Programming Articles - Page 1136 of 3363

To randomize column values of a data.table object for all columns in R, we can follow the below steps −First of all, create a data.table object.Then, use sample function with lapply to randomize the columns of the data.table object.Create the data frameLet's create a data frame as shown below −library(data.table) x

To create a clone of a data frame in R without data values, we can follow the below steps −First of all, create a data frame.Then, create the clone of the data frame by subsetting zero rows.Example 1Create the data frameLet's create a data frame as shown below − Live Demox1

To filter data frame by categorical variable in R, we can follow the below steps −Use inbuilt data sets or create a new data set and look at top few rows in the data set.Then, look at the bottom few rows in the data set.Check the data structure.Filter the data by categorical column using split function.Use inbuilt data setLet’s consider CO2 data set in base R − Live Demodata(CO2) head(CO2, 10)On executing, the above script generates the below output(this output will vary on your system due to randomization) −Grouped Data: uptake ~ conc | Plant   Plant Type Treatment conc uptake ... Read More

To find the summary by categorical variable, we can follow the below steps −Use inbuilt data sets or create a new data set.Find the summary statistics with by function.Use inbuilt data setLet’s consider mtcars data set in base R − Live Demodata(mtcars) head(mtcars, 25)On executing, the above script generates the below output(this output will vary on your system due to randomization) −                      mpg  cyl disp   hp  drat   wt   qsec vs am gear carb Mazda RX4             21.0 6   160.0 110  3.90 2.620 ... Read More

To add values in columns having same name and merge them in R, we can follow the below steps −First of all, create a data frame.Add column values that have same name and merge them by using cbind with do.call.Create the data frameLet's create a data frame as shown below −df

To create NA column for a contingency table in R, we can follow the below steps −First of all, create a data frame with two columns having some NA values.Create a contingency table for two columns.Create the same table using useNA.Create the data frameLet's create a data frame as shown below − Live Demox

To find the confusion matrix for linear discriminant analysis in R, we can follow the below steps −First of all, create a data frame.Create new features using linear discriminant analysis.Find the confusion matrix for linear discriminant analysis using table and predict function.Create the data frameLet's create a data frame as shown below − Live DemoGroup

To apply different function to grouping values in an R data frame, we can follow the below steps −First of all, create a data frame.Then, use ifelse function to apply different function to grouping values.Create the data frameLet's create a data frame as shown below − Live Demox

To find the starting position for consecutive values given the length of consecutive values in an R vector, we can follow the below steps −First of all, create a vector with duplicated values.Find the run length.Create a vector with FALSE of vector size.Find the starting position by setting running length of consecutive values to TRUE for given length.Create the vectorLet’s create a vector having many duplciates so that we can get same consecutive values − Live Demox

To find the unique elements in multiple vectors, we can follow the below steps −First of all, create a number of vectors.Use setdiff function to find the common elements in all the vectors.Create the vectorsLet’s create a number of vectors as shown below − Live Demox