Matplotlib双Y轴折线图小实例
- 2020 年 3 月 3 日
- 筆記
本文内容为重复 Learning Python: Part 2 – Visualizing the NBA Draft 教程的第二部分内容
简单注释
fig,ax1 = plt.subplots(figsize=(12,9))
创建画布,有点类似于ggplot2的ggplot()函数的作用;figsize
参数用来控制图片长和宽,但是单位是啥还没搞明白
plt.title()
添加标题
plt.grid()
添加网格axis
参数指定坐标轴
plt.tick_params()
可以控制坐标轴刻度标签字体大小labelsize
大小axis
坐标轴
ax1.set_ylabel()
坐标轴标签
ax1.set_ylim()
坐标轴范围
ax1.legend()
图例;loc
参数指点图例位置;其他参数还需要仔细研究一下
ax1.set_yticks(0,10,5)
坐标轴如何分割
ax1.spines["top"].set_visible(False)
边框
ax1.twinx()
生成另外一个坐标轴
fig.text(0.1,0.02,"Text")
添加文本内容
小例子
import matplotlib.pyplot as plt import numpy as np A = ["a","b","c","d","e"] B = [5,4,6,3,4] fig, ax1 = plt.subplots(figsize=(12,9)) ax1.plot(A,B,label="Practice") plt.title("Example") ax1.legend() ax1.grid(axis="y",color="grey",linestyle="--",alpha=0.5) ax1.tick_params(axis="x",labelsize=30) ax1.tick_params(axis="y",labelsize=20) ax1.set_ylabel("Y",fontsize = 18) ax1.set_xlabel("X",fontsize = 20) ax1.set_ylim(0,15) ax1.set_yticks(np.linspace(0,15,16)) for tl in ax1.get_yticklabels(): tl.set_color('r') ax1.spines['top'].set_visible(False) fig.text(0.1,0.02,"Author:MingYan") plt.savefig("Practice.png")

Practice.png
双Y轴折线图
(plot both of those plots in one plot with 2 y-axis labels) 一个Y轴用来展示每年选秀总人数,另一个Y轴用来展示赢球贡献值的平均值。
导入需要的模块、读入数据
(如需要下文用到的数据,可至公众号后台回复管检测 选秀)
import numpy as np import pandas as pd import matplotlib.pyplot as plt draft_df = pd.read_csv("draft_data_1996_to_2014.csv",index_col=0) X_values = draft_df.Draft_Yr.unique() Y_values_1 = draft_df.groupby('Draft_Yr').Pk.count() Y_values_2 = draft_df.groupby('Draft_Yr').WS_per_48.mean()
绘图
fig, ax1 = plt.subplots(figsize=(12,9)) title = ('The Number of Players Drafted and Average Career WS/48nfor each Draft (1966-2014)') plt.title(title,fontsize=20) plt.grid(axis='y',color='grey',linestyle='--',lw=0.5,alpha=0.5) plt.tick_params(axis='both',labelsize=14) plot1 = ax1.plot(X_values,Y_values_1,'b',label='No. of Players Drafted') ax1.set_ylabel('Number of Players Drafted', fontsize = 18) ax1.set_ylim(0,240) for tl in ax1.get_yticklabels(): tl.set_color('b') ax2 = ax1.twinx() plot2 = ax2.plot(X_values,Y_values_2,'g',label='Avg WS/48') ax2.set_ylabel('Win Shares Per 48 minutes',fontsize=18) ax2.set_ylim(0,0.08) ax2.tick_params(axis='y',labelsize=14) for tl in ax2.get_yticklabels(): tl.set_color('g') ax2.set_xlim(1966,2014.15) lines = plot1 + plot2 ax1.legend(lines,[l.get_label() for l in lines]) ax1.set_yticks(np.linspace(ax1.get_ybound()[0],ax1.get_ybound()[1],9)) ax2.set_yticks(np.linspace(ax2.get_ybound()[0],ax2.get_ybound()[1],9)) for ax in [ax1,ax2]: ax.spines['top'].set_visible(False) ax.spines['bottom'].set_visible(False) ax.spines['right'].set_visible(False) ax.spines['left'].set_visible(False) fig.text(0.1,0.02,'The original content: http://savvastjortjoglou.com/nba-draft-part02-visualizing.htmlnPorter: MingYan',fontsize=10) plt.savefig("Line_chart_4.png")

Line_chart_4.png