matplotlib 绘制柱状图的几个例子

1 error bar

#!/usr/bin/env python
# a bar plot with errorbars
import numpy as np
import matplotlib.pyplot as plt

N = 5
menMeans = (20, 35, 30, 35, 27)
menStd = (2, 3, 4, 1, 2)

ind = np.arange(N)  # the x locations for the groups
width = 0.35       # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(ind, menMeans, width, color='r', yerr=menStd)

womenMeans = (25, 32, 34, 20, 25)
womenStd = (3, 5, 2, 3, 3)
rects2 = ax.bar(ind + width, womenMeans, width, color='y', yerr=womenStd)

# add some text for labels, title and axes ticks
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind + width)
ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))

ax.legend((rects1[0], rects2[0]), ('Men', 'Women'))


def autolabel(rects):
    # attach some text labels
    for rect in rects:
        height = rect.get_height()
        ax.text(rect.get_x() + rect.get_width()/2., 1.05*height,
                '%d' % int(height),
                ha='center', va='bottom')

autolabel(rects1)
autolabel(rects2)

plt.show()

2 绘制两个量，一个在上，一个在下.关键点在于

p2 = plt.bar(ind, OECD, width, color = 'b', bottom = NonOECD) 这个bottom参数

import numpy as np
import matplotlib.pyplot as plt

N = 7
OECD = (242, 244, 255, 263, 269, 276, 285)
NonOECD = (282, 328, 375, 417, 460, 501, 535)
Sum = ('524', '572', '630', '680', '729', '777', '820')
ind = np.arange(N)
width = 0.5

p1 = plt.bar(ind, NonOECD, width, color = 'r')
p2 = plt.bar(ind, OECD, width, color = 'b', bottom = NonOECD)

plt.ylabel('Quadrillion Btu')
plt.title('World Total Energy Consumption 2010 - 2040')
plt.xticks(ind+width/2., ('2010', '2015', '2020', '2025', '2030', '2035', '2040'))
plt.yticks(np.arange(0, 1001, 200))
plt.legend((p1[0], p2[0]), ('Non - OECD', 'OECD'), loc = 2, frameon = 'false')
plt.tick_params(top = 'off', bottom = 'off', right = 'off')
plt.grid(axis = 'y', linestyle = '-')

plt.show()

3 默认的x轴刻度是[1,...]，而且一般会缩略，可是我们希望x轴刻度是x轴数据本身的范围。

如果这样

axes.bar(bin_index, num_list, bar_width, color='r')

axes.set_xticks(xticks)
是得不到我们想要的，因为在缩略后，刻度可能只有4个，而set_xticks时，就变成只有这四个刻度上有值，而且这些值不是想象中得自动缩略得到，而是只有xticks这个列表中前四个，这样就与我们的要求不符合