example.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 2,
  "metadata": {
    "colab": {
      "name": "Demo Notebook.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## Dataset 🧾"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "source": [
        "!gdown --id 1DHjy_vso6DhuN3xMsz6_TerdgHibVuqi"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1DHjy_vso6DhuN3xMsz6_TerdgHibVuqi\n",
            "To: /content/Musical_instruments_reviews.csv\n",
            "\r0.00B [00:00, ?B/s]\r6.09MB [00:00, 95.4MB/s]\n"
          ]
        }
      ],
      "metadata": {
        "id": "gKYJBrKJ-9yI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        },
        "outputId": "3c5220a3-f3ff-47c1-d910-0b7939708f5b"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Reading the data 💿"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "source": [
        "import pandas as pd\n",
        "df = pd.read_csv('/content/Musical_instruments_reviews.csv') "
      ],
      "outputs": [],
      "metadata": {
        "id": "-aJTPiTTEpca",
        "colab_type": "code",
        "colab": {}
      }
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "source": [
        "df.head() "
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       reviewerID        asin  ... unixReviewTime   reviewTime\n",
              "0  A2IBPI20UZIR0U  1384719342  ...     1393545600  02 28, 2014\n",
              "1  A14VAT5EAX3D9S  1384719342  ...     1363392000  03 16, 2013\n",
              "2  A195EZSQDW3E21  1384719342  ...     1377648000  08 28, 2013\n",
              "3  A2C00NNG1ZQQG2  1384719342  ...     1392336000  02 14, 2014\n",
              "4   A94QU4C90B1AX  1384719342  ...     1392940800  02 21, 2014\n",
              "\n",
              "[5 rows x 9 columns]"
            ],
            "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>reviewerID</th>\n",
              "      <th>asin</th>\n",
              "      <th>reviewerName</th>\n",
              "      <th>helpful</th>\n",
              "      <th>reviewText</th>\n",
              "      <th>overall</th>\n",
              "      <th>summary</th>\n",
              "      <th>unixReviewTime</th>\n",
              "      <th>reviewTime</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A2IBPI20UZIR0U</td>\n",
              "      <td>1384719342</td>\n",
              "      <td>cassandra tu \"Yeah, well, that's just like, u...</td>\n",
              "      <td>[0, 0]</td>\n",
              "      <td>Not much to write about here, but it does exac...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>good</td>\n",
              "      <td>1393545600</td>\n",
              "      <td>02 28, 2014</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A14VAT5EAX3D9S</td>\n",
              "      <td>1384719342</td>\n",
              "      <td>Jake</td>\n",
              "      <td>[13, 14]</td>\n",
              "      <td>The product does exactly as it should and is q...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Jake</td>\n",
              "      <td>1363392000</td>\n",
              "      <td>03 16, 2013</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A195EZSQDW3E21</td>\n",
              "      <td>1384719342</td>\n",
              "      <td>Rick Bennette \"Rick Bennette\"</td>\n",
              "      <td>[1, 1]</td>\n",
              "      <td>The primary job of this device is to block the...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>It Does The Job Well</td>\n",
              "      <td>1377648000</td>\n",
              "      <td>08 28, 2013</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A2C00NNG1ZQQG2</td>\n",
              "      <td>1384719342</td>\n",
              "      <td>RustyBill \"Sunday Rocker\"</td>\n",
              "      <td>[0, 0]</td>\n",
              "      <td>Nice windscreen protects my MXL mic and preven...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>GOOD WINDSCREEN FOR THE MONEY</td>\n",
              "      <td>1392336000</td>\n",
              "      <td>02 14, 2014</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A94QU4C90B1AX</td>\n",
              "      <td>1384719342</td>\n",
              "      <td>SEAN MASLANKA</td>\n",
              "      <td>[0, 0]</td>\n",
              "      <td>This pop filter is great. It looks and perform...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>No more pops when I record my vocals.</td>\n",
              "      <td>1392940800</td>\n",
              "      <td>02 21, 2014</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ],
      "metadata": {
        "id": "jJrqfy-g8DWf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 305
        },
        "outputId": "a63ec650-87dd-4ce6-ebbc-25f88c7d5294"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "source": [
        "df = df[['reviewText', 'overall']] "
      ],
      "outputs": [],
      "metadata": {
        "id": "qyCtrPGM8VP3",
        "colab_type": "code",
        "colab": {}
      }
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "source": [
        "df.head() "
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                          reviewText  overall\n",
              "0  Not much to write about here, but it does exac...      5.0\n",
              "1  The product does exactly as it should and is q...      5.0\n",
              "2  The primary job of this device is to block the...      5.0\n",
              "3  Nice windscreen protects my MXL mic and preven...      5.0\n",
              "4  This pop filter is great. It looks and perform...      5.0"
            ],
            "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>reviewText</th>\n",
              "      <th>overall</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Not much to write about here, but it does exac...</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>The product does exactly as it should and is q...</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>The primary job of this device is to block the...</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Nice windscreen protects my MXL mic and preven...</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>This pop filter is great. It looks and perform...</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ],
      "metadata": {
        "id": "0vCdGB8K8cPH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 201
        },
        "outputId": "0e264870-a0a0-443d-9abe-2f4644e54634"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## OneShot is all you need 🤫"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "source": [
        "!pip install git+https://github.com/nakshatrasinghh/OneShot.git"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/nakshatrasinghh/Preprocess_Nakshatra.git\n",
            "  Cloning https://github.com/nakshatrasinghh/Preprocess_Nakshatra.git to /tmp/pip-req-build-rr1lqrsd\n",
            "  Running command git clone -q https://github.com/nakshatrasinghh/Preprocess_Nakshatra.git /tmp/pip-req-build-rr1lqrsd\n",
            "Requirement already satisfied (use --upgrade to upgrade): Preprocess-Nakshatra==0.0.5 from git+https://github.com/nakshatrasinghh/Preprocess_Nakshatra.git in /usr/local/lib/python3.6/dist-packages\n",
            "Building wheels for collected packages: Preprocess-Nakshatra\n",
            "  Building wheel for Preprocess-Nakshatra (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for Preprocess-Nakshatra: filename=Preprocess_Nakshatra-0.0.5-cp36-none-any.whl size=5192 sha256=7d425be410f52c52cb7375ec3f89978a315ca5e7799cf7a8279bff03612bc37d\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-dwup0dv9/wheels/7c/40/7e/506590ed754a94a7d77c429bda69f1fb4a260a7d5905403d03\n",
            "Successfully built Preprocess-Nakshatra\n"
          ]
        }
      ],
      "metadata": {
        "id": "m0_fNNrr8c_4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        },
        "outputId": "54a8ef34-5c38-466e-c4cc-0e9e71ea61ae"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "source": [
        "!python -m spacy download en_core_web_md\n",
        "import OneShot as osx\n",
        "import re"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: en_core_web_md==2.2.5 from https://github.com/explosion/spacy-models/releases/download/en_core_web_md-2.2.5/en_core_web_md-2.2.5.tar.gz#egg=en_core_web_md==2.2.5 in /usr/local/lib/python3.6/dist-packages (2.2.5)\n",
            "Requirement already satisfied: spacy>=2.2.2 in /usr/local/lib/python3.6/dist-packages (from en_core_web_md==2.2.5) (2.2.4)\n",
            "Requirement already satisfied: wasabi<1.1.0,>=0.4.0 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (0.7.1)\n",
            "Requirement already satisfied: numpy>=1.15.0 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (1.18.5)\n",
            "Requirement already satisfied: thinc==7.4.0 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (7.4.0)\n",
            "Requirement already satisfied: requests<3.0.0,>=2.13.0 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (2.23.0)\n",
            "Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (2.0.3)\n",
            "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (1.0.2)\n",
            "Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (3.0.2)\n",
            "Requirement already satisfied: catalogue<1.1.0,>=0.0.7 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (1.0.0)\n",
            "Requirement already satisfied: plac<1.2.0,>=0.9.6 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (1.1.3)\n",
            "Requirement already satisfied: blis<0.5.0,>=0.4.0 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (0.4.1)\n",
            "Requirement already satisfied: srsly<1.1.0,>=1.0.2 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (1.0.2)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (49.6.0)\n",
            "Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /usr/local/lib/python3.6/dist-packages (from spacy>=2.2.2->en_core_web_md==2.2.5) (4.41.1)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_md==2.2.5) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_md==2.2.5) (3.0.4)\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<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_md==2.2.5) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_md==2.2.5) (2020.6.20)\n",
            "Requirement already satisfied: importlib-metadata>=0.20; python_version < \"3.8\" in /usr/local/lib/python3.6/dist-packages (from catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->en_core_web_md==2.2.5) (1.7.0)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.6/dist-packages (from importlib-metadata>=0.20; python_version < \"3.8\"->catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->en_core_web_md==2.2.5) (3.1.0)\n",
            "\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
            "You can now load the model via spacy.load('en_core_web_md')\n"
          ]
        }
      ],
      "metadata": {
        "id": "iXgr5ar38v03",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "outputId": "c2de19f0-04c7-46c6-da42-55c4a1ac3299"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "source": [
        "def get_clean(x):\n",
        "    x = str(x).lower().replace('\\\\', '').replace('_', ' ')\n",
        "    x = osx.cont_exp(x)\n",
        "    x = osx.remove_emails(x)\n",
        "    x = osx.remove_urls(x)\n",
        "    x = osx.remove_html_tags(x)\n",
        "    x = osx.remove_rt(x)\n",
        "    x = osx.remove_mentions(x)\n",
        "    x = osx.remove_accented_chars(x)\n",
        "    x = osx.remove_special_chars(x)\n",
        "    x = osx.remove_stopwords(x)\n",
        "    x = osx.remove_dups_char(x)\n",
        "    x = re.sub(\"(.)\\\\1{2,}\", \"\\\\1\", x)\n",
        "    return x "
      ],
      "outputs": [],
      "metadata": {
        "id": "RMhkXekk8_dX",
        "colab_type": "code",
        "colab": {}
      }
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "source": [
        "df['Cleaned_reviewText'] = df['reviewText'].apply(lambda x: get_clean(x)) "
      ],
      "outputs": [],
      "metadata": {
        "id": "aHmtjCqI-ySp",
        "colab_type": "code",
        "colab": {}
      }
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "source": [
        "df.head() "
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                          reviewText  ...                                 Cleaned_reviewText\n",
              "0  Not much to write about here, but it does exac...  ...  not much to write about here but it does exact...\n",
              "1  The product does exactly as it should and is q...  ...  the product does exactly as it should and is q...\n",
              "2  The primary job of this device is to block the...  ...  the primary job of this device is to block the...\n",
              "3  Nice windscreen protects my MXL mic and preven...  ...  nice windscreen protects my mxl mic and preven...\n",
              "4  This pop filter is great. It looks and perform...  ...  this pop filter is great it looks and performs...\n",
              "\n",
              "[5 rows x 3 columns]"
            ],
            "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>reviewText</th>\n",
              "      <th>overall</th>\n",
              "      <th>Cleaned_reviewText</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Not much to write about here, but it does exac...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>not much to write about here but it does exact...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>The product does exactly as it should and is q...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>the product does exactly as it should and is q...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>The primary job of this device is to block the...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>the primary job of this device is to block the...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Nice windscreen protects my MXL mic and preven...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>nice windscreen protects my mxl mic and preven...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>This pop filter is great. It looks and perform...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>this pop filter is great it looks and performs...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ],
      "metadata": {
        "id": "6R57NHCD-7_Q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 201
        },
        "outputId": "dc3bcc74-49d0-485a-c115-7bc9ae0e2d21"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Star the repo ❤️"
      ],
      "metadata": {}
    }
  ]
}