# R – Charts and Graphs

**R language** is mostly used for statistics and data analytics purposes to represent the data graphically in the software. To represent those data graphically, charts and graphs are used in R.

## R – graphs

There are hundreds of charts and graphs present in R. For example, bar plot, box plot, mosaic plot, dot chart, coplot, histogram, pie chart, scatter graph, etc.

### Types of R – Charts

- Bar Plot or Bar Chart
- Pie Diagram or Pie Chart
- Histogram
- Scatter Plot
- Box Plot

### Bar Plot or Bar Chart

Bar plot or Bar Chart in R is used to represent the values in data vector as height of the bars. The data vector passed to the function is represented over y-axis of the graph. Bar chart can behave like histogram by using **table()** function instead of data vector.

Syntax:barplot(data, xlab, ylab)

where:

datais the data vector to be represented on y-axisxlabis the label given to x-axisylabis the label given to y-axis

**Note:** To know about more optional parameters in **barplot()** function, use the below command in R console:

help("barplot")

**Example:**

## R

`# defining vector` `x <- ` `c` `(7, 15, 23, 12, 44, 56, 32)` `# output to be present as PNG file` `png` `(file = ` `"barplot.png"` `)` `# plotting vector` `barplot` `(x, xlab = ` `"GeeksforGeeks Audience"` `,` ` ` `ylab = ` `"Count"` `, col = ` `"white"` `,` ` ` `col.axis = ` `"darkgreen"` `,` ` ` `col.lab = ` `"darkgreen"` `)` `# saving the file` `dev.off` `()` |

**Output:**

### Pie Diagram or Pie Chart

Pie chart is a circular chart divided into different segments according to the ratio of data provided. The total value of the pie is 100 and the segments tell the fraction of the whole pie. It is another method to represent statistical data in graphical form and **pie()** function is used to perform the same.

Syntax:pie(x, labels, col, main, radius)

where,

xis data vectorlabelsshows names given to slicescolfills the color in the slices as given parametermainshows title name of the pie chartradiusindicates radius of the pie chart. It can be between -1 to +1

**Note:** To know about more optional parameters in **pie()** function, use the below command in the R console:

help("pie")

**Example:**

Assume, vector x indicates the number of articles present on the GeeksforGeeks portal in categories names(x)

## R

`# defining vector x with number of articles` `x <- ` `c` `(210, 450, 250, 100, 50, 90)` `# defining labels for each value in x` `names` `(x) <- ` `c` `(` `"Algo"` `, ` `"DS"` `, ` `"Java"` `, ` `"C"` `, ` `"C++"` `, ` `"Python"` `)` `# output to be present as PNG file` `png` `(file = ` `"piechart.png"` `)` `# creating pie chart` `pie` `(x, labels = ` `names` `(x), col = ` `"white"` `,` `main = ` `"Articles on GeeksforGeeks"` `, radius = -1,` `col.main = ` `"darkgreen"` `)` `# saving the file` `dev.off` `()` |

**Output:**

Pie chart in 3D can also be created in R by using following syntax but requires** plotrix** library.

Syntax:pie3D(x, labels, radius, main)

**Note:** To know about more optional parameters in pie3D() function, use below command in R console:

help("pie3D")

**Example: **

## R

`# importing library plotrix for pie3D()` `library` `(plotrix)` `# defining vector x with number of articles` `x <- ` `c` `(210, 450, 250, 100, 50, 90)` `# defining labels for each value in x` `names` `(x) <- ` `c` `(` `"Algo"` `, ` `"DS"` `, ` `"Java"` `, ` `"C"` `, ` `"C++"` `, ` `"Python"` `)` `# output to be present as PNG file` `png` `(file = ` `"piechart3d.png"` `)` `# creating pie chart` `pie3D` `(x, labels = ` `names` `(x), col = ` `"white"` `,` `main = ` `"Articles on GeeksforGeeks"` `,` `labelcol = ` `"darkgreen"` `, col.main = ` `"darkgreen"` `)` `# saving the file` `dev.off` `()` |

**Output:**

### Histogram

Histogram is a graphical representation used to create a graph with bars representing the frequency of grouped data in vector. Histogram is same as bar chart but only difference between them is histogram represents frequency of grouped data rather than data itself.

Syntax:hist(x, col, border, main, xlab, ylab)

where:

xis data vectorcolspecifies the color of the bars to be filledborderspecifies the color of border of barsmainspecifies the title name of histogramxlabspecifies the x-axis labelylabspecifies the y-axis label

**Note:** To know about more optional parameters in **hist()** function, use below command in R console:

help("hist")

**Example: **

## R

`# defining vector` `x <- ` `c` `(21, 23, 56, 90, 20, 7, 94, 12,` ` ` `57, 76, 69, 45, 34, 32, 49, 55, 57)` `# output to be present as PNG file` `png` `(file = ` `"hist.png"` `)` `# hist(x, main = "Histogram of Vector x",` ` ` `xlab = ` `"Values"` `,` ` ` `col.lab = ` `"darkgreen"` `,` ` ` `col.main = ` `"darkgreen"` `)` `# saving the file` `dev.off` `()` |

**Output:**

### Scatter Plot

A Scatter plot is another type of graphical representation used to plot the points to show relationship between two data vectors. One of the data vectors is represented on x-axis and another on y-axis.

Syntax:plot(x, y, type, xlab, ylab, main)

Where,

xis the data vector represented on x-axisyis the data vector represented on y-axistypespecifies the type of plot to be drawn. For example, “l” for lines, “p” for points, “s” for stair steps, etc.xlabspecifies the label for x-axisylabspecifies the label for y-axismainspecifies the title name of the graph

**Note:** To know about more optional parameters in **plot()** function, use the below command in R console:

help("plot")

**Example:**

## R

`# taking input from dataset Orange already` `# present in R` `orange <- Orange[, ` `c` `(` `'age'` `, ` `'circumference'` `)]` `# output to be present as PNG file` `png` `(file = ` `"plot.png"` `)` `# plotting` `plot` `(x = orange$age, y = orange$circumference, xlab = ` `"Age"` `,` `ylab = ` `"Circumference"` `, main = ` `"Age VS Circumference"` `,` `col.lab = ` `"darkgreen"` `, col.main = ` `"darkgreen"` `,` `col.axis = ` `"darkgreen"` `)` `# saving the file` `dev.off` `()` |

**Output:**

If a scatter plot has to be drawn to show the relation between 2 or more vectors or to plot the scatter plot matrix between the vectors, then **pairs()** function is used to satisfy the criteria.

Syntax:pairs(~formula, data)

where,

~formulais the mathematical formula such as ~a+b+cdatais the dataset form where data is taken in formula

**Note:** To know about more optional parameters in pairs() function, use the below command in R console:

help("pairs")

**Example :**

## R

`# output to be present as PNG file` `png` `(file = ` `"plotmatrix.png"` `)` `# plotting scatterplot matrix` `# using dataset Orange` `pairs` `(~age + circumference, data = Orange,` `col.axis = ` `"darkgreen"` `)` `# saving the file` `dev.off` `()` |

**Output:**

### Box Plot

Box plot shows how the data is distributed in the data vector. It represents five values in the graph i.e., minimum, first quartile, second quartile(median), third quartile, the maximum value of the data vector.

Syntax:boxplot(x, xlab, ylab, notch)

where,

xspecifies the data vectorxlabspecifies the label for x-axisylabspecifies the label for y-axisnotch,if TRUE then creates notch on both the sides of the box

**Note:** To know about more optional parameters in **boxplot()** function, use the below command in R console:

help("boxplot")

**Example:**

## R

`# defining vector with ages of employees` `x <- ` `c` `(42, 21, 22, 24, 25, 30, 29, 22,` ` ` `23, 23, 24, 28, 32, 45, 39, 40)` `# output to be present as PNG file` `png` `(file = ` `"boxplot.png"` `)` `# plotting` `boxplot` `(x, xlab = ` `"Box Plot"` `, ylab = ` `"Age"` `,` `col.axis = ` `"darkgreen"` `, col.lab = ` `"darkgreen"` `)` `# saving the file` `dev.off` `()` |

**Output:**