A plot generator may also help you to start thinking creatively again. Plot Generators List. Plot-Generator.org.uk - This plot generator features plots for short stories, plot twists, fairytales and more. Use the Story Ideas option if you want a quick random story idea. Some of the other options have more involved forms.

Plot is the series of events that make up your story, including the order in which they occur and how they relate to each other. Structure (also known as narrative structure), is the overall design or layout of your story. Genshin Impact's Story & Plot Explained Genshin Impact is incredibly popular, with a lot of attention given to its world and characters, but the game also has an intriguing story and plot. By Austin King Oct 21, 2020.

Generic X-Y Plotting

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

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

Story Plots With A Twist

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) ```

```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')

## 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')```

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 ```

Plot y versus x as lines and/or markers.

Call signatures:

The coordinates of the points or line nodes are given by x, y.

The optional parameter fmt is a convenient way for defining basicformatting like color, marker and linestyle. It's a shortcut stringnotation described in the Notes section below.

You can use Line2D properties as keyword arguments for morecontrol on the appearance. Line properties and fmt can be mixed.The following two calls yield identical results:

When conflicting with fmt, keyword arguments take precedence.

Plotting labelled data

There's a convenient way for plotting objects with labelled data (i.e.data that can be accessed by index obj['y']). Instead of givingthe data in x and y, you can provide the object in the dataparameter and just give the labels for x and y:

All indexable objects are supported. This could e.g. be a dict, apandas.DataFame or a structured numpy array.

Plotting multiple sets of data

There are various ways to plot multiple sets of data.

• The most straight forward way is just to call plot multiple times.Example:

• Alternatively, if your data is already a 2d array, you can pass itdirectly to x, y. A separate data set will be drawn for everycolumn.

  Example: an array a where the first column represents the xvalues and the other columns are the y columns:

• The third way is to specify multiple sets of [x], y, [fmt]groups:

  In this case, any additional keyword argument applies to alldatasets. Also this syntax cannot be combined with the dataparameter.

By default, each line is assigned a different style specified by a'style cycle'. The fmt and line property parameters are onlynecessary if you want explicit deviations from these defaults.Alternatively, you can also change the style cycle usingrcParams['axes.prop_cycle'] (default: cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'])).

Parameters:	x, yarray-like or scalar The horizontal / vertical coordinates of the data points.x values are optional and default to range(len(y)). Commonly, these parameters are 1D arrays. They can also be scalars, or two-dimensional (in that case, thecolumns represent separate data sets). These arguments cannot be passed as keywords. fmtstr, optional A format string, e.g. 'ro' for red circles. See the Notessection for a full description of the format strings. Format strings are just an abbreviation for quickly settingbasic line properties. All of these and more can also becontrolled by keyword arguments. This argument cannot be passed as keyword. dataindexable object, optional An object with labelled data. If given, provide the label names toplot in x and y. Note Technically there's a slight ambiguity in calls where thesecond label is a valid fmt. plot('n','o',data=obj)could be plt(x,y) or plt(y,fmt). In such cases,the former interpretation is chosen, but a warning is issued.You may suppress the warning by adding an empty format stringplot('n','o',',data=obj).
Returns:	lines A list of Line2D objects representing the plotted data.
Other Parameters:	scalex, scaleybool, optional, default: True These parameters determined if the view limits are adapted tothe data limits. The values are passed on to autoscale_view. **kwargsLine2D properties, optional kwargs are used to specify properties like a line label (forauto legends), linewidth, antialiasing, marker face color.Example: If you make multiple lines with one plot command, the kwargsapply to all those lines. Here is a list of available Line2D properties: Property Description agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha float or None animated bool antialiased or aa bool clip_box Bbox clip_on bool clip_path Patch or (Path, Transform) or None color or c color contains callable dash_capstyle {'butt', 'round', 'projecting'} dash_joinstyle {'miter', 'round', 'bevel'} dashes sequence of floats (on/off ink in points) or (None, None) data (2, N) array or two 1D arrays drawstyle or ds {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default' figure Figure fillstyle {'full', 'left', 'right', 'bottom', 'top', 'none'} gid str in_layout bool label object linestyle or ls {'-', '--', '-.', ':', ', (offset, on-off-seq), ...} linewidth or lw float marker marker style markeredgecolor or mec color markeredgewidth or mew float markerfacecolor or mfc color markerfacecoloralt or mfcalt color markersize or ms float markevery None or int or (int, int) or slice or List[int] or float or (float, float) path_effects AbstractPathEffect picker float or callable[[Artist, Event], Tuple[bool, dict]] pickradius float rasterized bool or None sketch_params (scale: float, length: float, randomness: float) snap bool or None solid_capstyle {'butt', 'round', 'projecting'} solid_joinstyle {'miter', 'round', 'bevel'} transform matplotlib.transforms.Transform url str visible bool xdata 1D array ydata 1D array zorder float

See also

scatter

XY scatter plot with markers of varying size and/or color ( sometimes also called bubble chart).

Notes

Format Strings

A format string consists of a part for color, marker and line:

Each of them is optional. If not provided, the value from the stylecycle is used. Exception: If line is given, but no marker,the data will be a line without markers.

Other combinations such as [color][marker][line] are alsosupported, but note that their parsing may be ambiguous.

Markers

Story Plots Ideas

character	description
'.'	point marker
','	pixel marker
'o'	circle marker
'v'	triangle_down marker
'^'	triangle_up marker
'<'	triangle_left marker
'>'	triangle_right marker
'1'	tri_down marker
'2'	tri_up marker
'3'	tri_left marker
'4'	tri_right marker
's'	square marker
'p'	pentagon marker
'*'	star marker
'h'	hexagon1 marker
'H'	hexagon2 marker
'+'	plus marker
'x'	x marker
'D'	diamond marker
'd'	thin_diamond marker
' '	vline marker
'_'	hline marker

Line Styles

character	description
'-'	solid line style
'--'	dashed line style
'-.'	dash-dot line style
':'	dotted line style

Example format strings:

Colors

The supported color abbreviations are the single letter codes

Story Plots Generator

character	color
'b'	blue
'g'	green
'r'	red
'c'	cyan
'm'	magenta
'y'	yellow
'k'	black
'w'	white

and the 'CN' colors that index into the default property cycle.

If the color is the only part of the format string, you canadditionally use any matplotlib.colors spec, e.g. full names('green') or hex strings ('#008000').