Update app.py

app.py

@@ -120,7 +120,41 @@ st.write("""
 Shown is the historical data of the prices (can be adapted with the values from the sidebar)
 """)
 
-temp_df
+today = date.today()
+days_ago = today - timedelta(days=25)
+
+# we get the last 30 days and keep just the last working days, which have prices
+nasdaq = yf.Ticker("^IXIC")
+hist = nasdaq.history(start=days_ago, end=today)
+hist = hist.drop(columns=['Dividends', 'Stock Splits'])
+
+# keeping the last working days data points
+hist = hist[-working_days:]
+
+
+inflation = []
+for t in hist.index:
+  inflation.append(get_rate("USD", "EUR", t))
+
+cpi_items_df = cpi.series.get(seasonally_adjusted=False).to_dataframe()
+cpi_items_df = cpi_items_df[cpi_items_df['period_type']=='monthly']
+cpi_items_df['date'] = pd.to_datetime(cpi_items_df['date'])
+cpi_items_df = cpi_items_df.set_index('date')
+cpi_df = cpi_items_df['value'].loc['2022':'2023']
+
+cpi_col = []
+for x in hist.index:
+  # ts = datetime(x.year, x.month, 1)
+
+  # just adding the latest inflation rate
+  cpi_col.append(cpi_df[-1])
+
+hist['Inflation'] = inflation
+hist['CPI'] = cpi_col
+hist['Quarter_end'] = np.where(hist.index.month%3==0,1,0)
+
+hist
+