sfin.py

import pandas as pd
from simfin.names import REVENUE, NET_INCOME

import simfin as sf

if __name__ == "__main__":
    # Set your API-key for downloading data.
    # Replace YOUR_API_KEY with your actual API-key.
    sf.set_api_key('8764b2f4-f668-479f-8e97-0dd22746af62')

    # Set the local directory where data-files are stored.
    # The dir will be created if it does not already exist.
    sf.set_data_dir('~/simfin_data/')

    # Load the annual Income Statements for all companies in the US.
    # The data is automatically downloaded if you don't have it already.
    df = sf.load_income(variant='annual', market='us')

    # Print all Revenue and Net Income for Microsoft (ticker MSFT).
    print(df.loc['MSFT', [REVENUE, NET_INCOME]])

    sf.load_cashflow()

    sp = sf.load_shareprices(variant='daily')

    g = sp.groupby(by='Ticker')

    # sp["date"] = sp.index.get_level_values('Date')
    # sp["prev_date"] = pd.Series(sp.date).shift(-1)

    sp["Div_adj"] = sp.Close
    flt = sp.Dividend.isna()
    sp.Div_adj[flt] = sp.Div_adj[flt] + sp.Dividend[flt]
    sp.loc[flt, 'Div_adj'] += sp.loc[flt, 'Dividend']

    px_chg_pct = sp.Close.pct_change()
    adj_px_cng_pct = sp.Div_adj.pct_change()
    px_chg_pct.loc[flt] = adj_px_cng_pct[flt]

    px_chg_pct.unstack().T

    print("something")