When we apply summary function in R, the output gives minimum, first quartile, median, mean, third quartile, and maximum but there are many other basic statistical values that help us to understand the variable such as range, sum, standard error of mean, variance, standard deviation, and coefficient of variation. Therefore, if we want to find all the values then we can use stat.desc function of pastecs package as shown in the below examples.Example1Consider the below data frame −Live Demo> x1 x2 x3 df1 df1Output            x1          x2         x3 ... Read More

To convert a column values to column names, we can use dcast function of reshape2 package. For example, if we have a data frame called df that contains two columns say x and y, where x is categorical and y is numerical. Now if we want to convert the categories in x as column names then it can be done as dcast(df, y~x).Example1Consider the below data frame −Live Demo> x1 x2 df1 df1Output   x1 x2 1   B  4 2   A  2 3   A  5 4   C  3 5   A  7 6   A  4 7 ... Read More

To find the sum of variables by row we mean the sum of row values in the data frame. This can be easily done with the help of rowSums function. For example, if we have a data frame called df then the sum of variables by row can be found by using the command −rowSums(df)Example1Consider the below data frame −Live Demo> x1 x2 x3 df1 df1Output   x1 x2 x3 1   0  2  3 2   1  0  1 3   1  0  2 4   3  3  2 5   4  2  2 6   3  1  5 7 ... Read More

The proportion total in a table helps us to understand the contribution of each row and each column in the total. Therefore, if we want to find the proportion total at margins, we can use addmargins function if we have the proportion table and if we do not have that table then firstly it needs to be created and then use the addmargins function. For example, if we have a proportion table called prop then the command will be addmargins(prop).Example1Consider the below table of proportions −Live Demo> x1 x2 x3 x4 x5 x6 x7 x8 table1 table1Output        ... Read More

When we want to apply t-test on columns of a data frame then we generally perform them one by one by accessing the appropriate columns but if we want to apply the test on all columns of the data frame then we can take the help of sapply function. For example, if we have a data frame called df that contains multiple columns then the one sample-test can be applied to all columns using the command sapply(df, t.test).Example1Consider the below data frame −Live Demo> x1 x2 x3 df1 df1Output            x1        x2   ... Read More

When we create a barplot in base R, the bars are plotted for all the values in the vector but if we have a gap in the values then the bar with zero frequency for that gap is not plotted. For example, if we have a vector called x that contains 100 values consisting of 0, 1, 3 then the barplot will not represent zero frequency for 2. To solve this problem, we can use factor function in the barplot function as shown in the below examples.Example1Live Demo> x xOutput  [1] 0 1 1 1 3 1 3 1 0 ... Read More

To plot row of a data frame as lines, we can use matplot function but we would need to transpose the data frame because transposed values of the data frame will be read as columns and the matplot function plot the columns not rows. For example, if we have a data frame called df then the plot of rows as lines can be created by using the command −matplot(t(df), type="l")Example1Consider the below data frame −Live Demo> x1 x2 x3 df1 df1Output  x1 x2 x3 1  0  9  5 2  3  4  2 3  0  2  1 4  3  7  3 ... Read More

To find the log10 of a data frame column then log10 function will be used but to find the inverse of the log10 can be found by putting 10 raises to the power of the log10 column. For example, if we have a data frame called df that contains a column x then the log10 will be found by usinglog10(df$x)after that the inverse will be found by using 10^(df$x).Example1Consider the below data frame −Live Demo> x1 x2 df1 df1Output      x1 x2 1  66210  2 2  42033  2 3  39309  2 4  80353  3 5  92864  2 6  48621 ... Read More

To split a vector by equal and different number of elements, we can use split function along with rep function. The rep function will define the repetition of the divisions for equal as well as different number of elements. For example, if a vector say x contains fifty values then splitting of x with different number of elements as 20, 10, 10, 5, 5 this can be done by using the command split(x, rep(1:5, c(20, 10, 10, 5, 5))).Example1Live Demo> x1 x1Output [1]  1.30316414 -0.80488291  0.23170812 -0.07318560 -0.73388857 -0.85952329  [7] -0.88713465 -0.26618866  1.45634603  0.31282735  1.39285785  0.32501145 [13] -1.72088389 -0.20699097 -0.37173907  0.03042574 ... Read More

To extract the row for groupwise maximum in another column of an R data.table object, can make use of which.max function by defining the grouping column. It means that if we have a categorical/grouping column and a numerical column then we groupwise maximum will be the maximum for each grouping level in the numerical column and we can extract the row based on these two columns. Check out the examples to understand how it works.Example1Loading data.table package and creating a data.table object −> library(data.table) > x1 x2 x3 DT1 DT1Output   x1 x2 x31:  B  3  2 2:  C  6  0 ... Read More