コード例 #1
0
def download_economy():

    #货币供应量
    ts.get_money_supply().to_csv(path + 'money_supply.csv')
    #季度GDP
    ts.get_gdp_quarter().to_csv(path + 'gdp_quarter.csv')
    #年度GDP
    ts.get_gdp_year().to_csv(path + 'gdp_year.csv')
    #CPI
    ts.get_cpi().to_csv(path + 'cpi.csv')

    #存款准备金率
    ts.get_rrr().to_csv(path + 'rrr.csv')
コード例 #2
0
ファイル: reportlab_sub.py プロジェクト: wang-shun/MoDeng
def add_reserve_base_rate_page(canvas_para):
    """
    函数功能:在pdf中增加准备金基率
    :param canvas_para:
    :return:
    """

    c = canvas_para

    c.setFont("song", 10)
    c.drawString(10, letter[1] - 20, '存款准备金基率')
    c.setLineWidth(3)
    c.line(10, letter[1] - 24, letter[0] - 10, letter[1] - 24)

    # 画银行准备金基率
    df_rbr = ts.get_rrr().replace('--', np.nan)
    # df_rbr['date'] = df_rbr.apply(lambda x: stdMonthDate2ISO(x['month']), axis=1)

    # 提取相关数据
    pot_before = extract_point_from_df_date_x(df_rbr, 'date', 'before')
    pot_now = extract_point_from_df_date_x(df_rbr, 'date', 'now')
    pot_changed = extract_point_from_df_date_x(df_rbr, 'date', 'changed')

    data_rbr = [tuple(pot_now)]
    data_rbr_note = ['准备金基率']

    money_drawing = gen_lp_drawing(data=data_rbr,
                                   data_note=data_rbr_note,
                                   height=letter[1] * 0.2)
    renderPDF.draw(drawing=money_drawing, canvas=c, x=10, y=letter[1] * 0.7)

    c.showPage()

    return c
コード例 #3
0
ファイル: dbutil.py プロジェクト: nfsli926/stock
def get_rrr(year, quarter):
    try:
        df = ts.get_rrr()
        engine = create_engine('mysql://*****:*****@127.0.0.1/stock?charset=utf8')
        df.to_sql('rrr', engine, if_exists='append')
        print "message"
    except Exception, e:
        e.message
コード例 #4
0
ファイル: stock_basic.py プロジェクト: cliicy/tu168share
def get_rrr_info():
    df = ts.get_rrr()
    if df is not None:
        res = df.to_sql(microE_rrr, engine, if_exists='replace')
        msg = 'ok' if res is None else res
        print('获取存款准备金率: ' + msg + '\n')
    else:
        print('获取存款准备金率: ' + 'None' + '\n')
コード例 #5
0
ファイル: stock.py プロジェクト: ccfr32/www
 def return_rrr(self):
     '''
     存款准备金率
     '''
     df = ts.get_rrr()
     detail = {}
     for col in df.columns:
         lt = df[col].values.tolist()
         lt.reverse()
         detail[col] = lt
     self.reply(detail=detail)
コード例 #6
0
ファイル: basic_job.py プロジェクト: zhizunbao84/stock-1
def stat_all(tmp_datetime):
    # 存款利率
    data = ts.get_deposit_rate()
    common.insert_db(data, "ts_deposit_rate", False, "`date`,`deposit_type`")

    # 贷款利率
    data = ts.get_loan_rate()
    common.insert_db(data, "ts_loan_rate", False, "`date`,`loan_type`")

    # 存款准备金率
    data = ts.get_rrr()
    common.insert_db(data, "ts_rrr", False, "`date`")

    # 货币供应量
    data = ts.get_money_supply()
    common.insert_db(data, "ts_money_supply", False, "`month`")

    # 货币供应量(年底余额)
    data = ts.get_money_supply_bal()
    common.insert_db(data, "ts_money_supply_bal", False, "`year`")

    # 国内生产总值(年度)
    data = ts.get_gdp_year()
    common.insert_db(data, "ts_gdp_year", False, "`year`")

    # 国内生产总值(季度)
    data = ts.get_gdp_quarter()
    common.insert_db(data, "ts_get_gdp_quarter", False, "`quarter`")

    # 三大需求对GDP贡献
    data = ts.get_gdp_for()
    common.insert_db(data, "ts_gdp_for", False, "`year`")

    # 三大产业对GDP拉动
    data = ts.get_gdp_pull()
    common.insert_db(data, "ts_gdp_pull", False, "`year`")

    # 三大产业贡献率
    data = ts.get_gdp_contrib()
    common.insert_db(data, "ts_gdp_contrib", False, "`year`")

    # 居民消费价格指数
    data = ts.get_cpi()
    common.insert_db(data, "ts_cpi", False, "`month`")

    # 工业品出厂价格指数
    data = ts.get_ppi()
    common.insert_db(data, "ts_ppi", False, "`month`")

    #############################基本面数据 http://tushare.org/fundamental.html
    # 股票列表
    data = ts.get_stock_basics()
    print(data.index)
    common.insert_db(data, "ts_stock_basics", True, "`code`")
コード例 #7
0
def download_economy():

    path = './data/'
    df = ts.get_money_supply()
    df.to_csv(path+'money_supply.csv')
    ts.get_gdp_quarter().to_csv(path+'gdp_quarter.csv')
    ts.get_gdp_year().to_csv(path + 'gdp_year.csv')
    ts.get_cpi().to_csv(path+'cpi.csv')
    # ts.get_hist_data('sz').to_csv(path + 'sz.csv')
    # ts.get_hist_data('sh').to_csv(path + 'sh.csv')

    # import time
    import datetime
    # now_year = time.localtime().tm_year
    # now_mon = time.localtime().tm_mon
    # now_day = time.localtime().tm_mday
    years = 3
    start = datetime.datetime.today().date() + datetime.timedelta(-365*years)
    end = datetime.datetime.today().date()
    ts.get_k_data('399001',  start=str(start), index=True).to_csv(path + 'sz.csv')  #默认2年 ,
    ts.get_k_data('000001',  start=str(start), index=True).to_csv(path + 'sh.csv')
    #
    ts.get_rrr().to_csv(path + 'rrr.csv')
コード例 #8
0
def download_economy():
    import tushare as ts
    path = 'C:/Users/Administrator/stockPriditionProjects/data/'
    ts.get_money_supply().to_csv(path + 'money_supply.csv')
    ts.get_gdp_quarter().to_csv(path + 'gdp_quarter.csv')
    ts.get_gdp_year().to_csv(path + 'gdp_year.csv')
    ts.get_cpi().to_csv(path + 'cpi.csv')
    # ts.get_hist_data('sz').to_csv(path + 'sz.csv')
    # ts.get_hist_data('sh').to_csv(path + 'sh.csv')

    # import time
    import datetime
    # now_year = time.localtime().tm_year
    # now_mon = time.localtime().tm_mon
    # now_day = time.localtime().tm_mday
    years = 3
    start = datetime.datetime.today().date() + datetime.timedelta(-365 * years)
    end = datetime.datetime.today().date()
    ts.get_k_data('399001', start=str(start),
                  index=True).to_csv(path + 'sz.csv')  #默认2年 ,
    ts.get_k_data('000001', start=str(start),
                  index=True).to_csv(path + 'sh.csv')
    #存款准备金率
    ts.get_rrr().to_csv(path + 'rrr.csv')
コード例 #9
0
ファイル: GetData.py プロジェクト: FrankDeng/21Trader
def get_macro():
    Macro={}
    Macro['Depo']=ts.get_deposit_rate()
    Macro['Loan']=ts.get_loan_rate()
    Macro['RRR']=ts.get_rrr()
    Macro['MoneySupply']=ts.get_money_supply()
    Macro['MoneyBalance']=ts.get_money_supply_bal()
    Macro['GDPYOY']=ts.get_gdp_year()
    Macro['GDPQOQ']=ts.get_gdp_quarter()
    Macro['GDPFOR']=ts.get_gdp_for()
    Macro['GDPPULL']=ts.get_gdp_pull()
    Macro['GDPCON']=ts.get_gdp_contrib()
    Macro['CPI']=ts.get_cpi()
    Macro['PPI']=ts.get_ppi()
    Macro['SHIBO']=ts.shibor_data()
    return Macro
コード例 #10
0
def get_required_reserves_rate():
    """得到存款准备金率"""
    logger.info('Begin get RequiredReservesRate.')
    try:
        data_df = ts.get_rrr()
    except Exception as e:
        logger.exception('Error get RequiredReservesRate.')
        return None
    else:
        data_dicts = []
        if data_df.empty:
            logger.warn('Empty get RequiredReservesRate.')
        else:
            data_dicts = [{'date': row[0], 'before': row[1], 'now': row[2], 'changed': row[3]}
                          for row in data_df.values]
            logger.info('Success get RequiredReservesRate.')
        return data_dicts
コード例 #11
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    def core_function(self, type):
        self.set_data()
        print(type)
        mongo = MongoClient("127.0.0.1", 27017)
        if (type == 'gdp_year'):
            print("gdp_year")
            df = fd.get_gdp_year()
        elif (type == 'gdp_quarter'):
            print("gdp_quarter")
            df = fd.get_gdp_quarter()
        elif (type == 'gdp_for'):
            print("gdp_for")
            df = fd.get_gdp_for()
        elif (type == 'gdp_pull'):
            print("gdp_pull")
            df = fd.get_gdp_pull()
        elif (type == 'get_money_supply_bal'):
            print("get_money_supply_bal")
            df = fd.get_money_supply_bal()
        elif (type == 'gdp_contrib'):
            print("gdp_contrib")
            df = fd.get_gdp_contrib()
        elif (type == 'get_cpi'):
            print("get_cpi")
            df = ts.get_cpi()
        elif (type == 'get_ppi'):
            print("get_ppi")
            df = ts.get_ppi()
        elif (type == 'get_rrr'):
            print("get_rrr")
            df = ts.get_rrr()
        elif (type == 'money_supply'):
            print("money_supply")
            df = ts.get_money_supply()
        elif (type == 'money_supply_bal'):
            print("money_supply_bal")
            df = ts.get_money_supply_bal()
        else:
            df = {}

        print(df)
        insert_string = df.to_json(orient='records')
        items = json.loads(insert_string)
        mongo.macro.gdp_year.insert(items)
コード例 #12
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    def __init__(self, instrument, timewindow):
        self.__instrument = instrument
        self.__timewindow = int(timewindow)
        self.__starttime = (
            datetime.datetime.now() -
            datetime.timedelta(days=self.__timewindow)).strftime('%Y-%m-%d')
        # __starttime is max time of entry point
        self.__endtime = datetime.datetime.now().strftime('%Y-%m-%d')
        basics = ts.get_stock_basics()
        profit = ts.get_profit_data(2014, 3)  #code is not the index
        report = ts.get_report_data(2014, 3)
        operation = ts.get_operation_data(2014, 3)
        growth = ts.get_growth_data(2014, 3)
        debtpay = ts.get_debtpaying_data(2014, 3)
        cashflow = ts.get_cashflow_data(2014, 3)
        # country wise

        rrr = ts.get_rrr()
        money_supply = ts.get_money_supply()
        cpi = ts.get_cpi()
コード例 #13
0
 def __call__(self, conns):
     self.base = Base()
     self.financial_data = conns['financial_data']
     '''存款利率'''
     deposit_rate = ts.get_deposit_rate()
     self.base.batchwri(deposit_rate, 'deposit_rate', self.financial_data)
     '''贷款利率'''
     loan_rate = ts.get_loan_rate()
     self.base.batchwri(loan_rate, 'loan_rate', self.financial_data)
     '''存款准备金率'''
     rrr = ts.get_rrr()
     self.base.batchwri(rrr, 'RatioOfDeposit', self.financial_data)
     '''货币供应量'''
     money_supply = ts.get_money_supply()
     self.base.batchwri(money_supply, 'money_supply', self.financial_data)
     '''货币供应量(年底余额)'''
     money_supply_bal = ts.get_money_supply_bal()
     self.base.batchwri(money_supply_bal, 'money_supply_bal',
                        self.financial_data)
     '''国内生产总值(年度)'''
     gdp_year = ts.get_gdp_year()
     self.base.batchwri(gdp_year, 'gdp_year', self.financial_data)
     '''国内生产总值(季度)'''
     gdp_quarter = ts.get_gdp_quarter()
     self.base.batchwri(gdp_quarter, 'gdp_quarter', self.financial_data)
     '''三大需求对GDP贡献'''
     gdp_for = ts.get_gdp_for()
     self.base.batchwri(gdp_for, 'gdp_for', self.financial_data)
     '''三大产业对GDP拉动'''
     gdp_pull = ts.get_gdp_pull()
     self.base.batchwri(gdp_pull, 'gdp_pull', self.financial_data)
     '''三大产业贡献率'''
     gdp_contrib = ts.get_gdp_contrib()
     self.base.batchwri(gdp_contrib, 'gdp_contrib', self.financial_data)
     '''居民消费价格指数'''
     cpi = ts.get_cpi()
     self.base.batchwri(cpi, 'cpi', self.financial_data)
     '''工业品出场价格指数'''
     ppi = ts.get_ppi()
     self.base.batchwri(ppi, 'ppi', self.financial_data)
コード例 #14
0
ファイル: 05_macro.py プロジェクト: yuzaishi/ai_qi
import tushare as ts

# 存款利率
# 结构不规整
dr = ts.get_deposit_rate()
print(dr)


# 贷款利率
# 结构不规整
lr = ts.get_loan_rate()
print(lr)

# 存款准备金率
rrr = ts.get_rrr()
print(rrr)


# 货币供应量
ms = ts.get_money_supply()
print(ms)


# 货币供应量(年底余额)
ms = ts.get_money_supply_bal()
print(ms)


# 国内生产总值(年度)
gy = ts.get_gdp_year()
print(gy)
コード例 #15
0
ファイル: macro.py プロジェクト: wgb128/anack
def rrr():
    return ts.get_rrr()
コード例 #16
0
ファイル: getTushareData.py プロジェクト: ssh352/RSTOCK_TRAIL
# -*- coding: utf-8 -*-
import tushare as ts
# 宏观经济数据
#存款利率
saving_rate = ts.get_deposit_rate()
#贷款利率
loan_rate = ts.get_loan_rate()
#存款准备金率
reserve_rate = ts.get_rrr()
#货币供应量
m_supply = ts.get_money_supply()

#货币供应量(年底余额)

m_supply_y = ts.get_money_supply_bal()

#GDP
gdp_y = ts.get_gdp_year()
gdp_q = ts.get_gdp_quarter()

#三大需求对GDP贡献
gdp_for = ts.get_gdp_for()

#三大产业对GDP拉动
gdp_pull = ts.get_gdp_pull()

#三大产业贡献率
gdp_contrib = ts.get_gdp_contrib()


cpi = ts.get_cpi()
コード例 #17
0
 def getRRRRate(self):
     file_name = 'rrr_rate.csv'
     path = self.index + self.index_rrr + file_name
     data = ts.get_rrr()
     data.to_csv(path, encoding='utf-8')
     print(file_name)
コード例 #18
0
ファイル: quotes.py プロジェクト: hicode/autotrade
def macro_type(macros_type):
    if macros_type == 'deposit_rate':
        deposit_rate = ts.get_deposit_rate()
        if deposit_rate is not None:
            deposit_rate.to_sql('macros_deposit_rate',
                                engine,
                                flavor='mysql',
                                if_exists='replace')
    elif macros_type == 'loan_rate':
        loan_rate = ts.get_loan_rate()
        if loan_rate is not None:
            loan_rate.to_sql('macros_loan_rate',
                             engine,
                             flavor='mysql',
                             if_exists='replace')
    elif macros_type == 'rrr':
        rrr = ts.get_rrr()
        if rrr is not None:
            rrr.to_sql('macros_rrr',
                       engine,
                       flavor='mysql',
                       if_exists='replace')
    elif macros_type == 'money_supply':
        money_supply = ts.get_money_supply()
        if money_supply is not None:
            money_supply.to_sql('macros_money_supply',
                                engine,
                                flavor='mysql',
                                if_exists='replace')
    elif macros_type == 'money_supply_bal':
        money_supply_bal = ts.get_money_supply_bal()
        if money_supply_bal is not None:
            money_supply_bal.to_sql('macros_money_supply_bal',
                                    engine,
                                    flavor='mysql',
                                    if_exists='replace')
    elif macros_type == 'gdp_year':
        gdp_year = ts.get_gdp_year()
        if gdp_year is not None:
            gdp_year.to_sql('macros_gdp_year',
                            engine,
                            flavor='mysql',
                            if_exists='replace')
    elif macros_type == 'gdp_quater':
        gdp_quater = ts.get_gdp_quarter()
        if gdp_quater is not None:
            gdp_quater.to_sql('macros_gdp_quater',
                              engine,
                              flavor='mysql',
                              if_exists='replace')
    elif macros_type == 'gdp_for':
        gdp_for = ts.get_gdp_for()
        if gdp_for is not None:
            gdp_for.to_sql('macros_gdp_for',
                           engine,
                           flavor='mysql',
                           if_exists='replace')
    elif macros_type == 'gdp_pull':
        gdp_pull = ts.get_gdp_pull()
        if gdp_pull is not None:
            gdp_pull.to_sql('macros_gdp_pull',
                            engine,
                            flavor='mysql',
                            if_exists='replace')
    elif macros_type == 'gdp_contrib':
        gdp_contrib = ts.get_gdp_contrib()
        if gdp_contrib is not None:
            gdp_contrib.to_sql('macros_gdp_contrib',
                               engine,
                               flavor='mysql',
                               if_exists='replace')
    elif macros_type == 'cpi':
        cpi = ts.get_cpi()
        if cpi is not None:
            cpi.to_sql('macros_cpi',
                       engine,
                       flavor='mysql',
                       if_exists='replace')
    elif macros_type == 'ppi':
        ppi = ts.get_ppi()
        if ppi is not None:
            ppi.to_sql('macros_ppi',
                       engine,
                       flavor='mysql',
                       if_exists='replace')
コード例 #19
0
ファイル: get_macros.py プロジェクト: deaniiyu/tscrawling
'''
i didn't multiprocess this one since the performance seems acceptable
'''

import tushare as ts
import pandas as pd

if __name__ =='__main__':

    deposit_rate=ts.get_deposit_rate()
    deposit_rate .to_csv('D:\\ts\\macro\\deposit_rate.csv',encoding='gbk')

    loan_rate=ts.get_loan_rate()
    loan_rate.to_csv('D:\\ts\\macro\\loan_rate.csv', encoding='gbk')

    rrr=ts.get_rrr()
    rrr.to_csv('D:\\ts\\macro\\rrr.csv', encoding='gbk')

    money_supply=ts.get_money_supply()
    money_supply.to_csv('D:\\ts\\macro\\money_supply.csv', encoding='gbk')

    money_supply_bal=ts.get_money_supply_bal()
    money_supply_bal.to_csv('D:\\ts\\macro\\money_supply_bal.csv', encoding='gbk')

    gdp_year=ts.get_gdp_year()
    gdp_year.to_csv('D:\\ts\\macro\\gdp_year.csv', encoding='gbk')

    gdp_quater=ts.get_gdp_quarter()
    gdp_quater.to_csv('D:\\ts\\macro\\gdp_quater.csv', encoding='gbk')

    gdp_for=ts.get_gdp_for()
コード例 #20
0
def getrrrdb():
	rrr = ts.get_rrr()
	rrr.to_sql('rrr_data',ENGINE,if_exists='append')
コード例 #21
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 def setRRR(self, isSave=False, tableName=MACROECONOMIC_RRR):
     df = ts.get_rrr()
     if isSave is True:
         df.to_sql(tableName, self.engine_sql, if_exists='append')
     return df
コード例 #22
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def init(engine, session):
	tbl = "macro_deposit"
	tsl.log(tbl + " start...")
	df = ts.get_deposit_rate()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_loan"
	tsl.log(tbl + " start...")
	df = ts.get_loan_rate()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_rrr"
	tsl.log(tbl + " start...")
	df = ts.get_rrr()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_money_supply"
	tsl.log(tbl + " start...")
	df = ts.get_money_supply()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_money_supply_year"
	tsl.log(tbl + " start...")
	df = ts.get_money_supply_bal()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_gdp_year"
	tsl.log(tbl + " start...")
	df = ts.get_gdp_year()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_gdp_quarter"
	tsl.log(tbl + " start...")
	df = ts.get_gdp_quarter()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_gdp_for"
	tsl.log(tbl + " start...")
	df = ts.get_gdp_for()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_gdp_pull"
	tsl.log(tbl + " start...")
	df = ts.get_gdp_pull()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_gdp_contrib"
	tsl.log(tbl + " start...")
	df = ts.get_gdp_contrib()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_cpi"
	tsl.log(tbl + " start...")
	df = ts.get_cpi()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "macro_ppi"
	tsl.log(tbl + " start...")
	df = ts.get_ppi()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
	
	tbl = "gold_and_foreign_reserves"
	tsl.log(tbl + " start...")
	df = ts.get_gold_and_foreign_reserves()
	df.to_sql(tbl,engine,if_exists='replace')
	tsl.log(tbl + " done")
コード例 #23
0
ファイル: zhishu.py プロジェクト: conanxu1/Gd-Hu-C-Cong
import tushare as ts
import matplotlib.pyplot as plt
import matplotlib as mpl
import mpl_finance as mpf
import numpy as np
import pandas as pd

lra = ts.get_rrr()

print(lra[:1])

c = lra.iloc[:, 2]
print(c.values)
n = np.shape(c.values)
print(n[0])
t = np.linspace(1, n[0], n[0])
plt.plot(t, c.values)
plt.show()
コード例 #24
0
ファイル: ts4.py プロジェクト: oJacker/_python
    rate:利率(%)

'''
df = ts.get_loan_rate()
print(df)

# 存款准备金率
'''
返回值说明:

    date :变动日期
    before :调整前存款准备金率(%)
    now:调整后存款准备金率(%)
    changed:调整幅度(%)
'''
df = ts.get_rrr()

#货币供应量
'''
返回值说明:

    month :统计时间
    m2 :货币和准货币(广义货币M2)(亿元)
    m2_yoy:货币和准货币(广义货币M2)同比增长(%)
    m1:货币(狭义货币M1)(亿元)
    m1_yoy:货币(狭义货币M1)同比增长(%)
    m0:流通中现金(M0)(亿元)
    m0_yoy:流通中现金(M0)同比增长(%)
    cd:活期存款(亿元)
    cd_yoy:活期存款同比增长(%)
    qm:准货币(亿元)
コード例 #25
0
ファイル: init.py プロジェクト: dengyongqing/one_strategy
def job_5():
    try:
        print("I'm working......宏观经济数据")
        # 存款利率
        deposit_rate = ts.get_deposit_rate()
        data = pd.DataFrame(deposit_rate)
        data.to_sql('deposit_rate',engine,index=True,if_exists='replace')
        print("存款利率......done")

        # 贷款利率
        loan_rate = ts.get_loan_rate()
        data = pd.DataFrame(loan_rate)
        data.to_sql('loan_rate',engine,index=True,if_exists='replace')
        print("贷款利率......done")

        # 存款准备金率
        rrr = ts.get_rrr()
        data = pd.DataFrame(rrr)
        data.to_sql('rrr',engine,index=True,if_exists='replace')
        print("存款准备金率......done")

        # 货币供应量
        money_supply = ts.get_money_supply()
        data = pd.DataFrame(money_supply)
        data.to_sql('money_supply',engine,index=True,if_exists='replace')
        print("货币供应量......done")

        # 货币供应量(年底余额)
        money_supply_bal = ts.get_money_supply_bal()
        data = pd.DataFrame(money_supply_bal)
        data.to_sql('money_supply_bal',engine,index=True,if_exists='replace')
        print("货币供应量(年底余额)......done")

        # 国内生产总值(年度)
        gdp_year = ts.get_gdp_year()
        data = pd.DataFrame(gdp_year)
        data.to_sql('gdp_year',engine,index=True,if_exists='replace')
        print("国内生产总值(年度)......done")

        # 国内生产总值(季度)
        gdp_quarter = ts.get_gdp_quarter()
        data = pd.DataFrame(gdp_quarter)
        data.to_sql('gdp_quarter',engine,index=True,if_exists='replace')
        print("国内生产总值(季度)......done")

        # 三大需求对GDP贡献
        gdp_for = ts.get_gdp_for()
        data = pd.DataFrame(gdp_for)
        data.to_sql('gdp_for',engine,index=True,if_exists='replace')
        print("三大需求对GDP贡献......done")

        # 三大产业对GDP拉动
        gdp_pull = ts.get_gdp_pull()
        data = pd.DataFrame(gdp_pull)
        data.to_sql('gdp_pull',engine,index=True,if_exists='replace')
        print("三大产业对GDP拉动......done")

        # 三大产业贡献率
        gdp_contrib = ts.get_gdp_contrib()
        data = pd.DataFrame(gdp_contrib)
        data.to_sql('gdp_contrib',engine,index=True,if_exists='replace')
        print("三大产业贡献率......done")

        # 居民消费价格指数
        cpi = ts.get_cpi()
        data = pd.DataFrame(cpi)
        data.to_sql('cpi',engine,index=True,if_exists='replace')
        print("居民消费价格指数......done")

        # 工业品出厂价格指数
        ppi = ts.get_ppi()
        data = pd.DataFrame(ppi)
        data.to_sql('ppi',engine,index=True,if_exists='replace')
        print("工业品出厂价格指数......done")

    except Exception as e:
        print(e)
コード例 #26
0
def load_macro_economy():
    # 下载存款利率
    try:
        rs = ts.get_deposit_rate()
        pd.DataFrame.to_sql(rs, "deposit_rate", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载存款利率ok")
    except:
        print("下载存款利率出错")
    # 下载贷款利率
    try:
        rs = ts.get_loan_rate()
        pd.DataFrame.to_sql(rs, "loan_rate", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载贷款利率ok")
    except:
        print("下载贷款利率出错")
    # 下载存款准备金率
    try:
        rs = ts.get_rrr()
        pd.DataFrame.to_sql(rs, "rrr", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载存款准备金率ok")
    except:
        print("下载存款准备金率出错")
    # 下载货币供应量
    try:
        rs = ts.get_money_supply()
        pd.DataFrame.to_sql(rs, "money_supply", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载货币供应量ok")
    except:
        print("下载货币供应量出错")
    # 下载货币供应量(年底余额)
    try:
        rs = ts.get_money_supply_bal()
        pd.DataFrame.to_sql(
            rs, "money_supply_bal", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True
        )
        print("下载货币供应量(年底余额)ok")
    except:
        print("下载货币供应量(年底余额)出错")
    # 下载国内生产总值(年度)
    try:
        rs = ts.get_gdp_year()
        pd.DataFrame.to_sql(rs, "gdp_year", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载国内生产总值(年度)ok")
    except:
        print("下载国内生产总值(年度)出错")
    # 下载国内生产总值(季度)
    try:
        rs = ts.get_gdp_quarter()
        pd.DataFrame.to_sql(rs, "gdp_quarter", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载国内生产总值(季度)ok")
    except:
        print("下载国内生产总值(季度)出错")
    # 下载三大需求对GDP贡献
    try:
        rs = ts.get_gdp_for()
        pd.DataFrame.to_sql(rs, "gdp_for", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载三大需求对GDP贡献ok")
    except:
        print("下载三大需求对GDP贡献出错")
    # 下载三大产业对GDP拉动
    try:
        rs = ts.get_gdp_pull()
        pd.DataFrame.to_sql(rs, "gdp_pull", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载三大产业对GDP拉动ok")
    except:
        print("下载三大产业对GDP拉动出错")
    # 下载三大产业贡献率
    try:
        rs = ts.get_gdp_contrib()
        pd.DataFrame.to_sql(rs, "gdp_contrib", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载三大产业贡献率ok")
    except:
        print("下载三大产业贡献率出错")
    # 下载居民消费价格指数
    try:
        rs = ts.get_cpi()
        pd.DataFrame.to_sql(rs, "gdp_cpi", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载居民消费价格指数ok")
    except:
        print("下载居民消费价格指数出错")
    # 下载工业品出厂价格指数
    try:
        rs = ts.get_ppi()
        pd.DataFrame.to_sql(rs, "gdp_ppi", con=conn_macro_economy, flavor="mysql", if_exists="replace", index=True)
        print("下载工业品出厂价格指数ok")
    except:
        print("下载工业品出厂价格指数出错")
コード例 #27
0
ファイル: opdata.py プロジェクト: BWZX/opdata
def macrodata(start=None, end=None):
    """macroeconomics data : Shibor | Reserve Ratio | M2 | GDP | CPI | Loan Rate.
    the data start from 2006-10-08. Cause it is when the shibor data start on Tushare.

    parameters:
    ---------
        start: a string present a date indicates the return data start from. for example: '2011-01-22'
        end  : refer to start
    return: 
    --------
        pandas.DataFrame        
    """
    T = __T
    T.rename(columns={'calendarDate': 'date'}, inplace=True)
    today = dt.today()
    today = dt.strftime(today, '%Y-%m-%d')
    T = T[T.date > '2006-04-01']
    T = T[T.date <= today]

    loan = ts.get_loan_rate()  #date loan_type rate
    loan = loan[loan.date > '2006-06-01']
    rate = pd.DataFrame()
    for i in range(len(loan)):
        if loan.iloc[i].loan_type == '短期贷款(六个月以内)':
            rate = rate.append(loan.iloc[i][['date', 'rate']])

    rrr = ts.get_rrr()[['date', 'now']]  # 准备金率
    rrr.rename(columns={'now': 'rrr'}, inplace=True)
    rrr = rrr[rrr.date > '2006-08-01']

    dataScale = ['15', '09']
    dataindex = 0

    def makeDate(raw_date):
        raw_date = str(raw_date)
        raw_date = raw_date.split('.')
        if int(raw_date[1]) <= 9:
            raw_date[1] = '0' + raw_date[1]
        return raw_date[0] + '-' + raw_date[1] + '-' + dataScale[dataindex]

    def makeQuarter(raw_date):
        raw_date = str(raw_date)
        raw_date = raw_date.split('.')
        p = raw_date[1]
        q = {'1': '01', '2': '04', '3': '07', '4': '10'}
        return raw_date[0] + '-' + q[p] + '-' + '15'

    supply = ts.get_money_supply()[['month', 'm2_yoy']]  #15th.
    supply.rename(columns={'month': 'date', 'm2_yoy': 'm2'}, inplace=True)
    if type(supply.iloc[1]['date']) == type(''):
        supply = supply[supply.date > '2006.6']
    else:
        supply = supply[supply.date > 2006.6]
    supply['date'] = supply['date'].apply(makeDate)
    dataindex = dataindex + 1
    m2 = supply

    gdp = ts.get_gdp_quarter()[['quarter',
                                'gdp_yoy']]  # gdp will available at 15th.
    gdp.rename(columns={'quarter': 'date', 'gdp_yoy': 'gdp'}, inplace=True)
    if type(gdp.iloc[1]['date']) == type(''):
        gdp = gdp[gdp.date > '2006.1']
    else:
        gdp = gdp[gdp.date > 2006.1]
    gdp['date'] = gdp['date'].apply(makeQuarter)

    cpi = ts.get_cpi()  #month , cpi,  available at 9th.
    cpi.rename(columns={'month': 'date'}, inplace=True)
    if type(cpi.iloc[1]['date']) == type(''):
        cpi = cpi[cpi.date > '2006.6']
    else:
        cpi = cpi[cpi.date > 2006.6]
    cpi['date'] = cpi['date'].apply(makeDate)

    lastvalue = 0.0

    def setValue(v):
        nonlocal lastvalue
        if pd.isnull(v) or v == 'None':
            return lastvalue
        else:
            lastvalue = v
            return lastvalue

    T = T.merge(cpi, on='date', how='left')
    lastvalue = cpi.iloc[-1]['cpi']
    T['cpi'] = T['cpi'].apply(setValue)

    T = T.merge(gdp, on='date', how='left')
    lastvalue = gdp.iloc[-1]['gdp']
    T['gdp'] = T['gdp'].apply(setValue)

    T = T.merge(m2, on='date', how='left')
    lastvalue = m2.iloc[-1]['m2']
    T['m2'] = T['m2'].apply(setValue)

    T = T.merge(rrr, on='date', how='left')
    lastvalue = rrr.iloc[-1]['rrr']
    T['rrr'] = T['rrr'].apply(setValue)

    T = T.merge(rate, on='date', how='left')
    lastvalue = rate.iloc[-1]['rate']
    T['rate'] = T['rate'].apply(setValue)

    # T=shibor.merge(T,on='date',how='left')
    T = T[T.isOpen > 0.5]
    T = T[T.date >= '2006-10-08']
    del T['isOpen']
    if start and end:
        T = T[T.date >= start]
        T = T[T.date <= end]

    T[['rrr']] = T[['rrr']].astype(float)
    T[['m2']] = T[['m2']].astype(float)
    T[['rate']] = T[['rate']].astype(float)
    T[['gdp']] = T[['gdp']].astype(float)
    T[['cpi']] = T[['cpi']].astype(float)
    T = T.reset_index()
    del T['index']
    return T