Drawing A Plot With Error Bars Using Python Matplotlib

Overview:

  • Error bars indicate how much each data point in a plot deviates from the actual value.

 

  • Error bars display the standard deviation of the distribution while the actual plot depicts the shape of the distribution.

 

  • For graphs present in the research papers it is a necessary to display the error value along with the data points which depicts the amount of uncertainty present in the data.

 

  • The function matplotlib.pyplot.errorbar() plots given x values and y values in a graph and marks the error or standard deviation of the distribution on each point.

 

Example:

import numpy as np

import matplotlib.pyplot as plot

 

# Depth data

xData        = np.arange(10, 110, 10)

 

multiplesOf  = 15

dataCount    = 10

 

# Water pressure data

yData        = list(range(multiplesOf, (dataCount+1)*multiplesOf, multiplesOf))

 

# Set error values for X axis and Y axis data

xerror         = 2

yerror         = 2

 

# Draw the plot with error bars

plot.errorbar(xData, yData, xerr=xerror, yerr=yerror, errorevery=1, markeredgewidth=10)

 

# Set X axis label for the errorbar graph

plot.xlabel('Water Depth in feet')

 

# Set Y axis label for the errorbar graph

plot.ylabel('Pressure in psi')

 

# Set Title for the errorbar graph

plot.title('Water Depth vs Pressure(pressure having a hypothetical error of 2 psi)')

 

# Display the errorbar graph

plot.show()

 

 

Output:

Drawing error bars using python matplotlib

 

 

 


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