Matplotlib annotate scatter plot

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pandas.DataFrame.plot.scatter¶ DataFrame.plot.scatter (self, x, y, s=None, c=None, **kwargs) [source] ¶ Create a scatter plot with varying marker point size and color. The coordinates of each point are defined by two dataframe columns and filled circles are used to represent each point. 2D Plotting¶ Sage provides extensive 2D plotting functionality. The underlying rendering is done using the matplotlib Python library. The following graphics primitives are supported: arrow() - an arrow from a min point to a max point. circle() - a circle with given radius; ellipse() - an ellipse with given radii and angle

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If you are doing calculations prior to plotting, and these take a while to get carried out, it is a good idea to separate the computational part of scripts from the plotting part (i.e. have a dedicated plotting script). You can use files to save the information from the computation routine, and then read this in to a plotting program.
Time Series Plot with datetime Objects¶ Time series can be represented using either functions (px.line, px.scatter) or plotly.graph_objects charts objects (go.Scatter). For more examples of such charts, see the documentation of line and scatter plots.

Jan 04, 2017 · Matplotlib is the leading visualization library in Python. It is powerful, flexible, and has a dizzying array of chart types for you to choose from. For new users, matplotlib often feels overwhelming. You could spend a long time tinkering with all of the options available, even if all you want to do is create a simple scatter plot.
Add legend to scatter plot(PCA) How to annotate the values of X and Y while hovering mouse over the bar graph Matplotlib canvas as numpy array artefacts

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Currently matplotlib supports wxpython, pygtk, tkinter and pyqt4/5. When embedding Matplotlib in a GUI, you must use the Matplotlib API directly rather than the pylab/pyplot proceedural interface, so take a look at the examples/api directory for some example code working with the API. Jun 21, 2016 · Contour plots are a little different. We don’t use a set_… method, but instead simply redraw the contour plot for each frame. The first line of the function gets rid of existing contours before plotting new ones. Using the contour_opts dict is a handy trick to avoid specifying the same keyword arguments in both calls to contour.
In Matplotlib version 2, the default color cycle is labeled as C[0-9], which is looking pretty great. 0.9 Tips 0.9.1 Generating a PNG with matplotlib when DISPLAY is undefined. For example, when you are using ssh. Data plot. This is similar to a scatter plot, but uses the plot() function instead. The only difference in the code here is the style argument. plt.plot(x, y, 'b^') # Create blue up-facing triangles Data and line. The style argument can take symbols for both markers and line style: plt.plot(x, y, 'go--') # green circles and dashed line Scatter ...