python使用matplotlib绘制柱状图教程

Matplotlib的概念这里就不多介绍了

小编之前也和大家分享过python使用matplotlib实现的折线图和制饼图效果，感兴趣的朋友们也可以点击查看，下面来看看python使用matplotlib绘制柱状图的方法吧，具体如下：

1. 基本的柱状图

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.bar(range(len(data)), data)plt.show()

bar(left, height, width=0.8, bottom=None, **kwargs)

事实上，left，height，width，bottom这四个参数确定了柱体的位置和大小。默认情况下，left为柱体的居中位置（可以通过align参数来改变left值的含义），即：

• (left - width / 2, bottom)为左下角位置

• (left + width / 2, bottom + height)为右上角位置

例如：

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.bar([0.3, 1.7, 4, 6, 7], data, width=0.6, bottom=[10, 0, 5, 0, 5])plt.show()

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.bar(range(len(data)), data, fc='g')plt.show()

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.bar(range(len(data)), data, color<a>本文来源gao($daima.com搞@代@#码(网</a>='rgb') # or `color=['r', 'g', 'b']`plt.show()

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.bar(range(len(data)), data, ec='r', ls='--', lw=2)plt.show()

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.bar(range(len(data)), data, ec='k', lw=1, hatch='o')plt.show()

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]labels = ['Tom', 'Dick', 'Harry', 'Slim', 'Jim']plt.bar(range(len(data)), data, tick_label=labels)plt.show()

import numpy as npimport matplotlib.pyplot as pltsize = 5x = np.arange(size)a = np.random.random(size)b = np.random.random(size)plt.bar(x, a, label='a')plt.bar(x, b, bottom=a, label='b')plt.legend()plt.show()

import numpy as npimport matplotlib.pyplot as pltsize = 5x = np.arange(size)a = np.random.random(size)b = np.random.random(size)c = np.random.random(size)total_width, n = 0.8, 3width = total_width / nx = x - (total_width - width) / 2plt.bar(x, a, width=width, label='a')plt.bar(x + width, b, width=width, label='b')plt.bar(x + 2 * width, c, width=width, label='c')plt.legend()plt.show()

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.barh(range(len(data)), data)plt.show()

barh(bottom, width, height=0.8, left=None, **kwargs)

可以看到与plt.bar方法类似。因此堆积条形图和并列条形图的画法与前面类似，不做赘述。

7. 正负条形图

import numpy as npimport matplotlib.pyplot as plta = np.array([5, 20, 15, 25, 10])b = np.array([10, 15, 20, 15, 5])plt.barh(range(len(a)), a)plt.barh(range(len(b)), -b)plt.show()

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