def insert_index_data():
m = MongoDB_io()
m.set_db('index_daily_data')
m.set_collection('index_info')
m.delete_document_include_condition()
logging_joinquant()
df = get_all_securities(types='index', date=None)
df.index.name = 'index'
df.reset_index(inplace=True)
df.start_date = pd.to_datetime(df.start_date)
df.end_date = pd.to_datetime(df.end_date)
# 插入数据库
m.insert_huge_dataframe_by_block_to_mongodb(df)
pass
def insert_zz500_data():
m = MongoDB_io()
m.set_db('index_daily_data')
m.set_collection('000905_XSHG')
m.delete_document_include_condition()
logging_joinquant()
df = get_price('000905.XSHG',
start_date='2005-01-01',
end_date='2019-09-25',
fq=None,
frequency='daily')
df.dropna(inplace=True)
## 指数没有复权一说
# df2=get_price('000905.XSHG',fq='pre')
df.index.name = 'date'
df.reset_index(inplace=True)
df.date = pd.to_datetime(df.date)
# 插入数据库
m.insert_huge_dataframe_by_block_to_mongodb(df)
pass
from jqdatasdk import *
from data_base.mongodb import MongoDB_io
auth('15915765128', '87662638qjf')
start_date = '2005-01-01'
df = get_industries(name='sw_l1')
df = df.append(get_industries(name='sw_l2'))
df = df.append(get_industries(name='sw_l3'))
df.index.name = 'industry_code'
df.reset_index(inplace=True)
pass
# 插入数据库
m = MongoDB_io()
m.set_db('stock_daily_data')
m.set_collection('stock_sw_industry_code')
m.insert_huge_dataframe_by_block_to_mongodb(df)
## 后面加上更新验证模块。
pass
from data_base.mongodb import MongoDB_io
auth('15915765128','87662638qjf')
start_date='2005-01-01'
trade_date_list=get_trade_days(start_date=start_date, end_date=None, count=None)
trade_date_info_df=pd.DataFrame()
trade_date_info_df['trade_date']=trade_date_list
trade_date_info_df['weekday']=trade_date_info_df['trade_date'].apply(lambda x:x.weekday())+1.0
trade_date_info_df['trade_month']=trade_date_info_df['trade_date'].apply(lambda x:str(x)[:7])
def get_ordinal_of_date(x):
x['ordinal_in_month']=range(x.shape[0])
x['ordinal_in_month']=x['ordinal_in_month']+1.0
return x
pass
trade_date_info_df=trade_date_info_df.groupby('trade_month').apply(get_ordinal_of_date)
trade_date_info_df['trade_date']=pd.to_datetime(trade_date_info_df['trade_date'])
# 插入数据库
m=MongoDB_io()
m.set_db('stock_daily_data')
m.set_collection('stock_trade_date')
m.insert_huge_dataframe_by_block_to_mongodb(trade_date_info_df)
## 后面加上更新验证模块。
pass
auth('15915765128', '87662638qjf')
m = MongoDB_io()
m.set_db('stock_daily_data')
m.set_collection('stock_sw_industry_code')
sw_indus = m.read_data_to_get_dataframe()
m.set_collection('stock_trade_date')
trade_day_df = m.read_data_to_get_dataframe()
trade_day_df = trade_day_df[
trade_day_df.trade_date > pd.to_datetime('2010-01-01')]
trade_day_list = trade_day_df.trade_date.astype(str)
industry_code_list = sw_indus.industry_code.iloc[:34].tolist()
industry_stock_grouping = pd.DataFrame()
for date in trade_day_list:
print(date)
daily_industry_series = pd.Series()
for industry_code in industry_code_list[:]:
stock_list = get_industry_stocks(industry_code, date=date)
daily_industry_series = daily_industry_series.append(
pd.Series(industry_code, index=stock_list))
pass
daily_industry_series.name = pd.to_datetime(date)
daily_industry_df = daily_industry_series.to_frame()
daily_industry_df_stack_up = daily_industry_df.stack().reset_index()
daily_industry_df_stack_up.columns = ['stock', 'date', 'industry_category']
m.set_collection('stock_sw_industry_category')
m.insert_huge_dataframe_by_block_to_mongodb(daily_industry_df_stack_up)
pass
