LinkedIn/LinkedIn_Get_connections_from_network.ipynb

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   "source": [
    "<img width=\"10%\" alt=\"Naas\" src=\"https://landen.imgix.net/jtci2pxwjczr/assets/5ice39g4.png?w=160\"/>"
   ]
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  {
   "cell_type": "markdown",
   "id": "federal-pixel",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "# LinkedIn - Get connections from network\n",
    "<a href=\"https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_connections_from_network.ipynb\" target=\"_parent\"><img src=\"https://img.shields.io/badge/-Open%20in%20Naas-success?labelColor=000000&logo=data:image/svg+xml;base64,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\"/></a>"
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   "source": [
    "**Tags**: #linkedin #network #connections #naas_drivers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "normal-rochester",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "## Input"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "import_cell",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Import library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "recreational-season",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "from naas_drivers import linkedin"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "wrapped-benjamin",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Get your cookies\n",
    "<a href='https://www.notion.so/LinkedIn-driver-Get-your-cookies-d20a8e7e508e42af8a5b52e33f3dba75'>How to get your cookies ?</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "yellow-footage",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "LI_AT = 'YOUR_COOKIE_LI_AT'  # EXAMPLE AQFAzQN_PLPR4wAAAXc-FCKmgiMit5FLdY1af3-2\n",
    "JSESSIONID = 'YOUR_COOKIE_JSESSIONID'  # EXAMPLE ajax:8379907400220387585"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pediatric-emerald",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "differential-agenda",
   "metadata": {
    "execution": {
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    "tags": []
   },
   "source": [
    "Get the information return in a dataframe.<br><br>\n",
    "**Available columns :**\n",
    "- PROFILE_URN : LinkedIn unique profile id\n",
    "- CREATED_AT : Date of connection between and your connection\n",
    "- PROFILE_ID : LinkedIn public profile id\n",
    "- FIRSTNAME : First name\n",
    "- LASTNAME : Last name\n",
    "- OCCUPATION : Text below the name in the profile page"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "indoor-colon",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "df = linkedin.connect(LI_AT, JSESSIONID).network.get_connections()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "piano-stylus",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "## Output"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "micro-funds",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "source": [
    "### Display result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "threaded-minister",
   "metadata": {
    "papermill": {},
    "tags": []
   },
   "outputs": [],
   "source": [
    "df"
   ]
  }
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