If we want to remove rows containing missing values based on a particular column then we should select that column by ignoring the missing values. This can be done by using is.na function. For example, if we have a data frame df that contains column x, y, z and each of the columns have some missing values then rows of x without missing values can be selected as df[!is.na(df$x),].ExampleConsider the below data frame − Live Demox1

The concatenation of vectors can be done by using combination function c. For example, if we have three vectors x, y, z then the concatenation of these vectors can be done as c(x,y,z). Also, we can concatenate different types of vectors at the same time using the same same function.Example1 Live Demoset.seed(999) x1

The calculation of total for integer column based on two different character columns simply means that we need to create a contingency table for the available data. For this purpose, we can use with and tapply function. For example, if we have a data frame df that contains two categorical columns defined as gender and ethnicity and an integer column defined as Package then the contingency table can be created as:with(df,tapply(Package,list(gender,ethnicity),sum))ExampleConsider the below data frame − Live Demoset.seed(777) Class

A list can contain multiple lists of different type as well as similar type elements such as data frames, vectors, matrices etcetera but accessing those elements become a little difficult task. Therefore, it is better to convert a list that contain multiple lists into a single list and it can be done using unlist function.ExampleConsider the below vectors −set.seed(871) x1

If we want to find the two−period moving average easily then it cannot be done in base R. We need to use rollmean function of zoo package that solves this problem in a single line of code. For example, if we have a vector x that contains hundred from starting from 1 to 100 then the two−period moving for x can be found by using rollmean(x,2)Loading zoo package −library(zoo)Examples Live Demox1

Like every other tool for statistical analysis R does not display the labels of a boxplot in italics, thus if we want to do this, we need to do it manually. In ggplot2, we have a function scale_x_discrete that can be used to change the default font to italic using expression function.Example Live DemoConsider the below data frame −set.seed(121) x

If we have named vectors but the names come from same family then they cannot be added to each other direct to get the sum of values based on names. To do this, we need to use tapply function. For example, if we have three vectors defined as x, y, and z then firstly they need to be combined as V

Special characters are generally treated as string values and they can be counted with the help of str_count function of stringr package. For example, if we have a vector x that contains $, #, %, ^, &, *, @, ! or any other special character then we can use str_count(x,"\$") to count the number of $ in the vector x, this can be done for all special characters separately.Example1x1

If we want to convert an object into a data frame then as.data.frame function can be used, we just need to read the object that we want to convert with as.data.frame. For example, if we have a vector x then it can be converted to data frame by using as.data.frame(x) and this can be done for a matrix as well.Example1 Live Demox

The easiest way to create a regression model with interactions is inputting the variables with multiplication sign that is * but this will create many other combinations that are of higher order. If we want to create the interaction of two variables combinations then power operator can be used as shown in the below examples.Example1 Live Demox1