Python Pylab scatter plot error bars (the error on each point is unique)

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Python Pylab scatter plot error bars (the error on each point is unique)



I am attempting a scatter plot of 2 arrays for which I have a third array containing the absolute error (error in y direction) on each point. I want the error bars to between (point a - error on a) and (point a + error on a). Is there a way of achieving this with pylab and if not any ideas on how else I could do it?




3 Answers
3


>>> import matplotlib.pyplot as plt
>>> a = [1,3,5,7]
>>> b = [11,-2,4,19]
>>> plt.pyplot.scatter(a,b)
>>> plt.scatter(a,b)
<matplotlib.collections.PathCollection object at 0x00000000057E2CF8>
>>> plt.show()
>>> c = [1,3,2,1]
>>> plt.errorbar(a,b,yerr=c, linestyle="None")
<Container object of 3 artists>
>>> plt.show()



where a is your x data
b is your y data
c is your y error if any



note that c is the error in each direction already



This is almost like the other answer but you don't need a scatter plot at all, you can simply specify a scatter-plot-like format (fmt-parameter) for errorbar:


scatter


fmt


errorbar


import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [1, 4, 9, 16]
e = [0.5, 1., 1.5, 2.]
plt.errorbar(x, y, yerr=e, fmt='o')
plt.show()



Result:



enter image description here



A list of the avaiable fmt parameters can be found for example in the plot documentation:


fmt


plot


character description
'-' solid line style
'--' dashed line style
'-.' dash-dot line style
':' dotted line style
'.' point marker
',' pixel marker
'o' circle marker
'v' triangle_down marker
'^' triangle_up marker
'<' triangle_left marker
'>' triangle_right marker
'1' tri_down marker
'2' tri_up marker
'3' tri_left marker
'4' tri_right marker
's' square marker
'p' pentagon marker
'*' star marker
'h' hexagon1 marker
'H' hexagon2 marker
'+' plus marker
'x' x marker
'D' diamond marker
'd' thin_diamond marker
'|' vline marker
'_' hline marker



Is there any way to have the bar at the end of the error line ? like in the picture in copy ?
enter image description here





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3 mins ago






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