adjacency_matrix.ipynb

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       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Platform</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30742</td>\n",
       "      <td>acacia</td>\n",
       "      <td>Cargo</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30745</td>\n",
       "      <td>aio</td>\n",
       "      <td>Cargo</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30746</td>\n",
       "      <td>advapi32-sys</td>\n",
       "      <td>Cargo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30747</td>\n",
       "      <td>alfred</td>\n",
       "      <td>Cargo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30748</td>\n",
       "      <td>algebloat</td>\n",
       "      <td>Cargo</td>\n",
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      "text/plain": [
       "      ID          Name Platform\n",
       "0  30742        acacia    Cargo\n",
       "1  30745           aio    Cargo\n",
       "2  30746  advapi32-sys    Cargo\n",
       "3  30747        alfred    Cargo\n",
       "4  30748     algebloat    Cargo"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import igraph as ig\n",
    "import pandas as pd\n",
    "from numpy.linalg import norm\n",
    "\n",
    "def l1_row(row):\n",
    "    row_sum = norm(row, ord=1)\n",
    "    if row_sum == 0:\n",
    "        return row\n",
    "    else:\n",
    "        return row / row_sum\n",
    "\n",
    "def norm_rows(df):\n",
    "    return df.apply(l1_row,axis=1)\n",
    "\n",
    "# list of all projects / accounts - will specify the ordering\n",
    "proj_meta = pd.read_csv('data/cargo-dependencies-meta.csv', delimiter=',', dtype={'ID': 'Int64'}).dropna();\n",
    "proj_ids = proj_meta['ID'].tolist()\n",
    "labels = proj_meta['Name'].tolist()\n",
    "# acc = ['a1', 'a2', 'a3']\n",
    "# labels = np.concatenate((proj,acc), axis=0)\n",
    "\n",
    "proj_meta.head()"
   ]
  },
  {
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   "execution_count": 2,
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   "outputs": [
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       "      <th></th>\n",
       "      <th>FROM_ID</th>\n",
       "      <th>TO_ID</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>31187</td>\n",
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       "      <th>2</th>\n",
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       "      <th>3</th>\n",
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       "      <td>31085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30742</td>\n",
       "      <td>428702</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "   FROM_ID   TO_ID\n",
       "0    30742   31187\n",
       "1    30742   31296\n",
       "2    30742   31295\n",
       "3    30742   31085\n",
       "4    30742  428702"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deps = pd.read_csv('data/cargo-dependencies.csv', delimiter=',');\n",
    "deps.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py:3209: DtypeWarning: Columns (2) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  if (yield from self.run_code(code, result)):\n"
     ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>maintainer</th>\n",
       "      <th>repo</th>\n",
       "      <th>contributions</th>\n",
       "      <th>Name</th>\n",
       "      <th>ID</th>\n",
       "      <th>Platform</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fe08d3c717adf2ae63592e4c9aec6e3e404d8e3e@davem...</td>\n",
       "      <td>Asus-T100/kernel</td>\n",
       "      <td>53029</td>\n",
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       "      <td>1748045</td>\n",
       "      <td>Cargo</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fe08d3c717adf2ae63592e4c9aec6e3e404d8e3e@davem...</td>\n",
       "      <td>julianjmaurer/kernel</td>\n",
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       "    <tr>\n",
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       "      <td>69652caca27c8b940640ad396ab71f93cacec34f@linux...</td>\n",
       "      <td>Asus-T100/kernel</td>\n",
       "      <td>42306</td>\n",
       "      <td>kernel</td>\n",
       "      <td>1748045</td>\n",
       "      <td>Cargo</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>fe08d3c717adf2ae63592e4c9aec6e3e404d8e3e@davem...</td>\n",
       "      <td>markgross/kernel</td>\n",
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       "      <td>kernel</td>\n",
       "      <td>1748045</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>69652caca27c8b940640ad396ab71f93cacec34f@linux...</td>\n",
       "      <td>julianjmaurer/kernel</td>\n",
       "      <td>41961</td>\n",
       "      <td>kernel</td>\n",
       "      <td>1748045</td>\n",
       "      <td>Cargo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "                                          maintainer                  repo  \\\n",
       "0  fe08d3c717adf2ae63592e4c9aec6e3e404d8e3e@davem...      Asus-T100/kernel   \n",
       "1  fe08d3c717adf2ae63592e4c9aec6e3e404d8e3e@davem...  julianjmaurer/kernel   \n",
       "2  69652caca27c8b940640ad396ab71f93cacec34f@linux...      Asus-T100/kernel   \n",
       "3  fe08d3c717adf2ae63592e4c9aec6e3e404d8e3e@davem...      markgross/kernel   \n",
       "4  69652caca27c8b940640ad396ab71f93cacec34f@linux...  julianjmaurer/kernel   \n",
       "\n",
       "  contributions    Name       ID Platform  \n",
       "0         53029  kernel  1748045    Cargo  \n",
       "1         52489  kernel  1748045    Cargo  \n",
       "2         42306  kernel  1748045    Cargo  \n",
       "3         42034  kernel  1748045    Cargo  \n",
       "4         41961  kernel  1748045    Cargo  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_contribs(csv_path, proj_names):\n",
    "    raw_contrib = pd.read_csv(csv_path, delimiter=\",\").dropna();\n",
    "    return raw_contrib[raw_contrib['Name'].isin(proj_names)].merge(proj_meta);\n",
    "\n",
    "contrib = get_contribs('data/gh-contributions.csv', labels)\n",
    "contributers = contrib['maintainer'].unique().tolist()\n",
    "contrib.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
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       "<p>5 rows × 48926 columns</p>\n",
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      "text/plain": [
       "       fe08d3c717adf2ae63592e4c9aec6e3e404d8e3e@davemloft.net  \\\n",
       "30742                                                  0        \n",
       "30745                                                  0        \n",
       "30746                                                  0        \n",
       "30747                                                  0        \n",
       "30748                                                  0        \n",
       "\n",
       "       69652caca27c8b940640ad396ab71f93cacec34f@linux-foundation.org  \\\n",
       "30742                                                  0               \n",
       "30745                                                  0               \n",
       "30746                                                  0               \n",
       "30747                                                  0               \n",
       "30748                                                  0               \n",
       "\n",
       "       4645f7897fd33786a2ee1264d590b3c400559d85@linuxfoundation.org  \\\n",
       "30742                                                  0              \n",
       "30745                                                  0              \n",
       "30746                                                  0              \n",
       "30747                                                  0              \n",
       "30748                                                  0              \n",
       "\n",
       "       3697fa5d1b229f59097c7d14eeabccb8d36f99e1@localhost  \\\n",
       "30742                                                  0    \n",
       "30745                                                  0    \n",
       "30746                                                  0    \n",
       "30747                                                  0    \n",
       "30748                                                  0    \n",
       "\n",
       "       4645f7897fd33786a2ee1264d590b3c400559d85@suse.de  \\\n",
       "30742                                                 0   \n",
       "30745                                                 0   \n",
       "30746                                                 0   \n",
       "30747                                                 0   \n",
       "30748                                                 0   \n",
       "\n",
       "       2a53bac7a5d324865ef46ec4c38b2c0fba1456b4@tuxdriver.com  \\\n",
       "30742                                                  0        \n",
       "30745                                                  0        \n",
       "30746                                                  0        \n",
       "30747                                                  0        \n",
       "30748                                                  0        \n",
       "\n",
       "       ad86ba2154032c9f55743a190faa2459a9d61d42@redhat.com  \\\n",
       "30742                                                  0     \n",
       "30745                                                  0     \n",
       "30746                                                  0     \n",
       "30747                                                  0     \n",
       "30748                                                  0     \n",
       "\n",
       "       9dbbbf0688fedc85ad4da37637f1a64b8c718ee2@elte.hu  \\\n",
       "30742                                                 0   \n",
       "30745                                                 0   \n",
       "30746                                                 0   \n",
       "30747                                                 0   \n",
       "30748                                                 0   \n",
       "\n",
       "       010521127f513270fe503d86ab8316ac5147f4b7@codeaurora.org  \\\n",
       "30742                                                  0         \n",
       "30745                                                  0         \n",
       "30746                                                  0         \n",
       "30747                                                  0         \n",
       "30748                                                  0         \n",
       "\n",
       "       69652caca27c8b940640ad396ab71f93cacec34f@g5.osdl.org  ...  \\\n",
       "30742                                                  0     ...   \n",
       "30745                                                  0     ...   \n",
       "30746                                                  0     ...   \n",
       "30747                                                  0     ...   \n",
       "30748                                                  0     ...   \n",
       "\n",
       "       2424f7e375ac81b78b3d01033b1a56d81924e5ae@gmail.com  \\\n",
       "30742                                                  0    \n",
       "30745                                                  0    \n",
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       "       d9f6a08f89e436fe15af44a948d5dd38dac9ea58@gmail.com  \\\n",
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       "[5 rows x 48926 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create the contributions matrix\n",
    "def adj_from_contrib(contrib, contributers, all_ids):\n",
    "    adj = pd.DataFrame(0, columns=contributers, index=all_ids)\n",
    "    for index, row in contrib.iterrows():\n",
    "        adj.at[row['ID'], row['maintainer']] = row['contributions']\n",
    "    return adj\n",
    "\n",
    "adj_contrib = adj_from_contrib(contrib, contributers, proj_ids);\n",
    "\n",
    "#Write adjacency matrix data to csv\n",
    "# adj_contrib.to_csv('data/cargo-contrib-adj.csv')\n",
    "\n",
    "adj_contrib.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ignore for now: create the maintainers matrix (for now empty)\n",
    "# adj_maintain = pd.DataFrame(0, columns=contributers, index=proj_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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     "execution_count": 5,
     "metadata": {},
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    }
   ],
   "source": [
    "# create the dependency matrix\n",
    "def adj_via_from_to(from_to, all_ids):\n",
    "    adj = pd.DataFrame(0, columns=all_ids, index=all_ids)\n",
    "    for index, row in from_to.iterrows():\n",
    "        if row['FROM_ID'] in adj.index.tolist():\n",
    "            adj.at[row['FROM_ID'], row['TO_ID']] = 1\n",
    "    return adj\n",
    "\n",
    "adjdf = adj_via_from_to(deps, proj_ids);\n",
    "\n",
    "\n",
    "#Write adjacency matrix data to csv\n",
    "# adjdf.to_csv('data/cargo-dep-adj.csv')\n",
    "\n",
    "adjdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# attempt to get the adjacency matrix ready -- preprocess dependency adj matrix\n",
    "def norm_dep(d = 4.0 / 7.0):\n",
    "    d_chunked = pd.read_csv('data/cargo-dep-adj.csv', delimiter=',', chunksize=2000, index_col=0);\n",
    "    d_chunk_list = []\n",
    "    for chunk in d_chunked:\n",
    "        processed_chunk = d * norm_rows(chunk)\n",
    "        d_chunk_list.append(processed_chunk)\n",
    "    return pd.concat(d_chunk_list)\n",
    "\n",
    "norm_dep().to_csv('data/cargo-dep-adj-normed.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# attempt to get the adjacency matrix ready -- preprocess contribution adj matrix\n",
    "def norm_contrib(c = 1.0 / 7.0):\n",
    "    c_chunked = pd.read_csv('data/cargo-contrib-adj.csv', delimiter=',', chunksize=2000, index_col=0);\n",
    "    c_chunk_list = []\n",
    "    for chunk in c_chunked:\n",
    "        processed_chunk = c * norm_rows(chunk)\n",
    "        c_chunk_list.append(processed_chunk)\n",
    "    return pd.concat(c_chunk_list)\n",
    "\n",
    "def norm_contrib_trans(c_ = 2.0 / 5.0):\n",
    "    contrib = pd.read_csv('data/cargo-contrib-adj.csv', delimiter=',', index_col=0);\n",
    "    return c_ * norm_rows(contrib.transpose())\n",
    "\n",
    "norm_contrib().to_csv('data/cargo-contrib-adj-normed.csv')\n",
    "norm_contrib_trans().to_csv('data/cargo-contrib-trans-adj-normed.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create the adjacency matrix from projects and contributions\n",
    "\n",
    "# ---- parameters that can be tweaked:\n",
    "# weight variables of edges of G\n",
    "## project -> account\n",
    "d = 4.0 / 7.0\n",
    "m = 2.0 / 7.0\n",
    "c = 1.0 / 7.0\n",
    "## account -> project\n",
    "m_ = 3.0 / 5.0\n",
    "c_ = 2.0 / 5.0\n",
    "\n",
    "#  ----------------------------------\n",
    "\n",
    "# for now without maintainers\n",
    "def adj_p_and_acc(C=0, M=0):\n",
    "#     acc0 = pd.DataFrame(0, columns=contributers, index=contributers)\n",
    "\n",
    "#     p_p = d * norm_rows(D)\n",
    "    p_p = pd.read_csv('data/cargo-dep-adj-normed.csv', delimiter=',', index_col=0);\n",
    "#     p_a = m * norm_rows(M) + c * norm_rows(C)\n",
    "    p_a = pd.read_csv('data/cargo-contrib-adj-normed.csv', delimiter=',', index_col=0);\n",
    "#     a_p = (m_ * M.transpose()).multiply(norm_rows(C.transpose())) + (c_ * norm_rows(C.transpose()))\n",
    "    a_p = pd.read_csv('data/cargo-contrib-trans-adj-normed.csv', delimiter=',', index_col=0);\n",
    "    # combine the matrices\n",
    "    return norm_rows(pd.concat([pd.concat([p_p,a_p], axis=0),pd.concat([p_a,pd.DataFrame(0, columns=contributers, index=contributers)], axis=0)], axis=1))\n",
    "\n",
    "# use adj matrices from memory\n",
    "# deps_adj = adj_via_from_to(deps, proj_ids)\n",
    "# use adj matrices from csv \n",
    "# deps_adj = pd.read_csv('data/cargo-dep-adj.csv', delimiter=',', index_col=0);\n",
    "# contrib_adj = pd.read_csv('data/cargo-contrib-adj.csv', delimiter=',', index_col=0);\n",
    "\n",
    "# adj_all = adj_p_and_acc(adjdf, adj_contrib, adj_maintain)\n",
    "adj_all = adj_p_and_acc()\n",
    "adj_all.to_csv('data/cargo-all-adj.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(66154, 66154)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adj_all.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ---- parameters that can be tweaked:\n",
    "\n",
    "# dapening factors\n",
    "e_proj = 0.85\n",
    "e_account = 0.85\n",
    "\n",
    "# number of iterations\n",
    "niter = 1000\n",
    "\n",
    "# -----------------------------------\n",
    "\n",
    "labels_all = np.concatenate((labels,contributers), axis=0);\n",
    "ids_all = np.concatenate((proj_ids, contributers), axis=0);\n",
    "\n",
    "def g_from_adj(adjdf):\n",
    "    adjmat = adjdf.values\n",
    "    # construct the graph from the adjacency matrix\n",
    "    g = ig.Graph.Adjacency(adjmat.astype(bool).tolist())\n",
    "    g.es['weight'] = adjmat[adjmat.nonzero()]\n",
    "    g.vs['label'] = labels\n",
    "    return g\n",
    "\n",
    "def page_rank(g):\n",
    "    reset = [e_proj] * len(proj_ids) + [e_account] * len(contributers)\n",
    "#     reset = [e_proj] * len(proj_ids)\n",
    "    page_rank = g.personalized_pagerank(reset=reset, niter=niter);\n",
    "    return pd.DataFrame({'ID': ids_all, 'Name': labels_all, 'page_rank': page_rank})\n",
    "\n",
    "# adjdf_from_csv for using the stored data\n",
    "# adjdf for the data from memory\n",
    "g = g_from_adj(adj_all)\n",
    "\n",
    "page_rank = page_rank(g)\n",
    "page_rank.sort_values(by=['page_rank'], ascending=False).to_csv('data/cargo-with-contrib-pagerank.csv', index= False)\n",
    "page_rank_top100 = page_rank.sort_values(by=['page_rank'], ascending=False).head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4550</th>\n",
       "      <td>1629953</td>\n",
       "      <td>serde_derive</td>\n",
       "      <td>0.003787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>31342</td>\n",
       "      <td>rustc-serialize</td>\n",
       "      <td>0.003620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6781</th>\n",
       "      <td>2209540</td>\n",
       "      <td>app</td>\n",
       "      <td>0.003572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5095</th>\n",
       "      <td>1748045</td>\n",
       "      <td>kernel</td>\n",
       "      <td>0.003371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7162</th>\n",
       "      <td>2274449</td>\n",
       "      <td>api</td>\n",
       "      <td>0.003274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1288</th>\n",
       "      <td>736264</td>\n",
       "      <td>docker</td>\n",
       "      <td>0.002905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12825</th>\n",
       "      <td>2952351</td>\n",
       "      <td>kubernetes</td>\n",
       "      <td>0.002856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1542</th>\n",
       "      <td>783030</td>\n",
       "      <td>clippy</td>\n",
       "      <td>0.002847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>30838</td>\n",
       "      <td>chrono</td>\n",
       "      <td>0.002684</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      ID  \\\n",
       "1005                                              428702   \n",
       "3563                                             1369785   \n",
       "242                                                31115   \n",
       "17546  1505422b2465e9a84f6fdfaa161078890c593f06@githu...   \n",
       "518                                                31533   \n",
       "259                                                31140   \n",
       "425                                                31384   \n",
       "165                                                31000   \n",
       "4593                                             1638796   \n",
       "379                                                31311   \n",
       "288                                                31186   \n",
       "4550                                             1629953   \n",
       "396                                                31342   \n",
       "6781                                             2209540   \n",
       "5095                                             1748045   \n",
       "7162                                             2274449   \n",
       "1288                                              736264   \n",
       "12825                                            2952351   \n",
       "1542                                              783030   \n",
       "67                                                 30838   \n",
       "\n",
       "                                                    Name  page_rank  \n",
       "1005                                                rand   0.011041  \n",
       "3563                                          num-traits   0.010627  \n",
       "242                                                 libc   0.010255  \n",
       "17546  1505422b2465e9a84f6fdfaa161078890c593f06@githu...   0.009175  \n",
       "518                                               winapi   0.006294  \n",
       "259                                                  log   0.006022  \n",
       "425                                                serde   0.005708  \n",
       "165                                                  gcc   0.005607  \n",
       "4593                                               quote   0.004829  \n",
       "379                                                regex   0.003967  \n",
       "288                                                mysql   0.003965  \n",
       "4550                                        serde_derive   0.003787  \n",
       "396                                      rustc-serialize   0.003620  \n",
       "6781                                                 app   0.003572  \n",
       "5095                                              kernel   0.003371  \n",
       "7162                                                 api   0.003274  \n",
       "1288                                              docker   0.002905  \n",
       "12825                                         kubernetes   0.002856  \n",
       "1542                                              clippy   0.002847  \n",
       "67                                                chrono   0.002684  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "page_rank_top100.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Write page_rank data to csv\n",
    "# page_rank.sort_values(by=['page_rank'], ascending=False).to_csv('data/cargo-pagerank.csv', index= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>page_rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3563</th>\n",
       "      <td>1369785</td>\n",
       "      <td>num-traits</td>\n",
       "      <td>0.059415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>428702</td>\n",
       "      <td>rand</td>\n",
       "      <td>0.035209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>31533</td>\n",
       "      <td>winapi</td>\n",
       "      <td>0.033656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>31384</td>\n",
       "      <td>serde</td>\n",
       "      <td>0.026141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>31115</td>\n",
       "      <td>libc</td>\n",
       "      <td>0.022697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4550</th>\n",
       "      <td>1629953</td>\n",
       "      <td>serde_derive</td>\n",
       "      <td>0.020821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16285</th>\n",
       "      <td>3414109</td>\n",
       "      <td>rustc-std-workspace-core</td>\n",
       "      <td>0.019508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>31342</td>\n",
       "      <td>rustc-serialize</td>\n",
       "      <td>0.014597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7998</th>\n",
       "      <td>2353652</td>\n",
       "      <td>proc-macro2</td>\n",
       "      <td>0.013991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1542</th>\n",
       "      <td>783030</td>\n",
       "      <td>clippy</td>\n",
       "      <td>0.013728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>31140</td>\n",
       "      <td>log</td>\n",
       "      <td>0.013532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>31105</td>\n",
       "      <td>lazy_static</td>\n",
       "      <td>0.011097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16220</th>\n",
       "      <td>796081</td>\n",
       "      <td>winapi-build</td>\n",
       "      <td>0.011065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1543</th>\n",
       "      <td>783031</td>\n",
       "      <td>compiletest_rs</td>\n",
       "      <td>0.011040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4593</th>\n",
       "      <td>1638796</td>\n",
       "      <td>quote</td>\n",
       "      <td>0.010733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>31212</td>\n",
       "      <td>num</td>\n",
       "      <td>0.010618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379</th>\n",
       "      <td>31311</td>\n",
       "      <td>regex</td>\n",
       "      <td>0.010106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>31296</td>\n",
       "      <td>quickcheck</td>\n",
       "      <td>0.008700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2077</th>\n",
       "      <td>922107</td>\n",
       "      <td>serde_json</td>\n",
       "      <td>0.008614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8962</th>\n",
       "      <td>2448837</td>\n",
       "      <td>rand_core</td>\n",
       "      <td>0.007968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4629</th>\n",
       "      <td>1647361</td>\n",
       "      <td>syn</td>\n",
       "      <td>0.007255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1078</th>\n",
       "      <td>653520</td>\n",
       "      <td>tempdir</td>\n",
       "      <td>0.006053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16226</th>\n",
       "      <td>30798</td>\n",
       "      <td>bitflags</td>\n",
       "      <td>0.005939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1143</th>\n",
       "      <td>702557</td>\n",
       "      <td>serde_macros</td>\n",
       "      <td>0.005612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1008</th>\n",
       "      <td>428781</td>\n",
       "      <td>byteorder</td>\n",
       "      <td>0.005509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>31094</td>\n",
       "      <td>kernel32-sys</td>\n",
       "      <td>0.005430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16328</th>\n",
       "      <td>770837</td>\n",
       "      <td>unicode-xid</td>\n",
       "      <td>0.005391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4102</th>\n",
       "      <td>1559116</td>\n",
       "      <td>serde_test</td>\n",
       "      <td>0.005060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4335</th>\n",
       "      <td>1595835</td>\n",
       "      <td>futures</td>\n",
       "      <td>0.004789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>31382</td>\n",
       "      <td>semver</td>\n",
       "      <td>0.004690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>30774</td>\n",
       "      <td>ansi_term</td>\n",
       "      <td>0.001548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>31457</td>\n",
       "      <td>term</td>\n",
       "      <td>0.001509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3558</th>\n",
       "      <td>1369780</td>\n",
       "      <td>num-bigint</td>\n",
       "      <td>0.001500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6979</th>\n",
       "      <td>2251865</td>\n",
       "      <td>serde_derive_internals</td>\n",
       "      <td>0.001498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3562</th>\n",
       "      <td>1369784</td>\n",
       "      <td>num-iter</td>\n",
       "      <td>0.001485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>396253</td>\n",
       "      <td>bytes</td>\n",
       "      <td>0.001390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6565</th>\n",
       "      <td>2181387</td>\n",
       "      <td>stdweb</td>\n",
       "      <td>0.001382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>31085</td>\n",
       "      <td>itertools</td>\n",
       "      <td>0.001361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13399</th>\n",
       "      <td>3187174</td>\n",
       "      <td>packed_simd</td>\n",
       "      <td>0.001332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16349</th>\n",
       "      <td>3286418</td>\n",
       "      <td>rand_xorshift</td>\n",
       "      <td>0.001322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16264</th>\n",
       "      <td>759818</td>\n",
       "      <td>unicode-width</td>\n",
       "      <td>0.001321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8010</th>\n",
       "      <td>2354817</td>\n",
       "      <td>magenta</td>\n",
       "      <td>0.001295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010</th>\n",
       "      <td>428784</td>\n",
       "      <td>rand_macros</td>\n",
       "      <td>0.001291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8716</th>\n",
       "      <td>2448528</td>\n",
       "      <td>fuchsia-zircon</td>\n",
       "      <td>0.001291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15134</th>\n",
       "      <td>3370220</td>\n",
       "      <td>rand_hc</td>\n",
       "      <td>0.001270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14611</th>\n",
       "      <td>3286426</td>\n",
       "      <td>rand_pcg</td>\n",
       "      <td>0.001270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14909</th>\n",
       "      <td>3334452</td>\n",
       "      <td>rand_chacha</td>\n",
       "      <td>0.001268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14879</th>\n",
       "      <td>3332574</td>\n",
       "      <td>rand_isaac</td>\n",
       "      <td>0.001261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10156</th>\n",
       "      <td>2576150</td>\n",
       "      <td>cloudabi</td>\n",
       "      <td>0.001261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7053</th>\n",
       "      <td>2262792</td>\n",
       "      <td>average</td>\n",
       "      <td>0.001261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14880</th>\n",
       "      <td>3332579</td>\n",
       "      <td>rand_hc128</td>\n",
       "      <td>0.001261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>30848</td>\n",
       "      <td>collect</td>\n",
       "      <td>0.001255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3561</th>\n",
       "      <td>1369783</td>\n",
       "      <td>num-rational</td>\n",
       "      <td>0.001227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4650</th>\n",
       "      <td>1649939</td>\n",
       "      <td>tokio-core</td>\n",
       "      <td>0.001222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11267</th>\n",
       "      <td>2676093</td>\n",
       "      <td>futures-core</td>\n",
       "      <td>0.001158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>30920</td>\n",
       "      <td>docopt</td>\n",
       "      <td>0.001153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2344</th>\n",
       "      <td>993776</td>\n",
       "      <td>walkdir</td>\n",
       "      <td>0.001132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16292</th>\n",
       "      <td>432620</td>\n",
       "      <td>void</td>\n",
       "      <td>0.001128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16329</th>\n",
       "      <td>1803959</td>\n",
       "      <td>redox_syscall</td>\n",
       "      <td>0.001125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6840</th>\n",
       "      <td>2216325</td>\n",
       "      <td>serde_bytes</td>\n",
       "      <td>0.001116</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ID                      Name  page_rank\n",
       "3563   1369785                num-traits   0.059415\n",
       "1005    428702                      rand   0.035209\n",
       "518      31533                    winapi   0.033656\n",
       "425      31384                     serde   0.026141\n",
       "242      31115                      libc   0.022697\n",
       "4550   1629953              serde_derive   0.020821\n",
       "16285  3414109  rustc-std-workspace-core   0.019508\n",
       "396      31342           rustc-serialize   0.014597\n",
       "7998   2353652               proc-macro2   0.013991\n",
       "1542    783030                    clippy   0.013728\n",
       "259      31140                       log   0.013532\n",
       "236      31105               lazy_static   0.011097\n",
       "16220   796081              winapi-build   0.011065\n",
       "1543    783031            compiletest_rs   0.011040\n",
       "4593   1638796                     quote   0.010733\n",
       "301      31212                       num   0.010618\n",
       "379      31311                     regex   0.010106\n",
       "368      31296                quickcheck   0.008700\n",
       "2077    922107                serde_json   0.008614\n",
       "8962   2448837                 rand_core   0.007968\n",
       "4629   1647361                       syn   0.007255\n",
       "1078    653520                   tempdir   0.006053\n",
       "16226    30798                  bitflags   0.005939\n",
       "1143    702557              serde_macros   0.005612\n",
       "1008    428781                 byteorder   0.005509\n",
       "228      31094              kernel32-sys   0.005430\n",
       "16328   770837               unicode-xid   0.005391\n",
       "4102   1559116                serde_test   0.005060\n",
       "4335   1595835                   futures   0.004789\n",
       "423      31382                    semver   0.004690\n",
       "...        ...                       ...        ...\n",
       "26       30774                 ansi_term   0.001548\n",
       "476      31457                      term   0.001509\n",
       "3558   1369780                num-bigint   0.001500\n",
       "6979   2251865    serde_derive_internals   0.001498\n",
       "3562   1369784                  num-iter   0.001485\n",
       "988     396253                     bytes   0.001390\n",
       "6565   2181387                    stdweb   0.001382\n",
       "221      31085                 itertools   0.001361\n",
       "13399  3187174               packed_simd   0.001332\n",
       "16349  3286418             rand_xorshift   0.001322\n",
       "16264   759818             unicode-width   0.001321\n",
       "8010   2354817                   magenta   0.001295\n",
       "1010    428784               rand_macros   0.001291\n",
       "8716   2448528            fuchsia-zircon   0.001291\n",
       "15134  3370220                   rand_hc   0.001270\n",
       "14611  3286426                  rand_pcg   0.001270\n",
       "14909  3334452               rand_chacha   0.001268\n",
       "14879  3332574                rand_isaac   0.001261\n",
       "10156  2576150                  cloudabi   0.001261\n",
       "7053   2262792                   average   0.001261\n",
       "14880  3332579                rand_hc128   0.001261\n",
       "74       30848                   collect   0.001255\n",
       "3561   1369783              num-rational   0.001227\n",
       "4650   1649939                tokio-core   0.001222\n",
       "11267  2676093              futures-core   0.001158\n",
       "112      30920                    docopt   0.001153\n",
       "2344    993776                   walkdir   0.001132\n",
       "16292   432620                      void   0.001128\n",
       "16329  1803959             redox_syscall   0.001125\n",
       "6840   2216325               serde_bytes   0.001116\n",
       "\n",
       "[100 rows x 3 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "page_rank_top100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "layout = g.layout(\"large\")\n",
    "vertex_weights = [i * 100 for i in page_rank['page_rank'].tolist()]\n",
    "adjmat = adjdf.values\n",
    "edge_weights = [i * 10 for i in adjmat[adjmat.nonzero()]]\n",
    "#ig.plot(g, vertex_size=vertex_weights, vertex_color=([\"blue\"] * len(proj_ids)), vertex_label_dist=1, edge_width=edge_weights, layout=layout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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