数据可视化｜用条形图进行对比分析

# 导入所需的库import numpy as npimport pandas as pdimport matplotlib as mplimport matplotlib.pyplot as pltimport matplotlib.image as image# 正常显示中文标签mpl.rcParams["font.sans-serif"] = ["SimHei"]# 自动适应布局mpl.rcParams.update({"figure.autolayout": True})# 正常显示负号mpl.rcParams["axes.unicode_minus"] = False# 定义颜色，主色：蓝色，辅助色：灰色，互补色：橙色c = {"蓝色":"#00589F", "深蓝色":"#003867", "浅蓝色":"#5D9BCF",     "灰色":"#999999", "深灰色":"#666666", "浅灰色":"#CCCCCC",     "橙色":"#F68F00", "深橙色":"#A05D00", "浅橙色":"#FBC171"}

# 数据源路径filepath="./data/问卷调查结果2.xlsx"# 读取 Excel文件df = pd.read_excel(filepath, index_col="功能")# 定义画图用的数据category_names = df.indexlabels = df.columnsdata = df.values

# 使用「面向对象」的方法画图，定义图片的大小fig, ax=plt.subplots(figsize=(8, 6))# 设置背景颜色fig.set_facecolor("w")ax.set_facecolor("w")# 设置标题ax.text(0, -1, "
用户满意度随时间的变化", fontsize=26, ha="left", color=c["深灰色"])# 设置 X 轴的取值范围ax.set_xlim(0, 1)# 倒转 Y 轴，让第一个功能排在最上面ax.invert_yaxis()# 定义颜色category_colors = [c["灰色"], c["灰色"], c["橙色"], c["浅蓝色"], c["浅蓝色"]]# 定义条形图所处的位置和高度x = np.arange(len(category_names))height = 0.35# 画条形图bar1 = ax.barh(x-height/2, data[:, 0], height, label=labels[0], color=c["浅灰色"])bar2 = ax.barh(x+height/2, data[:, 1], height, label=labels[1], color=category_colors)# 设置 Y 轴标签字体大小和颜色plt.yticks(range(len(category_names)), " " + category_names, ha="left", color=c["深灰色"], size=18)# ax.set_yticks(range(len(category_names)))# ax.set_yticklabels(category_names + " ")# ax.tick_params(labelsize=18, colors=c["深灰色"])# 设置标签的字体大小fontsize = 16# 设置第一个条形图的数据标签for (i, rect) in zip(range(len(bar1)), bar1):    w = rect.get_width()    ax.text(w, rect.get_y()+rect.get_height()/2, labels[0], ha="right", va="center", color=c["灰色"], fontsize=fontsize)    ax.text(w, rect.get_y()+rect.get_height()/2, " %.0f%%" % (w*100), ha="left", va="center", color=c["深灰色"], fontsize=fontsize)# 设置第二个条形图的数据标签for rect in bar2:    w = rect.get_width()    ax.text(w, rect.get_y()+rect.get_height()/2, labels[1], ha="right", va="center", color=c["浅灰色"], fontsize=fontsize)    ax.text(w, rect.get_y()+rect.get_height()/2, " %.0f%%" % (w*100), ha="left", va="center", color=c["深灰色"], fontsize=fontsize)# 隐藏 X 轴ax.xaxis.set_visible(False)# 隐藏边框ax.spines["top"].set_visible(False)ax.spines["right"].set_visible(False)ax.spines["left"].set_visible(False)ax.spines["bottom"].set_visible(False)# 隐藏 Y 轴的刻度线ax.tick_params(axis="y", which="major", length=0)plt.show()