To change the order of one column data frame and get the output in data frame format in R, we can follow the below steps −First of all, create a data frame.Then, use order function to change the order of column with drop argument set to FALSECreate the data frameLet's create a data frame as shown below − Live Demo> x df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −             x 1  -0.13734270 2  -1.02796577 3   1.40171778 4  -0.45367796 5   0.06634050 6  -1.27974403 ... Read More

To set the position of legend of a ggplot2 graph to left-top side in R, we can follow the below steps −First of all, create a data frame.Then, create a plot using ggplot2 with legend.After that, add theme function to the ggplot2 graph to change the position of legend.Create the data frameLet's create a data frame as shown below − Live Demo> x y Grp df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −          x          y     Grp 1   1.534536456 ... Read More

To divide the row values by row minimum in R’s data.table object, we can follow the below steps −First of all, create a data.table object.Then, use apply function to divide the data.table object row values by row minimum.Create the data.table objectLet’s create a data.table object as shown below −> library(data.table) > x y z DT DTOn executing, the above script generates the below output(this output will vary on your system due to randomization) −    x y z 1:  4 1 3 2:  4 3 1 3:  1 3 5 4:  1 5 5 5:  3 3 1 6:  3 ... Read More

To divide matrix row values by row minimum in R, we can follow the below steps −First of all, create a matrix.Then, use apply function to divide the matrix row values by row minimum.Create the matrixLet’s create a matrix as shown below − Live Demo> M MOn executing, the above script generates the below output(this output will vary on your system due to randomization) −     [,1] [,2] [,3] [1,]  16    1   18 [2,]  18   12    1 [3,]  12   19   19 [4,]   7    2   18 [5,]  10   14   16 [6,]   8    4    8 [7,]  15   14    4 [8,]   2    1   17 [9,]  11   12    8 [10,] 11   19    6 [11,]  8    2    7 [12,]  8   14    1 [13,]  5   19   18 [14,] 17   14    6 [15,] 13   12   18 [16,]  1   19   14 [17,]  9   19   17 [18,] 10   11    6 [19,]  3    2    2 [20,] 18   15    9 [21,] 11   18   11 [22,]  4   19    7 [23,]  3    9   19 [24,] 12    7   19 [25,]  5    5    2Divide the matrix row values by row minimumUsing apply function to divide the row values of M by row minimum − Live Demo> M M_new M_newOutput          [,1]      [,2]     [,3] [1,]  16.000000  1.000000  18.000000 [2,]  18.000000  12.000000 1.000000 [3,]  1.000000   1.583333  1.583333 [4,]  3.500000   1.000000  9.000000 [5,]  1.000000   1.400000  1.600000 [6,]  2.000000   1.000000  2.000000 [7,]  3.750000   3.500000  1.000000 [8,]  2.000000   1.000000  17.000000 [9,]  1.375000   1.500000  1.000000 [10,] 1.833333   3.166667  1.000000 [11,] 4.000000   1.000000 3.500000 [12,] 8.000000   14.000000 1.000000 [13,] 1.000000   3.800000 3.600000 [14,] 2.833333   2.333333 1.000000 [15,] 1.083333   1.000000 1.500000 [16,] 1.000000   19.000000 14.000000 [17,] 1.000000   2.111111 1.888889 [18,] 1.666667   1.833333 1.000000 [19,] 1.500000   1.000000 1.000000 [20,] 2.000000   1.666667 1.000000 [21,] 1.000000   1.636364 1.000000 [22,] 1.000000   4.750000 1.750000 [23,] 1.000000   3.000000 6.333333 [24,] 1.714286   1.000000 2.714286 [25,] 2.500000   2.500000 1.000000

To find the critical value of F for regression anova in R, we can follow the below steps −First of all, create a data frame.Then, create the regression model.After that, find the critical value of F statistic using qf function.Create the data frameLet's create a data frame as shown below − Live Demo> x y df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −   x y 1  5 5 2  0 9 3  1 3 4  3 5 5  2 5 6  2 4 7  3 6 8  4 6 ... Read More

To convert data frame values to their rank in R, we can follow the below steps −First of all, create a data frame.Then, find the rank of each value using rank function with lapply.Create the data frameLet's create a data frame as shown below − Live Demo> x1 y1 df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −           x1          y1 1  -0.9045608  1.95315551 2  -1.6222122 -1.19880638 3   0.8618855 -0.33643175 4  -0.3547085 -0.18097356 5  -0.3043621 -0.60342210 6   0.5606001 -0.83618995 7  -1.1752752 ... Read More

To create a new level using unique levels of a factor in R data frame, we can follow the below steps −First of all, create a data frame with factor column.Then, create a new level for the unique values in the factor column using table and levels function.Create the data frameLet's create a data frame as shown below − Live Demo> Factor df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −Factor 1 O 2 D 3 K 4 M 5 C 6 M 7 K 8 F 9 L 10 ... Read More

To create violin plot for categories with grey color palette using ggplot2, we can follow the below steps −First of all, create a data frame.Then, create the violin plot for categories with default color of violins.Create the violin plot for categories with color of violins in grey palette.Creating the data frameLet's create a data frame as shown below − Live Demo> Group Score df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −     Group  Score 1   Second   405 2    Third   947 3    First    78 ... Read More

To divide the data frame row values by row standard deviation in R, we can follow the below steps −First of all, create a data frame.Then, use apply function to divide the data frame row values by row standard deviation.Creating the data frameLet's create a data frame as shown below − Live Demo> x y df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −      x     y 1   1.48  0.86 2  -0.14 -0.58 3  -0.25  1.22 4   0.18  0.25 5   0.50  0.68 6  -1.34 ... Read More

To subtract column values from column means in R data frame, we can follow the below steps −First of all, create a data frame.Then, find the column means using colMeans function.After that, subtract column values from column means.Creating the data frameLet's create a data frame as shown below − Live Demo> x1 x2 x3 df dfOn executing, the above script generates the below output(this output will vary on your system due to randomization) −   x1  x2  x3 1  54  73  57 2  79  52  92 3  87  51  47 4  13  12   1 5  70  90  19 6  15  99 ... Read More