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Dashboard Update Button

Here is a smaller Version of my Dashboard, the real one has multiple tabs etc. The Dashboard creates all charts from 4 files

  • dfresult = pd.read_csv(“result.csv”, sep=",")
  • dfradar = pd.read_csv(“radar.csv”, sep=",")
  • dfoutput = pd.read_csv(“output.csv”, sep=",")
  • dfavg = pd.read_csv(“avg_input.csv”,sep=",")

Sometimes these files can change their content (name is same but values are different), i need a dashboard update, so that all these files are new loaded an the dashboard runs again, i created a dashboard-update button, but how to realize this?

import dash
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output, State
import plotly.graph_objs as go
from plotly import tools
import pandas as pd
import datetime
import plotly.tools
from plotly.subplots import make_subplots
import numpy as np

import plotly.io as pio
import sys

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']


dfresult = pd.read_csv("result.csv", sep=",")
dfradar =  pd.read_csv("radar.csv", sep=",")
dfoutput = pd.read_csv("output.csv", sep=",")
dfavg = pd.read_csv("avg_input.csv",sep=",")


#avg_input.csv
dfavg = round(dfavg,2)
avgtable = dfresult.drop(["Feed 1", "Feed 2","Sum Feed In", "Wind 4600","Solar 1900","Holiday", "Sun 2300",  "Total Feed In"],axis=1)
avgtable = avgtable.iloc[1:]
avgtable = round(avgtable.groupby("Date").mean(),2)
avgtable.reset_index( level=None, drop=False, inplace=True, col_level=2, col_fill='')


print(avgtable)

#radar.csv
dfradar = round(dfradar,2)

#output.csv
dfoutput= round(dfoutput,2)
dfoutput= dfoutput.fillna(0)
#result.csv
dfresult
dfresult.fillna(0)
#dfresult["Temperature"] = pd.to_numeric(dfresult["Temperature"])
#dfresavg = round(dfresavg,2)
#create new dataframe: grouped result table by date, calculate mean of consumption and round by two decimals
dfb = pd.DataFrame(round(dfresult.groupby("Date")["Consumption"].mean(),2))
#sort dataframe by date
dfb = dfb.sort_values("Date",ascending=False)
#split dataframe into first row and other rows
first= dfb.iloc[:1]
others = dfb.iloc[1:]
#sort all rows exept first row by consumption from high to low
others = others.sort_values("Consumption",ascending=False)
#create new Dataframe by concatinating first and others (both are Dataframes)
dfbar1 = pd.concat([first,others])

#reset index of Dataframe, replace Column and fill automaticly
dfbar1.reset_index( level=None, drop=False, inplace=True, col_level=2, col_fill='')
dfbar1.Date = dfbar1.Date.astype(str)
dfresult = dfresult.iloc[1:]



app = dash.Dash(__name__)#, external_stylesheets=external_stylesheets)
server = app.server
app.config.suppress_callback_exceptions = True
app.scripts.config.serve_locally = True




###################################################
#demand subplots
###################################################


figd = tools.make_subplots(
    rows=2, cols=2, print_grid=True,
    specs=[[{"type": "xy"}, {"type": "xy"}],[{"type": "xy"}, {"type": "polar"}]],
    subplot_titles=("A", "B", "C", "D"))

c = ["#67c2dc","#16336d","#ffbb0e","#213939","#cc66ff"]
c1 = ["#ffff01","#67c2dc","#16336d","#ffbb0e","#213939","#cc66ff"]

#check order of daylist from dfbar1
daylist = dfbar1.Date.unique()
daylist_small = daylist[1:]


#dfresult.sort_values(["Date","daylist"])

daylistresult = dfresult.Date.unique()

###Chart1
for i,j,a in zip(daylist,dfbar1["Consumption"],range(len(dfbar1.Date))):
    
    figd.append_trace(
        go.Bar(
           x=[i],
           y=[j],
           #name = dfbar1.Date,
           name=str(i),
           legendgroup='group'+str(i),
           showlegend=True,
           marker=dict(color=c1[a]),
    
       
            ),1,1
         ),
figd.update_xaxes(type = 'category')
###Chart2
for i,j in zip(daylist_small,range(len(dfresult.Date.unique()))):
    data = dfresult.loc[dfresult.Date == str(i)]
    
    figd.append_trace(
         go.Scatter(
            x=data["Time"],
            y=data["Consumption"],
            #name=str(data["Date"].unique())[2:-2],
            legendgroup='group'+str(i),
            showlegend=False,
            marker=dict(color=c[j]),
            mode="lines+markers"
            ),1,2
         ),

    
###Chart4
for i,j,a in zip(daylist,dfoutput["Consumption"],range(len(dfoutput.Date))):
    
    figd.append_trace(
        go.Bar(
           x=[i],
           y=[j],
           
           #name=str(i),
           legendgroup='group'+str(i),
           showlegend=False,
           marker=dict(color=c1[a]),
    
       
            ),2,1
         ),
figd.update_xaxes(type = 'category')


###Chart4
for a, i,j in zip(daylist, dfradar.Date.unique(),range(len(dfradar.Date.unique()))):
    figd.append_trace(go.Scatterpolar(
                        r=dfradar["Total"].loc[dfradar["Date"]==i],
                        theta=dfradar["Parameters"].loc[dfradar["Date"]==i],
                        showlegend=False,
                        legendgroup='group'+str(a),
                        marker=dict(color=c1[j]),
                        line_color = c1[j],
                        mode = "lines+markers",
                        opacity = round(j  * (0.4)+0.2,0),
                        fill ='toself'
                        ),2,2)
    
    figd.update_layout(
          #height=500,
          #width =500,
          autosize=True,
          polar = dict(angularaxis = dict( rotation = 45)
          
          ))
        


#set layout for each graph
figd['layout'].update(height=1100,autosize=True,polar = dict(angularaxis = dict( rotation = 45)))


bgc = "#f7f9ef"
background_color = "#f7f9ef"
graphwidth = "33%"
graphheight = "450px"
formwidth = "170px"
formheight = "30px"


templates = ['ggplot2', 'seaborn', 'simple_white', 'plotly','plotly_white', 'plotly_dark', 'presentation', 'xgridoff', 'ygridoff', 'gridon']


app.layout =html.Div([
            #header container with name, update button and logo
            dcc.Dropdown(id='drop-temp',
                                 style={
                                       
                                        "float":"right",
                                        "display": 'inline-block',
                                        "width": "220px",
                                        
                                        },
                                 
                                    options=[
                                        {'label': str(i), 'value': i} for i in templates]
                                        ,placeholder="Select Chart Template"
                                        ),
                
            html.Button("Update Dashboard",id="update", style={
                                                    "width": "220px",
                                                    "float":"left",
                                                    'display': 'inline-block',
                                                    "background":"#e29820",
                                                    "color":"white",
                                                    "height":"35px"
                                                   }),

    
    
    
    
            html.Div(id="empty-slot1",style={"height":"5px"}),
            dcc.Tabs(id="tabs", value='tab2', 
            children=[

            dcc.Tab(label='Overview', value='tab2', style={"height":"7%","width":"16.6%","background":"#e29820","color":"white"}),
            
            ],style={"background":background_color}
            ),

            html.Div(id='tabs-content'),
                
           
                   
                   ],style={"width":"100%",
                     "background":background_color,
                     })

@app.callback(Output('tabs-content', 'children'),
              [Input('tabs', 'value'),
])
def contents(tab):
    
    if tab == 'tab2':
        return html.Div(
            [
            html.H3('Overview'),
            
            dcc.Graph(id="g1",style={"width":"99%"},
                            figure=figd,
                             ),


            ],
                style={"width":"99%",
                       "background":background_color}
                )


if __name__ == '__main__':
    app.run_server(debug=False)