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tikazyq/graph_analysis_windeln

Created May 1, 2015 21:40
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Graph Analysis of Domains Referring to Windeln.de
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graph_analysis_windeln
{"nbformat_minor": 0, "cells": [{"source": "#Graph Analysis of Domains Referring to Windeln.de", "cell_type": "markdown", "metadata": {}}, {"source": "This notebook analyses the domains that are linking to Windeln.de and attempting to help understand the relationship between those websites.", "cell_type": "markdown", "metadata": {}}, {"execution_count": 13, "cell_type": "code", "source": "import os\nimport re\nfrom pandas import *\nimport numpy as np\nimport networkx as nx\nimport matplotlib.pyplot as plt\nfrom mpld3 import display\n\n%matplotlib inline", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"source": "###Read Raw Data\nData produced by backlinks.py", "cell_type": "markdown", "metadata": {}}, {"execution_count": 17, "cell_type": "code", "source": "df = read_csv('C:/workspace/analysis_reporting/joe/milk_china/anchor_urls.csv', sep='\\t')\n# df.head()", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 15, "cell_type": "code", "source": "df_domain = df.ix[:, ['source_domain','alexa_cc_rank']].drop_duplicates()", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"source": "Find relationship between source domains", "cell_type": "markdown", "metadata": {}}, {"execution_count": 16, "cell_type": "code", "source": "relation_pairs = []\nkey = ['source_domain','links']\ndf2 = df.ix[:,key].assign(num_links=1).dropna().groupby(key, as_index=0)['num_links'].sum()\n# df2 = df.ix[:,['source_domain','links']].drop_duplicates().dropna()\ndf2.index = range(len(df2))\nfor i in df2.index:\n source_domain = df2.ix[i, 'source_domain']\n num_links = df2.ix[i, 'num_links']\n for link_domain in df2.ix[i, 'links'].split('|'):\n \n pair = (source_domain, link_domain, num_links)\n \n relation_pairs.append(pair)\n \ndf_pair = DataFrame(list(set(relation_pairs)), columns=['src', 'target', 'num_links'])", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 20, "cell_type": "code", "source": "# plotting graph\nG = nx.Graph()\npos=nx.spring_layout(G)\nfor line in df_pair.values:\n src, tgt, wt = line.tolist()\n G.add_edge(src, tgt, weight=wt)\n\n# fig, ax = plt.subplots()\nplt.figure(figsize=(10, 10))\nnx.draw_networkx(G, with_labels=1)\n\ndisplay()", "outputs": [{"execution_count": 20, "output_type": "execute_result", "data": {"text/plain": "<IPython.core.display.HTML object>", "text/html": "\n\n<style>\n\n</style>\n\n<div id=\"fig_el94041510281124126122114\"></div>\n<script>\nfunction mpld3_load_lib(url, callback){\n var s = document.createElement('script');\n s.src = url;\n s.async = true;\n s.onreadystatechange = s.onload = callback;\n s.onerror = function(){console.warn(\"failed to load library \" + url);};\n document.getElementsByTagName(\"head\")[0].appendChild(s);\n}\n\nif(typeof(mpld3) !== \"undefined\" && mpld3._mpld3IsLoaded){\n // already loaded: just create the figure\n !function(mpld3){\n \n 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