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
Server Side Programming Articles
Page 1108 of 2109
How to add approximately equal sign in a plot using ggplot2 in R?
To add approximately equal sign in a plot using ggplot2, we can use tilde sign twice as ~~ in geom_text function of ggplot2 package. For example, we can do this by using the following syntax geom_text(aes(label="NULL%~~%")). Check out the below example to understand how it works.ExampleConsider the below data frame −x
Read MoreHow to change the point size in geom_point conditionally in R?
To change the point size in geom_point conditionally, we can define the condition in geom_point with aes and the size using scale_size_manual function of ggplot2 package. For example, if we have a data frame called df that contains two columns say x and y then the scatterplot with different size of points for x values greater than 5 and less than equal to 5 can be drawn by using the below command −ggplot(df, aes(x, y))+geom_point(aes(size=x>5))+scale_size_manual(values=c(4, 7))ExampleConsider the below data frame −x6))+scale_size_manual(values=c(4, 7)) Output
Read MoreHow to change default point size of geom_point in R?
To change the default point size of geom_point, we need to use update_geom_defaults function. Specifically, for the change of point size the syntax will be as follows −update_geom_defaults("point",list(size=”value”))Here, we can change the value according to our need.ExampleConsider the below data frame −x
Read MoreHow to create data frame using nested list elements in R?
To create data frame using nested list elements, we would need to unlist the list elements and store them in a matrix then read as a data frame using data.frame function. For example, if we have a nested called LIST then the data frame can be created by using the command −data.frame(matrix(unlist(LIST),ncol=”No of columns we want”,byrow=F))Check out the below example to understand how it works.ExamplenestedList
Read MoreHow to deal with Error: stat_count() can only have an x or y aesthetic in R?
To deal with Error: stat_count() can only have an x or y aesthetic, we need to pass the stat="identity" argument inside geom_bar function. Since we do not pass the count for bars and a bar graph can only contain only count variable, hence stat="identity" is needed so that geom_bar considers only one variable in aes for counting. Check out the below example to understand the difference.ExampleConsider the below data frame −factor
Read MoreHow to create multiple bar plots for varying categories with same width bars using ggplot2 in R?
To create multiple bar plots for varying categories with same width bars using ggplot2, we would need to play with width argument inside geom_bar function to match the width of the bars in each bar plot. The best way to do this would be setting the larger ones to 0.25 and the shorter ones to 0.50.ExampleConsider the below data frame −x1
Read MoreHow to randomly sample rows from an R data frame using sample_n?
To randomly sample rows from an R data frame using sample_n, we can directly pass the sample size inside sample_n function of dplyr package. For example, if we have data frame called df then to create a random sample of 5 rows in df can be done by using the command −df%>%sample_n(5)Example1Consider the below data frame −x1
Read MoreHow to find the sum of non-missing values in an R data frame column?
To find the sum of non-missing values in an R data frame column, we can simply use sum function and set the na.rm to TRUE. For example, if we have a data frame called df that contains a column say x which has some missing values then the sum of the non-missing values can be found by using the command sum(df$x,na.rm=TRUE).Example1Consider the below data frame −x1
Read MoreHow to find the column mean by excluding NA's and if all values are NA then output NA in R data frame?
To find the column mean by excluding NA’s can be easily done by using na,rm but if we want to have NA if all the values are NA then it won’t be that straight forward. Therefore, in such situation, we can use ifelse function and return the output as NA if all the values are NA as shown in the below examples.Example1Consider the below data frame −x1
Read MoreHow to detect multicollinearity in categorical variables using R?
The multicollinearity is the term is related to numerical variables. It means that independent variables are linearly correlated to each other and they are numerical in nature. The categorical variables are either ordinal or nominal in nature hence we cannot say that they can be linearly correlated.ExampleConsider the below data frame −x
Read More