Вот уменьшенная версия моей панели инструментов, реальная имеет несколько вкладок и т. Д. c. Панель инструментов создает все диаграммы из 4 файлов
- 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 = ",")
Иногда эти файлы могут изменять свое содержимое (имя одно и то же, но значения разные), мне нужно обновить панель, чтобы все эти файлы были загружены на панель. запускается снова, я создал кнопку обновления панели, но как это реализовать?
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)
Изображение панели инструментов 