题目：
读取 stock_hist_data.csv 中招商银行（股票代码 600036）2018 年下半年的
股票数据并完成如下数据处理和分析任务：
1、 数据只保留 date、open、high、close、low 和 volume 这几个属性，并按
时间先后顺序对数据进行排序；使用 matplotlib 绘制出收盘价（close）的走势折
线图。
2、 输出这半年内成交量（volume）最低和最高那两天的日期和分别的成交
量；
3、 列出成交量（volume）在 1000000 以上的记录；
4、 计算这半年中收盘价（close）高于开盘价（open）的天数；
5、 计算每月收盘价的平均值，并使用 matplotlib 绘制出柱状图。
import pandas as pdfrom pandas import to_datetimeimport matplotlib.pyplot as plt#读数据data_read = pd.DataFrame(pd.read_csv(open("data.csv",'r')))data_read.drop(['price_change','p_change','ma5','ma10','ma20','v_ma5','v_ma10','v_ma20'],axis=1,inplace=True)print(data_read)#转化为python可以识别的日期格式data_read['date'] = pd.to_datetime(data_read['date'])#按照时间戳进行排序data_read.sort_values(by = ['date'],ascending = True ,inplace = True)#绘制折线图plt.plot(data_read['date'],data_read['close'])plt.xticks()plt.xlabel("date")#x轴的文字说明plt.ylabel("close")#y轴文字说明plt.title("date-close")#此图像的标题plt.show()plt.close()#输出volume最大的和最小的data_read.sort_values(by = 'volume',ascending=True,inplace=True)volume_max = data_read[-1:]volume_min = data_read[0:1]print(volume_max)print(volume_min)#成交量在1000000以上的数据volume_data = data_read[data_read['volume']>1000000]print(volume_data)#收盘价高于开盘价的天数open_data = data_read['open']close_data = data_read['close']s=0for i,op in enumerate(close_data): if op > open_data[i]: s = s + 1;print("收盘价高于开盘价的天数为：",s)data_read['date']=pd.to_datetime(data_read['date'])data_read = data_read.set_index('date')volume_avg=[]seven_volume = data_read['2018-07']seven_temp = seven_volume['close']seven_avg = seven_temp.mean(axis=0)volume_avg.append(seven_avg)eight_volume = data_read['2018-08']eight_temp = eight_volume['close']eight_avg = eight_temp.mean(axis=0)volume_avg.append(eight_avg)nine_volume = data_read['2018-09']nine_temp = nine_volume['close']nine_avg = nine_temp.mean(axis=0)volume_avg.append(nine_avg)ten_volume = data_read['2018-10']ten_temp = ten_volume['close']ten_avg = ten_temp.mean(axis=0)volume_avg.append(ten_avg)eleven_volume = data_read['2018-11']eleven_temp = eleven_volume['close']eleven_avg = eleven_temp.mean(axis=0)volume_avg.append(eleven_avg)twelve_volume = data_read['2018-12']twelve_temp = twelve_volume['close']twelve_avg = twelve_temp.mean(axis=0)volume_avg.append(twelve_avg)print("七到十二月的平均收盘价为：",volume_avg)name_list = ['July','Auguest','September','October','November','December']plt.bar(range(len(volume_avg)),volume_avg,color = 'rgb',tick_label = name_list)plt.show()