数据可视化之matplotlib实战：plt.bar() 绘制并列柱状图 平行柱状图

import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np # 防止乱码 mpl.rcParams["font.sans-serif"] = ["SimHei"] mpl.rcParams["axes.unicode_minus"] = False # 生成数据 x = np.arange(5) y = [6,10,4,5,1] y1 = [2,6,3,8,5] bar_width = 0.35 tick_label = ["A","B","C","D","E"] # 生成多数据并列柱状图 plt.bar(x,y,bar_width,color="c",align="center",label="班级A",alpha=0.5) plt.bar(x+bar_width,y1,bar_width,color="b",align="center",label="班级B",alpha=0.5) # 生成多数据平行柱状图 # plt.barh(x,y,bar_width,color="c",align="center",label="班级A",alpha=0.5) # plt.barh(x+bar_width,y1,bar_width,color="b",align="center",label="班级B",alpha=0.5) # 设置x,y轴标签 plt.xlabel("测试难度") plt.ylabel("试卷份数") # 设置x轴标签位置 plt.xticks(x+bar_width/2,tick_label) plt.legend() plt.show()

import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np # 防止乱码 mpl.rcParams["font.sans-serif"] = ["SimHei"] mpl.rcParams["axes.unicode_minus"] = False # 生成数据 x = np.arange(5) y = [6,10,4,5,1] y1 = [2,6,3,8,5] bar_width = 0.35 tick_label = ["A","B","C","D","E"] # 生成多数据并列柱状图 # plt.bar(x,y,bar_width,color="c",align="center",label="班级A",alpha=0.5) # plt.bar(x+bar_width,y1,bar_width,color="b",align="center",label="班级B",alpha=0.5) # 生成多数据平行柱状图 plt.barh(x,y,bar_width,color="c",align="center",label="班级A",alpha=0.5) plt.barh(x+bar_width,y1,bar_width,color="b",align="center",label="班级B",alpha=0.5) # 设置x,y轴标签 plt.xlabel("测试难度") plt.ylabel("试卷份数") # 设置x轴标签位置 plt.xticks(x+bar_width/2,tick_label) plt.legend() plt.show()