Hello Friends! I’ll be sharing different resources to quickly revise analytics concepts. Sometimes if you don’t use some concepts for time you may forget and need a quick revision. Here I’m listing out few links you can use to revise.
Hello friends! today we’ll be see how to do exploratory data analysis (EDA) in R. EDA is an approach to analyse data and start with it read more. I’ve used medical cost data from Kaggle.
Reshaping data is one of the important steps for data analysis and data transformation. Today we’ll see few of the methods and function in R. The tutorials is easy to follow. I’m using mtcars dataset which is available in R.
Hello friends! Overplotting is one of common issue faced by analysts during EDA (Exploratory data analysis), data visualization and getting inference the results. We’ll see few methods to prevent it.
Today we’ll see about the dplyr package in R also known as grammar of data manipulation. In the last tutorial we saw about the ggplot2 which is another famous package in R. It consist of set of functions which helps you for different type of data manipulation. I’ll be using medical cost data set from Kaggle(data source). I’ve listed all possible documentation and resources to learn more about the dplyr package.
Today we’ll be seeing how to split data into Training data sets and Test data sets in R. While creating machine learning model we’ve to train our model on some part of the available data and test the accuracy of model on the part of the data.
Today we’ll be seeing to create the Heatmap in R. In my last tutorial I’ve created the heapmap in Tableau.
