![]() Notice that the y values are not necessarily discrete, they can take any value. We first generate some sequence of data, and then esentially, the stem function takes the array of values of the sequence along x, and the array of values of y for the same sequence. ![]() ![]() R doesn’t come with a built-in function for this type of graph, as Matlab and Python do, but don’t be dissapointed!, with the power of ggplot we can achieve very similar stem plots in R with a little few steps, maintaining the distinctive plotting style of R. This type of plot, the stem plot, it’s very common in the Matlab community and in the Python environment as well, actually, the Matplotlib python package claims its function to be inspired by the original stem function in Matlab. Likewise, any sample obtained from a continuous series at uniformly spaced times, would also fit this category. Another case are outcomes of experiments that are peformed in multiple phases, like a Bernoulli random variable trial at each hour. The most common data of this type are mathematical series, like sin and cosine type of sequences at distinct separates points in time, or, data from electrical discrete signals, where a signal can take values only at specific times, for example, a particular voltage that is only measured at fixed rates.īut in fact, there’s a whole other range of examples, any ranking list is sequential by nature and we can compare different values for each entity, or any index measure at particular points in time, like an economic indicator that only changes when there are market movements. This tutorial focuses on a not very common type of plot helpful to visualize sequences of discrete data, the Stem plot.
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