In this tutorial, we will learn how to use dplyr’s across() function to compute means of all columns in a dataframe. In R, we can use many approaches to compute column means. Here we will use tidyverse approach using dplyr’s across() function to compute column wise means. We will see two examples, first we will… Continue reading dplyr across(): Compute column-wise mean
How to remove columns with all NAs
In this tutorial, we will learn how to drop columns with values that are all NAs. We will use two approaches to remove columns with all NAs. First, we will use tidyverse approach, where we perform column-wise operation to see all values are NAs and select columns that are not all NAs. Next we will… Continue reading How to remove columns with all NAs
How to count number of missing values per row in a dataframe
In this tutorial, we will learn how to count the number missing values, NAs, in each row of a dataframe in R. We will see examples of counting NAs per row using four different approaches. For the first two solutions, we will use tidyverse function rowwise() from dplyr. The next two approaches to count NAs… Continue reading How to count number of missing values per row in a dataframe
How to Extract p-values from multiple simple linear regression models
Sometimes you might fit many simple linear regression models and would like to extract p-values from each model. In this tutorial, we will learn two approaches to extract p-values from multiple simple linear regression models built in R. We will first use for loop to build and extract pvalue from multiple linear models and then… Continue reading How to Extract p-values from multiple simple linear regression models
How to extract residuals from a linear regression model
In this tutorial, we will learn how to extract residual values from a linear regression model in R. Residuals are values that is remaining after adjusting or subtracting effects of variable in the model. We will see two approaches to pull residuals from linear regression model result we get after using lm() function. First we… Continue reading How to extract residuals from a linear regression model