Monthly Archives: May 2015

Visualizing web page views using D3js

In this post I am going to show you a Data Visualization using web page view data which is the number of web page views in every month for the year 2014. I have downloaded the data in a csv format and after a bit of cleansing the data file, it looks as below.

"MonthName","PageViews"
"Jan","1646"
"Feb","1143"
"Mar","1643"
"Apr","1591"
"May","1645"
"Jun","2082"
"Jul","2633"
"Aug","3035"
"Sep","2882"
"Oct","2900"
"Nov","2780"
"Dec","2448"

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Apache Spark – Big Data Platform for All

Apache Spark is a powerful open source in-memory cluster computing framework built around speed, ease of use, and sophisticated analytics. It runs everywhere – Hadoop (YARN), Mesos, standalone, or in the cloud. It can access diverse data sources including HDFS, Cassandra, HBase, S3 and more. Spark powers a stack of high-level tools including Spark SQL, MLlib for machine learning, GraphX for graph processing, and Spark Streaming to build scalable fault-tolerant streaming applications. These can also be combined seamlessly in an application.

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How domain and range works in D3js

When you are working with Scale functions in D3, there you need a domain and range to map the data values from an input domain to an output range, which means range of possible input data values to range of possible output values.

Below is the basic example to understand the domain and range.

Suppose you have a dataset like [100, 200, 300, 400, 500, 600] and you need to visualize each data to width of one bar into a canvas of 500px width and height. Code will look like as below.

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