Bivariate analysis
Bivariate analysis finds out the relationship between two variables. In this, we always look for association and disassociation between variables at a predefined significance level. This analysis could be performed for any combination of categorical and continuous variables. The various combinations can be: both the variables categorical, categorical and continuous, and continuous and continuous.
Getting ready
To step through this recipe, you will need a running Spark cluster in any one of the modes, that is, local, standalone, YARN, or Mesos. For installing Spark on a standalone cluster, please refer to http://spark.apache.org/docs/latest/spark-standalone.html. Also, include the Spark MLlib package in the build.sbt file so that it downloads the related libraries and the API can be used. Install Hadoop (optionally), Scala, and Java.
How to do it…
After univariate analysis, let's try to perform bivariate analysis on various combinations of continuous and categorical variables...
