gistfile1.txt

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1999-01-01    145\n",
       "1999-01-02    145\n",
       "1999-01-03    145\n",
       "1999-01-04    145\n",
       "1999-01-05    145\n",
       "Freq: D, Name: y, dtype: int64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import calendar\n",
    "import datetime\n",
    "import seaborn as sns\n",
    "import os\n",
    "import seaborn\n",
    "import matplotlib.pyplot as plt\n",
    "from fbprophet import Prophet\n",
    "import numpy as np\n",
    "from statsmodels.graphics.tsaplots import plot_acf,plot_pacf\n",
    "% matplotlib inline\n",
    "\n",
    "df=pd.read_csv('Discharge Article/Discharge_processed.csv')\n",
    "df.columns=['ds','y']\n",
    "     \n",
    "df.set_index('ds',inplace=True)\n",
    "ts = pd.Series(df['y'], index=pd.date_range(start=\"1999-01-01\", end=\"2018-07-31\"))\n",
    "ts.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018-07-27    1180\n",
       "2018-07-28    1524\n",
       "2018-07-29    1226\n",
       "2018-07-30     997\n",
       "2018-07-31     851\n",
       "Freq: D, Name: y, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.tail(5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
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   "language": "python",
   "name": "python3"
  },
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    "version": 3
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   "version": "3.6.5"
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 },
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}

Read-in.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1999-01-01    145\n",
       "1999-01-02    145\n",
       "1999-01-03    145\n",
       "1999-01-04    145\n",
       "1999-01-05    145\n",
       "Freq: D, Name: y, dtype: int64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import calendar\n",
    "import datetime\n",
    "import seaborn as sns\n",
    "import os\n",
    "import seaborn\n",
    "import matplotlib.pyplot as plt\n",
    "from fbprophet import Prophet\n",
    "import numpy as np\n",
    "from statsmodels.graphics.tsaplots import plot_acf,plot_pacf\n",
    "% matplotlib inline\n",
    "\n",
    "df=pd.read_csv('Discharge Article/Discharge_processed.csv')\n",
    "df.columns=['ds','y']\n",
    "     \n",
    "df.set_index('ds',inplace=True)\n",
    "ts = pd.Series(df['y'], index=pd.date_range(start=\"1999-01-01\", end=\"2018-07-31\"))\n",
    "ts.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018-07-27    1180\n",
       "2018-07-28    1524\n",
       "2018-07-29    1226\n",
       "2018-07-30     997\n",
       "2018-07-31     851\n",
       "Freq: D, Name: y, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.tail(5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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    "version": 3
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   "pygments_lexer": "ipython3",
   "version": "3.6.5"
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