#各種Importimport tushare as tsimport pandas as pdimport matplotlib.pyplot as pltimport matplotlib as mplimport seaborn as sbimport numpy as npsb.set_style("whitegrid")   #繪圖樣式mpl.rcParams['font.sans-serif'] = ['SimHei']   # 指定默認字體mpl.rcParams['axes.unicode_minus'] = False    # 解決保存圖像是負號'-'顯示為方塊的問題ts.set_token('08a1f9ec134442837328a82f2f5235394d84c') #請注冊使用自己的TS key，這個key沒用pro = ts.pro_api()stock_code = '000002.SZ'  #需要查閱的股票代碼，前邊是代碼，后邊是市場，詳見Tushare說明def get_data(x):          #取得股票數(shù)據(jù)的函數(shù)，包括股票價格，復權(quán)信息，基本的基本面信息    df_day = pro.daily(ts_code=x)                  #取日線行情，最新限制，只能取4000條，需要再多，用循環(huán)按日期取多次    df_adj_factor = pro.adj_factor(ts_code=x)      #取復權(quán)因子    df_basic = pro.daily_basic(ts_code=x)          #取基本面信息    del df_basic['close']                          #去掉冗余信息    #合并數(shù)據(jù)并返回    df = df_day.merge(right=df_adj_factor,how='left',on=['ts_code','trade_date'])    df = df.merge(right=df_basic,how='left',on=['ts_code','trade_date'])    return dfdef get_name(x): #返回股票名字    df = pro.namechange(ts_code=x, fields='name')    return df.iloc[0,0]def str_to_date(str): #轉(zhuǎn)換YYYYMMDD到Y(jié)YYY-MM-DD    if len(str)==8:        return str[0:4]+'-'+str[4:6]+'-'+str[6:8]   #老人家表示知道format但就愛那么干    else:        return str    title = stock_code + ' - ' + get_name(stock_code)    #顯示標題df = get_data(stock_code)                            #取得數(shù)據(jù)df['trade_date']=df['trade_date'].apply(str_to_date)  #轉(zhuǎn)換trade_date到日期類型，并設(shè)置為索引df['trade_date'] = pd.to_datetime(df['trade_date'])df.set_index('trade_date',inplace=True)#按季度做重采樣，并計算收盤價以及基本面信息period_type = 'Q' #Q季度，也可以用M月df_quote = df.resample(period_type).last()df_quote['close'] = df['close'].resample(period_type).last()df_quote['PE'] = df['pe'].resample(period_type).last()df_quote['PB'] = df['pb'].resample(period_type).last()df_quote['PS'] = df['ps'].resample(period_type).last()df_quote['adj_factor'] = df['adj_factor'].resample(period_type).last()df_quote = df_quote[df_quote['ts_code'].notnull()]df_quote['Price'] = df_quote['close']*df_quote['adj_factor'] #計算復權(quán)價df_quote.reset_index(inplace=True)                           #重置索引df = df_quote.loc[:,['trade_date','PE','PB','PS','Price']]   #取需要的列df.plot(kind='line',x='trade_date',             figsize=(15,13),title=title,             fontsize=20, subplots=True, logy=False)plt.show()

df.tail()

df.describe()

df = df.sort_values('PE')df.head(20)