Python ETL.get_Kospi_data_ex1 Examples

Example #1

from manager.dbmanager import DBManager
from etl.etl import ETL

manager = DBManager()
etl = ETL(manager=manager)
etl.get_Kospi_data_ex1("local_files/kospi.xlsx")

Example #2

File: run.py Project: ilyshnikova/OpenNeurons

##### LOADING DATA FROM VARIOUS SOURCES

    # Download local files for superviesd learning
    load_data_instr = {"category_name": 'Iris Fisher'}
    etl.load_supervised_data(path='local_files/iris.csv', ctg_name=load_data_instr["category_name"])

    # Define categories for JapanExchange_Derivatives_ex2
    cats = [Category(name='futures', description='azaza'),
            Category(name='call', description='azaza'),
            Category(name='put', description='azaza'),
            Category(name='cbr', description='azaza')]
    DB.session.add_all(cats)

    # Import Future Data
    c, r, rh = etl.get_Kospi_data_ex1('../Kospi Quotes Eikon Loader.xlsx')

    # Download file 'rb_e20161027.txt.csv'
    etl.get_JapanExchange_Derivatives_ex2('../rb_e20161027.txt.csv')

    # Import data from pdf
    path = "../Examples/Acts 2016/"
    etl.get_PDF_case_1(path)

    # Receiving daily data from the CBR (exchange rates, discount prices of precious metals ...)
    etl.get_CBR_ex3(datetime.datetime(2016, 10, 10), datetime.datetime.now())

    # Define categories for Quandl data
    Category = pd.DataFrame([{'name': 'Financial Markets', 'description': 'Financial Markets Data Branch'},
                             {'name': 'Europe', 'description': 'Europe', 'parent_name': 'Financial Markets'},
                             {'name': 'Russia', 'description': 'Russia', 'parent_name': 'Europe'},