n",
|
||
|
|
"2015-01-07 1.0\n",
|
||
|
|
"2015-01-08 1.0"
|
||
|
|
],
|
||
|
|
"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>Split Ratio</th>\n </tr>\n <tr>\n <th>Date</th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>2015-01-02</th>\n <td>1.0</td>\n </tr>\n <tr>\n <th>2015-01-05</th>\n <td>1.0</td>\n </tr>\n <tr>\n <th>2015-01-06</th>\n <td>1.0</td>\n </tr>\n <tr>\n <th>2015-01-07</th>\n <td>1.0</td>\n </tr>\n <tr>\n <th>2015-01-08</th>\n <td>1.0</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 18
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"mydata.head()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"### Exemple Prix Logement\n",
|
||
|
|
"\n",
|
||
|
|
"**Zillow Home Value Index (Metro: Indice Zillow des loyers - Tous les logements - San Francisco, CA**\n",
|
||
|
|
"\n",
|
||
|
|
"L'indice Zillow 'Home Value Index' est l'estimation par Zillow de la valeur marchande médiane de l'indice locatif Zillow pour toutes les maisons dans la zone de San Francisco, CA. Ces données sont calculées par Zillow Real Estate Research (www.zillow.com/research) à partir de leur base de données de 110 millions de foyers."
|
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]
|
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},
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{
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||
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"cell_type": "code",
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"execution_count": 19,
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||
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"metadata": {},
|
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"outputs": [],
|
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"source": [
|
||
|
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"houses = quandl.get('ZILLOW/M11_ZRIAH')"
|
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|
]
|
||
|
|
},
|
||
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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||
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"outputs": [
|
||
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{
|
||
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"output_type": "execute_result",
|
||
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"data": {
|
||
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"text/plain": [
|
||
|
|
" Value\n",
|
||
|
|
"Date \n",
|
||
|
|
"2010-11-30 2454.0\n",
|
||
|
|
"2010-12-31 2461.0\n",
|
||
|
|
"2011-01-31 2484.0\n",
|
||
|
|
"2011-02-28 2506.0\n",
|
||
|
|
"2011-03-31 2526.0"
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],
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"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>Value</th>\n </tr>\n <tr>\n <th>Date</th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>2010-11-30</th>\n <td>2454.0</td>\n </tr>\n <tr>\n <th>2010-12-31</th>\n <td>2461.0</td>\n </tr>\n <tr>\n <th>2011-01-31</th>\n <td>2484.0</td>\n </tr>\n <tr>\n <th>2011-02-28</th>\n <td>2506.0</td>\n </tr>\n <tr>\n <th>2011-03-31</th>\n <td>2526.0</td>\n </tr>\n </tbody>\n</table>\n</div>"
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},
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"metadata": {},
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}
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],
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"source": [
|
||
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"houses.head()"
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]
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},
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{
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"outputs": [
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{
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