import pandas as pd
import datetime
from hs_udata import set_token,stock_quote_daily
from mpl_finance import candlestick_ohlc
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
mpl.rcParams['font.sans-serif'] = ['SimHei'] # 指定默認字體
mpl.rcParams['axes.unicode_minus'] = False  # 解決保存圖像是負號'-'顯示為方塊的問題
def GetData(stock_code,start,end):
 #stock_code：獲取股票數(shù)據(jù)的股票代碼
 #start：開始日期
 #  end：結(jié)束日期
 date_start=datetime.datetime.strptime(start,'%Y-%m-%d')
 date_end  =datetime.datetime.strptime(end,'%Y-%m-%d')
 data = pd.DataFrame([])
 while date_start<date_end:
  # 獲取日行情數(shù)據(jù)，接口說明見 https://udata.hs.net/datas/332/
  # adjust_way枚舉值為：0-不復(fù)權(quán)，1-前復(fù)權(quán)，2-后復(fù)權(quán)，此處取前復(fù)權(quán)
  data_i = stock_quote_daily(en_prod_code=stock_code
 ,trading_date=date_start.strftime('%Y%m%d')
 ,adjust_way = 1)
  data=pd.concat([data,data_i],axis=0)# 將行情數(shù)據(jù)按行拼接
  date_start+=datetime.timedelta(days=1) # 日期變量自增
 # 返回行情數(shù)據(jù)
 return data
#1、獲取行情數(shù)據(jù)
stock_code = "600570.SH"# 恒生電子 股票代碼是600570.SH
start='2021-03-01'
end  ='2021-06-01'
set_token(token = 'xxxxxxxxxxxxxxxxxxxxxxxx')# 注冊恒有數(shù)之后，獲取并替換token
data = GetData(stock_code,start,end)

#2、數(shù)據(jù)處理
data = data.loc[data.turnover_status=='交易']# 剔除非交易日
data_price = data[['trading_date','open_price','high_price','low_price'
 ,'close_price','business_amount']]  # 選取日期與高開低收價格
data_price.set_index('trading_date', inplace=True) # 將日期作為索引
data_price = data_price.astype(float) # 將價格數(shù)據(jù)類型轉(zhuǎn)為浮點數(shù)
# 將日期格式轉(zhuǎn)為 candlestick_ohlc 可識別的數(shù)值
data_price['Date'] = list(map(lambda x:mdates.date2num(datetime.datetime.strptime(x,'%Y-%m-%d'))
 ,data_price.index.tolist()))
data_price

#3、計算均值
data_price['MA5']=data_price['close_price'].rolling(window=5).mean()
data_price['MA10']=data_price['close_price'].rolling(window=10).mean()
data_price['MA20']=data_price['close_price'].rolling(window=20).mean()
data_price
 title=

#4、繪制圖片
fig = plt.figure(figsize=(12,10))
grid = plt.GridSpec(12, 10, wspace=0.5, hspace=0.5)
#（1）繪制K線圖
#K線數(shù)據(jù)
ohlc = data_price[['Date','open_price','high_price','low_price','close_price']]
ohlc.loc[:,'Date'] = range(len(ohlc))  # 重新賦值橫軸數(shù)據(jù)，繪制K線圖無間隔
#繪制K線
ax1 = fig.add_subplot(grid[0:8,0:12])# 設(shè)置K線圖的尺寸
candlestick_ohlc(ax1, ohlc.values.tolist(), width=.7
  , colorup='red', colordown='green')
#（2）繪制均線
ax1.plot(range(len(data_price)), data_price['MA5']
, color='red', lw=2, label='MA (5)')
ax1.plot(range(len(data_price)), data_price['MA10']
, color='blue', lw=2, label='MA (10)')
ax1.plot(range(len(data_price)), data_price['MA20']
, color='green', lw=2, label='MA (20)')
#設(shè)置標注
plt.title(stock_code,fontsize = 14) # 設(shè)置圖片標題
plt.ylabel('價 格（元）',fontsize = 14)# 設(shè)置縱軸標題
plt.legend(loc='best')  # 繪制圖例
ax1.set_xticks([])# 日期標注在成交量中，故清空此處x軸刻度
ax1.set_xticklabels([]) # 日期標注在成交量中，故清空此處x軸 
#（3）繪制成交量
#成交量數(shù)據(jù)
data_volume = data_price[['Date','close_price','open_price','business_amount']]
data_volume['color'] = data_volume.apply(lambda row: 1 if row['close_price'] >= row['open_price'] else 0, axis=1)  # 計算成交量柱狀圖對應(yīng)的顏色，使之與K線顏色一致
data_volume.Date = ohlc.Date
 #繪制成交量
ax2 = fig.add_subplot(grid[8:10,0:12])  # 設(shè)置成交量圖形尺寸
ax2.bar(data_volume.query('color==1')['Date']
  , data_volume.query('color==1')['business_amount']
  , color='r')  # 繪制紅色柱狀圖
ax2.bar(data_volume.query('color==0')['Date']
  , data_volume.query('color==0')['business_amount']
  , color='g')  # 繪制綠色柱狀圖
plt.xticks(rotation=30) 
plt.xlabel('日 期',fontsize = 14)# 設(shè)置橫軸標題
#修改橫軸日期標注
date_list = ohlc.index.tolist()  # 獲取日期列表
xticks_len = round(len(date_list)/(len(ax2.get_xticks())-1))# 獲取默認橫軸標注的間隔
xticks_num = range(0,len(date_list),xticks_len) # 生成橫軸標注位置列表
xticks_str = list(map(lambda x:date_list[int(x)],xticks_num))  # 生成正在標注日期列表
ax2.set_xticks(xticks_num)# 設(shè)置橫軸標注位置
ax2.set_xticklabels(xticks_str) # 設(shè)置橫軸標注日期
plt.show()