S06-Working.ipynb

{
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       "<style type=\"text/css\">\n",
       "table.dataframe td, table.dataframe th {\n",
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       "<IPython.core.display.HTML object>"
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   "source": [
    "%%HTML\n",
    "<style type=\"text/css\">\n",
    "table.dataframe td, table.dataframe th {\n",
    "    border: 1px  black solid !important;\n",
    "  color: black !important;\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Python Mega Course: Build 10 Real World Applications\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains the source code for the video lectures of Section 6 of [The Python Mega Course: Build 10 Real World Applciations](https://www.udemy.com/the-python-mega-course/?couponCode=GITHEADSECTION)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Section 6: Data Analysis with Pandas\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [What is Pandas](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163238?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Note on IPython](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/7828164?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can install IPython from your command line / terminal by running:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pip install ipython"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pip3 install ipython"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Getting Started with Pandas](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163240?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    0   1   2\n",
       "0   2   4   6\n",
       "1  10  20  30"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a dataframe object\n",
    "df1 = pandas.DataFrame([[2, 4, 6], [10, 20, 30]])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Price</th>\n",
       "      <th>Age</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Price  Age  Value\n",
       "0      2    4      6\n",
       "1     10   20     30"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dataframe object with named columns\n",
    "df1 = pandas.DataFrame([[2, 4, 6], [10, 20, 30]], columns=[\"Price\", \"Age\", \"Value\"])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Price</th>\n",
       "      <th>Age</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>First</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Second</th>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Price  Age  Value\n",
       "First       2    4      6\n",
       "Second     10   20     30"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dataframe object with named columsn and rows\n",
    "df1 = pandas.DataFrame([[2, 4, 6], [10, 20, 30]], columns=[\"Price\", \"Age\", \"Value\"], index=[\"First\", \"Second\"])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>John</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jack</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Name\n",
       "0  John\n",
       "1  Jack"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dataframe object from a dictionary\n",
    "df2 = pandas.DataFrame([{\"Name\":\"John\"},{\"Name\":\"Jack\"}])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Name</th>\n",
       "      <th>Surname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>John</td>\n",
       "      <td>Johns</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jack</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Name Surname\n",
       "0  John   Johns\n",
       "1  Jack     NaN"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dataframe with many columns\n",
    "df2 = pandas.DataFrame([{\"Name\":\"John\", \"Surname\":\"Johns\"},{\"Name\":\"Jack\"}])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#get the object type\n",
    "type(df1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Price     6.0\n",
       "Age      12.0\n",
       "Value    18.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#get the mean value of each dataframe column\n",
    "df1.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the mean value of all columns\n",
    "df1.mean().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "First      2\n",
       "Second    10\n",
       "Name: Price, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#accessing a dataframe column\n",
    "df1[\"Price\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "First      2\n",
       "Second    10\n",
       "Name: Price, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#another way to access the dataframe column\n",
    "df1.Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the mean value of a column\n",
    "df1.Price.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Getting Started with Jupyter Notebooks](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163242?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This lecture contains a tutorial on how to use Jupyter Notebooks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Note on Loading Excel Files](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/7828274?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the next lecture among other things you're also going to learn how to load Excel (.xlsx) files in Python with pandas. Pandas may require the xlrd library as a dependency. If you get an error such as *ModuleNotFoundError: No module named 'xlrd'*  you can fix that by installing xlrd:\n",
    "<br>\n",
    "*pip install xlrd*\n",
    "<br>\n",
    "or\n",
    "<br>\n",
    "*pip3 install xlrd*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Loading Data in Python from CSV, Excel, TXT, and JSON Files](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163246?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "table.dataframe td, table.dataframe th {\n",
       "    border: 1px  black solid !important;\n",
       "  color: black !important;\n",
       "}"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%HTML\n",
    "<style type=\"text/css\">\n",
    "table.dataframe td, table.dataframe th {\n",
    "    border: 1px  black solid !important;\n",
    "  color: black !important;\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Please download the five files from [this link](http://pythonhow.com/data/python-mega-course-data/section6/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>ID</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Name</th>\n",
       "      <th>Employees</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3666 21st St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City             State Country         Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading data from a CSV file\n",
    "df1 = pandas.read_csv(\"supermarkets.csv\")\n",
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above CSV file had a first row that we wanted to be treated as a header in the dataframe. In case your data don't have a header, you have to set the header to None:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ID</td>\n",
       "      <td>Address</td>\n",
       "      <td>City</td>\n",
       "      <td>State</td>\n",
       "      <td>Country</td>\n",
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       "      <td>3666 21st St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    0                1              2                 3        4            5  \\\n",
       "0  ID          Address           City             State  Country         Name   \n",
       "1   1     3666 21st St  San Francisco          CA 94114      USA      Madeira   \n",
       "2   2   735 Dolores St  San Francisco          CA 94119      USA  Bready Shop   \n",
       "3   3      332 Hill St  San Francisco  California 94114      USA  Super River   \n",
       "4   4     3995 23rd St  San Francisco          CA 94114      USA   Ben's Shop   \n",
       "5   5  1056 Sanchez St  San Francisco        California      USA      Sanchez   \n",
       "6   6  551 Alvarado St  San Francisco          CA 94114      USA   Richvalley   \n",
       "\n",
       "           6  \n",
       "0  Employees  \n",
       "1          8  \n",
       "2         15  \n",
       "3         25  \n",
       "4         10  \n",
       "5         12  \n",
       "6         20  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading data with no header from a CSV\n",
    "df1 = pandas.read_csv(\"supermarkets.csv\", header=None)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City             State Country         Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#setting one of the columns as an index column\n",
    "df1 = pandas.read_csv(\"supermarkets.csv\")\n",
    "df1.set_index(\"ID\")\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6, 7)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#get the number of columns and rows\n",
    "df1.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
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       "      <th>1</th>\n",
       "      <td>3666 21st St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Address           City Country  Employees         Name  \\\n",
       "ID                                                                   \n",
       "1      3666 21st St  San Francisco     USA          8      Madeira   \n",
       "2    735 Dolores St  San Francisco     USA         15  Bready Shop   \n",
       "3       332 Hill St  San Francisco     USA         25  Super River   \n",
       "4      3995 23rd St  San Francisco     USA         10   Ben's Shop   \n",
       "5   1056 Sanchez St  San Francisco     USA         12      Sanchez   \n",
       "6   551 Alvarado St  San Francisco     USA         20   Richvalley   \n",
       "\n",
       "               State  \n",
       "ID                    \n",
       "1           CA 94114  \n",
       "2           CA 94119  \n",
       "3   California 94114  \n",
       "4           CA 94114  \n",
       "5         California  \n",
       "6           CA 94114  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading data from a JSON file\n",
    "df2 = pandas.read_json(\"supermarkets.json\")\n",
    "df2.set_index(\"ID\", inplace=True)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Supermarket Name</th>\n",
       "      <th>Number of Employees</th>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
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       "      <th>2</th>\n",
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       "      <td>25</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City             State Country  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   \n",
       "\n",
       "  Supermarket Name  Number of Employees  \n",
       "0          Madeira                    8  \n",
       "1      Bready Shop                   15  \n",
       "2      Super River                   25  \n",
       "3       Ben's Shop                   10  \n",
       "4          Sanchez                   12  \n",
       "5       Richvalley                   20  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading data from an Excel file (assuming they are in the first sheet)\n",
    "df3 = pandas.read_excel(\"supermarkets.xlsx\", sheet_name=0)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City             State Country         Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading data from a TXT file with columns divided by comas\n",
    "df4 = pandas.read_csv(\"supermarkets-commas.txt\")\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Name</th>\n",
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       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City             State Country          Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA       Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA   Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA   Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA    Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA       Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA    Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading data from a TXT file with columns divided by semi-colons\n",
    "df5 = pandas.read_csv(\"supermarkets-semi-colons.txt\", sep=\";\")\n",
    "df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
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       "      <td>8</td>\n",
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       "      <th>1</th>\n",
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       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
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       "      <td>25</td>\n",
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       "      <th>3</th>\n",
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       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
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       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City             State Country         Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading data from an URL of a TXT file\n",
    "df6 = pandas.read_csv(\"http://pythonhow.com/supermarkets.csv\")\n",
    "df6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>Address</th>\n",
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       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Address           City Country  Employees  ID         Name  \\\n",
       "0     3666 21st St  San Francisco     USA          8   1      Madeira   \n",
       "1   735 Dolores St  San Francisco     USA         15   2  Bready Shop   \n",
       "2      332 Hill St  San Francisco     USA         25   3  Super River   \n",
       "3     3995 23rd St  San Francisco     USA         10   4   Ben's Shop   \n",
       "4  1056 Sanchez St  San Francisco     USA         12   5      Sanchez   \n",
       "5  551 Alvarado St  San Francisco     USA         20   6   Richvalley   \n",
       "\n",
       "              State  \n",
       "0          CA 94114  \n",
       "1          CA 94119  \n",
       "2  California 94114  \n",
       "3          CA 94114  \n",
       "4        California  \n",
       "5          CA 94114  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df7 = pandas.read_json(\"http://pythonhow.com/supermarkets.json\")\n",
    "df7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
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       "      <td>Sanchez</td>\n",
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       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      "text/plain": [
       "   0                1              2                 3    4            5   6\n",
       "0  1     3666 21st St  San Francisco          CA 94114  USA      Madeira   8\n",
       "1  2   735 Dolores St  San Francisco          CA 94119  USA  Bready Shop  15\n",
       "2  3      332 Hill St  San Francisco  California 94114  USA  Super River  25\n",
       "3  4     3995 23rd St  San Francisco          CA 94114  USA   Ben's Shop  10\n",
       "4  5  1056 Sanchez St  San Francisco        California  USA      Sanchez  12\n",
       "5  6  551 Alvarado St  San Francisco          CA 94114  USA   Richvalley  20"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8 = pandas.read_csv(\"data.txt\", header = None)\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>3</td>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City               ZIP Country         Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8.columns = [\"ID\", \"Address\", \"City\", \"ZIP\", \"Country\", \"Name\", \"Employees\"]\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
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      "text/plain": [
       "            Address           City               ZIP Country         Name  \\\n",
       "ID                                                                          \n",
       "1      3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "2    735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "3       332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "4      3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "5   1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "6   551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "    Employees  \n",
       "ID             \n",
       "1           8  \n",
       "2          15  \n",
       "3          25  \n",
       "4          10  \n",
       "5          12  \n",
       "6          20  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8.set_index(\"ID\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
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       "   ID          Address           City               ZIP Country         Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df9 = df8.set_index(\"ID\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
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       "            Address           City               ZIP Country         Name  \\\n",
       "ID                                                                          \n",
       "1      3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "2    735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "3       332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "4      3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "5   1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "6   551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "    Employees  \n",
       "ID             \n",
       "1           8  \n",
       "2          15  \n",
       "3          25  \n",
       "4          10  \n",
       "5          12  \n",
       "6          20  "
      ]
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  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df8.set_index(\"ID\", inplace=True)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
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       "            Address           City               ZIP Country         Name  \\\n",
       "ID                                                                          \n",
       "1      3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "2    735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "3       332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "4      3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "5   1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "6   551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "    Employees  \n",
       "ID             \n",
       "1           8  \n",
       "2          15  \n",
       "3          25  \n",
       "4          10  \n",
       "5          12  \n",
       "6          20  "
      ]
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     "execution_count": 32,
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       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City               ZIP Country         Name  \\\n",
       "Address                                                                 \n",
       "3666 21st St     San Francisco          CA 94114     USA      Madeira   \n",
       "735 Dolores St   San Francisco          CA 94119     USA  Bready Shop   \n",
       "332 Hill St      San Francisco  California 94114     USA  Super River   \n",
       "3995 23rd St     San Francisco          CA 94114     USA   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "                 Employees  \n",
       "Address                     \n",
       "3666 21st St             8  \n",
       "735 Dolores St          15  \n",
       "332 Hill St             25  \n",
       "3995 23rd St            10  \n",
       "1056 Sanchez St         12  \n",
       "551 Alvarado St         20  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8.set_index(\"Address\", inplace=True)\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>City</th>\n",
       "      <th>ZIP</th>\n",
       "      <th>Country</th>\n",
       "      <th>Name</th>\n",
       "      <th>Employees</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</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>Madeira</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bready Shop</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Super River</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ben's Shop</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sanchez</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richvalley</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      City               ZIP Country         Name  Employees\n",
       "Name                                                                        \n",
       " Madeira     San Francisco          CA 94114     USA      Madeira          8\n",
       "Bready Shop  San Francisco          CA 94119     USA  Bready Shop         15\n",
       "Super River  San Francisco  California 94114     USA  Super River         25\n",
       "Ben's Shop   San Francisco          CA 94114     USA   Ben's Shop         10\n",
       "Sanchez      San Francisco        California     USA      Sanchez         12\n",
       "Richvalley   San Francisco          CA 94114     USA   Richvalley         20"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8.set_index(\"Name\", inplace=True, drop=False)\n",
    "df8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Indexing and Slicing Dataframes](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163250?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets suppose we have the following dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City Country  Employees  ID         Name  \\\n",
       "Address                                                              \n",
       "3666 21st St     San Francisco     USA          8   1      Madeira   \n",
       "735 Dolores St   San Francisco     USA         15   2  Bready Shop   \n",
       "332 Hill St      San Francisco     USA         25   3  Super River   \n",
       "3995 23rd St     San Francisco     USA         10   4   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco     USA         12   5      Sanchez   \n",
       "551 Alvarado St  San Francisco     USA         20   6   Richvalley   \n",
       "\n",
       "                            State  \n",
       "Address                            \n",
       "3666 21st St             CA 94114  \n",
       "735 Dolores St           CA 94119  \n",
       "332 Hill St      California 94114  \n",
       "3995 23rd St             CA 94114  \n",
       "1056 Sanchez St        California  \n",
       "551 Alvarado St          CA 94114  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8 = pandas.read_json(\"http://pythonhow.com/supermarkets.json\")\n",
    "df8 = df8.set_index(\"Address\")\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "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>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Country  Employees  ID\n",
       "Address                              \n",
       "735 Dolores St     USA         15   2\n",
       "332 Hill St        USA         25   3"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Extracting a portion of a dataframe based on labels\n",
    "df8.loc[\"735 Dolores St\":\"332 Hill St\", \"Country\":\"ID\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Address\n",
       "3666 21st St       USA\n",
       "735 Dolores St     USA\n",
       "332 Hill St        USA\n",
       "3995 23rd St       USA\n",
       "1056 Sanchez St    USA\n",
       "551 Alvarado St    USA\n",
       "Name: Country, dtype: object"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Extracting all rows (:) of the column Country\n",
    "df8.loc[:, \"Country\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['USA', 'USA', 'USA', 'USA', 'USA', 'USA']"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Extracting all rows (:) of the column Country as a list\n",
    "list(df8.loc[:, \"Country\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City Country  Employees  ID         Name  \\\n",
       "Address                                                              \n",
       "3666 21st St     San Francisco     USA          8   1      Madeira   \n",
       "735 Dolores St   San Francisco     USA         15   2  Bready Shop   \n",
       "332 Hill St      San Francisco     USA         25   3  Super River   \n",
       "3995 23rd St     San Francisco     USA         10   4   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco     USA         12   5      Sanchez   \n",
       "551 Alvarado St  San Francisco     USA         20   6   Richvalley   \n",
       "\n",
       "                            State  \n",
       "Address                            \n",
       "3666 21st St             CA 94114  \n",
       "735 Dolores St           CA 94119  \n",
       "332 Hill St      California 94114  \n",
       "3995 23rd St             CA 94114  \n",
       "1056 Sanchez St        California  \n",
       "551 Alvarado St          CA 94114  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#here is the dataframe again\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>Country</th>\n",
       "      <th>Employees</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Country  Employees\n",
       "Address                          \n",
       "735 Dolores St     USA         15\n",
       "332 Hill St        USA         25"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Extracting a portion of a dataframe based on index numbers\n",
    "df8.iloc[1:3, 1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country      USA\n",
       "Employees     10\n",
       "ID             4\n",
       "Name: 3995 23rd St, dtype: object"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Intersection between row with index 3 and columns with index 1 to 4\n",
    "df8.iloc[3, 1:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Dropping Dataframe Columns and Rows](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163254?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets again suppose we have the following dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df8 = pandas.read_json(\"http://pythonhow.com/supermarkets.json\")\n",
    "df8 = df8.set_index(\"Address\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Country  Employees  ID         Name             State\n",
       "Address                                                              \n",
       "3666 21st St        USA          8   1      Madeira          CA 94114\n",
       "735 Dolores St      USA         15   2  Bready Shop          CA 94119\n",
       "332 Hill St         USA         25   3  Super River  California 94114\n",
       "3995 23rd St        USA         10   4   Ben's Shop          CA 94114\n",
       "1056 Sanchez St     USA         12   5      Sanchez        California\n",
       "551 Alvarado St     USA         20   6   Richvalley          CA 94114"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#deleting the column City. 1 means you're deleting columns \n",
    "df8.drop(\"City\", 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the above simply returns a dataframe with the deleted column, but it doesn't change the original dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City Country  Employees  ID         Name  \\\n",
       "Address                                                              \n",
       "3666 21st St     San Francisco     USA          8   1      Madeira   \n",
       "735 Dolores St   San Francisco     USA         15   2  Bready Shop   \n",
       "332 Hill St      San Francisco     USA         25   3  Super River   \n",
       "3995 23rd St     San Francisco     USA         10   4   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco     USA         12   5      Sanchez   \n",
       "551 Alvarado St  San Francisco     USA         20   6   Richvalley   \n",
       "\n",
       "                            State  \n",
       "Address                            \n",
       "3666 21st St             CA 94114  \n",
       "735 Dolores St           CA 94119  \n",
       "332 Hill St      California 94114  \n",
       "3995 23rd St             CA 94114  \n",
       "1056 Sanchez St        California  \n",
       "551 Alvarado St          CA 94114  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the original dataframe still has the City column\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Country  Employees  ID         Name             State\n",
       "Address                                                              \n",
       "3666 21st St        USA          8   1      Madeira          CA 94114\n",
       "735 Dolores St      USA         15   2  Bready Shop          CA 94119\n",
       "332 Hill St         USA         25   3  Super River  California 94114\n",
       "3995 23rd St        USA         10   4   Ben's Shop          CA 94114\n",
       "1056 Sanchez St     USA         12   5      Sanchez        California\n",
       "551 Alvarado St     USA         20   6   Richvalley          CA 94114"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to change the original dataframe set inplace to True\n",
    "df8.drop(\"City\", 1, inplace=True)\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Country  Employees  ID         Name       State\n",
       "Address                                                        \n",
       "3666 21st St        USA          8   1      Madeira    CA 94114\n",
       "735 Dolores St      USA         15   2  Bready Shop    CA 94119\n",
       "3995 23rd St        USA         10   4   Ben's Shop    CA 94114\n",
       "1056 Sanchez St     USA         12   5      Sanchez  California\n",
       "551 Alvarado St     USA         20   6   Richvalley    CA 94114"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#delete a row\n",
    "df8.drop(\"332 Hill St\", 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3995 23rd St</th>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Country  Employees  ID        Name       State\n",
       "Address                                                       \n",
       "3995 23rd St        USA         10   4  Ben's Shop    CA 94114\n",
       "1056 Sanchez St     USA         12   5     Sanchez  California\n",
       "551 Alvarado St     USA         20   6  Richvalley    CA 94114"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#delete multiple rows\n",
    "df8.drop(df8.index[0:3], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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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>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3666 21st St</th>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Name             State\n",
       "Address                                       \n",
       "3666 21st St         Madeira          CA 94114\n",
       "735 Dolores St   Bready Shop          CA 94119\n",
       "332 Hill St      Super River  California 94114\n",
       "3995 23rd St      Ben's Shop          CA 94114\n",
       "1056 Sanchez St      Sanchez        California\n",
       "551 Alvarado St   Richvalley          CA 94114"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#delete multiple columns\n",
    "df8.drop(df8.columns[0:3], 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Updating and Adding new Columns and Rows](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163256?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, we're going to work with the following dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City Country  Employees  ID         Name  \\\n",
       "Address                                                              \n",
       "3666 21st St     San Francisco     USA          8   1      Madeira   \n",
       "735 Dolores St   San Francisco     USA         15   2  Bready Shop   \n",
       "332 Hill St      San Francisco     USA         25   3  Super River   \n",
       "3995 23rd St     San Francisco     USA         10   4   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco     USA         12   5      Sanchez   \n",
       "551 Alvarado St  San Francisco     USA         20   6   Richvalley   \n",
       "\n",
       "                            State  \n",
       "Address                            \n",
       "3666 21st St             CA 94114  \n",
       "735 Dolores St           CA 94119  \n",
       "332 Hill St      California 94114  \n",
       "3995 23rd St             CA 94114  \n",
       "1056 Sanchez St        California  \n",
       "551 Alvarado St          CA 94114  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8 = pandas.read_json(\"http://pythonhow.com/supermarkets.json\")\n",
    "df8 = df8.set_index(\"Address\")\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Continent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "      <td>North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>North America</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City Country  Employees  ID         Name  \\\n",
       "Address                                                              \n",
       "3666 21st St     San Francisco     USA          8   1      Madeira   \n",
       "735 Dolores St   San Francisco     USA         15   2  Bready Shop   \n",
       "332 Hill St      San Francisco     USA         25   3  Super River   \n",
       "3995 23rd St     San Francisco     USA         10   4   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco     USA         12   5      Sanchez   \n",
       "551 Alvarado St  San Francisco     USA         20   6   Richvalley   \n",
       "\n",
       "                            State      Continent  \n",
       "Address                                           \n",
       "3666 21st St             CA 94114  North America  \n",
       "735 Dolores St           CA 94119  North America  \n",
       "332 Hill St      California 94114  North America  \n",
       "3995 23rd St             CA 94114  North America  \n",
       "1056 Sanchez St        California  North America  \n",
       "551 Alvarado St          CA 94114  North America  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#adding a new column\n",
    "df8[\"Continent\"] = \"North America\"\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Continent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City Country  Employees  ID         Name  \\\n",
       "Address                                                              \n",
       "3666 21st St     San Francisco     USA          8   1      Madeira   \n",
       "735 Dolores St   San Francisco     USA         15   2  Bready Shop   \n",
       "332 Hill St      San Francisco     USA         25   3  Super River   \n",
       "3995 23rd St     San Francisco     USA         10   4   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco     USA         12   5      Sanchez   \n",
       "551 Alvarado St  San Francisco     USA         20   6   Richvalley   \n",
       "\n",
       "                            State           Continent  \n",
       "Address                                                \n",
       "3666 21st St             CA 94114  USA, North America  \n",
       "735 Dolores St           CA 94119  USA, North America  \n",
       "332 Hill St      California 94114  USA, North America  \n",
       "3995 23rd St             CA 94114  USA, North America  \n",
       "1056 Sanchez St        California  USA, North America  \n",
       "551 Alvarado St          CA 94114  USA, North America  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#changing the values of an existing column\n",
    "df8[\"Continent\"] = df8[\"Country\"] + \", \" + \"North America\"\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Employees</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>State</th>\n",
       "      <th>Continent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Address</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>3666 21st St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735 Dolores St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332 Hill St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>Super River</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3995 23rd St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056 Sanchez St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>California</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551 Alvarado St</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>USA</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA, North America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>My Address</th>\n",
       "      <td>My City</td>\n",
       "      <td>My Country</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>My Shop</td>\n",
       "      <td>My State</td>\n",
       "      <td>My Continent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          City     Country Employees ID         Name  \\\n",
       "Address                                                                \n",
       "3666 21st St     San Francisco         USA         8  1      Madeira   \n",
       "735 Dolores St   San Francisco         USA        15  2  Bready Shop   \n",
       "332 Hill St      San Francisco         USA        25  3  Super River   \n",
       "3995 23rd St     San Francisco         USA        10  4   Ben's Shop   \n",
       "1056 Sanchez St  San Francisco         USA        12  5      Sanchez   \n",
       "551 Alvarado St  San Francisco         USA        20  6   Richvalley   \n",
       "My Address             My City  My Country        10  7      My Shop   \n",
       "\n",
       "                            State           Continent  \n",
       "Address                                                \n",
       "3666 21st St             CA 94114  USA, North America  \n",
       "735 Dolores St           CA 94119  USA, North America  \n",
       "332 Hill St      California 94114  USA, North America  \n",
       "3995 23rd St             CA 94114  USA, North America  \n",
       "1056 Sanchez St        California  USA, North America  \n",
       "551 Alvarado St          CA 94114  USA, North America  \n",
       "My Address               My State        My Continent  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#adding a new row\n",
    "df8_t = df8.T\n",
    "df8_t[\"My Address\"] = [\"My City\", \"My Country\", 10, 7, \"My Shop\", \"My State\", \"My Continent\"]\n",
    "df8 = df8_t.T\n",
    "df8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Lecture:** [Example: Geocoding Addresses with Pandas and Geopy](https://www.udemy.com/the-python-mega-course/learn/v4/t/lecture/5163258?start=0)\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This lecture shows how to convert (geocode) address strings to geographical latitude and longitude coordinates. For that you need to install geopy with:<br> *pip install geopy*<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import the ArcGIS geocoder\n",
    "from geopy.geocoders import ArcGIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#create a geocoder object\n",
    "nom = ArcGIS()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Location(3995 23rd St, San Francisco, California, 94114, (37.75298458728149, -122.4317017142651, 0.0))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#geocode an address\n",
    "nom.geocode(\"3995 23rd St, San Francisco, CA 94114\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#you can also store the results in a variable\n",
    "n = nom.geocode(\"3995 23rd St, San Francisco, CA 94114\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "geopy.location.Location"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#you can see that n is a location object of geopy\n",
    "type(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37.75298458728149 -122.4317017142651\n"
     ]
    }
   ],
   "source": [
    "#extract latitude and longitude\n",
    "print(n.latitude, n.longitude)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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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>ID</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Name</th>\n",
       "      <th>Employees</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3666 21st St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID          Address           City             State Country         Name  \\\n",
       "0   1     3666 21st St  San Francisco          CA 94114     USA      Madeira   \n",
       "1   2   735 Dolores St  San Francisco          CA 94119     USA  Bready Shop   \n",
       "2   3      332 Hill St  San Francisco  California 94114     USA  Super River   \n",
       "3   4     3995 23rd St  San Francisco          CA 94114     USA   Ben's Shop   \n",
       "4   5  1056 Sanchez St  San Francisco        California     USA      Sanchez   \n",
       "5   6  551 Alvarado St  San Francisco          CA 94114     USA   Richvalley   \n",
       "\n",
       "   Employees  \n",
       "0          8  \n",
       "1         15  \n",
       "2         25  \n",
       "3         10  \n",
       "4         12  \n",
       "5         20  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#lets load some csv data with addresses\n",
    "import pandas\n",
    "df = pandas.read_csv(\"supermarkets.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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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>ID</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Name</th>\n",
       "      <th>Employees</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3666 21st St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St, San Francisco, CA 94119, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St, San Francisco, California 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St, San Francisco, California, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID                                            Address           City  \\\n",
       "0   1         3666 21st St, San Francisco, CA 94114, USA  San Francisco   \n",
       "1   2       735 Dolores St, San Francisco, CA 94119, USA  San Francisco   \n",
       "2   3  332 Hill St, San Francisco, California 94114, USA  San Francisco   \n",
       "3   4         3995 23rd St, San Francisco, CA 94114, USA  San Francisco   \n",
       "4   5    1056 Sanchez St, San Francisco, California, USA  San Francisco   \n",
       "5   6      551 Alvarado St, San Francisco, CA 94114, USA  San Francisco   \n",
       "\n",
       "              State Country         Name  Employees  \n",
       "0          CA 94114     USA      Madeira          8  \n",
       "1          CA 94119     USA  Bready Shop         15  \n",
       "2  California 94114     USA  Super River         25  \n",
       "3          CA 94114     USA   Ben's Shop         10  \n",
       "4        California     USA      Sanchez         12  \n",
       "5          CA 94114     USA   Richvalley         20  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#update the address column so it also has city, state, and country\n",
    "df[\"Address\"] = df[\"Address\"] + \", \" + df[\"City\"] + \", \" + df[\"State\"] + \", \" + df[\"Country\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Name</th>\n",
       "      <th>Employees</th>\n",
       "      <th>Coordinates</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3666 21st St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "      <td>(3666 21st St, San Francisco, California, 9411...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St, San Francisco, CA 94119, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
       "      <td>USA</td>\n",
       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "      <td>(735 Dolores St, San Francisco, California, 94...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St, San Francisco, California 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "      <td>(332 Hill St, San Francisco, California, 94114...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "      <td>(3995 23rd St, San Francisco, California, 9411...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St, San Francisco, California, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "      <td>(1056 Sanchez St, San Francisco, California, 9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "      <td>(551 Alvarado St, San Francisco, California, 9...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID                                            Address           City  \\\n",
       "0   1         3666 21st St, San Francisco, CA 94114, USA  San Francisco   \n",
       "1   2       735 Dolores St, San Francisco, CA 94119, USA  San Francisco   \n",
       "2   3  332 Hill St, San Francisco, California 94114, USA  San Francisco   \n",
       "3   4         3995 23rd St, San Francisco, CA 94114, USA  San Francisco   \n",
       "4   5    1056 Sanchez St, San Francisco, California, USA  San Francisco   \n",
       "5   6      551 Alvarado St, San Francisco, CA 94114, USA  San Francisco   \n",
       "\n",
       "              State Country         Name  Employees  \\\n",
       "0          CA 94114     USA      Madeira          8   \n",
       "1          CA 94119     USA  Bready Shop         15   \n",
       "2  California 94114     USA  Super River         25   \n",
       "3          CA 94114     USA   Ben's Shop         10   \n",
       "4        California     USA      Sanchez         12   \n",
       "5          CA 94114     USA   Richvalley         20   \n",
       "\n",
       "                                         Coordinates  \n",
       "0  (3666 21st St, San Francisco, California, 9411...  \n",
       "1  (735 Dolores St, San Francisco, California, 94...  \n",
       "2  (332 Hill St, San Francisco, California, 94114...  \n",
       "3  (3995 23rd St, San Francisco, California, 9411...  \n",
       "4  (1056 Sanchez St, San Francisco, California, 9...  \n",
       "5  (551 Alvarado St, San Francisco, California, 9...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a coordinates column to store the geocoded values\n",
    "df[\"Coordinates\"] = df[\"Address\"].apply(nom.geocode)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37.75644449321933"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#extracting the latitude of the first value of the Coordinates column\n",
    "df.Coordinates[0].latitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
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       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>Name</th>\n",
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       "      <th>0</th>\n",
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       "      <td>3666 21st St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Madeira</td>\n",
       "      <td>8</td>\n",
       "      <td>(3666 21st St, San Francisco, California, 9411...</td>\n",
       "      <td>37.756444</td>\n",
       "      <td>-122.429353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>735 Dolores St, San Francisco, CA 94119, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94119</td>\n",
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       "      <td>Bready Shop</td>\n",
       "      <td>15</td>\n",
       "      <td>(735 Dolores St, San Francisco, California, 94...</td>\n",
       "      <td>37.757801</td>\n",
       "      <td>-122.425599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>332 Hill St, San Francisco, California 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Super River</td>\n",
       "      <td>25</td>\n",
       "      <td>(332 Hill St, San Francisco, California, 94114...</td>\n",
       "      <td>37.755641</td>\n",
       "      <td>-122.428794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3995 23rd St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Ben's Shop</td>\n",
       "      <td>10</td>\n",
       "      <td>(3995 23rd St, San Francisco, California, 9411...</td>\n",
       "      <td>37.752985</td>\n",
       "      <td>-122.431702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1056 Sanchez St, San Francisco, California, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>USA</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>12</td>\n",
       "      <td>(1056 Sanchez St, San Francisco, California, 9...</td>\n",
       "      <td>37.752144</td>\n",
       "      <td>-122.429758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>551 Alvarado St, San Francisco, CA 94114, USA</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA 94114</td>\n",
       "      <td>USA</td>\n",
       "      <td>Richvalley</td>\n",
       "      <td>20</td>\n",
       "      <td>(551 Alvarado St, San Francisco, California, 9...</td>\n",
       "      <td>37.753709</td>\n",
       "      <td>-122.433251</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID                                            Address           City  \\\n",
       "0   1         3666 21st St, San Francisco, CA 94114, USA  San Francisco   \n",
       "1   2       735 Dolores St, San Francisco, CA 94119, USA  San Francisco   \n",
       "2   3  332 Hill St, San Francisco, California 94114, USA  San Francisco   \n",
       "3   4         3995 23rd St, San Francisco, CA 94114, USA  San Francisco   \n",
       "4   5    1056 Sanchez St, San Francisco, California, USA  San Francisco   \n",
       "5   6      551 Alvarado St, San Francisco, CA 94114, USA  San Francisco   \n",
       "\n",
       "              State Country         Name  Employees  \\\n",
       "0          CA 94114     USA      Madeira          8   \n",
       "1          CA 94119     USA  Bready Shop         15   \n",
       "2  California 94114     USA  Super River         25   \n",
       "3          CA 94114     USA   Ben's Shop         10   \n",
       "4        California     USA      Sanchez         12   \n",
       "5          CA 94114     USA   Richvalley         20   \n",
       "\n",
       "                                         Coordinates   Latitude   Longitude  \n",
       "0  (3666 21st St, San Francisco, California, 9411...  37.756444 -122.429353  \n",
       "1  (735 Dolores St, San Francisco, California, 94...  37.757801 -122.425599  \n",
       "2  (332 Hill St, San Francisco, California, 94114...  37.755641 -122.428794  \n",
       "3  (3995 23rd St, San Francisco, California, 9411...  37.752985 -122.431702  \n",
       "4  (1056 Sanchez St, San Francisco, California, 9...  37.752144 -122.429758  \n",
       "5  (551 Alvarado St, San Francisco, California, 9...  37.753709 -122.433251  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create latitude and longitude columns\n",
    "df[\"Latitude\"] = df[\"Coordinates\"].apply(lambda x: x.latitude if x != None else None)\n",
    "df[\"Longitude\"] = df[\"Coordinates\"].apply(lambda x: x.longitude if x != None else None)\n",
    "df"
   ]
  }
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