实现功能：
列表交易次数统计；
交易次数折线图；
交易k线图买入卖出标注；
如果想要实现放大功能，聚宽没有对应的包，本地可以：
法一：
在前面加 %matlabplotlib notebook ，可惜聚宽报错，可能是装包的版本问题
法二：
Now thanks to mpld3 it's super easy to enable zooming in inline plots!
All you have to do is install mpld3 (pip install mpld3), and then add this to your notebook:
%matplotlib inline
import mpld3
mpld3.enable_notebook()
Now your plots will get a toolbar menu at the bottom left, in which you can enable mouse zooming :)
import tushare as ts
import matplotlib.pyplot as plt
import matplotlib.finance as mpf
from matplotlib.pylab import date2num
import datetime
import pandas as pd
class tradelist_analysis(object):
def __init__(self, path=None,symbol=None):
self.path = path
self.symbol = symbol
# 交易次数统计
def symbol_counts(self):
syms = self.extract_symbols()
return syms.value_counts()
def plot_symbol_counts(self):
syms = self.extract_symbols()
syms.value_counts().plot()
# 读取交易列表
def get_all_df(self):
df = pd.read_csv(self.path) # 导出的时候设置转为utf8无bom格式
df = df[~(df['成交价']=='--')]
return df
# 提取股票代码
def extract_symbols(self):
df = self.get_all_df()
pattern = r'[0-9]{6}.[A-Z]{4}'
syms = df['标的'].str.findall(pattern)
syms = syms.apply(lambda x : x[0])
return syms
# 股票代码添加后缀
def trans_symbol(self):
if len(self.symbol)==11:
return self.symbol
if int(self.symbol[0])==6:
self.symbol = self.symbol+'.XSHG'
else:
self.symbol = self.symbol+'.XSHE'
return self.symbol
# 获取个股买入卖出信息
def get_symbol_df(self):
self.symbol = self.trans_symbol()
df = self.get_all_df()
df['日期']=pd.to_datetime(df['日期'])
bs = df['标的'].str.contains(self.symbol)
dfs = df[bs]
return dfs
# 获取行情数据
def get_hist_data(self):
self.symbol = self.trans_symbol()
dfs = self.get_symbol_df()
start = dfs['日期'].iloc[0]
end = dfs['日期'].iloc[-1]
hist_data = get_price(self.symbol,start_date = start-datetime.timedelta(5), end_date=end+datetime.timedelta(5), frequency='daily', fields=['open', 'high','low','close'])
hist_data.reset_index(inplace=True)
hist_data['index']=hist_data['index'].apply(lambda s:date2num(s))
hist_data=hist_data.as_matrix()
return hist_data
# 创建子图
def plot_candle(self):
hist_data=self.get_hist_data()
dfs = self.get_symbol_df()
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.1)
# 设置X轴刻度为日期时间
ax.xaxis_date()
ax.autoscale_view()
plt.xticks(rotation=45)
plt.yticks()
plt.title("股票代码：xx")
plt.xlabel("时间")
plt.ylabel("股价（元）")
mpf.candlestick_ohlc(ax,hist_data,width=1,colorup='r',colordown='green')
plt.grid()
for i in range(len(dfs)):
dt = dfs['日期'].iloc[i]
price = dfs['成交价'].iloc[i]
#print dt,price
if dfs['交易类型'].iloc[i]=='买':
ax.annotate('buy%s'%price, xy=(dt, float(price)), xytext=(dt, float(price)-0.2),arrowprops=dict(facecolor='black', shrink=0.1),)
else:
ax.annotate('sell%s'%price, xy=(dt, float(price)), xytext=(dt, float(price)+0.2),arrowprops=dict(facecolor='yellow', shrink=0.1),)
ta = tradelist_analysis('transaction_1.csv','000498')
ta.plot_candle()
ta.get_symbol_df()
