Programming Articles - Page 1631 of 3366

If there exists an NA in a vector or column of an R data frame, the output of the sd command for standard deviation results in NA. To solve this problem, we need to use na.rm=TRUE as we do it for vectors that do not contain missing values. For example, if we have a column of a data frame df defined as x that contains missing values then sd of x can be calculated as sd(df$x).ExampleConsider the below data frame:Live Demo> set.seed(3521) > x df1 df1Outputx 1 NA 2 5.107864 3 4.797851 4 5.184345 5 4.680958 6 5.245151 7 5.760667 ... Read More

The default position of legend in a plot created by using ggplot2 is right hand side but we can change the position by using theme function that has legend.position argument and legend.justification argument. To set the legend on top-right side we can use legend.position="top" and legend.justification="right".ExampleConsider the below data frame:Consider the below data frame:Live Demo> x freq df dfOutputx freq 1 Mango 212 2 Guava 220 3 Pomegranate 218Loading ggplot2 package and creating bar chart with legend:> library(ggplot2) > ggplot(df, aes(x, freq, fill=x))+geom_bar(stat="identity")Output:Creating the bar chart with legend on top-right hand side of the chart:Example> ggplot(df, aes(x, freq, fill=x))+geom_bar(stat="identity")+theme(legend.position="top", legend.justification="right")Output:Read More

Aesthetics is one of the most important aspect of a chart, hence we should try to use the best possible aesthetic properties in a plot. In a bar chart, we can represent the center of bars in many ways and one such way is using dots at the center of the top edge of the bars. We can use geom_point function by defining colour argument to put points at the center of top edge of the bars in a bar chart created by using ggplot2.ExampleConsider the below data frame:> freq df dfOutputx freq 1 Mango 212 2 Guava 220 3 ... Read More

Generally, cumulative sums are calculated for a single variable and in some cases based on a single categorical variable, there are very few situations when we want to do it for two categorical variables. If we want to find it for two categorical variables then we need to convert the data frame to a data.table object and use the cumsum function to define the column with cumulative sums.ExampleConsider the below data frame:Live Demo> set.seed(1361) > Factor1 Factor2 Response df1 df1OutputFactor1 Factor2 Response 1 A T2 9 2 B T1 8 3 B T1 2 4 A T2 3 5 B ... Read More

To create a vector with lowercase we can use the word letters and for uppercase the word LETTERS is used in R. If we want to create a vector with both type of letters then both of these words can be combined using c function and if want to create a vector with randomly sampled values of lowercase and uppercase letters then sample function can be used.ExamplesLive Demo> x1 x1Output[1] "A" "B" "C" "D" "a" "b" "c" "d"ExampleLive Demo> x2 x2Output[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" ... Read More

The random sample can be repeated by using replicate function in R. For example, if we have a vector that contains 1, 2, 3, 4, 5 and we want to repeat this random sample five times then replicate(5, x) can be used and the output will be matrix of the below form:[, 1] [, 2] [, 3] [, 4] [, 5] [1, ] 1 1 1 1 1 [2, ] 2 2 2 2 2 [3, ] 3 3 3 3 3 [4, ] 4 4 4 4 4 [5, ] 5 5 5 5 5Example 1Live Demo> x1 x1Output[1] ... Read More

To find the minimum value of a numeric vector we can directly use min function but if the values are read with double-inverted commas then min function does not work. In this case, we will have to use as.numeric with the vector name so that it can be converted to numeric form before finding the minimum value. For example, if we have a character vector that contains 1, 2, 3, and 4 then the minimum can be found as min(as.numeric(x)).Example1 Live Demox1

After getting some experience with data frame people generally move on to data.table object because it is easy to play with a data.table object as compared to a data frame. We also need to create a subset of a data.table object and it can be easily done with the help of square brackets. For example, if we have a data.table object called DT that contains 10 columns and we want to create a subset of 1 to 8 columns then we can use DT[,−c(9,10),with=FALSE] to create that subset.Examplelibrary(data.table) x1

To combine two factor vectors, we can extract the unique levels of both the vectors then combine those levels. This can be done by using unique function. Also, we can set the levels of the original vectors to the combination of the levels, in this way, we can complete both the vectors with missing levels. Check out the examples below to understand how it works.Example1x1

We can use %in% to check whether a matrix element is present in another matrix or not. For example, suppose we have two matrices defined as −   M1 1 2 3 1 2 3 1 2 3    M2 1 2 3 4 5 6 7 8 9Then M1%in%M2 will return −[1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUEBut M2%in%M1 will return −[1] TRUE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSEExample1 Live DemoM1