The Complete ggplot2 Tutorial - Part2 | How To Customize ggplot2 (Full R code)
Learn how to create a scatterplot in R. The basic function is plot(x, y), where x and y are numeric vectors denoting the (x,y) points to key=list(title="Three Cylinder Options", It can also color code the cells to reflect the size of the correlations. The below plot has the essential components such as the title, axis labels and . If you are creating a geom where the aesthetics are static, a legend is not .. But what if you want to study how this relationship varies for different classes of. Figures should not duplicate the same information found in tables and vice versa. Elements of a table include the Legend or Title, Column Titles, and the Table Body . Scatter plots are another way to illustrate the relationship between two.
Can you guess what function to use if you have a legend for shape and is based on a categorical variable? The new legend labels are supplied as a character vector to the labels argument. If you want to change the color of the categories, it can be assigned to the values argument as shown in below example. The order of the legend has to be set as desired. If you want to change the position of the labels inside the legend, set it in the required order as seen in previous example.
So it can be modified using the theme function. If you want to place the legend inside the plot, you can additionally control the hinge point of the legend using legend.
Top-Left Inside the Plot" 3. We will add text to only those counties that have population greater than K. This is quite simple. It is available in the ggplot2 package, or you can import it from this link. But what if you want to study how this relationship varies for different classes of vehicles?
It takes a formula as the main argument. Leave the category set to Basic plots and the type set to Scatter. For the Y variable select or type mpg, and for the X variable select or type weight.
Linux Stata does not allow you to select variables so you'll need to type their names. In Windows Stata you can do either. If you click Submit, the graph will be created without closing the dialog box. This allows you to look over the results and then easily make adjustments and try again.
Click Submit now and you should get a simple but professional looking scatter plot. Adding More Variables If you want to add a second Y variable to the scatterplot, the easiest way is to type its name into the Y variable box after the one you've already selected. Stata does not allow you to select multiple variables from the list with the mouse, but it has no trouble understanding multiple variables in the Y variables box as long as you put them there yourself.
To make a sensible graph with two Y variables without having multiple scales we need variables with similar values. The trunk variable qualifies, so type it in the Y variable box after mpg and click Submit again.
The result will be a scatter plot with both variables. Note how Stata automatically puts the two variables in different colors and adds a legend explaining which is which.
An Introduction to Stata Graphics
The legend text is drawn from the variable labels, but you could override all these default behaviors if you so desired. You can then type a condition in the If: Do not type the word if, as that is assumed. To only plot foreign cars, type foreign in the If: Recall that in Stata one is true and zero is false, and foreign is coded accordingly. Click Submit and you'll get a much sparser graph. You can also use more complicated expressions.
Controlling the Markers By default Stata marks each point with a small dot, but you can change this. First click on the Plot tab again, and for best results set the Y variable back to just mpg. Then click Marker Properties. Set Symbol to Hollow circle. Next check Add labels to markers and set the Variable to make, then click Submit. As you see, each point is now a hollow circle with the name of the car printed next to it, but many of the names overlap. You can improve the situation somewhat by changing Label angle to 45 degrees, but in general you can only put useful labels on a scatter plot if it has a small number of observations and they're spread out.
Overlaying Plots Next we'll combine multiple plots. Uncheck Add labels to markers. Click Accept to accept these settings for Marker properties and go back to the Plot 1 window, then click Accept again to accept the plot as it is and go back to the main twoway window. Click Create to add another plot to the graph. This time we'll make a line plot. Set the plot type to Line, and again choose mpg and weight as the Y and X variables.
Click Submit to see the result. It's probably not what you expected--in fact it looks like a scribble. That's because by default Stata draws the line from observation one to observation two to observation three and so forth. What you want is a line from the observation with the lowest weight to the one with the next lowest weight, etc. That's why Stata included the checkbox Sort on x variable.
This does not change the actual order of the observations in your data set, just the order in which they are connected in your line plot. Check it and click Submit again. This time you should get the graph you expected.
Chemistry Lab Resources (for CHM 1XX and 2XX Labs): Graphs/Tables
Note that while the line connects all the points in the scatter plot, it goes to a lot of points that the scatter plot does not include. That's because you didn't set an if condition for the line plot, so it's plotting all the observations in the data.
Line properties You can control what the line looks like by clicking Line Properties. The most commonly used option here is Pattern. By default Stata distinguishes different line plots by color, but that doesn't help if the graph needs to be printed in black and white. So instead you can set a pattern for each line. Alternatively you can choose a scheme designed for printing.
To see it in action set Pattern to Dash. Also try setting Connecting method to Stairstep. Plotting Subsamples Let's go back to just plotting mpg vs. You can do this by creating two plots, one for the foreign cars and one for the domestic cars, each having an if condition that limits it to the proper subpopulation. Then Stata will make them different colors automatically.
Begin by resetting everything. Click Accept twice to get back to the main twoway window, then click the R button in the lower left to reset the plots. Next click Create, leave the type as Scatter, set the Y variable to mpg and set the X variable to weight. Thus this plot will only include the domestic cars. Click Accept to get back to the main twoway window, then click Create again and repeat the entire process with one vital difference: This plot will include only the foreign cars.
The resulting graph very nicely makes the domestic cars blue and the foreign cars red. However, the legend gives you no indication which is which.
To do that you'll need to take control of the legend yourself. Controlling the Appearance of a Graph You haven't seen any options for controlling the legend, because thus far we've been focused on the properties of individual plots. The legend is not associated with a particular plot because it potentially contains information from all the plots.
Thus to get to it you need to click Accept and get back to the twoway window. This is where you control aspects of the graph as a whole, including the legend.
Legends Click on the Legend tab. The Legend behavior just controls whether the legend is shown or not. Since Stata thinks our graph should have one and we agree, we can leave it set to Default. On the other hand, the default keys don't provide any useful information for this graph, so we need to override them. Check Override default keys. Then in the box below you need to type the number of each plot followed by how you want it to be labeled in quotation marks.
For this graph type: Note that the order in which you list the plots is the order in which they'll appear in the legend: The Labels and Region tabs allow you to control the appearance of the legend text and the entire legend box respectively. The various options like sizes and colors are self-explanatory, but these same options appear in many different contexts so it's worth taking a moment to experiment and see how they work.
Choose some different colors and such just to see how they work. Then click Accept to get back to the main twoway window. When you have ordered pairs of points to plot, the ordinate is the element of the ordered pair that is plotted along the vertical axis sometimes called the "y-axis".
Plot numerical scales along each axis. Your plot should have regularly spaced tickmarks and numerical scales along each axis. You do not have to give a number for each tickmark, but you should give enough numbers that the reader can easily interpret the plot. Often one can make neater plots by having your "major" tick mark intervals subdivided into "minor" tick mark intervals; one should only label the major tickmarks.
Use of major and minor tick marks.
Data Frames and Plotting
Make good use of available space. The range of the numerical scale for each axis should be sensible -- large enough to include all data of interest, but small enough that there aren't large sections of the plot that are empty, serve no purpose, and have the net effect of compressing the available space for the plotted data. The plot itself should be large enough and neatly drawn so as to be easily legible.
Three examples of scatterplots making poor use of space and one the last one with a good use of space. Despite the admonition to make good use of space, it is often helpful to include the origin 0,0 in the plot, if it isn't going to make the plot ridiculous in the use of space. Sometimes you will have spurious, outlier points that are very distant from the main group.
In the case of ridiculously separated points, rather than squeeze a lot of points into a small area in the plot just so you can include one extreme outlier into the plot, it is acceptable to leave the outlier out of the plot, but indicate its presence with an arrow pointing to it just inside the nearest edge of the plot to the point.
Generally, any such point is being ignored in the estimation of any linear trend from the data see below. Example of a scatterplot showing an obviously suspicious outlier. Example of a scatterplot right hand panel where some points are so far from the main group of points that their positions are only shown by arrows to indicate the direction they lie and a label stating the abscissa point corresponding to that point, so the reader can determine how far from the plot the point lies.
From Munoz et al. Always label what variable is plotted along each axis. These labels should also make clear what units are being used for the variables being plotted.
For example, in Lab 1 you will be making a plot that should have on the ordinate a label of "field of view arcminutes ". If you do not put the units it will be impossible for the reader to know whether you are taking about degrees, arcminutes, radians, etc. In the golfing plots you see the units are speed in mph and distance in yards.
Plot your x, f x pairs on the plot using points or other clear symbols. If you are plotting multiple data sets on the same plot, make sure each set has a unique and easily distinguishable symbol or color for all its points. Include a legend in the plot that explains what the different symbols mean.
Example of a scatterplot showing what relationship I cannot understand! The "legend" in the upper left hand diagram explains the points and the lines associated with each set of points.
Do not use a bar graph! Many commercial plotting packages are made with business, not science, applications in mind, and their default is to plot vertical bar graphs, not point plots.
Unless you are intentionally trying to make a histogram you should not use a bar graph. Use of a bar graph when a scatterplot is appropriate. Do NOT do this!! If you know the uncertainties in your measurement, plot the points with appropriate eror bars showing the uncertainties in both the downward and upward directions.