Matplotlib errorbar function draws error margin with datapoints in matplotlib graph. The erorbar() is a function of matplotlib.pyplot.In this article, We will see the implementation of errorbar() with a minimal example stepwise.
Step wise Implementation of matplotlib errorbar –
Please follow below the steps to implement the above function.
Firstly, We need to import matplotlib because errorbar() is the part of this function. We also need NumPy package for data point creation.
import numpy as np import matplotlib.pyplot as plt
Secondly, As we know graph needs data points. Here we need NumPy module and create some data points.
x_axis = np.arange(1, 4, 0.3) y_axis = np.exp(-x)
Inorder to draw the error bar, We need some value for X-Axis and Y-Axis. That is why We have created x_axis and y_axis NumPy array.
In this step, We will invoke the errorbar(). But we need a few more parameter which we need to set before calling this function.
xerr = 0.2 yerr = 0.3
Here we have used a constant value for xerr and yerr. But it may be an array. This array can have different error magnitude for each data points. But as we have given a constant value hence the magnitude will be fixed.
plt.errorbar(x_axis, y_axis, 0.2, 0.3)
Complete code –
In the above section, We have done an example in steps. In this section, we will converge them and provide you with a runnable example of matplotlib errorbar()function.
import matplotlib.pyplot as plt import numpy as np x_axis = np.arange(1, 4, 0.3) y_axis = np.exp(-x) plt.errorbar(x_axis, y_axis, 0.2, 0.3) plt.title("Demo errorbars")
When we execute the above code we get the below output.
Now we have plot the errorbar() function on the above data points.
Errorbar has widely used visuals in Data Science. In this article, We have seen the implementation of errorbar() function in python with a real example. I hope this stepwise explanation makes this concept clear to you. Still, If you have any doubt on the errorbar topic, Please comment in the comment box.
Data Science Learner Team
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