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To find the sum of squared values of an R data frame column, we can simply square the column with ^ sign and take the sum using sum function. For example, if we have a data frame called df that contains a column say V then the sum of squared values of V can be found by using the command sum(df$V^2).ExampleConsider the below data frame − Live DemoID
If the numeric values are being read as character then we need to convert them into numeric values by using the function as.numeric. For example, if we have a data frame called df that contains a column say x which has numerical values stored in character format then we can convert them into numeric values using the command as.numeric(df$x).ExampleConsider the below data frame − Live Demox1
To find the number of unique values for each column in data.table object, we can use uniqueN function along with lapply. For example, if we have a data.table object called DT that contains five columns each containing some duplicate values then the number of unique values in each of these columns can be found by using DT[,lapply(.SD,uniqueN)].ExampleConsider the below data.table object −x1
When we have a factor column in an R data frame that has two levels and multiple numerical columns then we can apply paired-test on this data frame but the data must be collected for same subjects, otherwise it will not be a paired data. The t.test application on the data discussed here can be done by using the command lapply(df[-1], function(x) t.test(x~df$group)), where group is the factor column and lies at the first position in the data frame, x contains all the numerical columns in the data frame, and all these columns are stored in data frame called df.ExampleConsider ... Read More
To create a frequency column for categorical variable in an R data frame, we can use the transform function by defining the length of categorical variable using ave function. The output will have the duplicated frequencies as one value in the categorical column is likely to be repeated. Check out the below examples to understand how it can be done.ExampleConsider the below data frame − Live DemoCountry
To display p-value in stargazer output for linear regression model, we can use the report argument. For example, if we have a model called RegressionModel then to display the p-value with coefficients can be done by using the below command −stargazer(RegressionModel,type="text",report=("vc*p"))ExampleConsider the below data frame − Live Demox1
To create a blank column with randomization in an R data frame, we can use sample function and pass the blanks with single space. For example, if we want to create a vector say x that will be added in the data frame can be created by using the command −x
The combination of values with repetition is the combination where the values can be repeated when creating the combination. For example, if we have three values say 1 and 2 then the combination of these values with repetition will be as follows −1 1 2 1 1 2 2 2For this purpose, we can use expand.grid function as shown in the below examples.Example 1 Live Demoexpand.grid(rep(list(1:2),2))Output Var1 Var2 1 1 1 2 2 1 3 1 2 4 2 2Example2 Live Demoexpand.grid(rep(list(1:2),3))Output Var1 Var2 Var3 1 1 1 1 2 2 1 1 3 1 2 1 4 2 2 1 5 1 1 2 6 2 1 2 7 1 2 2 8 2 2 2Example3 Live Demoexpand.grid(rep(list(1:2),4))Output Var1 Var2 Var3 Var4 1 1 1 1 1 2 2 1 1 1 3 1 2 1 1 4 2 2 1 1 5 1 1 2 1 6 2 1 2 1 7 1 2 2 1 8 2 2 2 1 9 1 1 1 2 10 2 1 1 2 11 1 2 1 2 12 2 2 1 2 13 1 1 2 2 14 2 1 2 2 15 1 2 2 2 16 2 2 2 2Example4 Live Demoexpand.grid(rep(list(1:2),5))Output Var1 Var2 Var3 Var4 Var5 1 1 1 1 1 1 2 2 1 1 1 1 3 1 2 1 1 1 4 2 2 1 1 1 5 1 1 2 1 1 6 2 1 2 1 1 7 1 2 2 1 1 8 2 2 2 1 1 9 1 1 1 2 1 10 2 1 1 2 1 11 1 2 1 2 1 12 2 2 1 2 1 13 1 1 2 2 1 14 2 1 2 2 1 15 1 2 2 2 1 16 2 2 2 2 1 17 1 1 1 1 2 18 2 1 1 1 2 19 1 2 1 1 2 20 2 2 1 1 2 21 1 1 2 1 2 22 2 1 2 1 2 23 1 2 2 1 2 24 2 2 2 1 2 25 1 1 1 2 2 26 2 1 1 2 2 27 1 2 1 2 2 28 2 2 1 2 2 29 1 1 2 2 2 30 2 1 2 2 2 31 1 2 2 2 2 32 2 2 2 2 2
To find the sum of every n values in R data frame columns, we can use rowsum function along with rep function that will repeat the sum for rows. For example, if we have a data frame called df that contains 4 columns each containing twenty values then we can find the column sums for every 5 rows by using the command rowsum(df,rep(1:5,each=4)).ExampleConsider the below data frame − Live Demox1
When we have a factor column in an R data frame that has two levels and a numerical column then we can apply paired-test on this data frame but the data must be collected for same subjects, otherwise it will not be a paired data. The t.test application on the data discussed here can be done by using the command t.test(y1~x1,data=df), where y1 is the numerical column, x1 is the factor column, and both these columns are stored in data frame called df.ExampleConsider the below data frame − Live Demox1