用python画M2和GDP走势图

最新推荐文章于 2025-06-05 11:32:42 发布

Chelseady

最新推荐文章于 2025-06-05 11:32:42 发布

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分类专栏： python

本文链接：https://blog.youkuaiyun.com/Chelseady/article/details/97812864

数据网上查的，分析从1991到2018

# -*- coding: utf-8 -*-
"""
Created on Wed Jun 26 12:46:41 2019

@author: DY
"""
import matplotlib.pyplot as plt
# 1991-2018
gdp=[9.18,14.24,13.96,13.08
     ,10.92,10,9.3,7.83,7.62,8.43,8.3,9.08,10.03,10.09,11.31,12.68,14.16,9.63,
     9.21,10.45,9.3,7.65,7.67,7.4,6.9,6.7,6.9,6.6]
m2=[26.52,31.27,37.31,34.52,29.46,25.25,19.58,14.83,14.73,12.27,17.6,16.86,19.57
    ,14.86,17.57,15.68,16.73,17.77,27.58,19.73,17.32,14.39,13.6,16.7,13.3,11.9,
    8.2,8.2]
x_ax=('91','92','93','94','95','96','97','98','99','00','01','02','03','04','05','06','07',
      '08','09','10','11','12','13','14','15','16','17','18')
tp=[]
for i in range(0,28):
   tp.append(m2[i]-gdp[i])
  #tp[i]=float(m2[i])-float(gdp[i])  
#plt.xticks(x,x_ax)
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.plot(x_ax,gdp,color='blue',label='GDP')
plt.plot(x_ax,m2,color='green',label='m2')
plt.plot(x_ax,tp,color='red',label='m2')
plt.text('96',30,'M2')
plt.text('93',10,'GDP')
plt.t