Google Trends - PyTrends - Notebook.ipynb

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   "source": [
    "This notebook explore the availability and shape of Google Trends data, as well as the functions of the PyTrends package. Some of this code was tested here and then written in Atom as a python file and run in command line. \n",
    "\n",
    "Installation / docs for PyTrends here: \n",
    "\n",
    "https://github.com/GeneralMills/pytrends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pytrends.request import TrendReq\n",
    "\n",
    "pytrends = TrendReq(hl='en-US', tz=360)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'mid': '/m/0108bn2x', 'title': 'Ethereum', 'type': 'Topic'}]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pytrends.suggestions('ethereum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# kw_list = [\"Blockchain\"]\n",
    "# timeframe = '2017-02-26 2018-09-01'\n",
    "# pytrends.build_payload(kw_list, , timeframe='today 5-y')\n",
    "# time.sleep(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Would prefer hourly historical data to match up with existing \n",
    "\n",
    "kw_list = ['Ethereum', 'eth', 'bitcoin', 'blockchain', 'buy ethereum']\n",
    "\n",
    "test = pytrends.get_historical_interest(kw_list, \n",
    "                                         year_start=2017, month_start=2, day_start=20, hour_start=0, \n",
    "                                         year_end=2018, month_end=9, day_end=8, hour_end=0, \n",
    "                                         cat=0, geo='', gprop='', sleep=4)\n",
    "\n",
    "# Usage note: it'll only return 'weeks' for hourly data. So if you tried to grab six days, it wouldn't return\n",
    "# anything and if you tried to grab eight days, it'll only return seven. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>banana</th>\n",
       "      <th>Banana</th>\n",
       "      <th>isPartial</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
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       "      <th>2018-01-01 00:00:00</th>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>2018-01-01 01:00:00</th>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 02:00:00</th>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 03:00:00</th>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 04:00:00</th>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "                     banana  Banana  isPartial\n",
       "date                                          \n",
       "2018-01-01 00:00:00      74      74      False\n",
       "2018-01-01 01:00:00      75      75      False\n",
       "2018-01-01 02:00:00      72      72      False\n",
       "2018-01-01 03:00:00      70      70      False\n",
       "2018-01-01 04:00:00      63      63      False"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()\n",
    "\n",
    "# tested on two words, banana and Banana - does not appear to be case sensitive "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(169, 3)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>2018-01-07 20:00:00</th>\n",
       "      <td>85</td>\n",
       "      <td>85</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>2018-01-07 21:00:00</th>\n",
       "      <td>88</td>\n",
       "      <td>88</td>\n",
       "      <td>False</td>\n",
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       "      <th>2018-01-07 22:00:00</th>\n",
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       "      <td>False</td>\n",
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       "      <th>2018-01-07 23:00:00</th>\n",
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       "                     banana  Banana  isPartial\n",
       "date                                          \n",
       "2018-01-07 20:00:00      85      85      False\n",
       "2018-01-07 21:00:00      88      88      False\n",
       "2018-01-07 22:00:00      94      94      False\n",
       "2018-01-07 23:00:00     100     100      False\n",
       "2018-01-08 00:00:00      96      96      False"
      ]
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     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "test.tail()"
   ]
  }
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