spx_ndq_weeks_in_a_row_up.py

import yfinance_download

spx = yfinance_download.update_records('^GSPC', interval='1wk')

ndq = yfinance_download.update_records('^IXIC', interval='1wk')

# ndq = yfinance_download.update_records('^NDX', interval='1wk')

# ----------------------------------------------

df = spx['Close'].to_frame()

df['Close_diff_1'] = df['Close'].diff(1)

df['is_positive'] = df['Close_diff_1'] > 0

spx = df

# ----------------------------------------------

df = ndq['Close'].to_frame()

df['Close_diff_1'] = df['Close'].diff(1)

df['is_positive'] = df['Close_diff_1'] > 0

ndq = df

# ----------------------------------------------

df = pd.merge(spx, ndq, left_index=True, right_index=True, suffixes=('_spx', '_ndq'))

df['is_positive'] = df['is_positive_spx'] & df['is_positive_ndq']

df['switch'] = (df['is_positive'] != df['is_positive'].shift(1))

df['group'] = df['switch'].cumsum()

df['group_is_positive_cumsum'] = df.groupby('group')['is_positive'].cumsum()

df['weeks_in_a_row_up'] = df['group_is_positive_cumsum'].where(df['is_positive'], 0)

tmp = df.groupby('group').tail(1)

tmp[tmp['weeks_in_a_row_up'] >= 6][['Close_spx', 'Close_ndq', 'weeks_in_a_row_up']]

tmp[tmp['weeks_in_a_row_up'] >= 6]['weeks_in_a_row_up']