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To find the groupwise number of positive and negative values in an R data frame, we can use mutate function of dplyr package. For example, if we have a data frame called df with one categorical column x and one numerical column y then the number of positive and negative values for categorical column can be found by using the below command −df%>%group_by(x)%>%mutate(positive=sum(y>0),negative=sum(y
To create a linear model with interaction term only, we can use the interaction variable while creating the model. For example, if we have a data frame called df that has two independent variables say V1 and V2 and one dependent variable Y then the linear model with interaction term only can be created as lm(Y~V1:V2,data=df).Consider the below data frame −Example Live Demox1
To create a perpendicular arrow in base R plot, we can use arrows function. There are five arguments of arrows function that will be used to create the perpendicular arrow. The first four values define the position of the arrow and the last argument xpd allows R to create the arrow. Check out the below examples to understand how it works.Exampleplot(1:10) arrows(1,-1,1,0,xpd=TRUE)OutputExampleplot(1:10) arrows(1,-1,1,2,xpd=TRUE)OutputExampleplot(1:10) arrows(2,-1,2,2,xpd=TRUE)Output
When we create histogram using ggplot2 we need to pass the number of bins we want to have in the histogram and on the basis of these bin numbers the histogram will be created, these bin numbers are actually the number of bars we will have in the histogram. To fill those bars with different colors, we need to use fill argument and pass a range of values equal to the number of bins as shown in the below example.Consider the below data frame −x
To display mean in a histogram using ggplot2, we can use geom_vline function where we need to define the x-intercept value as the mean of the column for which we want to create the histogram. Also, we can change the size of the line for mean in the histogram by using size argument inside geom_vline function.Consider the below data frame −x
By default, the space between bars is equal irrespective of the number of bars in the plot. If we want to have different space between bars then space arguments need to be used inside the barplot function but the first value does not make an impact because the first space is fixed between Y-axis and the first bar. For example, if we have a vector x that contains three values then the barplot with different space between bars can be created by using the below command −barplot(x,space=c(0.5,0.1,0.5))Example Live Demox
The residuals are the difference between actual values and the predicted values and the predicted values are the values predicted for the actual values by the linear model. To extract the residuals and predicted values from linear model, we need to use resid and predict function with the model object.Consider the below data frame −Example Live Demox1
A qqplot is the plot of quantiles that helps to understand whether the supplied data comes from the specified distribution, mostly it is used to check whether the data follows normal distribution or not. If we want to create the qqplot with confidence interval then qqPlot function of car package can be used as shown in the below example.Consider the below data frame −Example Live Demox
If we have values scattered in multiple columns in an R data frame then we need to combine them and create a single column, this combining process is called concatenation. The scatteredness of the values mostly happens when the data is not well formatted to be loaded in R. Therefore, to deal with this scatteredness problem we need to use apply function.Consider the below data frame −Example Live Demox1
Most of the times the date data is available only in date format and there is not information about the quarter of the year. The quarter of the year is required when we want compare the quarters or do some time series analysis. For the conversion of date into quarter and year can be done by using as.yearqtr function from zoo package as shown in the below examples.Examplelibrary(zoo) as.yearqtr("2021-01-19", format="%Y-%m-%d")Output[1] "2021 Q1"as.yearqtr("2021-04-19", format="%Y-%m-%d")[1] "2021 Q2"as.yearqtr(c("2021-04-19", "2020-05-24", "2020-11-09"), format="%Y-%m-%d")[1] "2021 Q2" "2020 Q2" "2020 Q4" Example Live Demox1Read More