Pandas- Reading Data.ipynb

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   "source": [
    "import pandas as pd"
   ]
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   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
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   "outputs": [],
   "source": [
    "some_data = pd.read_csv(\"dataset.csv\")"
   ]
  },
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   "execution_count": 67,
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date@ Data1@ Data2@Data3</th>\n",
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       "      <th>0</th>\n",
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       "  Date@ Data1@ Data2@Data3\n",
       "0         06/29/2018@2@3@4\n",
       "1         06/30/2018@2@2@2\n",
       "2         07/21/2018@8@8@8"
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    "some_data"
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   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "some_data = pd.read_csv(\"dataset.csv\",sep=\"@\")"
   ]
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   "execution_count": 69,
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       "      <th>Date</th>\n",
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       "         Date   Data1   Data2  Data3\n",
       "0  06/29/2018       2       3      4\n",
       "1  06/30/2018       2       2      2\n",
       "2  07/21/2018       8       8      8"
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  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "some_data = pd.read_csv(\"dataset.csv\",sep=\"@\",index_col=\"Date\",parse_dates=[\"Date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
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       "      <th>Date</th>\n",
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       "      <th>Data3</th>\n",
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      "text/plain": [
       "        Date   Data1   Data2  Data3\n",
       "0 2018-06-29       2       3      4\n",
       "1 2018-06-30       2       2      2\n",
       "2 2018-07-21       8       8      8"
      ]
     },
     "execution_count": 73,
     "metadata": {},
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   "source": [
    "some_data"
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  {
   "cell_type": "code",
   "execution_count": 74,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2018-06-29\n",
       "1   2018-06-30\n",
       "2   2018-07-21\n",
       "Name: Date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
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   "source": [
    "some_data.Date"
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   "execution_count": null,
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