如图，这种误差棒是如何画出的？

平时常见的画法如下：

二者的区别是什么？

你使用什么软件画图

最近一直用python，第二个图可以用 plt.errorbar(x, y, yerr=e, fmt='ro')直接画出。

我想知道第一种errorbar如何画的， 意义应该也不一样？

http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo.html

# fake up some more data
spread= rand(50) * 100
center = ones(25) * 40
flier_high = rand(10) * 100 + 100
flier_low = rand(10) * -100
d2 = concatenate( (spread, center, flier_high, flier_low), 0 )
data.shape = (-1, 1)
d2.shape = (-1, 1)
#data = concatenate( (data, d2), 1 )
# Making a 2-D array only works if all the columns are the
# same length.  If they are not, then use a list instead.
# This is actually more efficient because boxplot converts
# a 2-D array into a list of vectors internally anyway.
data = [data, d2, d2[::2,0]]
# multiple box plots on one figure
figure()
boxplot(data)

show()
就链接中的代码：为什么d2 = concatenate( (spread, center, flier_high, flier_low), 0 )中各个变量的长度不一样还可以 concatenate运算。
从python help了解到的信息是
concatenate((a1, a2, ...), axis=0)
    
    Join a sequence of arrays together.
    
    Parameters
    ----------
    a1, a2, ... : sequence of ndarrays
        The arrays must have the same shape

Type:       builtin_function_or_method
Base Class: <type 'builtin_function_or_method'>
String Form:<built-in function concatenate>
Namespace:  Interactive
Docstring:
concatenate((a1, a2, ...), axis=0)

Join a sequence of arrays together.

Parameters
----------
a1, a2, ... : sequence of array_like
    The arrays must have the same shape, except in the dimension
    corresponding to `axis` (the first, by default).

Examples
--------
>>> a = np.array([[1, 2], [3, 4]])
>>> b = np.array([[5, 6]])
>>> np.concatenate((a, b), axis=0)
array([[1, 2],
       [3, 4],
       [5, 6]])
>>> np.concatenate((a, b.T), axis=1)
array([[1, 2, 5],
       [3, 4, 6]])