While Matplotlib provides an Arc, an inherent problem when directly using it for such purposes is that an arc being circular in data space is not necessarily. It is often useful to mark angles between lines or inside shapes with a circular arc. Perhaps the most basic types of annotations you will use are axes labels. In some cases, this story can be told in an entirely visual manner, without the need for added text, but in others, small textual cues and labels are necessary. The text appears on top of the axis tick labels. This example shows how to create a scale invariant angle annotation. Creating a good visualization involves guiding the reader so that the figure tells a story. The y position of the data is 1, which is the 1 degree Celsius value at that date. Here, the value to annotate has the x position of the TimeStamp of that date. At the very least, this function takes the annotation text as input, in this case, the string ">1 degree", and the xy coordinate that we would like to annotate. Next, we call a method of the Axes object called annotate. For example, for SMILES: > m Chem.MolFromMolFile. Here again is the code that generates the plot, using the function that we implemented previously. Single molecules can be converted to text using several functions present in the rdkit.Chem module. For example, let's say that we noticed that the first date in which the relative temperature exceeded 1 degree Celsius was October 6th, 2015. This means drawing an arrow that points to part of the plot and being able to include text to explain it. It features NER, POS tagging, dependency parsing, word vectors and more. This includes highlighting specific points of interest. spaCy is a free open-source library for Natural Language Processing in Python. One way to draw attention to part of a plot is by annotating it. The following examples show how it is possible to annotate plots in Matplotlib.
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