work.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>testname</th>\n",
       "      <th>pname1</th>\n",
       "      <th>pname2</th>\n",
       "      <th>pname3</th>\n",
       "      <th>pname4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  testname  pname1  pname2  pname3  pname4\n",
       "0        a       1       2       7       8\n",
       "1        b       3       4       9      10\n",
       "2        c       5       6      11      12"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a dataframe \n",
    "import pandas as pd \n",
    "df = pd.DataFrame({'testname':{0:'a',1:'b',2:'c'},\n",
    "                   'pname1':{0:1,1:3,2:5},\n",
    "                   'pname2':{0:2,1:4,2:6},\n",
    "                   'pname3':{0:7,1:9,2:11},\n",
    "                   'pname4':{0:8,1:10,2:12}})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 5)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape # rows,columns # wide table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# wide table --> lengthy table melt(unpivot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=pd.melt(\n",
    "    frame=df,\n",
    "    id_vars=\"testname\",\n",
    "    value_vars=[\"pname1\",\"pname2\",\"pname3\",\"pname4\"],\n",
    "    var_name=\"pname\",\n",
    "    value_name='test_results')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12, 3)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.shape #12 rows 3 columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2=pd.pivot(data=df1, index=\"testname\", columns=\"pname\", values=\"test_results\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>testname</th>\n",
       "      <th>pname1</th>\n",
       "      <th>pname2</th>\n",
       "      <th>pname3</th>\n",
       "      <th>pname4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  testname  pname1  pname2  pname3  pname4\n",
       "0        a       1       2       7       8\n",
       "1        b       3       4       9      10\n",
       "2        c       5       6      11      12"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>pname</th>\n",
       "      <th>pname1</th>\n",
       "      <th>pname2</th>\n",
       "      <th>pname3</th>\n",
       "      <th>pname4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>testname</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "pname     pname1  pname2  pname3  pname4\n",
       "testname                                \n",
       "a              1       2       7       8\n",
       "b              3       4       9      10\n",
       "c              5       6      11      12"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Concat (append)\n",
    "# axis =0 > row wise append\n",
    "# axis = 1 > column wise append"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=pd.read_csv(\"data/Py_cleaning_pivot_concat1.csv\")\n",
    "df2=pd.read_csv(\"data/Py_cleaning_pivot_concat2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>date</th>\n",
       "      <th>element</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmax</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmin</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date element  value\n",
       "0  2017-09-15    tmax     30\n",
       "1  2017-09-15    tmin     14"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>date</th>\n",
       "      <th>element</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmax</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmin</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date element  value\n",
       "0  2017-09-16    tmax     32\n",
       "1  2017-09-16    tmin     17"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>date</th>\n",
       "      <th>element</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmax</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmin</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmax</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmin</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date element  value\n",
       "0  2017-09-15    tmax     30\n",
       "1  2017-09-15    tmin     14\n",
       "0  2017-09-16    tmax     32\n",
       "1  2017-09-16    tmin     17"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([df1,df2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>date</th>\n",
       "      <th>element</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmax</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmin</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmax</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmin</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date element  value\n",
       "0  2017-09-15    tmax     30\n",
       "1  2017-09-15    tmin     14\n",
       "2  2017-09-16    tmax     32\n",
       "3  2017-09-16    tmin     17"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([df1,df2],ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>date</th>\n",
       "      <th>element</th>\n",
       "      <th>value</th>\n",
       "      <th>date</th>\n",
       "      <th>element</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmax</td>\n",
       "      <td>30</td>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmax</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>tmin</td>\n",
       "      <td>14</td>\n",
       "      <td>2017-09-16</td>\n",
       "      <td>tmin</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date element  value        date element  value\n",
       "0  2017-09-15    tmax     30  2017-09-16    tmax     32\n",
       "1  2017-09-15    tmin     14  2017-09-16    tmin     17"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([df1,df2],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# glob(now we learn)\n",
    "# shutill"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mType:\u001b[0m        module\n",
       "\u001b[1;31mString form:\u001b[0m <module 'glob' from 'C:\\\\Users\\\\ramreddymyla\\\\Anaconda3\\\\envs\\\\dl\\\\lib\\\\glob.py'>\n",
       "\u001b[1;31mFile:\u001b[0m        c:\\users\\ramreddymyla\\anaconda3\\envs\\dl\\lib\\glob.py\n",
       "\u001b[1;31mDocstring:\u001b[0m   Filename globbing utility.\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "glob?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mglob\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mglob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpathname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrecursive\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Return a list of paths matching a pathname pattern.\n",
       "\n",
       "The pattern may contain simple shell-style wildcards a la\n",
       "fnmatch. However, unlike fnmatch, filenames starting with a\n",
       "dot are special cases that are not matched by '*' and '?'\n",
       "patterns.\n",
       "\n",
       "If recursive is true, the pattern '**' will match any files and\n",
       "zero or more directories and subdirectories.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\users\\ramreddymyla\\anaconda3\\envs\\dl\\lib\\glob.py\n",
       "\u001b[1;31mType:\u001b[0m      function\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "glob.glob?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['data\\\\emp_part1.csv', 'data\\\\emp_part2.csv']"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glob.glob(\"data/emp_part?.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "rs = [] # list sequence \n",
    "for i in range(len(glob.glob(\"data/emp_part?.csv\"))):\n",
    "    rs.append(pd.read_csv(glob.glob(\"data/emp_part?.csv\")[i]))\n",
    "final_df=pd.concat(rs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EMPNO</th>\n",
       "      <th>ENAME</th>\n",
       "      <th>JOB</th>\n",
       "      <th>MGR</th>\n",
       "      <th>HIREDATE</th>\n",
       "      <th>SAL</th>\n",
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       "      <td>7693</td>\n",
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       "      <td>22-FEB-81</td>\n",
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       "      <td>02-APR-81</td>\n",
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       "      <td>MARTIN</td>\n",
       "      <td>SALESMAN</td>\n",
       "      <td>7698.0</td>\n",
       "      <td>28-SEP-81</td>\n",
       "      <td>1250</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>30</td>\n",
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       "      <th>0</th>\n",
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       "      <td>BLAKE</td>\n",
       "      <td>MANAGER</td>\n",
       "      <td>7839.0</td>\n",
       "      <td>01-MAY-81</td>\n",
       "      <td>2850</td>\n",
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       "      <td>30</td>\n",
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       "      <td>7839.0</td>\n",
       "      <td>09-JUN-81</td>\n",
       "      <td>2450</td>\n",
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       "      <td>10</td>\n",
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       "      <th>2</th>\n",
       "      <td>7788</td>\n",
       "      <td>SCOTT</td>\n",
       "      <td>ANALYST</td>\n",
       "      <td>7566.0</td>\n",
       "      <td>19-APR-87</td>\n",
       "      <td>3000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7839</td>\n",
       "      <td>KING</td>\n",
       "      <td>PRESIDENT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17-NOV-81</td>\n",
       "      <td>5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7844</td>\n",
       "      <td>TURNER</td>\n",
       "      <td>SALESMAN</td>\n",
       "      <td>7698.0</td>\n",
       "      <td>08-SEP-81</td>\n",
       "      <td>1500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7876</td>\n",
       "      <td>ADAMS</td>\n",
       "      <td>CLERK</td>\n",
       "      <td>7788.0</td>\n",
       "      <td>23-MAY-87</td>\n",
       "      <td>1100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
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       "      <th>6</th>\n",
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       "      <td>JAMES</td>\n",
       "      <td>CLERK</td>\n",
       "      <td>7698.0</td>\n",
       "      <td>03-DEC-81</td>\n",
       "      <td>950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7902</td>\n",
       "      <td>FORD</td>\n",
       "      <td>ANALYST</td>\n",
       "      <td>7566.0</td>\n",
       "      <td>03-DEC-81</td>\n",
       "      <td>3000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7934</td>\n",
       "      <td>MILLER</td>\n",
       "      <td>CLERK</td>\n",
       "      <td>7782.0</td>\n",
       "      <td>23-JAN-82</td>\n",
       "      <td>1300</td>\n",
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       "      <td>10</td>\n",
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      "text/plain": [
       "   EMPNO   ENAME        JOB     MGR   HIREDATE   SAL    COMM  DEPTNO\n",
       "0   7693   SMITH      CLERK  7902.0  17-DEC-80   960     NaN      20\n",
       "1   7499   ALLEN   SALESMAN  7698.0  20-FEB-81  1600   300.0      30\n",
       "2   7521    WARD   SALESMAN  7698.0  22-FEB-81  1250   500.0      30\n",
       "3   7566   JONES    MANAGER  7839.0  02-APR-81  2975     NaN      20\n",
       "4   7654  MARTIN   SALESMAN  7698.0  28-SEP-81  1250  1400.0      30\n",
       "0   7698   BLAKE    MANAGER  7839.0  01-MAY-81  2850     NaN      30\n",
       "1   7782   CLARK    MANAGER  7839.0  09-JUN-81  2450     NaN      10\n",
       "2   7788   SCOTT    ANALYST  7566.0  19-APR-87  3000     NaN      20\n",
       "3   7839    KING  PRESIDENT     NaN  17-NOV-81  5000     NaN      10\n",
       "4   7844  TURNER   SALESMAN  7698.0  08-SEP-81  1500     0.0      30\n",
       "5   7876   ADAMS      CLERK  7788.0  23-MAY-87  1100     NaN      20\n",
       "6   7900   JAMES      CLERK  7698.0  03-DEC-81   950     NaN      30\n",
       "7   7902    FORD    ANALYST  7566.0  03-DEC-81  3000     NaN      20\n",
       "8   7934  MILLER      CLERK  7782.0  23-JAN-82  1300     NaN      10"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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