R Plots Examples
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In this article, you will learn to create different types of bar plot in R programming using both vector and matrix.
*Multiple Plots In R
*Plot Data In R
Time series aim to study the evolution of one or several variables through time. This section gives examples using R.A focus is made on the tidyverse: the lubridate package is indeed your best friend to deal with the date format, and ggplot2 allows to plot it efficiently. Welcome the R graph gallery, a collection of charts made with the R programming language. Hundreds of charts are displayed in several sections, always with their reproducible code available. The gallery makes a focus on the tidyverse and ggplot2. Feel free to suggest a chart or report a bug; any feedback is highly welcome. Correlation plots, also known as correlograms for more than two variables, help us to visualize the correlation between continuous variables. In this tutorial we will show you how to plot correlation in base R with different functions and packages.
Bar plots can be created in R using the barplot() function. We can supply a vector or matrix to this function. If we supply a vector, the plot will have bars with their heights equal to the elements in the vector.
Let us suppose, we have a vector of maximum temperatures (in degree Celsius) for seven days as follows.
Now we can make a bar plot out of this data.
This function can take a lot of argument to control the way our data is plotted. You can read about them in the help section ?barplot.
Some of the frequently used ones are, main to give the title, xlab and ylab to provide labels for the axes, names.arg for naming each bar, col to define color etc.
We can also plot bars horizontally by providing the argument horiz = TRUE.
Graphics in R (Gallery with Examples) This page shows an overview of (almost all) different types of graphics, plots, charts, diagrams, and figures of the R programming language. R par function. We can put multiple graphs in a single plot by setting some graphical parameters with the help of par function. R programming has a lot of graphical parameters which control the way our graphs are displayed. The par function helps us in setting or inquiring about these parameters. For example, you can look at all the.Plotting Categorical Data
Sometimes we have to plot the count of each item as bar plots from categorical data. For example, here is a vector of age of 10 college freshmen.
Simply doing barplot(age) will not give us the required plot. It will plot 10 bars with height equal to the student’s age. But we want to know the number of student in each age category.
This count can be quickly found using the table() function, as shown below.
Now plotting this data will give our required bar plot. Note below, that we define the argument density to shade the bars.How to plot higher dimensional tables?
Sometimes the data is in the form of a contingency table. For example, let us take the built-in Titanic dataset.
This data set provides information on the fate of passengers on the fatal maiden voyage of the ocean liner ‘Titanic’, summarized according to economic status (class), sex, age and survival.-R documentation.
We can see that this data has 4 dimensions, class, sex, age and survival. Suppose we wanted to bar plot the count of males and females.
In this case we can use the margin.table() function. This function sums up the table entries according to the given index.Multiple Plots In R
Now that we have our data in the required format, we can plot, survival for example, as barplot(margin.table(Titanic,4)) or plot male vs female count as barplot(margin.table(Titanic,2)).How to plot barplot with matrix?
As mentioned before, barplot() function can take in vector as well as matrix. If the input is matrix, a stacked bar is plotted. Each column of the matrix will be represented by a stacked bar.
Let us consider the following matrix which is derived from our Titanic dataset.
This data is plotted as follows.
We have used the legend() function to appropriately display the legend.
Instead of a stacked bar we can have different bars for each element in a column juxtaposed to each other by specifying the parameter beside = TRUE as shown below.
*PREVIOUSR Inheritance
*NEXTR Histograms
*R Tutorial
*R Data Interfaces
*R Charts & Graphs
*R Statistics Examples
*R Useful Resources
*Selected Reading
A line chart is a graph that connects a series of points by drawing line segments between them. These points are ordered in one of their coordinate (usually the x-coordinate) value. Line charts are usually used in identifying the trends in data.
The plot() function in R is used to create the line graph.Syntax
The basic syntax to create a line chart in R is −
Following is the description of the parameters used −Plot Data In R
*
v is a vector containing the numeric values.
*
type takes the value ’p’ to draw only the points, ’l’ to draw only the lines and ’o’ to draw both points and lines.
*
xlab is the label for x axis.
*
ylab is the label for y axis.
*
main is the Title of the chart.
*
col is used to give colors to both the points and lines.Example
A simple line chart is created using the input vector and the type parameter as ’O’. The below script will create and save a line chart in the current R working directory.
When we execute the above code, it produces the following result −Line Chart Title, Color and Labels
The features of the line chart can be expanded by using additional parameters. We add color to the points and lines, give a title to the chart and add labels to the axes.Example
When we execute the above code, it produces the following result −Multiple Lines in a Line Chart
More than one line can be drawn on the same chart by using the lines()function.
After the first line is plotted, the lines() function can use an additional vector as input to draw the second line in the chart,
When we execute the above code, it produces the following result −
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In this article, you will learn to create different types of bar plot in R programming using both vector and matrix.
*Multiple Plots In R
*Plot Data In R
Time series aim to study the evolution of one or several variables through time. This section gives examples using R.A focus is made on the tidyverse: the lubridate package is indeed your best friend to deal with the date format, and ggplot2 allows to plot it efficiently. Welcome the R graph gallery, a collection of charts made with the R programming language. Hundreds of charts are displayed in several sections, always with their reproducible code available. The gallery makes a focus on the tidyverse and ggplot2. Feel free to suggest a chart or report a bug; any feedback is highly welcome. Correlation plots, also known as correlograms for more than two variables, help us to visualize the correlation between continuous variables. In this tutorial we will show you how to plot correlation in base R with different functions and packages.
Bar plots can be created in R using the barplot() function. We can supply a vector or matrix to this function. If we supply a vector, the plot will have bars with their heights equal to the elements in the vector.
Let us suppose, we have a vector of maximum temperatures (in degree Celsius) for seven days as follows.
Now we can make a bar plot out of this data.
This function can take a lot of argument to control the way our data is plotted. You can read about them in the help section ?barplot.
Some of the frequently used ones are, main to give the title, xlab and ylab to provide labels for the axes, names.arg for naming each bar, col to define color etc.
We can also plot bars horizontally by providing the argument horiz = TRUE.
Graphics in R (Gallery with Examples) This page shows an overview of (almost all) different types of graphics, plots, charts, diagrams, and figures of the R programming language. R par function. We can put multiple graphs in a single plot by setting some graphical parameters with the help of par function. R programming has a lot of graphical parameters which control the way our graphs are displayed. The par function helps us in setting or inquiring about these parameters. For example, you can look at all the.Plotting Categorical Data
Sometimes we have to plot the count of each item as bar plots from categorical data. For example, here is a vector of age of 10 college freshmen.
Simply doing barplot(age) will not give us the required plot. It will plot 10 bars with height equal to the student’s age. But we want to know the number of student in each age category.
This count can be quickly found using the table() function, as shown below.
Now plotting this data will give our required bar plot. Note below, that we define the argument density to shade the bars.How to plot higher dimensional tables?
Sometimes the data is in the form of a contingency table. For example, let us take the built-in Titanic dataset.
This data set provides information on the fate of passengers on the fatal maiden voyage of the ocean liner ‘Titanic’, summarized according to economic status (class), sex, age and survival.-R documentation.
We can see that this data has 4 dimensions, class, sex, age and survival. Suppose we wanted to bar plot the count of males and females.
In this case we can use the margin.table() function. This function sums up the table entries according to the given index.Multiple Plots In R
Now that we have our data in the required format, we can plot, survival for example, as barplot(margin.table(Titanic,4)) or plot male vs female count as barplot(margin.table(Titanic,2)).How to plot barplot with matrix?
As mentioned before, barplot() function can take in vector as well as matrix. If the input is matrix, a stacked bar is plotted. Each column of the matrix will be represented by a stacked bar.
Let us consider the following matrix which is derived from our Titanic dataset.
This data is plotted as follows.
We have used the legend() function to appropriately display the legend.
Instead of a stacked bar we can have different bars for each element in a column juxtaposed to each other by specifying the parameter beside = TRUE as shown below.
*PREVIOUSR Inheritance
*NEXTR Histograms
*R Tutorial
*R Data Interfaces
*R Charts & Graphs
*R Statistics Examples
*R Useful Resources
*Selected Reading
A line chart is a graph that connects a series of points by drawing line segments between them. These points are ordered in one of their coordinate (usually the x-coordinate) value. Line charts are usually used in identifying the trends in data.
The plot() function in R is used to create the line graph.Syntax
The basic syntax to create a line chart in R is −
Following is the description of the parameters used −Plot Data In R
*
v is a vector containing the numeric values.
*
type takes the value ’p’ to draw only the points, ’l’ to draw only the lines and ’o’ to draw both points and lines.
*
xlab is the label for x axis.
*
ylab is the label for y axis.
*
main is the Title of the chart.
*
col is used to give colors to both the points and lines.Example
A simple line chart is created using the input vector and the type parameter as ’O’. The below script will create and save a line chart in the current R working directory.
When we execute the above code, it produces the following result −Line Chart Title, Color and Labels
The features of the line chart can be expanded by using additional parameters. We add color to the points and lines, give a title to the chart and add labels to the axes.Example
When we execute the above code, it produces the following result −Multiple Lines in a Line Chart
More than one line can be drawn on the same chart by using the lines()function.
After the first line is plotted, the lines() function can use an additional vector as input to draw the second line in the chart,
When we execute the above code, it produces the following result −
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