Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
R Programming Articles
Page 28 of 174
How to sort each row of an R data frame in increasing order?
To sort each row of an R data frame in increasing order, we can use apply function for sorting the columns and then transpose the output. For example, if we have a data frame called df that contains 5 columns then each row of df can be sorted in increasing order by using the command t(apply(df,1,sort)).Example1Consider the below data frame −x1
Read MoreHow to minus one column from another in an R matrix?
To minus one column from another in an R matrix, we first need to read the matrix as a data frame using as.data.frame then find minus the columns using minus sign and accessing the column of the data frame. To understand how it can be done look at the steps in below examples.ExampleConsider the below data frame −M1
Read MoreHow to calculate the z score for grouped data in R?
To calculate the z score for grouped data, we can use ave function and scale function. For example, if we have a data frame called df that contains a grouping coloumn say GROUP and a numerical column say Response then we can use the below command to calculate the z score for this data −ave(df$Response,df$GROUP,FUN=scale)ExampleConsider the below data frame −grp
Read MoreHow to convert negative values in a matrix to 0 in R?
To convert negative values in a matrix to 0, we can use pmax function. For example, if we have a matrix called M that contains some negative and some positive and zero values then the negative values in M can be converted to 0 by using the command pmax(M,0).ExampleConsider the below data frame −M1
Read MoreHow to display tick marks on upper as well as right side of the plot using ggplot2 in R?
To display tick marks on upper as well as right side of the plot, we can create duplicate axes for X as well Y by using scale_x_continuous and scale_y_continuous functions. The argument that will help us in this case is sec.axis and we need to set it to dup_axis as scale_x_continuous(sec.axis=dup_axis()) and scale_y_continuous(sec.axis=dup_axis()). Check out the below example to understand how it can be done.ExampleConsider the below data frame −x
Read MoreHow to combine a data frame and a named vector if name matches with a column in R?
If we have a data frame that contains a character column and a named vector which has the same names as in the character column of the data frame then we can combine this data frame and the vector by using match function be appropriately defining the names and the character column. Check out the below example to understand how it can be done.ExampleConsider the below data frame df1 and the vector v1 −df1
Read MoreHow to convert the row values in a matrix to row percentage in R?
To convert the row values in a matrix to row percentage, we can find the row sums and divide each row value by this sum. For example, if we have a matrix called M then we can convert the row values in M to row percentage by using the commandround((M/rowSums(M))*100,2)ExampleConsider the below matrix −M1
Read MoreHow to display mean in a boxplot with cross sign in base R?
To display mean in a boxplot with cross sign in base R, we can use the points function and pass the mean with pch = 4 that represents a star, also we can change the color to highlight the mean using col argument and the size of the start can be changed using lwd argument as shown in the below examples.Examplex
Read MoreHow to select columns in R without missing values?
There are two easy methods to select columns of an R data frame without missing values, first one results in a vector and other returns a matrix. For example, if we have a data frame called df then the first method can be used as df[,colSums(is.na(df))==0] and the second method will be used as t(na.omit(t(df))).ExampleConsider the below data frame −df1
Read MoreHow to perform paired t test in R with a factor column in the data frame?
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 −x1
Read More