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Server Side Programming Articles - Page 1416 of 2650
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To create a plot with reversed Y-axis we need to use the rev function for the Y-axis labels with ylim but we would also need to define the range for the y-axis values, otherwise, R will throw an error. For example, if we have two vectors named as x and y then the plot with reversed Y-axis labels can be created by using plot(x,ylim=rev(range(y))).Example Live Demox
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To create a plot with tick marks manually between X-axis values in base R, we first need to create the plot without X-axis labels then add the axis values using axis function with appropriate labels, this will create tick marks as well as labels. After this step, we would need to use the axis function again to add the tick marks without labels.Example Live Demoplot(1:10,xaxt='n',type="l") axis(1,at=1:10) axis(1,at=seq(0,11,0.2),labels=NA)OutputExample Live Demoplot(1,xaxt='n') axis(1,at=1) axis(1,at=seq(0,2,0.05),labels=NA)Output
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To create the boxplots in base R ordered by means, we first need to order the categorical column based on the mean of the numerical column and then the boxplot will be created.For example, if we have a data frame df that has a categorical column x and a numerical column y then the boxplot ordered by means can be created by using df$x
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A data frame might be very long and contain columns with only string values as well as numerical values. While doing the analysis, we might want to check which columns contain a particular string value. For example, if we have a column with string values as A, B, and C and we want to check which column contains a value “A” then apply function can be used as shown in the below examples.ExampleConsider the below data frame − Live Demox1
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If we have two categorical columns along with a numerical column in an R data frame then we can find the mean of the numerical column by using the combination of the categorical columns with the help of aggregate function. For example, if a data frame df contains a numerical column X and two categorical columns C1 and C2 then the mean of X can be found for the combinations of C1 and C2 by using the below command −aggregate(X~C1+C2,data=df,FUN="mean")ExampleConsider the below data frame −C1
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If we want to add variables to the model in base R then update function can be used. The update function will update the previous modle by adding the new variable and this variable can be a single variable as well as an interaction of the two or more also any possible transformation of the existing variables.ExampleConsider the below data frame − Live Demox1
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The range for 95% of all values actually represents the middle 95% values. Therefore, we can find the 2.5th percentile and 97.5th percentile so that the range for middle 95% can be obtained. For this purpose, we can use quantile function in R. To find the 2.5th percentile, we would need to use the probability = 0.025 and for the 97.5th percentile we can use probability = 0.0975.Example Live Demox1
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Sometimes values are missing in a sequence and R program records them as NA (Not Available). In this type of situation, we might want to replace consecutive NA records with single NA value. This can be done by using is.na along with diff function as shown in the below examples.Example Live Demox1
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To create side by side histograms in base R, we first need to create a histogram using hist function by defining a larger limit of X-axis with xlim argument. After that we can create another histogram that has the larger mean and smaller standard deviation so that the bars do not clash with each other and add=T argument must also be added inside the second hist function.Example Live Demohist(rnorm(5000,mean=5,sd=2.1),col="green",xlim=c(1,20))OutputExamplehist(rnorm(5000,mean=15,sd=1.25),col="red",add=T)Output
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We can easily identify duplicate values in a matrix by using duplicated function but it does not specify that the first occurrence is also duplicated. Therefore, we need to use it with OR sign | and the argument fromLast = TRUE of duplicated function so that the first occurrence of the duplicated values will be also identified as duplicate.Example Live DemoM1