comparison_of_keywords_trends_in_same_chart_decodemai.ipynb

comparison_of_keywords_trends_in_same_chart_decodemai.ipynb

{
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  "metadata": {
    "colab": {
      "name": "comparison_of_keywords_trends_in_same_chart_decodemai.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "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/gist/NehaAkashDeo/72b3e12f21d0cc2bc83df215bb53008e/comparison_of_keywords_trends_in_same_chart_decodemai.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZKBcGl2qYXsv",
        "colab_type": "text"
      },
      "source": [
        "# Trends Comparison\n",
        "*   Get multiple keywords from user\n",
        "*   Obtain search trends\n",
        "*   Create single chart with the trends using different color codes\n",
        "\n",
        "To be done:\n",
        "- What if wrong keyword is given?\n",
        "- What of there is no data... exception handling needs to be added?\n",
        "- Give user flexibility to change timeline... currently fixed to last 5 years\n",
        "- Give other options like color, size of image etc\n",
        "- Add disclaimers and T&Cs\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "(c) Decodem Technologies Private Limited. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ohQ6cIMDBEmc",
        "colab_type": "text"
      },
      "source": [
        "# New Section"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z7fYqw5FYhQV",
        "colab_type": "text"
      },
      "source": [
        "###Installations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mZtyWC5brIoK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        },
        "outputId": "79568ad2-f39c-46d1-d6cf-4dd979ea9b0a"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive', force_remount=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0s2TpdhQrFFR",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "path='/content/gdrive/My Drive/Data/'\n",
        "project='googlesearch keyword comparison'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zOxyx8Ja2ujY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "outputId": "92b3ed70-4b9b-476e-a364-99857d240216"
      },
      "source": [
        "!pip install pytrends"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting pytrends\n",
            "  Downloading https://files.pythonhosted.org/packages/96/53/a4a74c33bfdbe1740183e00769377352072e64182913562daf9f5e4f1938/pytrends-4.7.3-py3-none-any.whl\n",
            "Requirement already satisfied: pandas>=0.25 in /usr/local/lib/python3.6/dist-packages (from pytrends) (1.0.5)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from pytrends) (2.23.0)\n",
            "Requirement already satisfied: lxml in /usr/local/lib/python3.6/dist-packages (from pytrends) (4.2.6)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.25->pytrends) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.25->pytrends) (2.8.1)\n",
            "Requirement already satisfied: numpy>=1.13.3 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.25->pytrends) (1.18.5)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->pytrends) (2020.6.20)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->pytrends) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->pytrends) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->pytrends) (1.24.3)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.6.1->pandas>=0.25->pytrends) (1.12.0)\n",
            "Installing collected packages: pytrends\n",
            "Successfully installed pytrends-4.7.3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Tb2C0TUs20mV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pytrends\n",
        "from pytrends.request import TrendReq\n",
        "import pandas as pd\n",
        "import time\n",
        "import datetime\n",
        "from datetime import datetime, date, time"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_MDYLATaYpN8",
        "colab_type": "text"
      },
      "source": [
        "###Get inputs as a list"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "07jjaq6WZ1v9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        },
        "outputId": "38797bd5-ba18-48c5-cda6-c09e85e44365"
      },
      "source": [
        "a = input(\"Compare Search Trends (Provide keywords seperated by commas):\")\n",
        "kw_list=a.split(',')\n",
        "print(kw_list)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Compare Search Trends (Provide keywords seperated by commas):Cold,Fever,Headaches\n",
            "['Cold', 'Fever', 'Headaches']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lr457Jc-zlgQ",
        "colab_type": "text"
      },
      "source": [
        "###Get google search trends data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ppEgFvapnoeF",
        "colab_type": "text"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w0rQ_-cD23U4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "\n",
        "pytrend = TrendReq(retries=50, backoff_factor=0.5)\n",
        "pytrend.build_payload(kw_list=kw_list, timeframe='today 5-y', geo = 'IN')\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XAcB_Ghv2-Ag",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 431
        },
        "outputId": "c484fe1e-5d5c-4465-fb9e-50f7f49a8202"
      },
      "source": [
        "interest_over_time_df = pytrend.interest_over_time() \n",
        "interest_over_time_df"
      ],
      "execution_count": null,
      "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>Cold</th>\n",
              "      <th>Fever</th>\n",
              "      <th>Headaches</th>\n",
              "      <th>isPartial</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-07-19</th>\n",
              "      <td>30</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-07-26</th>\n",
              "      <td>30</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-08-02</th>\n",
              "      <td>31</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-08-09</th>\n",
              "      <td>30</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-08-16</th>\n",
              "      <td>31</td>\n",
              "      <td>30</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-14</th>\n",
              "      <td>44</td>\n",
              "      <td>41</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-21</th>\n",
              "      <td>43</td>\n",
              "      <td>41</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-28</th>\n",
              "      <td>49</td>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-07-05</th>\n",
              "      <td>50</td>\n",
              "      <td>47</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-07-12</th>\n",
              "      <td>50</td>\n",
              "      <td>53</td>\n",
              "      <td>1</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>261 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Cold  Fever  Headaches isPartial\n",
              "date                                        \n",
              "2015-07-19    30     26          1     False\n",
              "2015-07-26    30     27          1     False\n",
              "2015-08-02    31     27          1     False\n",
              "2015-08-09    30     26          1     False\n",
              "2015-08-16    31     30          1     False\n",
              "...          ...    ...        ...       ...\n",
              "2020-06-14    44     41          1     False\n",
              "2020-06-21    43     41          1     False\n",
              "2020-06-28    49     45          1     False\n",
              "2020-07-05    50     47          1     False\n",
              "2020-07-12    50     53          1      True\n",
              "\n",
              "[261 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pG-IfL4AziiI",
        "colab_type": "text"
      },
      "source": [
        "###Generate Chart"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MK3Oz_h9H1K1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "c63f152d-0981-4b42-b184-c453862119cc"
      },
      "source": [
        "!python -m pip install -U matplotlib\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting matplotlib\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/93/ae/81b1c98ae97350711adb021ee12ea678b37f608ec2faa35c3a7db11795fa/matplotlib-3.3.0-1-cp36-cp36m-manylinux1_x86_64.whl (11.5MB)\n",
            "\u001b[K     |████████████████████████████████| 11.5MB 2.6MB/s \n",
            "\u001b[?25hRequirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib) (1.2.0)\n",
            "Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib) (2.8.1)\n",
            "Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib) (0.10.0)\n",
            "Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /usr/local/lib/python3.6/dist-packages (from matplotlib) (2.4.7)\n",
            "Requirement already satisfied, skipping upgrade: numpy>=1.15 in /usr/local/lib/python3.6/dist-packages (from matplotlib) (1.18.5)\n",
            "Requirement already satisfied, skipping upgrade: pillow>=6.2.0 in /usr/local/lib/python3.6/dist-packages (from matplotlib) (7.0.0)\n",
            "Requirement already satisfied, skipping upgrade: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.1->matplotlib) (1.12.0)\n",
            "\u001b[31mERROR: albumentations 0.1.12 has requirement imgaug<0.2.7,>=0.2.5, but you'll have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Installing collected packages: matplotlib\n",
            "  Found existing installation: matplotlib 3.2.2\n",
            "    Uninstalling matplotlib-3.2.2:\n",
            "      Successfully uninstalled matplotlib-3.2.2\n",
            "Successfully installed matplotlib-3.3.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i2HOSlQq3I58",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 546
        },
        "outputId": "ef841232-d68a-4a1f-855b-af2af67f57d4"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.image as image\n",
        "\n",
        "im = image.imread(path+'decodem logo with research firm.png')\n",
        "\n",
        "fig, ax = plt.subplots(figsize = (12, 8))\n",
        "\n",
        "ax1 = plt.axes([0.79,0.1, 0.1, 0.1], frameon=False)  # Change the numbers in this array to position your image [left, bottom, width, height])\n",
        "ax1.imshow(im,)\n",
        "ax1.axis('off')\n",
        "\n",
        "dx = interest_over_time_df.plot.line(figsize = (12,8), title = \"Interest Over Time\",colormap='Set1', linewidth=3,ax=ax)\n",
        "dx.set_xlabel('Date',fontsize=22)\n",
        "dx.set_ylabel('Trends Index',fontsize=22)\n",
        "dx.tick_params(axis='both', which='major', labelsize=22)\n",
        "dx.legend(fontsize=15)\n",
        "dx.set_title('Comparison Across Keywords',fontsize=30)\n",
        "\n",
        "dx.text(2640,-2,'Machine Generated Insights', style='italic', bbox={'facecolor': 'grey', 'alpha': 0.5, 'pad': 3}, rotation=270)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "maBoW43czgRa",
        "colab_type": "text"
      },
      "source": [
        "###End"
      ]
    }
  ]
}