visualizing data - - - - - - - - [( )( )( )( )( )for each iteration of the page rank algorithm it prints the average change in page rank per page the network initially is quite unbalanced and so the individual page rank values change wildly between iterations but in few short iterationsthe page rank converges you should run sprank py long enough that the page rank values converge if you want to visualize the current top pages in terms of page rankrun spjson py to read the database and write the data for the most highly linked pages in json format to be viewed in web browser creating json output on spider json how many nodes open force html in browser to view the visualization you can view this data by opening the file force html in your web browser this shows an automatic layout of the nodes and links you can click and drag any node and you can also double-click on node to find the url that is represented by the node if you rerun the other utilitiesrerun spjson py and press refresh in the browser to get the new data from spider json visualizing mail data up to this point in the bookyou have become quite familiar with our mboxshort txt and mbox txt data files now it is time to take our analysis of email data to the next level in the real worldsometimes you have to pull down mail data from servers that might take quite some time and the data might be inconsistenterror-filledand need lot of cleanup or adjustment in this sectionwe work with an application that is the most complex so far and pull down nearly gigabyte of data and visualize it you can download this application from