matplotlib图表 - 创建水平条形图

Question

我在以下片段中偶然发现,使用matplotlib创建水平条形图:

import matplotlib
from pylab import *

val = 3+10*rand(5)    # the bar lengths
pos = arange(5)+.5    # the bar centers on the y axis
print pos
figure(1)
barh(pos,val, align='center')
yticks(pos, ('Tom', 'Dick', 'Harry', 'Slim', 'Jim'))
xlabel('Performance')
title('horizontal bar chart using matplotlib')
grid(True)
show()

我想修改上面的脚本如下:

1. 使绘制的条纹"不那么粗糙"(即降低绘制的水平条的高度)
2. 将负数和正数绘制为同一图上的水平条

任何帮助(代码片段或链接),以帮助我进行上述修改将非常有帮助.

顺便说一句,如果我想制作堆叠的水平条(比如每个标签有3个堆叠的水平条),我如何修改上面的代码来绘制3个堆叠的水平条形图？

[[编辑]]

有人可以发布两个简短的代码片段,显示如何:

1. 在水平条的另一侧打印标签(例如,第一个隔离区中出现"负"条的标签,第二个象限中出现"正"条的标签

2. 绘制多个(比如说2或3个)水平条(而不是一个).很好的例子是这里显示的前两个图像

Answer 1

import matplotlib
from pylab import *

val = 3-6*rand(5)    # the bar lengths        # changed your data slightly
pos = arange(5)+.5    # the bar centers on the y axis
print pos
figure(1)
barh(pos,val, align='center',height=0.1)    # notice the 'height' argument
yticks(pos, ('Tom', 'Dick', 'Harry', 'Slim', 'Jim'))

gca().axvline(0,color='k',lw=3)   # poor man's zero level

xlabel('Performance')
title('horizontal bar chart using matplotlib')
grid(True)
show()

一般来说,我建议不要使用from pyplot import *.除非您处于交互模式,否则请使用面向对象的方法:

import matplotlib.pyplot as plt
from numpy.random import rand
from numpy import arange

val = 3-6*rand(5)    # the bar lengths
pos = arange(5)+.5    # the bar centers on the y axis
print pos

fig = plt.figure()
ax = fig.add_subplot(111)
ax.barh(pos,val, align='center',height=0.1)
ax.set_yticks(pos, ('Tom', 'Dick', 'Harry', 'Slim', 'Jim'))

ax.axvline(0,color='k',lw=3)   # poor man's zero level

ax.set_xlabel('Performance')
ax.set_title('horizontal bar chart using matplotlib')
ax.grid(True)
plt.show()

画廊是各种情节的良好起点matplotlib

Answer 2

正如振亚所说,你必须调整你的情节.

例如,下面是一个生成自定义水平条形图的函数:

• 输入是数据,包含在字典中
• 然后根据每个类别(人)中的度量(条形)数量以及要在每个类别之间放置的空间计算Y刻度的位置.
• 最后,它绘制每个数据度量(如果您指定了它,则使用不同的颜色)

默认情况下,它会在右侧绘制类别(人员)的名称,但您当然可以更改它.

import numpy as np
import matplotlib.pyplot as plt

# creation of the data
name_list = ['day1', 'day2', 'day3', 'day4']
data = {name: 3+10*np.random.rand(5) for name in name_list}

colors_list = ['0.5', 'r', 'b', 'g'] #optional

def customize_barh(data, width_bar=1, width_space=0.5, colors=None):
    n_measure = len(data)                   #number of measure per people
    n_people = data[data.keys()[0]].size    # number of people

    #some calculation to determine the position of Y ticks labels
    total_space = n_people*(n_measure*width_bar)+(n_people-1)*width_space
    ind_space = n_measure*width_bar
    step = ind_space/2.
    pos = np.arange(step, total_space+width_space, ind_space+width_space)

    # create the figure and the axes to plot the data 
    fig = plt.figure(figsize=(8,6))
    ax = fig.add_axes([0.15, 0.15, 0.65, 0.7])

    # remove top and right spines and turn ticks off if no spine
    ax.spines['right'].set_color('none')
    ax.spines['top'].set_color('none')
    ax.xaxis.set_ticks_position('bottom')
    ax.yaxis.set_ticks_position('right')    # ticks position on the right
    # postition of tick out
    ax.tick_params(axis='both', direction='out', width=3, length=6,
                   labelsize=24, pad=8)
    ax.spines['left'].set_linewidth(3)
    ax.spines['bottom'].set_linewidth(3)

    # plot the data
    for i,day in enumerate(data.keys()):
        if colors == None:
            ax.barh(pos-step+i*width_bar, data[day], width_bar, #facecolor='0.4',
                    edgecolor='k', linewidth=3)
        else:
            ax.barh(pos-step+i*width_bar, data[day], width_bar, facecolor=colors[i],
                    edgecolor='k', linewidth=3)


    ax.set_yticks(pos)
    # you may want to use the list of name as argument of the function to be more
    # flexible (if you have to add a people)
    ax.set_yticklabels(('Tom', 'Dick', 'Harry', 'Slim', 'Jim'))         
    ax.set_ylim((-width_space, total_space+width_space))
    ax.set_xlabel('Performance', size=26, labelpad=10)

customize_barh(data, colors=colors_list)
plt.savefig('perf.png')
plt.show()

产生: