Update space_stock_plot.py

space_stock_plot.py

@@ -1,7 +1,44 @@
-gradio
-yfinance
-pandas
-numpy
-datetime
-pytz
+'''
+graphical line diagram of stock cumulative returns
+
+Note: Raw Data is from Yahoo Finance using python yfinance
+'''
+script_version = '(2024-01-28.1)'
+# Import the libraries
+import gradio as gr
+import yfinance as yf
+import pandas as pd
+
+def stock_return_df(tickers, start, end):
+  # Download the historical data
+  data = yf.download(tickers, start=start, end=end)
+  # Calculate the daily and cumulative percentage change
+  data_adj_close = data['Adj Close']
+  data_adj_close_pct = data_adj_close.pct_change()
+  data_adj_close_pct_cum = (data_adj_close_pct + 1).cumprod(axis=0) - 1
+  return data_adj_close_pct_cum
+
+def plot_graph(tickers, start, end):
+  data_adj_close_pct_cum=stock_return_df(tickers, start, end)
+  # Plot a line chart of the salary by name
+  #ax = data_adj_close_pct_cum.plot.line(x="Name", y="Salary", rot=0, legend=False, style="-o", markersize=10, color="green")
+  ax = data_adj_close_pct_cum.plot()
+  ax.set_ylabel("Percentage")
+  ax.set_title("Cumulative Returns")
+  # Return the plot as a matplotlib figure
+  return ax.get_figure()
+
+# Create a gradio.Interface object with the DataFrame component as input and the Matplotlib component as output
+interface = gr.Interface(
+    fn=plot_graph, # The function to call
+    inputs=[gr.Textbox(label="Tickers", value="qqq,spy,vfv.to,xiu.to,xfn.to,ry.to"),
+        gr.Textbox(label="Start Date", value="2014-01-01"),
+        gr.Textbox(label="End Date", value="2023-12-30")],
+    outputs=gr.Plot(label="Output Plot"), # The Matplotlib component as output
+    title="Stock cumulative returns - DataFrame Line Plot by Gradio" # The title of the interface
+)
+
+# Launch the interface
+interface.launch(debug=False)
+