Update app.py

app.py

@@ -46,33 +46,23 @@ def get_hvplot(ticker , startdate , enddate , interval,window,window2):
     DF = getPolygonDF(ticker , startdate=startdate , enddate=enddate , intervalperiod=interval,window=window,window2=window2)
 
     import hvplot.pandas  # Ensure hvplot is installed (pip install hvplot)
-    from sklearn.linear_model import LinearRegression
+
     import holoviews as hv
     hv.extension('bokeh')
     # Assuming your dataframe is named 'df' with columns 'Date' and 'Close'
     # If not, replace 'Date' and 'Close' with your actual column names.
 
     # Step 1: Create a scatter plot using hvplot
-    scatter_plot = DF.hvplot(x='Date', y='Close',  kind='scatter',title=f'{ticker} Close vs. Date')
-
-    # Step 2: Fit a linear regression model
-    DF['Date2'] = pd.to_numeric(DF['Date'])
-    X = DF[['Date2']]
-    y = DF[['Close']] #.values
-    model = LinearRegression().fit(X, y)
+    scatter_plot = DF.hvplot(x='UNIXTIME', y='c',  kind='scatter',title=f'{ticker} Close vs. Date')
 
-    # # Step 3: Predict using the linear regression model
-    DF['Predicted_Close'] = model.predict(X)
 
-    # # Step 4: Create a line plot for linear regression
-    line_plot = DF.hvplot(x='Date', y='Predicted_Close', kind='line',line_dash='dashed', color='red')
-    line_plot_SMA = DF.hvplot(x='Date', y='SMA', kind='line',line_dash='dashed', color='orange')
-    line_plot_SMA2 = DF.hvplot(x='Date', y='SMA2', kind='line',line_dash='dashed', color='orange')
+    line_plot_SMA = DF.hvplot(x='UNIXTIME', y='SMA', kind='line',line_dash='dashed', color='orange')
+    line_plot_SMA2 = DF.hvplot(x='UNIXTIME', y='SMA2', kind='line',line_dash='dashed', color='orange')
 
     # # Step 5: Overlay scatter plot and linear regression line
     # return (scatter_plot * line_plot).opts(width=800, height=600, show_grid=True, gridstyle={ 'grid_line_color': 'gray'})
     # grid_style = {'grid_line_color': 'black'}#, 'grid_line_width': 1.5, 'ygrid_bounds': (0.3, 0.7),'minor_xgrid_line_color': 'lightgray', 'xgrid_line_dash': [4, 4]}
-    return (scatter_plot * line_plot *line_plot_SMA *line_plot_SMA2).opts(width=800, height=600, show_grid=True)
+    return (scatter_plot *line_plot_SMA *line_plot_SMA2).opts(width=800, height=600, show_grid=True)
 
 
 tickers = ['AAPL', 'META', 'GOOG', 'IBM', 'MSFT','NKE','DLTR','DG']