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R Programming Articles
Page 35 of 174
How to create a line chart with mean and standard deviation using ggplot2 in R?
Sometimes we have mean and standard deviation given for groups or factors, these are generally obtained from previous research studies and is referred to as the secondary data. In this case. the line chart with mean and standard deviation using ggplot2 can be created by defining the minimum and maximum inside geom_error function of ggplot2 package, where the difference between mean and standard deviation defines the standard deviation if the minimum is set as mean minus one standard deviation and the maximum is set as mean plus one standard deviation.ExampleConsider the below data frame −Group
Read MoreHow to find the sum by distinct column for factor levels in an R data frame?
If the data frame contains a factor column and some numerical columns then we might want to find the sum of numerical columns for the factor levels. For this purpose, we can use aggregate function. For example, if we have a data frame df that contains a factor column defined by Group and some numerical columns then the sum by distinct column for factor levels can be calculated by using aggregate(.~Group,data=df,sum)Example1Class
Read MoreHow to convert matrix rows into a list in R?
Depending on our objective, a matrix rows might be needed to converted into a list that means each row will be an element of the list. This can be done by using the function as.list but firstly we need to convert the matrix into data frame after transposing. For example, if we have a matrix called M then it’s rows will be converted to a list using the command writtem below −as.list(data.frame(t(M)))Example1M1
Read MoreHow to find the mean of multiple columns based on a character column in R?
If we have a character column that means we are more likely to have duplicated values in that column hence finding the mean of numerical columns based on the values in character column cannot be done directly. For this purpose, we can use aggregate function as shown in the below examples.Example1Consider the below data frame −set.seed(214) x1
Read MoreHow to replace missing values with row means in an R data frame?
If we have similar characteristics in each column of an R data frame then we can replace the missing values with row means. To replace the missing values with row means we can use the na.aggregate function of zoo package but we would need to use the transposed version of the data frame as na.aggregate works for column means.Example1Consider the below data frame −x1
Read MoreHow to check if a variable contains number greater than 1 in an R data frame?
The variables in an R data frame are referred to as the columns of the data frame. Sometimes we have a threshold value for a particular column and we need to check whether all the values in that column are greater than or less than the threshold. For this purpose, we can make use of ifelse function as shown in the below examples.Example1y
Read MoreHow to change the order of elements in a list in R?
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.ExampleList1
Read MoreHow to perform Wilcoxon test for all columns in an R data frame?
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 −Examplex1
Read MoreWhat is the difference between na.omit and na.rm in R?
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 −Examplex1
Read MoreHow to extract unique values in multiple columns in an R data frame using a single line code?
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 −Examplex1
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