Python tushare.get_industry_classified() Examples

def get_industry_classified(self):
        """
        行业分类
         code    name      c_name
        """
        
        industry = ts.get_industry_classified()
        industry = industry[['code','name','c_name']]
        industry.columns = ['code','name','industryName']
        ##合并多个行业分类
        industryDict = {}
        for line in industry.to_dict('record'):
            if industryDict.get(line['code']) is None:
                industryDict[line['code']] = []
            industryDict[line['code']].append(line['industryName'])
        industry = pd.DataFrame(industryDict.items(),columns=['code','industryName'])
        if self.data is None:
            self.data = industry 

def __init__(self,save=True):
        """
        """
        self.columns = ['code',
                   'name',
                   'industryName',##行业名称
                   'conceptName',##概念分类
                   'areaName',##地域分类
                   'smeName',##是否属于中小板分类
                   'gemName',##是否属于创业板分类
                   'stName',##是否属于警示板分类
                   'hs300s',##是否是沪深300当前成份股及所占权重
                   'sz50s',##获取上证50成份股
                   'zz500s',##中证500成份股
                   'terminated',##终止上市股票列表
                   'suspended',##暂停上市股票列表
                   ]
        self.data = None
        self.get_industry_classified()
        self.get_concept_classified()
        self.get_area_classified()
        self.get_sme_classified()
        self.get_gem_classified()
        self.get_st_classified()
        self.get_hs300s_classified()
        self.get_sz50s_classified()
        self.get_zz500s_classified()
        self.get_terminated_classified()
        self.get_suspended_classified()
        now = dt.datetime.now()
        self.data['datatime']  =  now.strftime('%Y-%m-%d')
        self.data['datatimestramp']  =  now.strftime('%H:%M:%S')
        indexlist = ['code','datatime']##数据库索引
        tableName = 'symbClassified'  
        database(self.data,indexlist,tableName,save) 

def classify_info_to_sql():
    create_classify_table()    
    
    a = ts.get_industry_classified()
    a.columns = ['code', 'name', 'industry']
    b = ts.get_area_classified()
    c = ts.get_sz50s()
    c = c.iloc[:,1::]
    c['sz50'] = '1'
    d = ts.get_hs300s()
    d = d.iloc[:,1::]
    d.columns = ['code','name','hs300_weight']
    e = ts.get_zz500s()
    e = e.iloc[:,1::]
    e.columns = ['code','name','zz500_weight']
    result = pd.merge(a, b, how='left', on=None, left_on=None, right_on=None,
             left_index=False, right_index=False, sort=True,
             suffixes=('_x', '_y'), copy=True, indicator=False)
    result = pd.merge(result, c, how='left', on=None, left_on=None, right_on=None,
             left_index=False, right_index=False, sort=True,
             suffixes=('_x', '_y'), copy=True, indicator=False)
    result = pd.merge(result, d, how='left', on=None, left_on=None, right_on=None,
             left_index=False, right_index=False, sort=True,
             suffixes=('_x', '_y'), copy=True, indicator=False)
    result = pd.merge(result, e, how='left', on=None, left_on=None, right_on=None,
             left_index=False, right_index=False, sort=True,
             suffixes=('_x', '_y'), copy=True, indicator=False)
    df_to_mysql('anack_classify',result)
    
#    ------------------------------------------------------------- 

def industry():
    return ts.get_industry_classified() 

def plot_days():
    if request.method == 'GET' :
        today = ts.get_today_all()
        code_info = ts.get_industry_classified()

        today['code'] = today['code'].astype(unicode)
        one_day = gd.get_data_real_time(code_info, today)
        body = heatmap.get_heatmap('Today', one_day)
        return render_template('heatmap.html', body=body)