01
# 引言
今天继续复现一下朋友发我了一张论文里的图表（原图如下所示），主要是Matplotlib的箱线图+散点图+折线图的组合图，能够非常直观地展现数据的分布情况及其趋势。
02
# 读取数据
由于论文中没提供数据，就拿本地数据做代替，如下图所示，借助pandas读取并转置数据，将年份作为列标签。
import pandas as pdfn = r'D:\ForestMeteorology\FM230331\data\1.xlsx'df = pd.read_excel(fn)df1 = df.iloc[:,:11]df1.set_index('w1',inplace=True)df1.columns = ['v'+str(i) for i in range(1,11)]df1 = df1.Tprint(df1)
03
# 可视化
fig,axs = plt.subplots(1,2,figsize=(8,4))ax = axs[0]箱线图df1.boxplot(ax = ax,showfliers = False,grid = False,color = 'black')折线图ax.plot(range(1,2020-1995+2),df1.describe().loc['mean'],c = 'k',marker = 's',markersize = 3.5,zorder = 10)散点图for j in range(len(df1)):ax.scatter(range(1,2020-1995+2),df1.iloc[j,:],s = 3.5,zorder = 5)ax.set_xticks(range(1,2020-1995+2,5))ax.set_xticklabels(range(1995,2021,5))plt.show()
04
# 完整代码
由于两个子图绘制内容一致，将绘图部分代码封装成函数，方便调用，然后调整一下细节就可以了。
# -*- encoding: utf-8 -*-'''@File : GZH.py@Time : 2023/03/31 23:02:23@Author : HMX@Version : 1.0@Contact : kzdhb8023@163.com'''# here put the import libimport pandas as pdimport matplotlib.pyplot as pltimport matplotlib as mplfontdict = {'weight': 'normal','size':10,'color':'k','family':'SimHei'}mpl.rcParams.update({'text.usetex': False,'font.family': 'stixgeneral','mathtext.fontset': 'stix',"font.family":'serif',"font.size": 10,"mathtext.fontset":'stix',"font.serif": ['Times New Roman'],})def df2png(idf,ax,label):# 箱线图idf.boxplot(ax = ax,showfliers = False,grid = False,color = 'black')# 折线图ax.plot(range(1,2020-1995+2),idf.describe().loc['mean'],c = 'k',marker = 's',markersize = 3.5,zorder = 10)# 散点图for j in range(len(idf)):ax.scatter(range(1,2020-1995+2),idf.iloc[j,:],s = 3.5,zorder = 5)ax.set_xticks(range(1,2020-1995+2,5))ax.set_xticklabels(range(1995,2021,5))ax.set_xlabel('年份',fontdict =fontdict)ax.set_ylabel('森气笔记',fontdict =fontdict)ax.set_ylim(9,15)ax.set_title(label,loc = 'left',y = 0.9)# 读取处理数据fn = r'D:\ForestMeteorology\FM230331\data\1.xlsx'df = pd.read_excel(fn)df1 = df.iloc[:,:11]df1.set_index('w1',inplace=True)df1.columns = ['v'+str(i) for i in range(1,11)]df1 = df1.T# print(df1)df2 = df.iloc[:,13:-1]df2.set_index('w2',inplace=True)df2.columns = ['v'+str(i) for i in range(1,11)]df2 = df2.T# 可视化fig,axs = plt.subplots(1,2,figsize=(8,4))ax1 = axs[0]ax2 = axs[1]df2png(df1,ax1,' (a)')df2png(df2,ax2,' (b)')plt.tight_layout()plt.savefig(r'D:\ForestMeteorology\FM230331\data\GZH.png',dpi = 600)plt.show()
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