07-finanical-sentiment/explore-data.ipynb

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   "source": [
    "## Data Downloading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
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   "source": [
    "%%bash\n",
    "sudo yum install -y unzip\n",
    "mkdir target\n",
    "curl 'https://static.us-east-1.prod.workshops.aws/public/40de25f9-f9de-4fba-8871-0bf4761d175e/static/resources/finserv/sentiment.zip' --output sentiment.zip\n",
    "unzip sentiment.zip -d target\n",
    "mkdir data\n",
    "mv ./target/sentiment/data/data.csv ./data/\n",
    "rm -rf target\n",
    "rm sentiment.zip"
   ]
  },
  {
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   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "import pandas as pd\n",
    "import sagemaker"
   ]
  },
  {
   "cell_type": "markdown",
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    "deletable": true,
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   },
   "source": [
    "### Explore data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "button": false,
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    "new_sheet": false,
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   "outputs": [],
   "source": [
    "inverse_label_map = {0: 'negative', 1: 'positive', 2: 'neutral'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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    "deletable": true,
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   "source": [
    "df = pd.read_csv('./data/data.csv', names=['label', 'headline'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "outputs": [],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "df['headline'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "inverse_label_map[df['label'][0]]"
   ]
  }
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