#!/usr/bin/env python
# coding: utf-8

# In[32]:
# 更多代码，请关注公众号：Crossin的编程教室

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import tushare as ts
from datetime import *
#设置显示中文
plt.rcParams['font.sans-serif'] = 'SimHei' # windows可设为SimHei，mac可设为Hiragino Sans GB

ts.set_token('你的tushare token')
pro = ts.pro_api()

ts_code = '000001.SZ'
index_df = pro.daily(ts_code=ts_code, start_date='20130101', end_date='20201203')
# index_df = pro.index_dailybasic(ts_code = "000001.SH",start_date = "20130101",
#                                 end_date = "20200311",fields="trade_date,pe_ttm")
index_df.sort_values(by="trade_date",inplace=True)
x = pd.to_datetime(index_df["trade_date"]).values
y = index_df["close"].values
# y = index_df["pe_ttm"].values

index_df
# print(x,y)


# In[33]:


fig,ax = plt.subplots(figsize=(12,8))
ax.plot(x,y)


# In[34]:


max = np.max(y)
pe_80 = np.percentile(y,80)
pe_20 = np.percentile(y,20)
min = np.min(y)
now = y[-1]   #为了后面标注最新收盘价用


# In[35]:


fig,ax = plt.subplots(figsize=(12,8))
ax.plot(x,y,linewidth=3)
ax.fill_between(x,min-1,pe_20,facecolor = "#00ff80",alpha=0.2)
ax.fill_between(x,pe_20,pe_80,facecolor = "#ffff4d",alpha=0.2)
ax.fill_between(x,pe_80,max+1,facecolor = "#ff69b4",alpha=0.2)


# In[36]:


fig,ax = plt.subplots(figsize=(12,8))
ax.plot(x,y,linewidth=3)
ax.fill_between(x,min-1,pe_20,facecolor = "#00ff80",alpha=0.2)
ax.fill_between(x,pe_20,pe_80,facecolor = "#ffff4d",alpha=0.2)
ax.fill_between(x,pe_80,max+1,facecolor = "#ff69b4",alpha=0.2)
ax.tick_params(axis='both', which='both',length=0)
ax.tick_params(axis='both', which='major', labelsize=16)
ax.margins(0.01,0)
ax.text(0.75,0.9,"最新收盘价：{}".format(now),transform=ax.transAxes,fontdict={'size':18})
plt.xticks(rotation=45)
plt.box(False)
plt.title("{} 价格分布区间".format(ts_code), fontdict={'size':24})


# In[37]:


def pe_plot(ts_code = "",name="",period=5):
    #准备数据
    now = datetime.now()
    end_date = str(now.date()).replace("-","")
    start_date = str(now.year-period)+end_date[4:]
    index_df = pro.daily(ts_code=ts_code, start_date='20130101', end_date='20201203')
    index_df.sort_values(by="trade_date",inplace=True)
    x = pd.to_datetime(index_df["trade_date"]).values
    y = index_df["close"].values

    #划定分割范围
    max = np.max(y)
    pe_80 = np.percentile(y,80)
    pe_20 = np.percentile(y,20)
    min = np.min(y)
    now = y[-1]

    #绘图
    fig,ax = plt.subplots(figsize=(12,8))
    ax.plot(x,y,linewidth=3)
    ax.fill_between(x,min-1,pe_20,facecolor = "#00ff80",alpha=0.2)
    ax.fill_between(x,pe_20,pe_80,facecolor = "#ffff4d",alpha=0.2)
    ax.fill_between(x,pe_80,max+1,facecolor = "#ff69b4",alpha=0.2)
    ax.tick_params(axis='both', which='both',length=0)
    ax.tick_params(axis='both', which='major', labelsize=16)
    ax.margins(0.01,0)
    ax.text(0.75,0.9,"最新收盘价：{}".format(now),
            transform=ax.transAxes,fontdict={'size':18})
    plt.xticks(rotation=45)
    plt.box(False)
    plt.title("{} 价格分布区间".format(ts_code),fontdict={'size':24})
    plt.show()


# In[38]:


pe_plot(ts_code="600519.SH",period=5)


# In[ ]: