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Then, you should be able to update the example.txt file with new coordinates. The result of running this graph should give you a graph as usual. We run the animation, putting the animation to the figure (fig), running the animation function of "animate," and then finally we have an interval of 1000, which is 1000 milliseconds, or one second. Then: ani = animation.FuncAnimation(fig, animate, interval=1000) We open the above file, and then store each line, split by comma, into xs and ys, which we'll plot. We read data from an example file, which has the contents of: 1,5 What we're doing here is building the data and then plotting it. Graph_data = open('example.txt','r').read() Now we write the animation function: def animate(i): Next, we'll add some code that you should be familiar with if you're following this series: e('fivethirtyeight') Regardless of your chosen genre of expertise, mastering these key narrative elements will help to make you a more successful writer. This is the module that will allow us to animate the figure after it has been shown. In a market where publishers and editors are critical of every story or poem, understanding the seven key elements of a narrative is more important than ever before. Here, the only new import is the matplotlib.animation as animation.

To start: import matplotlib.pyplot as plt To do this, we use the animation functionality with Matplotlib. You may want to use this for something like graphing live stock pricing data, or maybe you have a sensor connected to your computer, and you want to display the live sensor data. In this Matplotlib tutorial, we're going to cover how to create live updating graphs that can update their plots live as the data-source updates.