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Upload IoT23DatasetPreprocessingNotebook.ipynb

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IoT23DatasetPreprocessingNotebook.ipynb ADDED
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "metadata": {
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+ "id": "YbyU8YKP5KOh"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Capture to supress the download ouput\n",
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+ "%%capture\n",
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+ "!pip install datasets evaluate transformers;\n",
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+ "!pip install huggingface_hub;\n",
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+ "!pip install pandas;"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 18,
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "hzlMD2hyVrtD",
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+ "outputId": "53ad9ba2-a64b-4bd8-eeca-4449035b0595"
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+ },
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+ "outputs": [
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+ {
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+ "output_type": "stream",
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+ "name": "stdout",
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+ "text": [
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+ "Mounted at /content/drive\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "# Load dataset with google drive\n",
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+ "# We downloaded the dataset from kaggle and uploaded it to google drive, then used google colab to load\n",
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+ "# It is possible to download it directly using the kaggle api\n",
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+ "\n",
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+ "# Link to dataset: https://www.kaggle.com/datasets/engraqeel/iot23preprocesseddata?resource=download\n",
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+ "# Link to kaggle api docs: https://www.kaggle.com/docs/api#interacting-with-datasets\n",
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+ "\n",
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+ "from google.colab import drive\n",
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+ "drive.mount('/content/drive')\n",
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+ "reduced_iot_path = \"/content/drive/MyDrive/_Final Semester/Networks/CS513 Final Project/Resources/iot23_combined_new.csv\""
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 19,
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+ "metadata": {
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+ "id": "9fLFeygkITnn"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "import pandas as pd\n",
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+ "\n",
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+ "# Define Features\n",
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+ "# ts\tuid\tid.orig_h\tid.orig_p\tid.resp_h\tid.resp_p\tproto\tservice\tduration\torig_bytes\tresp_bytes\tconn_state\tlocal_orig\tlocal_resp\tmissed_bytes\thistory\torig_pkts\torig_ip_bytes\tresp_pkts\tresp_ip_bytes\tlabel\n",
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+ "# https://docs.zeek.org/en/master/scripts/base/protocols/conn/main.zeek.html#type-Conn::Info\n",
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+ "\n",
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+ "pandas_features = {\n",
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+ " 'id.orig_p': int,\n",
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+ " 'id.resp_p': int,\n",
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+ " 'proto': str,\n",
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+ " 'service': str,\n",
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+ " 'duration': float,\n",
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+ " 'orig_bytes': pd.Int64Dtype(),\n",
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+ " 'resp_bytes': pd.Int64Dtype(),\n",
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+ " 'conn_state': str,\n",
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+ " 'missed_bytes': pd.Int64Dtype(),\n",
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+ " 'history': str,\n",
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+ " 'orig_pkts': pd.Int64Dtype(),\n",
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+ " 'orig_ip_bytes': pd.Int64Dtype(),\n",
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+ " 'resp_pkts': pd.Int64Dtype(),\n",
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+ " 'resp_ip_bytes': pd.Int64Dtype(),\n",
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+ " 'label': str\n",
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+ "}\n",
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+ "\n",
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+ "all_column_names = ['ts', 'uid', 'id.orig_h', 'id.orig_p', 'id.resp_h', 'id.resp_p', 'proto', 'service', 'duration', 'orig_bytes', 'resp_bytes', 'conn_state', 'local_orig', 'local_resp', 'missed_bytes', 'history', 'orig_pkts', 'orig_ip_bytes', 'resp_pkts', 'resp_ip_bytes', 'label'];\n",
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+ "important_column_names = ['id.resp_p', 'proto', 'conn_state', 'orig_pkts', 'orig_ip_bytes', 'resp_ip_bytes', 'label'];\n",
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+ "exclude_column_names = ['ts','uid','id.orig_h', 'id.resp_h', 'local_orig', 'local_resp']\n",
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+ "\n",
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+ "column_names = [column for column in all_column_names if column not in exclude_column_names]"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 20,
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+ "metadata": {
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+ "id": "Zll2DOeT9yv2"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Load dataset with Pandas\n",
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+ "from datasets import Dataset\n",
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+ "import pandas as pd\n",
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+ "reduced_iot_dataset_pandas = pd.read_csv(reduced_iot_path, usecols=column_names, na_values=['-'], dtype=pandas_features)"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 21,
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+ "metadata": {
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+ "id": "SUb01Eg7I7wS"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Remove Duplicates\n",
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+ "reduced_iot_dataset_pandas = reduced_iot_dataset_pandas.drop_duplicates()"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "# Make label Benign / Malicious\n",
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+ "reduced_iot_dataset_pandas['label'] = reduced_iot_dataset_pandas['label'].apply(lambda x: \"Benign\" if x == \"Benign\" else \"Malicious\")"
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+ ],
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+ "metadata": {
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+ "id": "M06Rb8fj2fzk"
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+ },
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+ "execution_count": null,
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+ "outputs": []
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": null,
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "xamjYrWbgxkf",
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+ "outputId": "1ddb22b6-98ab-44b4-83e1-b995e8c1ea4a"
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+ },
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+ "outputs": [
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+ {
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+ "output_type": "execute_result",
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+ "data": {
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+ "text/plain": [
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+ "orig_bytes\n",
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+ "0 564771\n",
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+ "<NA> 241092\n",
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+ "48 2121\n",
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+ "29 1463\n",
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+ "45 1348\n",
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+ " ... \n",
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+ "1088 1\n",
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+ "1093 1\n",
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+ "1094 1\n",
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+ "1104 1\n",
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+ "770 1\n",
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+ "Length: 431, dtype: int64"
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+ ]
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+ },
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+ "metadata": {},
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+ "execution_count": 8
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+ }
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+ ],
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+ "source": [
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+ "# Test distribution of data\n",
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+ "reduced_iot_dataset_pandas.value_counts('orig_bytes', dropna=False)"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": null,
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+ "metadata": {
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+ "id": "Js3KG0xNvwpf"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Final step: convert to hugging face dataset\n",
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+ "reduced_iot_dataset = Dataset.from_pandas(reduced_iot_dataset_pandas).remove_columns(\"__index_level_0__\")"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "# Test distribution of data again\n",
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+ "reduced_iot_dataset.to_pandas().value_counts('orig_bytes', dropna=False)"
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+ ],
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "pOxVs7H-0-3k",
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+ "outputId": "dcd084dd-3369-4d8e-91ca-c9fbfc1636f0"
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+ },
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+ "execution_count": null,
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+ "outputs": [
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+ {
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+ "output_type": "execute_result",
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+ "data": {
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+ "text/plain": [
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+ "orig_bytes\n",
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+ "0.0 564771\n",
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+ "NaN 241092\n",
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+ "48.0 2121\n",
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+ "29.0 1463\n",
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+ "45.0 1348\n",
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+ " ... \n",
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+ "1088.0 1\n",
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+ "1093.0 1\n",
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+ "1094.0 1\n",
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+ "1104.0 1\n",
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+ "770.0 1\n",
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+ "Length: 431, dtype: int64"
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+ ]
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+ },
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+ "metadata": {},
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+ "execution_count": 12
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+ }
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "# Authenticate hugging face\n",
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+ "!huggingface-cli login"
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+ ],
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "pq6DF3Z8wdmF",
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+ "outputId": "aaf5e476-96ce-4edc-d65c-858a7e4e52ec"
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+ },
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+ "execution_count": null,
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+ "outputs": [
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+ {
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+ "output_type": "stream",
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+ "name": "stdout",
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+ "text": [
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+ "\n",
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+ " _| _| _| _| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _|_|_|_| _|_| _|_|_| _|_|_|_|\n",
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+ " _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|\n",
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+ " _|_|_|_| _| _| _| _|_| _| _|_| _| _| _| _| _| _|_| _|_|_| _|_|_|_| _| _|_|_|\n",
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+ " _| _| _| _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _|\n",
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+ " _| _| _|_| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _| _| _| _|_|_| _|_|_|_|\n",
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+ " \n",
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+ " A token is already saved on your machine. Run `huggingface-cli whoami` to get more information or `huggingface-cli logout` if you want to log out.\n",
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+ " Setting a new token will erase the existing one.\n",
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+ " To login, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n",
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+ "Token: \n",
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+ "Add token as git credential? (Y/n) Y\n",
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+ "Token is valid (permission: write).\n",
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+ "Your token has been saved in your configured git credential helpers (store).\n",
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+ "Your token has been saved to /root/.cache/huggingface/token\n",
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+ "Login successful\n"
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+ ]
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+ }
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "# Push to the hugging face hub\n",
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+ "reduced_iot_dataset.push_to_hub(\"19kmunz/iot-23-preprocessed-allcolumns\")"
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+ ],
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+ "metadata": {
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+ "id": "Nz5RwnjxwnwY"
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+ },
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+ "execution_count": null,
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+ "outputs": []
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "# Test loading the data set\n",
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+ "from datasets import load_dataset\n",
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+ "pulledDataSet= load_dataset(\"19kmunz/iot-23-preprocessed\", download_mode=\"force_redownload\")"
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+ ],
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+ "metadata": {
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+ "id": "6rMEA58Pzlyx"
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+ },
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+ "execution_count": null,
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+ "outputs": []
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+ }
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+ ],
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+ "metadata": {
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+ "colab": {
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+ "provenance": []
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+ },
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+ "kernelspec": {
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+ "display_name": "Python 3",
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+ "name": "python3"
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+ },
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+ "language_info": {
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+ "name": "python"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 0
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+ }