def get_stock_data(self):
df = pd.read_csv(self.csv_file_name)
report_date = datetime.strptime(self.report_date, "%Y-%m-%d")
report_date_n_days_ago = report_date - timedelta(days=self.trendfac)
report_date = report_date.strftime("%Y-%m-%d")
report_date_n_days_ago = report_date_n_days_ago.strftime("%Y-%m-%d")
fulldata = pd.DataFrame()
for stock in df['stock']:
data = pseapi.get_stock_data(stock, report_date_n_days_ago,
report_date)
data = data.round(2)
fulldata = fulldata.append(data, ignore_index=True)
keys = pseapi.get_uniq_stock_keys(fulldata)
filtered_df_score = self.get_whitesoldier_score(
fulldata, keys, self.trendfac, self.resfac, self.supfac,
self.pc_fac, self.volfac1, self.volfac2, self.volfac3,
self.netffac, self.pc_crit, self.volfac_crit, self.res_crit,
self.sup_crit)
filtered_keys = pseapi.get_uniq_stock_keys(filtered_df_score)
filtered_df = self.get_whitesoldier_stocks(fulldata, filtered_keys,
self.trendfac)
return filtered_df, filtered_df_score
def get_stock_data(self):
df = pd.read_csv(self.csv_file_name)
report_date = datetime.strptime(self.report_date, "%Y-%m-%d")
report_date_n_days_ago = report_date - timedelta(days=self.trendfac)
report_date = report_date.strftime("%Y-%m-%d")
report_date_n_days_ago = report_date_n_days_ago.strftime("%Y-%m-%d")
fulldata = pd.DataFrame()
for stock in df['stock']:
data = pseapi.get_stock_data(stock, report_date_n_days_ago,
self.report_date)
data = data.round(2)
fulldata = fulldata.append(data, ignore_index=True)
return fulldata