Traditionally, the stacked bar plot has multiple bars for each level of categories lying upon each other. But this visual can be changed by creating vertical bars for each level of categories, this will help us to read the stacked bar easily as compared to traditional stacked bar plot because people have a habit to read vertical bars.Consider the below data frame −Example Live Demoset.seed(999) Class

If we have two data frames with same number of columns of same data type and equal number of rows then we might want to find the difference between the corresponding values of the data frames. To do this, we simply need to use minus sign. For example, if we have data-frames df1 and df2 then the subtraction can be found as df1-df2.Consider the below data frame −Example Live Demox1

An unordered combination of elements means that the combination of the values in a way that does not make any particular arrangement. For example, if we have three values one, two, and three then they can be arranged in the following way which is unordered −"one" "two" "three" "one" "two" "one" three" "two" "three" "one" "two" "three"Example Live Demox

Almost everyone knows that a leap has 366 instead of 365 days and it occurs once in four years. If we want to check whether a particular year is a leap year or in a range of years which years correspond to leap year then we can use leap_year function of leap year. The length function can be used with the year value and if the output is 1 then it will be a leap year otherwise the output will be 0 which refers to the non-leap year.Loading lubridate package −Examplelibrary("lubridate") year1

If a graph is created by specifying main title of the plot using the plot function then the default font is plain text. We might want to change the style of the font to italic so that the title gets a little more attraction of the viewers. This can be done by using font.main argument with plot function. The value 4 of font.main refers to the bold italic font and if we want to make it bold then we can use the value 3.Consider the below vectors and create the scatterplot between the two with title of the plot −ExamplexRead More

To find the correlation matrix, we simply need to use cor function with the data frame object name. For example, if we have a data frame named as df then the correlation matrix can be found by using cor(df). But the result will have too many decimal places to represent the correlation. If we want to avoid the values after decimal places, we can use round function.Consider the mtcars data in base R −Example Live Demodata(mtcars) cor(mtcars)Output      mpg           cyl        disp        hp         drat     ... Read More

To find the root mean square of a vector we can find the mean of the squared values then take the square root of the resulting vector. This can be done in a single and very short line of code. For example, if we have a vector x and we want to find the root mean square of this vector then it can be done as sqrt(mean(x^2)).Example Live Demox1

The default color of boxplot area in R using ggplot2 is white but we might want to change that color to something more attracting, for example blue or red. To do this purpose, we can use geom_boxplot function of ggplot2 package with fill argument by passing the color names.Consider the below data frame −Example Live Demoset.seed(1321) v1

There are multiple ways to fill missing values in data analysis and one of the ways is filling them with the previous value in the same column of the data frame. For example, if we have a column x in data frame df and this columns x contains some NA values then we can fill them with the values in the upper row. This can be done with the help of na.locf function of zoo package.Consider the below data frame −Example Live Demoset.seed(477) x

If we have missing values in a data frame then all the values cannot be considered complete cases and we might want to extract only values that are complete. We might want extract the complete cases for a particular column only. Therefore, we can use negation of is.na for the column of the data frame that we want to subset.Consider the below data frame −Example Live Demoset.seed(123) x