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    "# lab 12\n",
    "\n",
    "Explore migration-related databy  interpreting some of the metrics. Along are presented some forms of calculating relevant metrics.\n",
    "\n",
    "data: migracoes2015.csv\n",
    "\n",
    "You may use, for example:\n",
    "\n",
    "•\tSlides of the course\n",
    "\n",
    "•\thttps://networkx.github.io/documentation/stable/ (https://networkx.github.io/documentation/stable/\n",
    "\n",
    "•\thttps://www.analyticsvidhya.com/blog/2018/04/introduction-to-graph-theorynetwork-analysis-python-codes/ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "#libraries that you may use\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "G = nx.DiGraph()\n",
    "\n",
    "G.add_edge(a,b, weight= c)\n",
    "\n",
    "for a,b,c in zip(df.origem, df.destino, df.numeros):\n",
    "       G.add_edge(a,b, weight= c)\n",
    "\n",
    "G.degree(weight='weight')\n",
    "degree=G.degree()\n",
    "\n",
    "#dictionary with degrees\n",
    "degree_values = dict(degree).values()\n",
    "G.nodes\n",
    "G.edges\n",
    "\n",
    "#draw chart\n",
    "nx.draw(G, dim=100, with_labels=True)\n",
    "\n",
    "#or\n",
    "plt.figure(figsize=(20, 20))\n",
    "po1 = nx.spring_layout(G,scale=2)\n",
    "nx.draw(G, node_size=10, pos=po1, edge_color='y', label='r', with_labels=True)\n",
    "plt.show()\n",
    "\n",
    "#or for po1 and po1 = nx.random_layout(G)\n",
    "degree =[deg for node, deg in nx.degree(G)]\n",
    "max(degree)\n",
    "min(degree)\n",
    "kavg = np.mean(degrees)\n",
    "print(kavg)\n",
    "\n",
    "#convert directed to undirected\n",
    "G1 = G.to_undirected()\n",
    "Coeficiente de clustering\n",
    "nx.clustering(G1)\n",
    "\n",
    "#clioseness centrality\n",
    "nx.closeness_centrality(G)\n",
    "\n",
    "#eigenvector centrality\n",
    "nx.eigenvector_centrality(G)\n",
    "\n",
    "#degree centrality\n",
    "nx.degree_centrality(G)\n",
    "\n",
    "#number of linked components\n",
    "nx.number_connected_components(G1)\n",
    "\n",
    "#node linked to component\n",
    "nx.node_connected_component(G1, 'João')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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