Ggplot multiple geom line color

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Ggplot multiple geom_line color

Source: R/geom-path.r geom_path() combines observations in the order in which they are presented in the data. geom_line() connects them in order of variable on the x. geom_step() axis creates a stairstep plot, highlighting exactly when the changes will occur. The group aesthetic determines which cases are joined together. geom_path( mapping = NULL, data = NULL, stat = identity, position = identity, ..., lineend = ass, linejoin = round, linemitre = 10, arrow = NULL, to.rm = FALSE, show.legend = NA, inherit.aes = TRUE ) geom_line( mapping = NULL, data = NULL, stat = identity, position = identity, to.rm = FALSE, orientation = NA, show.legend = NA, inherit.aes = TRUE, ... ) geom_step( mapping = NULL, data = NULL, stat = identity, position = identity, direction = hv, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ... ) mapping A set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (default), it is combined with the default mapping at the highest level of the plot. If there is no land assignment, you must specify an assignment. data The data to be displayed in this layer. There are three options: If NULL, by default, the data is inherited from the plot data as indicated in the call to ggplot(). A data.frame or other object overwrites rendering data. All objects will be fortified to create a data frame. See fortify(), for which variables will be created. The function is called with one argument, data about the plot. The return value must be data.frame and will be used as a data layer. You can create a function from a formula (e.g. ~head(.x, 10)). Statistics The statistical transformation to be used as a string on the data for this layer. positioning as either a string or the result of a call to the location setting function. ... Additional arguments transferred to layer(). It is often an aesthetic that is used to set aesthetics to a fixed value, such as color = red or size = 3. Parameters can also be paired with geom/stat. lineend line end style (round, ass, square). linejoin line join style (round, mitre, bevel). linemiters Bee-bee limit (number greater than 1). Specification arrow as gridlines are created::arrow(). on.rm if the value is FALSE, the default, the missing values are deleted with a warning. If TRUE, the missing values are quietly deleted. show.legend logical. Should this layer be included in legends? NA, by default, includes if aesthetics are assigned. FALSE never contains, and true always includes. It can also be named logical vector to gently select aesthetics to display. inherit.aes If false, override the default aesthetics rather than combine them. This is most useful for auxiliary functions that define both data and aesthetics and should not inherit behavior from the default plot specification, e.g. orientation layer orientation. The default value (NA) automatically determines the orientation from the aesthetic mapping. In rare cases where can be explicitly stated by setting the orientation to either x or y. For more detailed information, see Orientation. direction of stairs: vh for vertical then horizontal, hv for horizontal then vertical, or middle for step halfway between adjacent values x. Alternative parameterization geom_segment(), where each row corresponds to a single case that provides start and end coordinates. Orientation This geom treats each oss differently, so it can have two orientations. Orientation is often easily derived from a combination of given mapping and types of applicable positional balances. Thus, ggplot2 will by default try to guess which orientation layer it should have. In rare circumstances, orientation is ambiguous and guessing can fail. In this case, the orientation may be specified directly by means of an indicative parameter, which may be either x or y. The value gives the axis that the geom should run along, x is the default orientation you would expect for geom. Aesthetics geom_path() means the following aesthetics (the desired aesthetics is bold): x y alpha color group linetype size More information about setting this aesthetic in highway notoriety (ggplot2-specs). Missing processing geom_path(), geom_line(), and geom_step HANDLE NA as follows: If a NA value occurs in the middle of the line, it breaks the line. Regardless of whether the value is .rm TRUE or FALSE, no warning is displayed. If NA occurs at the beginning or end of the line and .rm is FALSE (default), NA is removed with a warning. If NA occurs at the beginning or end of the line and on.rm is true, NA will be removed silently, without warning. See also geom_polygon(): Completed paths (polygons); geom_segment(): Line Segments Examples # geom_line() is suitable for time series ggplot(economics, aes(date, unemployed)) + geom_line()ggplot(economics_long, aes(date, value01, color =variable)) + geom_line() # You can get a crater that runs vertically by setting the orientation ggplot(economics, aes(unemployed, date)) + geom_line(orientation =y) # geom_step() is useful when you want to emphasize exactly when the #y value changes recent <- economy [economy $date > as. Date(2013-01-01), ] ggplot (recent, aes (date, unemployed)) + geom_line()ggplot (recent, aes (date, unemployed)) + geom_step() # geom_path allows you to explore how two variables are combined over time, # eg <. psavert)) m + geom_path()m + geom_path(aes(color = as.numeric(date))) # Change ---------------------------------------------- ggplot(economics, aes(date, unemployed)) + geom_line(color = red) # Use the arrow parameter to add an arrow to the line # See arrow for more information c <- ggplot(economics, aes(x = date, y = pop)) c + geom_line(arrow = arrow())c + geom_line( arrow = arrow (angle = 15, ends = both, type = closed) ) # Control line joins parameters df <- data.frame(x = 1:3, y = 1, 9)) base <- ggplot(df, aes(x, y)) base + geom_path(size = 10)base + geom_path(size = 10, lineend = round)base + geom_path(size = 10, linejoin = mitre, lineend = ass) # You can use NAs to break the line. df <- data.frame(x = 1:5, y = c(1, 2, NA, 4, 5)) ggplot(df, aes(x, y)) + geom_point() + geom_line()#> Warning: Removed 1 rows containing missing values (geom_point). # \donttest{ # Setting line type vs colour/size # Line type needs to be applied to a line as a whole, so it can #not be used with colour or size that vary across a line x <- seq(0.01, .99, length.out = 100) df <- data.frame( x = rep(x, 2), y = c(qlogis(x), 2 * qlogis(x)), group = rep(c(a,b), each = 100) ) p <- ggplot(df, aes(x=x, y=y, group=group)) # These work p + geom_line(linetype = 2)p + geom_line(aes(colour = group), linetype = 2)p + geom_line(aes(colour = x))# But this doesn't should_stop(p+geom_line(aes(colour=x), linetype=2))# } Hello, First question as a new member : I have a chart with four lines (4 curves , the code is below) and I want to create a legend that matches the color that I use. I try to use scale_color_manual as shown in this tutorial ( . Note: The letter W X Y Z so far are only placeholders. However, no legend appears on my chart. Any help would be appreciated. require(ggplot2) library(grid) x <- theta_vec df <- data.frame(x,likelihood_mtrx) names(df)[1] <- theta names(df)[2] <- pattern1 names(df) [3] < < pattern2 names(df)[4] <- pattern3 (df)[5] <- pattern4 df number_ticks <- function(n) {function(limits) pretty(limits; n)} gg1 <- ggplot(df, aes(x)) + geom_line(aes(y=likelihood_mtrx[,1]), colour=black) + # first layer geom_line(aes(y=likelihood_mtrx[,2]), colour=green) + # second layer geom_line (aes(y=likelihood_mtrx[,]), colour=green) + # second layer geom_line (aes(y=likelihood_mtrx[,,3]), colour=blue) + # third layer geom_line(aes(y =likelihood_mtrx[,4]), colour=red) + # fourth layer laboratories (title=Brute Force Estimate, x=Property Level (\u03b8), y=Probability of response pattern) + scale_x_continuous(breaks =number_ticks(10)) + # 10 looks good , not sure why topic (legend.position=top) + scale_color_manual(name=Liklihood, labels = c(W, X, Y, Z), values = c(W=blue, X=red, Y=green, Z=orange)) printing(gg1) This tutorial R describes how to change the types of chart lines generated using the ggplot2 package. The different types of lines available in the R software are: blank, fixed, dashed, dotted, dotdash, longdash, twodash. Note that row types can also be specified using numbers: 0, 1, 2, 3, 4, 5, 6. 0 is for blank, 1 is for fixed, 2 is for dashed, .... A chart of different line types is shown below: df ## time account ## 1 breakfeast 10 ## 2 Lunch 30 ## 3 Dinner 15 Argument type is used to change the line type : library(ggplot2) # Baseline with ggplot points(data=df, aes(x=time, y=bill, + geom_line()+ geom_point() # Change Change row type ggplot(data=df, aes(x=time, y=bill, group=1)) + geom_line(linetype = dashed)+ geom_point() df2 ## sex time bill ## 1 Female breakfeast 10 ## 2 Female Lunch 30 ## 3 Woman Dinner 15 ## 4 Male breakfeast 13 ## 5 Male Lunch 40 ## 6 Man dinner 17 In charts below, line types, colors and sizes are the same for two groups: library(ggplot2) # Line fence with multiple groups ggplot (data = df2, aes (x = time, y = bill, group=sex)) + geom_line()+ geom_point() # Change row types ggplot(data=df2, aes(x =time, y=bill, group=sex)) + geom_line(linetype= dashed)+ geom_point() # Change the color and size of the line ggplot(data = df2, aes (x = time, y = bill, group = sex)) + geom_line (linetype = dotted , color=red, size=2)+ geom_point(color=blue , size=3) In the charts below, the line types colors and sizes automatically change by variable gender levels : # Change row types by group (sex) ggplot(df2, aes(x=time, y =bill, group=sex)) + geom_line(aes(linetype=sex))+ geom_point()+ topic(legend.position=top) # Change row types + colors ggplot(df2, aes(x=time, y=bill, group=sex)) + geom_line (aes(linetype=sex, color=sex))+ geom_point(aes(color=sex))+ theme(legend.position=top) The following functions can be used : scale_linetype_manual() : to change row types scale_color_manual() : to change line color scale_size_manual () : to resize lines # Set row types manually ggplot(1df2, aes(x =time, y = account , group=sex)) + geom_line(aes(linetype=sex))+ geom_point()+ scale_linetype_manual(values=c(twodash , dotted))+ topic(legend.position=top) # Change the color and size of lines ggplot(df2, aes(x=time, y=bill, group=sex)) + geom_line(aes(linetype=sex, color=sex, size=sex))+ geom_point()+ scale_linetype_manual(values=c(twodash, dotted))+ scale_color_manual(values=c('#999999','#E69F00'))+ scale_size_manual(values=c(1, 1.5))+ topic(legend.position=top) Enjoyed this article? 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