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in Data Science by (17.9k points)

I have the list like this:

symbols = ['AAPL', 'MSFT']

I want to use values in a list to complete the process as below.

df_AAPL_income = get_annual_finData_by_symbol('income','AAPL','us')

df_AAPL_balancesheet = get_annual_finData_by_symbol('balancesheet','AAPL','us')

df_MSFT_income = get_annual_finData_by_symbol('income','MSFT','us')

df_MSFT_balancesheet = get_annual_finData_by_symbol('balancesheet','MSFT','us')

MSFT = calculateMetrics('df_'+'MSFT'+'_balancesheet','df_'+'MSFT'+'_income')

MSFT = MSFT.T

MSFT = MSFT.reset_index()

MSFT = MSFT.rename(columns={'breakdown': 'fiscal_year'})

MSFT.insert(0, 'Ticker', 'MSFT')

MSFT = MSFT.set_index(['Ticker','fiscal_year'])

AAPL = calculateMetrics(df_AAPL_balancesheet,df_AAPL_income)

AAPL = AAPL.T

AAPL = AAPL.reset_index()

AAPL = AAPL.rename(columns={'breakdown': 'fiscal_year'})

AAPL.insert(0, 'Ticker', 'AAPL')

AAPL = AAPL.set_index(['Ticker','fiscal_year'])

concate = pd.concat([AAPL, MSFT])

can create the function to pull values from the list and process?

1 Answer

0 votes
by (36k points)

You can do it like this:

symbols = ['AAPL', 'MSFT']

def process_symbol(symbol: str):

  df_income= get_annual_finData_by_symbol('income',symbol,'us')

  df_balancesheet = get_annual_finData_by_symbol('balancesheet',symbol,'us')

  ret = calculateMetrics(df_balancesheet,df_income)

  ret = ret.T

  ret = ret.reset_index()

  ret = ret.rename(columns={'breakdown': 'fiscal_year'})

  ret.insert(0, 'Ticker', symbol)

  ret = ret.set_index(['Ticker','fiscal_year'])

  return ret

concate = pd.DataFrame(columns = ['Ticker','fiscal_year']) //define it with header you need

for symbol in symbols:

  what_i_need = process_symbol(symbol)

  concate = pd.concat([concate, what_i_need])

Looping over a list should allow you to process the list with any length. If there are empty lists then you should take care of this, you might end up with an empty variable.

Do check out Data Science with Python course which helps you understand from scratch

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