• Plots Of The Story
• Story Plots With A Twist
• Plots For A Story
• Plots In Short Story
• Story Plots To Write About

Generic X-Y Plotting

Generic function for plotting of R objects. For more details about the graphical parameter arguments, see par.

Plot of a Story Examples The plot is, arguably, the most important element of a story. It is literally the sequence of events and, in that sequence, we learn more about the characters, the setting, and the moral of the story. In a way, the plot is the trunk from which all the other elements of a story grow. Plot diagram is a schematic representation of the events that unfold in a story. The diagram does so with the help of a triangular or pyramid shaped drawing. When the events of a story are mapped in this way, the audience finds it easy to visualize the story’s key aspects. The exposition is the introduction to a story, including the primary characters' names, setting, mood, and time. The conflict is the primary problem that drives the plot of the story, often a main goal for the protagonist to achieve or overcome. The rising action of the story is all of the events that lead to the eventual climax, including character.

• It has the absolute best plot line and, I'd have to say, the best plot twist. Basically, the person on the phone ended up being the husband of the woman involved in the prank of the beginning of.
• Plot Generator Our aim is to inspire you to write your own stories, using common genres and themes. We'll help you set the scene then build characters, describe them, name them, and work out how they fit together in an interesting story. We draft a compelling blurb to get you started.

For simple scatter plots, plot.default will be used. However, there are plot methods for many R objects, including functions, data.frames, density objects, etc. Use methods(plot) and the documentation for these.

Keywords

hplot

Usage

Arguments

x

the coordinates of points in the plot. Alternatively, a single plotting structure, function or any R object with a plot method can be provided.

y

the y coordinates of points in the plot, optional if x is an appropriate structure.

…

Arguments to be passed to methods, such as graphical parameters (see par). Many methods will accept the following arguments:

type

what type of plot should be drawn. Possible types are

• 'p' for points,

• 'l' for lines,

• 'b' for both,

• 'c' for the lines part alone of 'b',

• 'o' for both ‘overplotted’,

• 'h' for ‘histogram’ like (or ‘high-density’) vertical lines,

• 's' for stair steps,

• 'S' for other steps, see ‘Details’ below,

• 'n' for no plotting.

All other types give a warning or an error; using, e.g., type = 'punkte' being equivalent to type = 'p' for S compatibility. Note that some methods, e.g.plot.factor, do not accept this.

main

an overall title for the plot: see title.

sub

a sub title for the plot: see title.

xlab

a title for the x axis: see title.

ylab

a title for the y axis: see title.

asp

the (y/x) aspect ratio, see plot.window.

Details

The two step types differ in their x-y preference: Going from ((x1,y1)) to ((x2,y2)) with (x1 < x2), type = 's' moves first horizontal, then vertical, whereas type = 'S' moves the other way around.

See Also

plot.default, plot.formula and other methods; points, lines, par. For thousands of points, consider using smoothScatter() instead of plot().

For X-Y-Z plotting see contour, persp and image.

Aliases

• plot

Examples

Documentation reproduced from package graphics, version 3.6.2, License: Part of R 3.6.2

Community examples

```r # Plot with multiple lines in different color: plot(sin,-pi, 4*pi, col = 'red') plot(cos,-pi, 4*pi, col = 'blue', add = TRUE) ```

Plots Of The Story

```r ## Plot with multiple lines in different color: plot(sin,-pi, 4*pi, col = 'red') plot(cos,-pi, 4*pi, col = 'blue', add = TRUE) ```

plot(basedata1$iq, basedata$read_ab, main='Diagrama de Dispersión', xlab = 'read_ab', ylab = 'iq')

Story Plots With A Twist

Plots For A Story

## Linear Regression ExamplePlot points and add linear regression model line:```rlinreg <- lm(dist ~ speed, cars)linreg_coeffs <- coef(linreg)lineq <- paste('distance = ', linreg_coeffs[2], ' * speed + ', linreg_coeffs[1])plot(cars, main = 'Car distance by speed', sub = lineq, xlab = 'speed', ylab = 'distance', pch = 19)abline(linreg, col = 'blue')```

Plots In Short Story

Pass a numeric vector to the `x` and `y` arguments, and you get a scatter plot. The `main` argument provides a [`title()`](https://www.rdocumentation.org/packages/graphics/topics/title). ```{r} plot(1:100, (1:100) ^ 2, main = 'plot(1:100, (1:100) ^ 2)') ``` If you only pass a single argument, it is interpreted as the `y` argument, and the `x` argument is the sequence from 1 to the length of `y`. ```{r} plot((1:100) ^ 2, main = 'plot((1:100) ^ 2)') ``` `cex` ('character expansion') controls the size of points. `lwd` controls the line width. `pch` controls the shape of points - you get 25 symbols to choose from, as well as alphabetic characters. `col` controls the color of the points. When `pch` is `21:25`, the points also get a background color which is set using `bg`. [`points()`](https://www.rdocumentation.org/packages/graphics/topics/points) for more on how to change the appearance of points in a scatter plot. ```{r} plot( 1:25, cex = 3, lwd = 3, pch = 1:25, col = rainbow(25), bg = c(rep(NA, 20), terrain.colors(5)), main = 'plot(1:25, pch = 1:25, ...)' ) ``` If you specify `type = 'l'`, you get a line plot instead. See [`plot.default()`](https://www.rdocumentation.org/packages/graphics/topics/plot.default) for a demonstration of all the possible values for type. ```{r} plot( (1:100) ^ 2, type = 'l', main = 'plot((1:100) ^ 2, type = 'l')' ) ``` `lty` controls the line type. `col` and `lwd` work in the same way as with points. [`lines()`](https://www.rdocumentation.org/packages/graphics/topics/lines) for more on how to change the appearance of lines in a line plot. ```{r} plot( (1:100) ^ 2, type = 'l', lty = 'dashed', lwd = 3, col = 'chocolate', main = 'plot((1:100) ^ 2, type = 'l', lty = 'dashed', ...)' ) ``` It is best practise to keep your `x` and `y` variables together, rather than as separate variables. ```{r} with( cars, plot(speed, dist, main = 'with(cars, plot(speed, dist))') ) ``` The formula interface, similar to modeling functions like [`lm()`](https://www.rdocumentation.org/packages/stats/topics/lm), makes this convenient. See [`plot.formula()`](https://www.rdocumentation.org/packages/graphics/topics/plot.formula) for more information. ```{r} plot( dist ~ speed, data = cars, main = 'plot(dist ~ speed, data = cars)' ) ``` If you pass a two column data frame or matrix then the columns are treated as the x and y values. So in this case, you can simply do: ```{r} plot(cars, main = 'plot(cars)') ``` The [`lines()`](https://www.rdocumentation.org/packages/graphics/topics/lines), [`points()`](https://www.rdocumentation.org/packages/graphics/topics/points) and [`title()`](https://www.rdocumentation.org/packages/graphics/topics/title) functions add lines, points and titles respectively to an existing plot. ```{r} plot(cars) lines(lowess(cars)) title('plot(cars); lines(lowess(cars))') ``` If the `x` variable is categorical, `plot()` knows to draw a box plot instead of a scatter plot. See [`boxplot()`](https://www.rdocumentation.org/packages/graphics/topics/boxplot) for more information on drawing those. ```{r} with( sleep, plot(group, extra, main = 'with(sleep, plot(group, extra))') ) ``` Again, the formula interface can be useful here. ```{r} plot(extra ~ group, sleep, main = 'plot(extra ~ group, sleep)') ``` Axis limits can be set using `xlim` and `ylim`. ```{r} plot( (1:100) ^ 2, xlim = c(-100, 200), ylim = c(2500, 7500), main = 'plot((1:100) ^ 2, xlim = c(-100, 200), ylim = c(2500, 7500))' ) ``` You can set log-scale axes using the `log` argument. ```{r} plot( exp(1:10), 2 ^ (1:10), main = 'plot(exp(1:10), 2 ^ (1:10))' ) plot( exp(1:10), 2 ^ (1:10), log = 'x', main = 'plot(exp(1:10), 2 ^ (1:10), log = 'x')' ) plot( exp(1:10), 2 ^ (1:10), log = 'y', main = 'plot(exp(1:10), 2 ^ (1:10), log = 'y')' ) plot( exp(1:10), 2 ^ (1:10), log = 'xy', main = 'plot(exp(1:10), 2 ^ (1:10), log = 'xy')' ) ``` If you pass a table of counts for a vector, `plot()` draws a simple histogram-like plot. See [`hist()`](https://www.rdocumentation.org/packages/graphics/topics/hist) for a more comprehensive histogram function. ```{r} plot( table(rpois(100, 5)), main = 'plot(table(rpois(100, 5)))' ) ``` For multi-dimensional tables, you get a mosaic plot. See [`mosaicplot()`](https://www.rdocumentation.org/packages/graphics/topics/mosaicplot) for more information. ```{r} plot( table(X = rpois(100, 5), Y = rbinom(100, 10, 0.75)), main = 'plot(table(X = rpois(100, 5), Y = rbinom(100, 10, 0.75)))' ) ``` You can also pass functions to plot. See [`curve()`](https://www.rdocumentation.org/packages/graphics/topics/curve) for more examples. ```{r} plot( sin, from = -pi, to = 2 * pi, main = 'plot(sin, from = -pi, to = 2 * pi)' ) ``` Use the axis function to give fine control over how the axes are created. See [`axis()`](https://www.rdocumentation.org/packages/graphics/topics/axis) and [`Axis()`](https://www.rdocumentation.org/packages/graphics/topics/Axis) for more info. ```{r} plot( sin, from = -pi, to = 2 * pi, axes = FALSE, main = 'plot(sin, axes = FALSE, ...); axis(1, ...); axis(2)' ) axis( 1, # bottom axis pi * (-1:2), c(expression(-pi), 0, expression(pi), expression(2 * pi)) ) axis(2) # left axis ``` Further graphical parameters can be set using [`par()`](https://www.rdocumentation.org/packages/graphics/topics/par). See [`with_par()`](https://www.rdocumentation.org/packages/withr/topics/with_par) for the best way to use `par()`. ```{r} old_pars <- par(las = 1) # horizontal axis labels plot((1:100) ^ 2, main = 'par(las = 1); plot((1:100) ^ 2)') par(old_pars) # reset parameters ```

Story Plots To Write About