First Commit

DynamicReports.py

+
+''' Start simple with Dash / Plotly '''
+
+import pandas as pd
+import plotly.express as px
+import dash
+from dash import dcc
+from dash import html
+from dash.dependencies import Output, Input
+
+
+app = dash.Dash(__name__)
+
+#---------------------- auto run the broswer------------------------#
+
+import webbrowser 
+webbrowser.open_new("http://127.0.0.1:8050") 
+
+
+#-----------------------------dataframe works ------------------------#
+''' the data analysis task is to count the Down, No ,
+Steady and Up for every mediceince and graph it''' 
+
+
+data_frame = pd.read_csv('diabetes_data.csv')
+data_frame = data_frame.loc[:,'metformin':'metformin-pioglitazone']
+
+df = pd.DataFrame()   # empty data frame to collect "column in data_frame.columns"
+
+
+
+for column in data_frame.columns:            # for each colum labeled with midicne do the following
+    df1=data_frame[column].value_counts()    # count the occurance of (Down, No, Steady, Up) for each medicine 
+    print(df1)                               # tst output 
+    df=df.append(df1)                        # append / accomulator @ self
+
+df = df.T                                    # transpose
+df.index.rename('Catagory', inplace=True)    #the indixing problem 
+df.reset_index(level=0, inplace=True)        #the indixing problem   
+
+df.to_csv('append.csv')                      # tst output
+
+
+
+
+
+
+#----------------------------graphs------------------------------#
+
+#fig1 = px.bar(df, x='Down', y='metformin')
+
+#fig_md = px.pie (df, names='Catagory', values='metformin')
+
+#fig2 = px.bar(df, x='Catagory', y='metformin',barmode="group" , color='Catagory')
+
+#fig = px.scatter(df, x="month", y="sales",size="sales", color="month", log_x=True, size_max=60)
+
+#fig3 = px.pie (df, names='month', values='sales')
+
+#fig4 = px.pie (df, names='month', values='cost')
+
+
+#------------------------------app layout-------------------------#
+
+
+app.layout = html.Div([
+    html.H1('Diabetes Medicine Abstraction '),
+
+    dcc.Dropdown(id='medicine' ,
+                 options=[{'label' : medc , 'value' : medc}
+                          for medc in data_frame.columns ],
+                 value ='metformin'
+                 ),
+
+
+                 
+    dcc.Graph(id="fig_bi" , figure={}), # the bi graph in html page 
+    
+    dcc.Graph(id="fig_bar" , figure={}),  # the bar graph
+    
+    ])
+
+@app.callback(                                                      # the link between   def lst_update(value_in) > app.layout                      
+    Output(component_id = "fig_bi", component_property = 'figure'), #link to dcc.Graph(id="fig_bi" , figure={})
+    Output(component_id = "fig_bar", component_property = 'figure'),
+    Input(component_id = 'medicine', component_property = 'value')
+
+
+     )
+
+def lst_update(value_in):
+    dff = df[['Catagory',value_in]]
+                                                                     #dff.to_csv('dff.csv') # index see 
+                                                                     #print(dff)   tst dff 
+    fig_md = px.pie (dff, names = 'Catagory', values = value_in)
+    fig_bar = fig2 = px.bar(dff, x = 'Catagory', y = value_in ,barmode="group")
+    return fig_md,fig_bar
+
+
+
+
+#----------------------------debug server------------------------#
+
+
+
+if __name__ == "__main__":
+    app.run_server(debug=True)
+
+
+
+    

append.csv

+,Catagory,metformin,repaglinide,nateglinide,chlorpropamide,glimepiride,acetohexamide,glipizide,glyburide,tolbutamide,pioglitazone,rosiglitazone,acarbose,miglitol,troglitazone,tolazamide,examide,citoglipton,insulin,glyburide-metformin,glipizide-metformin,glimepiride-pioglitazone,metformin-rosiglitazone,metformin-pioglitazone
+0,Down,575.0,45.0,11.0,1.0,194.0,,560.0,564.0,,118.0,87.0,3.0,5.0,,,,,12218.0,6.0,,,,
+1,No,81778.0,100227.0,101063.0,101680.0,96575.0,101765.0,89080.0,91116.0,101743.0,94438.0,95401.0,101458.0,101728.0,101763.0,101727.0,101766.0,101766.0,47383.0,101060.0,101753.0,101765.0,101764.0,101765.0
+2,Steady,18346.0,1384.0,668.0,79.0,4670.0,1.0,11356.0,9274.0,23.0,6976.0,6100.0,295.0,31.0,3.0,38.0,,,30849.0,692.0,13.0,1.0,2.0,1.0
+3,Up,1067.0,110.0,24.0,6.0,327.0,,770.0,812.0,,234.0,178.0,10.0,2.0,,1.0,,,11316.0,8.0,,,,