![stata xline color stata xline color](http://5b0988e595225.cdn.sohucs.com/images/20170822/35139ffe78964dcf841e206be2ca85c6.png)
You may refer either to a colour, such as inįind more about filling colours by typing help colorstyle. With histograms, try the fcolor() option. Often, you may add an option referring to the colours used to fill bars or boxes. The width, or thickness, of the line may be changed via option lwidth, such as inĪpart from some keywords that are available (such as medthin, vthin, or thick ), you can use numbers, as in lwidth(*1.2), which will multiply the default width by a factor of 1.2, or in lwidth(1.2), with the value in parentheses difficult to interpret in substantial terms (it refers to a percentage of the width or height of the graph, whichever is smaller - but to translate this into line width is not easy). (dot = short dash) and # (= small amount of blank space). You may combine elements _ (underscore = long dash), - (hyphen = medium dash). Line sales1 sales2 year, lpattern("_-." "_#") You may also create your own line pattern with the help of a "formula", such as in The last option is just in case you wish to draw an invisible line for some reason or other. Other pattern styles are dot, dash_dot, shortdash, shortdash_dot, longdash, longdash_dot or blank. With the first line being drawn as a solid line and the second as a dashed line. Line sales1 sales2 year, lpattern(solid dash)
![stata xline color stata xline color](https://pic2.zhimg.com/v2-1eb7e5229e803d3de553820c016ddf31_r.jpg)
The pattern of the line may be changed via option lpattern, such as in You may also wish to change the thickness of the line.
![stata xline color stata xline color](https://cdn.miacar.it/thumbs/vehicle-gallery-800x560/cars/BMW/X1/sdrive18d-xline-auto/glaciersilber/u40bf4u/a.jpg)
In a line chart, you may distinguish different lines by colour or pattern. Multiple Imputation: Analysis and Pooling StepsĬhanging the Look of Elements of the Graph Lines.Confidence Intervals with ci and centile.Changing the Look of Lines, Symbols etc.
#Stata xline color full
Lastly, we can change the actual color of the box plot by using the box(variable #, color(color_choice)) command:Ī full list of available colors can be found in the Stata Documentation. Graph box mpg, note(“Source: 1978 Automobile Data”) We can also add a note or comment at the bottom of the graph by using the note() command: Graph box mpg, title(“Distribution of mpg”) subtitle(“(sample size = 74 cars)”) We can also add a subtitle underneath the title using the subtitle() command: Graph box mpg, title(“Distribution of mpg”) We can add a title to the plot using the title() command: We can use several different commands to modify the appearance of the box plots. Graph box headroom gear_ratio, over(foreign) For example, the following command can be used to create box plots for the variables headroom and gear_ratio, based on the categorical variable foreign: We can also create box plots for more than one variable based on a categorical variable. For example, the following command can be used to create box plots that show the distribution of mpg, based on the categorical variable foreign, which indicates whether a car is foreign or domestic. We can also create several box plots based on a single categorical variable using the over() command. We can create a vertical box plot for the variable mpg by using the graph box command:Īlternatively, we can create a horizontal box plot by using the graph hbox command:
#Stata xline color how to
We’ll use a dataset called auto to illustrate how to create and modify boxplots in Stata.įirst, load the data by typing the following into the Command box and clicking Enter: This tutorial explains how to create and modify box plots in Stata.
![stata xline color stata xline color](https://www.stata.com/stata-news/news35-2/spotlight/i/slg1.png)
A box plot is a type of plot that we can use to visualize the five number summary of a dataset, which includes: