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To round values in proportion table in R, we can first save the proportion table in an object and then use the round function.For example, if we have a vector say X then we can create a proportion table for data in X using prop.table(table(X)) and store it in an object called Tab and then round the values to two decimal places by using the below given command −round(Tab,2)Example 1Following snippet creates a sample data frame −x1
A list may contain vectors, data frames, matrices, lists etc. If a list contains matrices and we want to convert those matrices into data frames then lapply function can be used along with as.data.frame function.For example, if we have a list called LIST that contains matrices then we can convert those matrices into data frames by using the below command −lapply(LIST,function(x) as.data.frame(x))ExampleFollowing snippet creates a list of matrices −M1
To find the mean of a column grouped by date, we can simply use aggregate function. For Example, if we have a data frame called df that contains a date column say Date and numerical column say Num then we can find the mean of Num by dates in the Date column by using the below command −aggregate(Num~Date,df,mean)Example 1Following snippet creates a sample data frame −Date
To rotate a ggplot2 graph, we can save it in an object and then use the print function by defining the angle with viewport.For example, if we have a graph saved in an object called PLOT then we can rotate it to 180 degrees by using the below mentioned command −print(PLOT,vp=viewport(angle=180))ExampleFollowing snippet creates a sample data frame −x
To find the conditional frequency for all columns based on a condition, we can use for loop where we will define the length of each column with condition for which we want to find the frequency.For example, if we have a data frame called df and we want to find the number of values in each column that are greater than 5 then we can use the below given command − Columns
To add row percentage to contingency table in R, we can use rowSums and sum function with table values and combine them with cbind function.For Example, if we have a table called TAB then we can add row percentages to TAB by using the below command −cbind(TAB,rowSums(TAB),rowSums(TAB)/sum(TAB))Example 1Following snippet creates a sample data frame −Grp1
When we have large number of columns and only few of them are useful for analysis then extraction of such columns becomes helpful.If we have a vector that contains column numbers and we want to extract the columns from a data.table object then we can use the single square brackets for subsetting of columns as shown in the below given examples.Example 1Following snippet creates data.table object and Vector1 −x1
To divide all columns of data frame in R by one column and keeping the original data, we can use mutate_at function of dplyr package along with list function.For example, if we have a data frame called df that contains five columns say x, y, z, a, and b then we can divide all columns by b and keep the original data by using the below given command −df%>%mutate_at(vars(x:b),list(All_by_b=~./b))Example 1Following snippet creates a sample data frame −x1
To create a histogram with horizontal boxplot on top in base R, we first need to define the layout of the plotting area with layout function and par function margin (mar) then the boxplot will be created and after that the histogram will be created. While creating the boxplot and histogram we need to make sure that the ylim for boxplot and xlim for histogram are same.Check out the below Example to understand how it can be done.ExampleTo create a histogram with horizontal boxplot on top in base R, use the following snippet −x
We are given an integer array, a set of segment start and end pointers and a key value and the problem statement here is to find all the values in the given range which are smaller than or equal to the given key value.Let us understand with exampleInput − arr[] = {7, 8 , 1, 4 , 6 , 8 , 10 }Segment 1: start = 2, end = 4, k = 2Segment 2: start = 1, end = 6, k = 3Output − Count of number which are smaller than or equal to key value in the given range are 2 ... Read More