统计1990年以来哪一个月份星期几容易出现缺口

每个月份出现缺口数量

每个星期出现的缺口数量

从图形上观察，发现A股在星期一、星期五容易出现缺口，5月份到9月份是缺口高发期；

# -*- coding: utf-8 -*-"""Created on Fri Oct 27 10:10:31 2017@author: Administrator"""import pandas as pdimport numpy as npimport timeimport datetime#获取每日交易缺口数据df=pd.read_csv('C:/Users/Administrator/Desktop/quekou.csv')df.columns=['date','up','down','all']#分析每月产生缺口df.index=pd.to_datetime([str(x) for x in list(df['date'])])result={}for j in range(1,13):    data=pd.DataFrame()    for i in range(1990,2018):        if j<10:           index=str(i)+'-0'+str(j)        if j>=10:           index=str(i)+'-'+str(j)        if (i==1990 and j<12) or (i==2017 and j>10):            pass        else:           data_new=df[index]           data=pd.concat([data,data_new])    result[j]=dict(data.sum())    result=pd.DataFrame(result).T    result.to_csv('每月缺口数量.csv')del result['date']result.plot()#计算每个交易日的星期数df['xingqi']=[i.weekday()+1 for i in list(df.index)]result_riqi={}for i in range(1,6):    result_riqi[i]=dict(df[df['xingqi']==i].sum())result_riqi=pd.DataFrame(result_riqi).Tresult_riqi.to_csv('星期每天的缺口数量.csv')del result_riqi['date']del result_riqi['xingqi']result_riqi.plot()