(编辑:jimmy 日期: 2024/12/26 浏览:2)
使用matplotlib
创建百分比堆积柱状图的思路与堆积柱状图类似,只不过bottom
参数累计的不是数值而是百分比,因此,需要事先计算每组柱子的数值总和,进而求百分比。
适用于少量数据,数据结构需要手动构造。
import matplotlib.pyplot as plt labels = ['G1', 'G2', 'G3', 'G4', 'G5'] first = [20, 34, 30, 35, 27] second = [25, 32, 34, 20, 25] third = [21, 31, 37, 21, 28] fourth = [26, 31, 35, 27, 21] data = [first, second, third, fourth] x = range(len(labels)) width = 0.35 # 将bottom_y元素都初始化为0 bottom_y = [0] * len(labels) # 计算每组柱子的总和,为计算百分比做准备 sums = [sum(i) for i in zip(first, second, third, fourth)] for i in data: # 计算每个柱子的高度,即百分比 y = [a/b for a, b in zip(i, sums)] plt.bar(x, y, width, bottom=bottom_y) # 计算bottom参数的位置 bottom_y = [(a+b) for a, b in zip(y, bottom_y)] plt.xticks(x, labels) plt.title('Percent stacked bar ') plt.show()
第一个版本的缺陷在于数据需要手动构造,而且计算稍微繁琐一些。
使用numpy便于处理规模比较大且已存储在文件中数据的数据,计算更简便。
import numpy as np import matplotlib.pyplot as plt labels = ['G1', 'G2', 'G3', 'G4', 'G5'] first = [20, 34, 30, 35, 27] second = [25, 32, 34, 20, 25] third = [21, 31, 37, 21, 28] fourth = [26, 31, 35, 27, 21] data = [first, second, third, fourth] x = range(len(labels)) width = 0.35 # 将bottom_y元素都初始化为0 bottom_y = np.zeros(len(labels)) data = np.array(data) # 按列计算计算每组柱子的总和,为计算百分比做准备 sums = np.sum(data, axis=0) for i in data: # 计算每个柱子的高度,即百分比 y = i / sums plt.bar(x, y, width, bottom=bottom_y) # 计算bottom参数的位置 bottom_y = y + bottom_y plt.xticks(x, labels) plt.title('Percent stacked bar ') plt.show()