Take the tour ×  I'm trying to generate bar plots from a
DataFrame like this:              Pre    Post  Measure1   0.4
1.9  These values are median values I calculated from elsewhere,
and I have also their variance and standard deviation (and
standard error, too). I would like to plot the results as a bar
plot with the proper error bars, but specifying more than one
error value to yerr yields an exception:  # Data is a DataFrame
instance fig = data.plot(kind="bar", yerr=[0.1, 0.3])
ValueError: In safezip, len(args[0])=1 but len(args[1])=2  If I
specify a single value (incorrect) all is fine. How can I
actually give each column its correct error bar?  share|improve
this question add comment  1 Answer  up vote 3 down vote
accepted  What is your data shape ?  For an n-by-1 data vector,
you need a n-by-2 error vector (positive error and negative
error ) :  import pandas as pd  import numpy as np import
matplotlib.pyplot as plt  df2 = pd.DataFrame( [  0.4 , 1.9 ] )
df2.plot(kind='bar', yerr = [ [0.1,3.0] , [3.