# 导入必备模块
import matplotlib.finance as mpf
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
sns.set()
def show_ma_kline(security = '000300.XSHG', start_date=None, end_date=None, count=None, FastWindow = 7, ExtraPct = 1.0):
"""
在图一个画布上绘制K线与均线
"""
# 条件约束
if start_date is not None:
count = None
elif count is not None:
start_date = None
# 价格信息
price = get_price(security, start_date=start_date, end_date=end_date, count=count)
# 创建画布
fig, ax = plt.subplots(figsize=(20, 10))
# 绘制K线
qutotes = []
for index, (d, o, c, h, l) in enumerate(zip(price.index,
price['open'],
price['close'],
price['high'],
price['low'])):
d = mpf.date2num(d)
val = (d, o, c, h, l)
qutotes.append(val)
mpf.candlestick_ochl(ax, qutotes, width=0.6, colorup='red', colordown='black')
ax.autoscale_view()
ax.xaxis_date()
# 绘制移动平均线
index_date = np.array([mpf.date2num(dt) for dt in price.index])
ma_df = pd.DataFrame()
for ma in [5, 10, 20, 30, 60, 120]:
ma_df['ma'+str(ma)] = pd.rolling_mean(price['close'], ma)
ma_df.plot(ax=ax, x=index_date)
plt.show()
show_ma_kline(security='000300.XSHG', end_date='2015-8-5', count=100)
