NPlot (alias nanoplot) aims to be a minimalistic, easy-to-use data analysis application. Slots oxford casino. NPlot is a free charting library for.NET. It boasts an elegant, flexible API and includes controls for Windows.Forms, ASP.NET and a class for creating Bitmaps. A GTK# control is also available.
Description: NPlot is a free charting library for.NET. It boasts an elegant, flexible API and includes controls for Windows.Forms, ASP.NET and a class for creating Bitmaps.
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
the coordinates of points in the plot. Alternatively, a single plotting structure, function or any R object with a plot method can be provided.
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:
typewhat 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'Casino 10 euro einzahlen. for no plotting.
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.mainan overall title for the plot: see title.
suba sub title for the plot: see title.
xlaba title for the x axis: see title.
ylaba title for the y axis: see title.
aspthe (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
Plot Documentation
Examples
library(graphics)# NOT RUN {require(stats) # for lowess, rpois, rnormplot(cars)lines(lowess(cars))plot(sin, -pi, 2*pi) # see ?plot.function## Discrete Distribution Plot:plot(table(rpois(100, 5)), type = 'h', col = 'red', lwd = 10, main = 'rpois(100, lambda = 5)')## Simple quantiles/ECDF, see ecdf() {library(stats)} for a better one:plot(x <- sort(rnorm(47)), type = 's', main = 'plot(x, type = 's')')points(x, cex = .5, col = 'dark red')# }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')
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
the coordinates of points in the plot. Alternatively, a single plotting structure, function or any R object with a plot method can be provided.
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:
typewhat 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'Casino 10 euro einzahlen. for no plotting.
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.mainan overall title for the plot: see title.
suba sub title for the plot: see title.
xlaba title for the x axis: see title.
ylaba title for the y axis: see title.
aspthe (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
Plot Documentation
Examples
library(graphics)# NOT RUN {require(stats) # for lowess, rpois, rnormplot(cars)lines(lowess(cars))plot(sin, -pi, 2*pi) # see ?plot.function## Discrete Distribution Plot:plot(table(rpois(100, 5)), type = 'h', col = 'red', lwd = 10, main = 'rpois(100, lambda = 5)')## Simple quantiles/ECDF, see ecdf() {library(stats)} for a better one:plot(x <- sort(rnorm(47)), type = 's', main = 'plot(x, type = 's')')points(x, cex = .5, col = 'dark red')# }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 ```
Operation Garden Plot Document
