{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unzip a pre-harvested dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make it easier to start exploring the NMA data without harvesting it all yourself, I've zipped up some pre-harvested versions of the `object`, `party`, and `place` data. to unzip it and make the datasets available to the notebooks in this repository just run this cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipfile import ZipFile\n",
    "\n",
    "with ZipFile('nma_data.zip', 'r') as zipObj:\n",
    "    \n",
    "    # Extract all the contents of zip file in current directory\n",
    "    zipObj.extractall()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These datasets were harvested in July 2020. If you're doing detailed analysis, I'd strongly suggest you harvest your own to make sure you have the most recent data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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