Programming Articles - Page 905 of 3363

Any numerical data can be divided into four parts by using three quartiles, first quartile at 25%, second quartile at 50% and third quartile at 75% hence there will be four quarters to represent first 25%, second 25%, third 25% and the last 25% in a set of data.If we want to create a quartile (1 to 4) column for each value in an R data frame column then we can use the quantile function and cut function as shown in the below Examples.Example 1Following snippet creates a sample data frame −x

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 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 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 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

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 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

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

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

The histogram like plot in base R is the plots of vertical lines instead of points in a vector or column of a data frame. If we increase the width of these lines then the plot becomes more like a histogram as the increment in widths make the vertical lines look like bars.To increase the width of lines for histogram like plots in base R, we can use lwd argument.Check out the below example to understand the difference between point chart and histogram like plot in base R.ExampleUse the code given below to increase the width of lines for histogram ... Read More