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
Articles by Nizamuddin Siddiqui
Page 169 of 196
How to find pairwise maximum among multiple vectors in R?
The pairwise maximum refer to the values that are largest between the vectors. For example, if we have a vector that contains 1, 2, 3 and a second vector contains 2, 1, 4 then the pairwise maximum will be 2, 2, 4 because the maximum between 1 and 2 is 2, the maximum between 2 and 1 is 2, and the maximum between 3 and 4 is 4. In R, we can find these maximum values for many vectors using pmax function.Example> x1 y1 pmax(x1, y1) [1] 27 28 65 25 17 21 29 > x2 x2 [1] 7 ...
Read MoreHow to repeat a simulation to a fixed number of times in R?
Often, we simulate random values from different distributions in R. The base R provides some inbuilt functions for the same and if we want to repeat the simulation a fixed number of times then we write these inbuilt functions again and again. But we can do multiple simulations using a single line of code with the help of replicate function, that means if we want to simulate ten uniform random variables ten times then it can be done by using replicate function.Examplesreplicate(10, runif(5, 2, 5)) [, 1] [, 2] [, 3] [, 4] [, 5] [, 6] [, 7] [, ...
Read MoreHow to create a column in an R data frame with cumulative sum?
The cumulative sum is used to determine the total sum of a variable or group and helps us to understand the changes in the values of that variable or group over time. While creating the cumulative, we must be sure that the total sum and the cumulative sum of the last value (depending on the direction of sum) are same. We can use mutate function of dplyr package to find the cumulative and create a column for it.ExampleConsider the below data frame −x1
Read MoreHow to create a rank variable using mutate function of dplyr package in R?
A rank variable is created to convert a numerical variable into ordinal variable. This is useful for non-parametric analysis because if the distribution of the numerical variable is not normal or there are assumptions of parametric analysis that cannot be followed by the numerical variable then the raw variable values are not analyzed directly. To create a rank variable using mutate function, we can use dense_rank argument.ExampleConsider the below data frame −set.seed(7) x1
Read MoreHow to create boxplot with horizontal lines on the minimum and maximum in R?
A boxplot shows the minimum, first quartile, median, third quartile, and maximum. When we create a boxplot with ggplot2 it shows the boxplot without horizontal lines on the minimum and maximum, if we want to create the horizontal lines we can use stat_boxplot(geom= 'errorbar') with ggplot function of ggplot2.ExampleConsider the below data frame −set.seed(101) Gender
Read MoreHow to perform mathematical operations on elements of a list in R?
A list can contain many elements and each of them can be of different type but if they are numerical then we can perform some mathematical operations on them such as addition, multiplication, subtraction, division, etc. To do this, we can use Reduce function by mentioning the mathematical operation and the list name as Reduce(“Mathematical_Operation”, List_name).Examplex1
Read MoreHow to write the plot title in multiple lines using plot function in R?
Mostly, the main title of a plot is short but we might have a long line to write for the main title of the plot. For example, a short version might be “Scatterplot” and a longer version might be “Scatterplot between X and Y”. Therefore, in plot function of R we can use line breaks for the main title as "Scatterplot between X and Y".Exampleset.seed(123) x
Read MoreHow to fill the missing values of an R data frame from the mean of columns?
Dealing with missing values is one of the initial steps in data analysis and it is also most difficult because we don’t fill the missing values with the appropriate method then the result of the whole analysis might become meaningless. Therefore, we must be very careful about dealing with missing values. Mostly for learning purposes, people use mean to fill the missing values but can use many other values depending on our data characteristic. To fill the missing value with mean of columns, we can use na.aggregate function of zoo package.ExampleConsider the below data frame −x1
Read MoreHow to create a scatterplot with log10 of dependent variable in R?
Most of the times, the relationship between independent variable and dependent variable is not linear. Therefore, we want to transform the dependent variable or independent variable based on our experiences. Hence, we also want to plot those transformations to visualize the relationship, one such transformation is taking log10 of the dependent variable. To plot this transformation of the dependent variable, we can use scale_y_continuous(trans='log10').ExampleConsider the below data frame −set.seed(10) x
Read MoreWhat is the difference between NA and <NA> in R?
The missing values are represented by NA but if we read them as "NA" then it becomes a level of a factor variable. If we believe that a vector is numeric and we have an "NA" in that vector then it will not be a numeric vector. On the other hand, if we have a vector with NA then it will be a numeric vector.Examplesx1
Read More