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If we have two vectors say x and y, x contains 1, 6 and y contains 5,10 then the sequence of values between these two vectors will be 1, 2, 3, 4, 5 and 6, 7, 8, 9, 10. Here the sequence is created by using the corresponding elements in x and y. To do this in R, we can use mapply function as shown in the below examples.Example Live Demox1
The first quartile is the value that exists at the 25th percentile, that means there are 25% of values in the data that lie below first quartile. When we find the summary of data frame the output returns this value but if we want to extract only the first quartile then quantile function can be used by specifying the percentage using 0.25.Consider the below data frame −Example Live Demox
The length of the largest string can be found with the help of max function combined with nchar function. For this purpose, we first need to access the appropriate column that contains string values. Suppose, we have a data frame called df that contains a string column defined as CHAR then the length of the largest string will be found by using the command max(nchar(df$CHAR)).Consider the below data frame −Example Live Demox
If we have a column that is key that means we want to use that column as an independent variable and find the statistical values such as sum, mean, standard deviation, range, etc. for the dependent variable. This can be done with the combination of with and tapply function as shown in the below examples.Consider the below data frame −Example Live Demox1
To extract unique values in multiple columns in an R data frame, we first need to create a vector of the column values but for that we would need to read the columns in matrix form. After that we can simply unique function for the extraction. To understand how it works check out the below examples.Consider the below data frame −Example Live Demox1
The splitting of comma separated values in an R vector can be done by unlisting the elements of the vector then using strsplit function for splitting. For example, if we have a vector say x that contains comma separated values then the splitting of those values will be done by using the command unlist(strsplit(x,",")).Example Live Demox1
The na.omit performs any calculation by considering the NA values but do not include them in the calculation, on the other hand, na.rm remove the NA values and then perform any calculation. For example, if a vector has one NA and 5 values in total then their sum using na.omit will be calculated by excluding NA and by using na.rm it will be calculated by removing NA.Consider the below data frame −Example Live Demox1
Performing Wilcoxon test for all columns in an R data frame means that we want to use this test for single samples and the Wilcoxon test for single sample is used to test for the median of the sample, whether the median is equal to something or not. And if we do not provide any value then zero is the reference value. To perform Wilcoxon test for all columns can be done with the help of apply function and wilcox.test as shown in the below example.Consider the below data frame −Example Live Demox1
When we create a plot in base R the Y-axis values are generated automatically and mostly zero is now shown except in few cases that can’t be defined in particular but happens when there exists a zero in data. Therefore, if we want to include a zero with tick in base R plot then ylim argument can be used with the plot function.Exampleplot(5,ylim=c(0,5))OutputExampleplot(rnorm(100),ylim=c(-5,5))OutputExampleplot(rpois(10,2),ylim=c(0,10))Output
A list in R can contain many types of elements such as vector, data frame, matrices, etc. Sometimes the order of these elements matter, especially in situations when we have large size elements because it is difficult to view large size elements of a list. This ordering can be done with the help of single square bracket and combine operator c as shown in the below examples.Example Live DemoList1