A point chart is usually drawn to see the relationship between two continuous variables and it is also called scatterplot but if the independent variable is categorical then we simply call it a point chart. Often, we want to join or connect the points of a point chart to visually represent the variation of categories of the independent variable and make it a line chart. This can be done by setting stat_summary argument geom to line and setting group = 1 in aes.ExampleConsider the below data frame − Live DemoClass

The value NULL is used to represent an object especially a list of length zero. If a list contains NULL then we might want to replace it with another value or remove it from the list if we do not have any replacement for it. To remove the NULL value from a list, we can use the negation of sapply with is.NULL.Examples Live Demox

In our daily life, we might want to know what was the date before some number of days. This is also required in professional life, especially in those professions where we work on projects and have tight deadlines. To find the date before a certain number of days we can just use subtraction sign after reading the date with as.Date.Examplesas.Date("2001-01-01")-30 [1] "2000-12-02" as.Date("2020-06-30")-30 [1] "2020-05-31" as.Date("2020-06-30")-50 [1] "2020-05-11" as.Date("2020-06-30")-100 [1] "2020-03-22" as.Date("2020-06-30")-120 [1] "2020-03-02" as.Date("2020-06-30")-15 [1] "2020-06-15" as.Date("2020-06-30")-45 [1] "2020-05-16" as.Date("2020-06-30")-40 [1] "2020-05-21" as.Date("2020-12-25")-20 [1] "2020-12-05" as.Date("2020-12-25")-300 [1] "2020-02-29" as.Date("2020-12-25")-125 [1] "2020-08-22" as.Date("2020-12-25")-80 [1] "2020-10-06"We can also use / to ... Read More

The permutation is the combination with orders. For example, if we want to create a key for lock with a sequence of numbers then it must be order in some direction, otherwise, it will be difficult to remember and easy to unlock. We can find the permutation of some numbers or characters by using permn function of combinat package.Loading the combinat package −library(combinat)Examples that create list of permutations −permn(LETTERS[1:4]) [[1]] [1] "A" "B" "C" "D" [[2]] [1] "A" "B" "D" "C" [[3]] [1] "A" "D" "B" "C" [[4]] [1] "D" "A" "B" "C" [[5]] [1] "D" "A" "C" "B" [[6]] ... Read More

When we create a plot in R, the variable names are automatically plotted as axes labels but sometimes we want to give a brief detail of the X-label or a Y-label. If that brief is not small so that the expression function can contain the length of the label then it becomes difficult but it can be done with the help of atop inside expression.ExampleConsider the below data frame − Live Demoset.seed(123) x

Sometimes the vector values are recorded in the reverse order in R, therefore, we need to again reverse those vectors to get the actual order we want. For example, a sequence of numbers might be recorded as 1 to 20 but we wanted it to be from 20 to 1. The reversing of order of the vector values can be easily done with the help of rev function.Examplesx1

Splitting a continuous variable is required when we want to compare different levels of a categorical variable based on some characteristics of the continuous variable. For example, creating the salary groups from salary and then comparing those groups using analysis of variance or Kruskal-Wallis test. To split a continuous variable into multiple groups we can use cut2 function of Hmisc package −Example Live DemoConsider the below data frame −set.seed(2) ID

If a vector is recorded as a single string by mistake or the file that contains the data did not separated the string in an appropriate way then we might need to split in the correct form so that we can proceed with the further analysis. This might happen when the levels of a factor variable that have equal name length are not separated. In this case, we can split the string into a vector that contain substring of equal sizes by using substring function.ExamplesJust look at these examples to understand how substring function can help us to split the ... Read More

The first step to analyze a variable is checking whether it is normally distributed or not and to visually do this, we create a histogram. If the histogram depicts a bell then we consider that the variable is normally distributed otherwise, it is not. We can create a histogram for any column of an R data frame by using hist function.ExampleConsider the below data frame −set.seed(9) df

There are multiple ways to represent a chart, specifically a bar plot is represented with so many variations. We can also include bar labels in a bar plot so that the viewer can easily understand the frequency of the categories for bars. To put the labels on top of the bars in a bar plot we can use vjust = 0 with geom_text in ggplot2.Example Live DemoConsider the below data frame −df