wind pandas 数据分析绘图

最新推荐文章于 2023-05-24 17:21:04 发布

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最新推荐文章于 2023-05-24 17:21:04 发布 · 置顶 · 2.1k 阅读

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#!/usr/bin/env python
#coding:utf-8
from WindPy import w
from datetime import datetime
from pandas.tseries.offsets import Day
from pandas import Series
from pandas import DataFrame
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

#plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
#plt.rcParams['axes.unicode_minus']=False #用来正常显示负号
period_day=60
Long='1701'
Short='1609'
#varieties=['M.DCE','Y.DCE','P.DCE','JD.DCE','L.DCE','J.DCE','JM.DCE','I.DCE','SR.CZC','CF.CZC','FG.CZC','MA.CZC','RM.CZC','TA.CZC','RU.SHF','RB.SHF']
varieties=['M.DCE','Y.DCE','P.DCE','JD.DCE','L.DCE','J.DCE','JM.DCE','I.DCE','SR.CZC','CF.CZC','FG.CZC','MA.CZC','RM.CZC','TA.CZC','RB.SHF']
#varieties=['P.DCE','CF.CZC','FG.CZC','MA.CZC','RM.CZC']
dfall=DataFrame()

def generate_pd(contracts):
    #wsd_data=w.wsd(contracts, "close", (datetime.now()-period_day*Day()).strftime('%Y-%m-%d'), datetime.now().strftime('%Y-%m-%d'), "")
    wsd_data=w.wsd(contracts, "c