Update app.py

app.py

@@ -1,17 +1,39 @@
 import gradio as gr
 import numpy as np
+import matplotlib.pyplot as plt
 import pandas as pd
 
-demo = gr.Blocks() 
-def fileRead(x):
-    df = pd.read_csv('Plashkar/diabetes-predict-db')
-    # Renaming DiabetesPedigreeFunction as DPF
-    df = df.rename(columns={'DiabetesPedigreeFunction':'DPF'})
-    return df       
-
+demo = gr.Block
+def graphPlot(inpX):
+    inp_list = [[13,0,8425333,'Asia'],
+            [15,1,9712569,'Oceania'],
+            [52,0,76039390,'Americas'],
+            [2,0,637408000,'Asia'],
+            [35,1,44310863,'Europe'],
+            [20,0,3.72e+08,'Asia'],
+            [45,1,171984000,'Americas']]
+    mypredictions = [1,1,0,0,1,0,1]
+    # creating a pandas dataframe
+    df = pd.DataFrame(inp_list,columns=['week','diabetes_binary',
+                                        'Population','Continent'])
+      
+    # Sorting by column 'week'
+    df2=df.sort_values(by=['week'],ascending=True)
+    
+    X = list(df2.iloc[:, 0])
+    Y = mypredictions
+      
+    # Plot the data using bar() method
+    plt.plot(X, Y, 'o-g')
+    plt.title("Diabetes prediction graph")
+    plt.xlabel("week")
+    plt.ylabel("diabetes_binary")
+    for i in range(len(X)):
+        b=str(X[i])+","+str(Y[i])
+        plt.annotate(b, xy=(X[i], Y[i])) 
+    # Show the plot
+    return plt
+    
 with demo:
-    inp = gr.Textbox(placeholder="Enter a statement to complete")
-    out1 = gr.Textbox()
-    inp.change(fn=fileRead, inputs=inp,
-                   outputs=out1)   
+    gr.plot(fn=graphPolt)
 demo.launch()