examples/Getting_Started/Getting Started with a Dask Example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dd2d6783",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3516d2d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import pyscisci.all as pyscisci\n",
    "\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "import dask.dataframe as dd\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9265c653",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set this path to where the MAG database will be stored\n",
    "path2mag = '/home/ajgates/MAG'\n",
    "path2mag = '/users/hgt6rn/Documents/DataSets/MAG'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9ae59de0",
   "metadata": {},
   "outputs": [],
   "source": [
    "mymag = pyscisci.MAG(path2mag, database_extension='csv.gz', enable_dask=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8cdec26a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a52584b761bb4d14931200e6e0828df5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Loading Publications:   0%|          | 0/132 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "magpubs = mymag.load_publications(columns=['PublicationId', 'Year', 'JournalId', 'DocType'],\n",
    "                                  dropna = ['Year', 'JournalId', 'DocType'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b74345ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "magpubs = magpubs[magpubs['DocType'] == 'j']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "335c768f",
   "metadata": {},
   "outputs": [],
   "source": [
    "npubs_mag = magpubs.groupby('Year')['PublicationId'].nunique().compute()\n",
    "njournals_mag = magpubs.groupby('Year')['JournalId'].nunique().compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "01bdb99b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>NumPubs</th>\n",
       "      <th>NumJournals</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1800.0</td>\n",
       "      <td>661</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1801.0</td>\n",
       "      <td>165</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1802.0</td>\n",
       "      <td>237</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1805.0</td>\n",
       "      <td>219</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1806.0</td>\n",
       "      <td>233</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>1371</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>1803.0</td>\n",
       "      <td>264</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>1804.0</td>\n",
       "      <td>198</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>1816.0</td>\n",
       "      <td>300</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>1817.0</td>\n",
       "      <td>274</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>223 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Year  NumPubs  NumJournals\n",
       "0    1800.0      661           38\n",
       "1    1801.0      165            5\n",
       "2    1802.0      237            6\n",
       "3    1805.0      219            5\n",
       "4    1806.0      233            5\n",
       "..      ...      ...          ...\n",
       "218  2022.0     1371          116\n",
       "219  1803.0      264            5\n",
       "220  1804.0      198            6\n",
       "221  1816.0      300           10\n",
       "222  1817.0      274           12\n",
       "\n",
       "[223 rows x 3 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mag_values = npubs_mag.to_frame().reset_index().merge(njournals_mag.to_frame().reset_index(), how='left', on='Year')\n",
    "mag_values = mag_values.rename(columns={'PublicationId':'NumPubs', 'JournalId':'NumJournals'})\n",
    "mag_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d95e5f95",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "mag_color = '#12664F'\n",
    "\n",
    "dflabels = ['MAG']\n",
    "dfcolors = [mag_color]\n",
    "dfs = [mag_values.sort_values('Year')]\n",
    "\n",
    "vmax = 2017\n",
    "\n",
    "fig, ax = plt.subplots(2, 1, figsize=(6, 8))\n",
    "\n",
    "for idf in range(1):\n",
    "    idy = np.logical_and(dfs[idf]['Year'].values > 1000, dfs[idf]['Year'].values < vmax)\n",
    "    for iax,v in enumerate(['NumPubs', 'NumJournals']):\n",
    "        ax[iax].plot(dfs[idf]['Year'].values[idy], dfs[idf][v].values[idy], lw=3, \n",
    "               color=dfcolors[idf], label=dflabels[idf])\n",
    "    #ax[1].plot(njournals_dblp.index.values[years], njournals_dblp.values[years], lw=2, color=dblp_color)\n",
    "    #ax[2].plot(nauthors_dblp.index.values[years], nauthors_dblp.values[years], lw=2, color=dblp_color)\n",
    "\n",
    "ax[0].set_ylabel('Number of publications')\n",
    "ax[1].set_ylabel('Number of journals')\n",
    "\n",
    "\n",
    "handles, labels = ax[0].get_legend_handles_labels()\n",
    "ax[0].legend(handles, labels, loc='lower left')\n",
    "\n",
    "for iax in range(2):\n",
    "    ax[iax].set_yscale('log')\n",
    "    \n",
    "    ax[iax].set_xlim([1800, 2020])\n",
    "\n",
    "for iax in [0]:\n",
    "    ax[iax].set_yticks([10**0, 10**2, 10**4, 10**6])\n",
    "\n",
    "plt.show()"
   ]
  },
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