examples/time-series.ipynb

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    "title = \"Stock Time Series\""
   ]
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   "source": [
    "import datetime\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "\n",
    "import plotly.graph_objects as go"
   ]
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   "source": [
    "start = datetime.datetime(2015, 1, 1)\n",
    "end = datetime.datetime(2019, 12, 1)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "df_1 = web.DataReader(\"AAPL\", \"yahoo\", start, end).reset_index()\n",
    "df_2 = web.DataReader(\"MSFT\", \"yahoo\", start, end).reset_index()\n",
    "df_3 = web.DataReader(\"AMZN\", \"yahoo\", start, end).reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Apple"
   ]
  },
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   "outputs": [],
   "source": [
    "margin = go.layout.Margin(l=20, r=20, b=20, t=30)"
   ]
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   "source": [
    "fig = go.Figure([go.Scatter(x=df_1['Date'], y=df_1['Close'])])\n",
    "fig.update_layout(margin=margin)\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Microsoft"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "chart"
    ]
   },
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    "fig = go.Figure([go.Scatter(x=df_2['Date'], y=df_2['Close'])])\n",
    "fig.update_layout(margin=margin)\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Amazon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "chart"
    ]
   },
   "outputs": [],
   "source": [
    "fig = go.Figure([go.Scatter(x=df_3['Date'], y=df_3['Close'])])\n",
    "fig.update_layout(margin=margin)\n",
    "fig"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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