Using_the_Pandas_DataFrame_in_Day_To_Day_Life.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Using the Pandas DataFrame in Day-To-Day Life.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOXIzXr5A0Nx2pT5MXt6K6c",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Tanu-N-Prabhu/Python/blob/master/Using_the_Pandas_DataFrame_in_Day_To_Day_Life.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dwwsfSp0pmUw"
      },
      "source": [
        "# **Using the Pandas DataFrame in Day-To-Day Life**\n",
        "\n",
        "## **In this article, you will know how to use Pandas DataFrame in everyday life.**\n",
        "\n",
        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)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZQuGIGSTqFtI"
      },
      "source": [
        "Before getting started let us do a quick revision, Pandas is a [python library](https://pandas.pydata.org/) that gives elite, and simple to-utilize information structure for data analysis tools for python programming language. Show below is the article which will help you gain your understanding level in the Pandas library. Don’t forget to have a look at it. In fact, this is the official docs. It is worth reading it\n",
        "\n",
        "\n",
        "[Official Docs](https://pandas.pydata.org/)\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "# **Necessary set-up to get you started**\n",
        "\n",
        "\n",
        "## **There are two important necessary steps that you need to take care to perform smooth functioning:**\n",
        "\n",
        "\n",
        "1. **IDE or Jupyter Notebook**: It doesn’t really matter whether you use an IDE like **[PyCharm](https://www.jetbrains.com/pycharm/)**, **[Visual Studio Code](https://code.visualstudio.com/)**, **[IntelliJ IDEA](https://www.jetbrains.com/idea/)**, or **[Jupyter Notebook environment](https://jupyter.org/)**. Personally, I use **[Google Colab](https://colab.research.google.com/)** with is a **[Jypter Notebook environment](https://jupyter.org/)** because of its good documentation feature. We can explain things in a clear and more precise manner.\n",
        "2. **Python**: If this is your first time installing Python, don’t worry I got your back. Follow the article given underneath and follow the means to effectively install Python.\n",
        "\n",
        "**[Python installation steps](https://realpython.com/installing-python/)**\n",
        "\n",
        "\n",
        "> **Note** → If you are using [Google Colab](https://colab.research.google.com/) or any [Jupyter notebook environment](https://jupyter.org/), then you can skip the Python installation step.\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Xj05i2TTrmjC"
      },
      "source": [
        "# **Scenario**\n",
        "Let’s understand a scenario here and come up with a solution using Pandas DataFrame.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "> **“Everybody does and loves to do shopping (grocery). Not all the time you grocery shop at the same store, you shop based on discounts and offers (I do). Now obviously it’s a good practice to keep track of shopping details like the store name, location, amount, date, etc.”**\n",
        "\n",
        "\n",
        "To store and manipulate date I know you will use “**[Microsoft Excel](https://office.live.com/start/excel.aspx)**” but the catch point here is we will use “**Pandas DataFrame**” which is by far easier and fun to use. Don’t worry, I’ll show you how.\n",
        "\n",
        "\n",
        "> **Don’t get me wrong, “[Microsoft Excel](https://office.live.com/start/excel.aspx)” is where it’s at. But to all those Python enthusiasts this is the best example to understand and take Pandas to next level.**\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V-vvHPnfsALf"
      },
      "source": [
        "# **Solution**\n",
        "Let’s solve the above scenario using Pandas DataFrame. Now in order to that, you need to follow certain steps to not commit mistakes. I will provide a systematic way of using Pandas so that you can use it mechanically in your upcoming projects or whatever.\n",
        "\n",
        "\n",
        "## **Importing the Pandas DataFrame library**\n",
        "Let’s use the concept of aliasing and use the pandas as `pd`. So in the later steps, rather than using `pandas` every time, we can just tell `pd`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HUorgBAup3DW"
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ahBVT9JrsNzX"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "## **Storing the shopping details in a list — for the first time**\n",
        "\n",
        "For those of you who don’t about Python list. Please look it up **[here](https://docs.python.org/3/tutorial/datastructures.html)**. Since I’m currently living in Regina, Saskatchewan, Canada. So most of the grocery stores would be similar or different when compared to yours. Please bear that in mind. It really does not matter, you can feed the data as per your choice.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4McBxOHisvgl"
      },
      "source": [
        "date = ['1-9-20', '3-9-20', '3-9-20', '6-9-20', '9-9-20']\n",
        "\n",
        "storeName = ['Walmart', 'Real Canadian Superstore', 'Co-op Food Store', 'Sobeys', 'M&M Food Market']\n",
        "\n",
        "storeLocation = ['Gordon Road', 'Albert Street', 'Albert Street', 'Quance Street', 'Gordon Street']\n",
        "\n",
        "amount = [55.65, 21.62, 7.10, 15.56, 5.85]"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4UeAPkMwsze1"
      },
      "source": [
        "Now, what do I mean by “**for the first time**”, is that later say suppose if you keep on doing grocery shopping in the future, rather than storing the values manually in the list. The list would be grown **as long as a train**. Also, this is not recommended. So I have written a way to handle this situation in the lower sections.\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "## **Creating a Pandas DataFrame to store all the list values**\n",
        "Here, since we have all the values store in a list, let’s put them in a DataFrame. We can use `pd.DataFrame()` and pass the value, which is all the list in this case."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0EnOp8D9s9D0",
        "outputId": "8f269353-c809-4629-ed7d-24682bad9cc1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "df = pd.DataFrame({'Date': date, \n",
        "                   'Store Name': storeName,\n",
        "                   'Store Location': storeLocation,\n",
        "                   'Amount Purchased': amount})\n",
        "df"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Store Name</th>\n",
              "      <th>Store Location</th>\n",
              "      <th>Amount Purchased</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1-9-20</td>\n",
              "      <td>Walmart</td>\n",
              "      <td>Gordon Road</td>\n",
              "      <td>55.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Real Canadian Superstore</td>\n",
              "      <td>Albert Street</td>\n",
              "      <td>21.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Co-op Food Store</td>\n",
              "      <td>Albert Street</td>\n",
              "      <td>7.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6-9-20</td>\n",
              "      <td>Sobeys</td>\n",
              "      <td>Quance Street</td>\n",
              "      <td>15.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9-9-20</td>\n",
              "      <td>M&amp;M Food Market</td>\n",
              "      <td>Gordon Street</td>\n",
              "      <td>5.85</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Date                Store Name Store Location  Amount Purchased\n",
              "0  1-9-20                   Walmart    Gordon Road             55.65\n",
              "1  3-9-20  Real Canadian Superstore  Albert Street             21.62\n",
              "2  3-9-20          Co-op Food Store  Albert Street              7.10\n",
              "3  6-9-20                    Sobeys  Quance Street             15.56\n",
              "4  9-9-20           M&M Food Market  Gordon Street              5.85"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BagXvq4WtA1Q"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "## **Taking the shopping details as input from the user — for future visits**\n",
        "\n",
        "\n",
        "As I said, it’s not a very good practice to store all the values in a list. In this way, we automatically make the list grow. There is a neat and cute way to handle this kind of situation. First, let’s take the input from the input and store them in temporary variables as shown below:\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4ktxbtt9tFbe",
        "outputId": "76e95ad6-6533-4c40-a7ca-cd4e8de350bc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        }
      },
      "source": [
        "dateNew = input(\"Enter the date in dd-mm-yy format ---> \")\n",
        "storeNameNew = input(\"Enter the name of the store ---> \")\n",
        "storeLocationNew = input(\"Enter the location of the store ---> \")\n",
        "amountNew = float(input(\"Enter the total amount purchased ---> \"))"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Enter the date in dd-mm-yy format ---> 10-9-20\n",
            "Enter the name of the store ---> India Market\n",
            "Enter the location of the store ---> Albert Street\n",
            "Enter the total amount purchased ---> 24.68\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lwz-LiDptHbi"
      },
      "source": [
        "So on the next day, I mean 10–9–20 I went to the grocery store to shop for some spices with **[Gordon Ramsay](https://www.gordonramsay.com/)**, just kidding I went alone. Below are the details of the new store.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "Enter the date in dd-mm-yy format ---> 10-9-20 \n",
        "Enter the name of the store ---> India Market \n",
        "Enter the location of the store ---> Albert Street \n",
        "Enter the total amount purchased ---> 24.68\n",
        "```\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "## **Appending the new data to the existing list**\n",
        "This is an obvious step because we need to append the new data (shopping details) to the existing DataFrame. We can do this with the help of append() Python.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xNpE02A-teC2"
      },
      "source": [
        "date.append(dateNew)\n",
        "storeName.append(storeNameNew)\n",
        "storeLocation.append(storeLocationNew)\n",
        "amount.append(amountNew)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tGQYr5sotgM9"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "## **Displaying the updated result via a DataFrame**\n",
        "This step is trivial because all we are doing is just displaying all the updated results from the above step as a DataFrame. Similar to the “**Creating a Pandas DataFrame to store all the list values**” step shown above.\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jPD-ei0rtlXE",
        "outputId": "1d3b7a08-cec6-43d2-a83b-601e3eda1e24",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        }
      },
      "source": [
        "df = pd.DataFrame({'Date': date, \n",
        "                   'Store Name': storeName,\n",
        "                   'Store Location': storeLocation,\n",
        "                   'Amount': amount})\n",
        "df"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Store Name</th>\n",
              "      <th>Store Location</th>\n",
              "      <th>Amount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1-9-20</td>\n",
              "      <td>Walmart</td>\n",
              "      <td>Gordon Road</td>\n",
              "      <td>55.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Real Canadian Superstore</td>\n",
              "      <td>Albert Street</td>\n",
              "      <td>21.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Co-op Food Store</td>\n",
              "      <td>Albert Street</td>\n",
              "      <td>7.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6-9-20</td>\n",
              "      <td>Sobeys</td>\n",
              "      <td>Quance Street</td>\n",
              "      <td>15.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9-9-20</td>\n",
              "      <td>M&amp;M Food Market</td>\n",
              "      <td>Gordon Street</td>\n",
              "      <td>5.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>10-9-20</td>\n",
              "      <td>India Market</td>\n",
              "      <td>Albert Street</td>\n",
              "      <td>24.68</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Date                Store Name Store Location  Amount\n",
              "0   1-9-20                   Walmart    Gordon Road   55.65\n",
              "1   3-9-20  Real Canadian Superstore  Albert Street   21.62\n",
              "2   3-9-20          Co-op Food Store  Albert Street    7.10\n",
              "3   6-9-20                    Sobeys  Quance Street   15.56\n",
              "4   9-9-20           M&M Food Market  Gordon Street    5.85\n",
              "5  10-9-20              India Market  Albert Street   24.68"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i3SO5jRBtnZT"
      },
      "source": [
        "There you go, you have successfully handled the scenario like a piece of cake. You can keep on adding more data (shopping details) and maintain monthly or yearly wise.\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "# **Bonus**\n",
        "## **Nifty tricks that you can perform on the existing DataFrame**\n",
        "Shown below are some tips and tricks that you can perform or do in your free time. Because they are that easy to understand. Let me get into it.\n",
        "## **Plotting a bar plot**\n",
        "It’s always a good practice to plot the data for better readability. Now for plotting let us use the column `Amount` so that we know how much we have spent till now with the help of a plot. This can be done by using `df.plot.bar()` as shown below\n",
        "\n",
        "> **Note**: Always remember only numeric data can be plotted in Pandas\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gaa2GN18t3sF",
        "outputId": "1ec1488d-655e-4521-9f5a-cfa670e35c6b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "df.plot.bar()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fef662459e8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SFDWhGHKt5vo"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "## **Deleting an entire row/column**\n",
        "Say suppose we need to delete the last row because there is a mistake in the entry so this can be performed as follows. Now to delete an entire row we need to use `drop()` in Pandas as shown below:\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EXz1IP4Yt_U4",
        "outputId": "6a99e989-6b04-4444-bc58-641c58a4f4eb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "df = df.drop([5])\n",
        "df"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Store Name</th>\n",
              "      <th>Store Location</th>\n",
              "      <th>Amount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1-9-20</td>\n",
              "      <td>Walmart</td>\n",
              "      <td>Gordon Road</td>\n",
              "      <td>55.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Real Canadian Superstore</td>\n",
              "      <td>Albert Street</td>\n",
              "      <td>21.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Co-op Food Store</td>\n",
              "      <td>Albert Street</td>\n",
              "      <td>7.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6-9-20</td>\n",
              "      <td>Sobeys</td>\n",
              "      <td>Quance Street</td>\n",
              "      <td>15.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9-9-20</td>\n",
              "      <td>M&amp;M Food Market</td>\n",
              "      <td>Gordon Street</td>\n",
              "      <td>5.85</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Date                Store Name Store Location  Amount\n",
              "0  1-9-20                   Walmart    Gordon Road   55.65\n",
              "1  3-9-20  Real Canadian Superstore  Albert Street   21.62\n",
              "2  3-9-20          Co-op Food Store  Albert Street    7.10\n",
              "3  6-9-20                    Sobeys  Quance Street   15.56\n",
              "4  9-9-20           M&M Food Market  Gordon Street    5.85"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6E5yjpxGuB0j"
      },
      "source": [
        "> Note: Here the value 5 is the index value of the last row"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eJafJWmPuESD"
      },
      "source": [
        "Deleting the column is like that of a row all you have to do is pass the column names to delete in this case like `df.drop([column_name, axis = 1])` the `axis = 1` is important here. Say suppose you need to delete the column `Amount` in the DataFrame then all you need to say is:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2bty-oJkuJ8q",
        "outputId": "b98b0156-df8f-44ce-f5da-00faa0badbeb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "df = df.drop(['Amount'], axis = 1)\n",
        "df"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Store Name</th>\n",
              "      <th>Store Location</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1-9-20</td>\n",
              "      <td>Walmart</td>\n",
              "      <td>Gordon Road</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Real Canadian Superstore</td>\n",
              "      <td>Albert Street</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Co-op Food Store</td>\n",
              "      <td>Albert Street</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6-9-20</td>\n",
              "      <td>Sobeys</td>\n",
              "      <td>Quance Street</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9-9-20</td>\n",
              "      <td>M&amp;M Food Market</td>\n",
              "      <td>Gordon Street</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Date                Store Name Store Location\n",
              "0  1-9-20                   Walmart    Gordon Road\n",
              "1  3-9-20  Real Canadian Superstore  Albert Street\n",
              "2  3-9-20          Co-op Food Store  Albert Street\n",
              "3  6-9-20                    Sobeys  Quance Street\n",
              "4  9-9-20           M&M Food Market  Gordon Street"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9MPWWGfhuMDz"
      },
      "source": [
        "By executing this you can now see that the column Amount has now been dropped.\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "## **Modifying specific entries**\n",
        "Suppose we need to update a specific entry in the DataFrame, in this case, the 4th index with the store name M&M Food Market has a mistake in its store Location (wrong entry) Gordon Street, we need to correct it to Gordon Road. To do this just use:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yy17TnGzuRzl",
        "outputId": "2f630c78-9725-4a7e-b0e3-fe1827d86558",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "df['Store Location'][4] = \"Gordon Road\"\n",
        "df"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Store Name</th>\n",
              "      <th>Store Location</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1-9-20</td>\n",
              "      <td>Walmart</td>\n",
              "      <td>Gordon Road</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Real Canadian Superstore</td>\n",
              "      <td>Albert Street</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3-9-20</td>\n",
              "      <td>Co-op Food Store</td>\n",
              "      <td>Albert Street</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6-9-20</td>\n",
              "      <td>Sobeys</td>\n",
              "      <td>Quance Street</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9-9-20</td>\n",
              "      <td>M&amp;M Food Market</td>\n",
              "      <td>Gordon Road</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Date                Store Name Store Location\n",
              "0  1-9-20                   Walmart    Gordon Road\n",
              "1  3-9-20  Real Canadian Superstore  Albert Street\n",
              "2  3-9-20          Co-op Food Store  Albert Street\n",
              "3  6-9-20                    Sobeys  Quance Street\n",
              "4  9-9-20           M&M Food Market    Gordon Road"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vniJQ0WpuTTy"
      },
      "source": [
        "We need to know the index of the particular entry to update the entry, so after executing the above we get the updated result\n",
        "\n",
        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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kvn3hxMXuh-5"
      },
      "source": [
        "# **Conclusion**\n",
        "Well, congratulations guys you have successfully completed reading/implementing this beautiful article “**Using the Pandas DataFrame in Day-To-Day Life**”. Now, this is not the end, there are many other methods or functions of DataFrame that we can use and take it to next level. I have only covered only the basics here. If you guys find something new or creative, then comment it down below. I hope you guys have learned something new today. Stay tuned for more updates, until then see you next time. Bye Have a good day and stay safe!\n",
        "\n",
        "\n",
        "---"
      ]
    }
  ]
}