Examples 
====================

Some examples to retrieve data 


Basic usage:

.. code-block:: python


    index = """
    TP.DK.USD.A
    TP.DK.EUR.A
    TP.DK.CHF.A
    TP.DK.GBP.A
    TP.DK.JPY.A


    """
    df = get_series(index, start_date="01-01-2017", end_date="31-12-2017" )
    print(df.head())



Using multiple indexes and cache:

.. code-block:: python

    from evdspy import get_series , get_series_exp 
    index = """
    TP.DK.USD.A
    TP.DK.EUR.A
    TP.DK.CHF.A
    TP.DK.GBP.A
    TP.DK.JPY.A


    """
    result = get_series_exp(index, start_date="01-01-2017", end_date="31-12-2017" )
    print(result.data)
    print(result.metadata)

cache True for eficient requests. Only checks request result for the current day. 

.. code-block:: python

    from evdspy import get_series , get_series_exp 
    index = """
    TP.DK.USD.A
    TP.DK.EUR.A
    TP.DK.CHF.A
    TP.DK.GBP.A
    TP.DK.JPY.A


    """
    result = get_series_exp(index, cache = True  , start_date="01-01-2017", end_date="31-12-2017" )
    print(result.data)



.. code-block:: python

    from evdspy import get_series , get_series_exp 



    CPI = """
    TP.FG.J0  # Consumer Price Index 
    """

    inf_exp_market_part = """

    TP.ENFBEK.PKA12ENF # Annual inflation expectations of market participants (12-month ahead, %) 

    """
    inf_exp_real_sector = """

    TP.ENFBEK.IYA12ENF # Annual inflation expectations of real sector (12-month ahead, %) 

    """


    for index  in [CPI, inf_exp_market_part, inf_exp_real_sector]:
        res = get_series_exp(index , cache = True  , start_date = "01-01-2010" )
        print(res.data)
        print(res.metadata)


.. code-block:: python


    from evdspy import get_series_exp

    reserves = """
    TP.AB.TOPLAM # Central Bank Reserves 
    """


    result = get_series_exp(reserves, frequency="monthly", start_date="01-01-1994" , aggregation ="avg")
    df = result.data
    print(df.head())  
    df.to_excel("data.xlsx") # only data 
    result.to_excel("result.xlsx") # data and metadata sheets together 


.. code-block:: python


    from evdspy import get_series_exp 
    cpi_table = """
    bie_tukfiy4  # CPI 
    """
    inf_exp_table = """
    bie_enfbek   # inflation expectations 

    """
    reserves_table = """
    bie_abres2   # reserves 

    """

    def clean_name(name : str ) : 
        return name.replace("\n" , "" ).replace(" " , "") 


    for index in [cpi_table, inf_exp_table, reserves_table]:
        res = get_series_exp(index, cache=True, start_date="01-01-2010")
        print(res.data)
        print(res.metadata)
        res.to_excel(clean_name(index) + ".xlsx")