In [3]:

    

from org.tradesafe.data.history_data import HistoryData
from datetime import datetime, date, timedelta
import os

from pandas.io import sql
from org.tradesafe.utils import utils
from org.tradesafe.data.index_code_conf import indices
from org.tradesafe.conf import config
# from org.tradesafe.utils.memo import Memo
from org.tradesafe.db import sqlite_db as db
import pandas as pd
import tushare as ts
from urllib2 import Request, urlopen
import demjson


    

In [6]:

    

from org.tradesafe.bt.strategy import abstrictStrategy
a = abstrictStrategy(stock_pool=['600036'], start='2015-01-01', end='2016-12-01')
data = a.btData.datas['600036']


    

In [85]:

    

%matplotlib inline
import time
import pandas as pd
import numpy as np
import matplotlib.colors as colors
import matplotlib.finance as finance
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY,YEARLY
from matplotlib.pylab import date2num
import datetime

fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
dates = []
for d in data.index:
    date_time = datetime.datetime.strptime(d,'%Y-%m-%d')
    t = date2num(date_time)
#     dates.append(time.strptime(d, '%Y-%m-%d'))
    dates.append(t)
plt.plot(dates,data.close)
# for label in ax1.xaxis.get_ticklabels():   
#    label.set_rotation(45)
ax1.xaxis.set_major_locator(mdates.MonthLocator())
ax1.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
plt.subplots_adjust(bottom=0.13,top=0.95)
plt.xticks(rotation=45)

fig.suptitle("figure title",fontsize = 14, fontweight="bold")
ax.set_title("axes title")
ax.set_xlabel("x label")
ax.set_ylabel("y label")
# data.plot()

plt.show()


    

In [83]:

    

data_list = []
for d in range(len(data.index)):
    row = data.ix[d]
#     print data.ix[d]['date']
    # 将时间转换为数字
    date_time = datetime.datetime.strptime(row['date'],'%Y-%m-%d')
    t = date2num(date_time)
    datas = (t,row.open,row.high,row.low,row.close,row.volume)
    data_list.append(datas)
# 创建子图
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis_date()
ax.autoscale_view()
# 设置X轴刻度为日期时间
ax.xaxis_date()
plt.xticks(rotation=45)
plt.yticks()
# plt.title("股票代码：601558两年K线图")
# plt.xlabel("时间")
# plt.ylabel("股价（元）")

finance.candlestick_ohlc(ax,data_list,width=1.2,colorup='r',colordown='green')
plt.grid()


    

In [25]:

    

import sklearn
from pandas.io.data import DataReader
from sklearn.linear_model import LogisticRegression
from sklearn.lda import LDA
from sklearn.qda import QDA


    

In [37]:

    

# print len(df)
split = 0.8

df=df[df['target']>0]
X_train = df.ix[0:split,'code':'turnover']
y_train = df.ix[0:split,'target']
X_test = df.ix[split:,'code':'turnover']
y_test = df.ix[split:,'target']


    

In [1]:

    

# print X_train.head(2)
lr = LogisticRegression()
lr.fit(X_train, y_train)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-1-7d3c501bda38> in <module>()
      1 # print X_train.head(2)
----> 2 lr = LogisticRegression()
      3 lr.fit(X_train, y_train)

NameError: name 'LogisticRegression' is not defined

In [2]:

    

pred = model.predict(X_test)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-2-c9f80cad03c6> in <module>()
----> 1 pred = model.predict(X_test)

NameError: name 'model' is not defined

In [ ]: