Day2document

Day 2 document influxdata

https://www.influxdata.com/

Result Shuffle

based on the rand()

done

Lesson

step by step updates Update the domain on one sec based manner

import datetimeimport dashfrom dash import dcc, htmlimport plotlyfrom dash.dependencies import Input, Outputimport datetimeimport randomimport dash_tableimport pandas as pdtotal_power_df = pd.Dataframe(columns=["Total Power"], index=pd.DatetimeIndex([]))def random_data_df(): total_power_df.loc[datetime.datetime.now()] = random.randint(0, 200) return total_power_df# pip install pyorbitalfrom pyorbital.orbital import Orbitalsatellite = Orbital('TERRA')external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']app = dash.Dash(__name__, external_stylesheets=external_stylesheets)app.layout = html.Div( html.Div([ html.H4('TERRA Satellite Live Feed'), html.Div(id='live-update-text'), dcc.Graph(id='live-update-graph'), dash_table.DataTable(total_power_df.to_dict('records'), [{"name": i, "id": i} for i in total_power_df.columns]), dcc.Interval( id='interval-component', interval=1*1000, # in milliseconds n_intervals=0 ) ]))@app.callback(Output('live-update-text', 'children'), Input('interval-component', 'n_intervals'))def update_metrics(n): lon, lat, alt = satellite.get_lonlatalt(datetime.datetime.now()) random_data_df() style = {'padding': '5px', 'fontSize': '16px'} return [ html.Span('Longitude: {0:.2f}'.format(lon), style=style), html.Span('Latitude: {0:.2f}'.format(lat), style=style), html.Span('Altitude: {0:0.2f}'.format(alt), style=style) ]# Multiple components can update everytime interval gets fired.@app.callback(Output('live-update-graph', 'figure'), Input('interval-component', 'n_intervals'))def update_graph_live(n): satellite = Orbital('TERRA') data = { 'time': [], 'Latitude': [], 'Longitude': [], 'Altitude': [] } # Collect some data for i in range(180): time = datetime.datetime.now() - datetime.timedelta(seconds=i*20) lon, lat, alt = satellite.get_lonlatalt( time ) data['Longitude'].append(lon) data['Latitude'].append(lat) data['Altitude'].append(alt) data['time'].append(time) # Create the graph with subplots fig = plotly.tools.make_subplots(rows=2, cols=1, vertical_spacing=0.2) fig['layout']['margin'] = { 'l': 30, 'r': 10, 'b': 30, 't': 10 } fig['layout']['legend'] = {'x': 0, 'y': 1, 'xanchor': 'left'} fig.append_trace({ 'x': data['time'], 'y': data['Altitude'], 'name': 'Altitude', 'mode': 'lines+markers', 'type': 'scatter' }, 1, 1) fig.append_trace({ 'x': data['Longitude'], 'y': data['Latitude'], 'text': data['time'], 'name': 'Longitude vs Latitude', 'mode': 'lines+markers', 'type': 'scatter' }, 2, 1) return figif __name__ == '__main__': app.run_server(debug=True)

While approach

from dash import Dash, dcc, html, Input, Output, dash_table, callbackimport dash_html_components as htmlimport dash_core_components as dccimport numpy as npimport datetimeimport randomfrom time import time, sleepimport pandas as pdfrom dash.dependencies import Input, Outputimport timetotal_power_df = pd.Dataframe(columns=["Total Power"], index=pd.DatetimeIndex([]))def random_data_df(): total_power_df.loc[datetime.datetime.now()] = random.randint(0, 200) return total_power_dft_end = time.time() + 2while time.time() < t_end: sleep(1) random_data_df() app = Dash(__name__) app.layout = html.Div([ html.H6("Change the value in the text box to see callbacks in action!"), dash_table.DataTable(total_power_df.to_dict('records'), [{"name": i, "id": i} for i in total_power_df.columns]), ])if __name__ == '__main__': app.run_server(debug=True) # do whatever you do

Auto update

import datetimeimport datetimeimport randomimport dashfrom dash import dcc, html,dash_tableimport plotlyimport pandas as pdtotal_power_df = pd.Dataframe(columns=["Total Power"], index=pd.DatetimeIndex([]))from dash.dependencies import Input, Output# pip install pyorbitalfrom pyorbital.orbital import Orbitalsatellite = Orbital('TERRA')def random_data_df(): total_power_df.loc[datetime.datetime.now()] = random.randint(0, 200) return total_power_dfexternal_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']app = dash.Dash(__name__, external_stylesheets=external_stylesheets)app.layout = html.Div( html.Div([ html.H4('Total Power'), html.Div(id='live-update-text'), dcc.Interval( id='interval-component', interval=1*1000, # in milliseconds n_intervals=0 ) ]))@app.callback(Output('live-update-text', 'children'), Input('interval-component', 'n_intervals'))def update_metrics(n): lon, lat, alt = satellite.get_lonlatalt(datetime.datetime.now()) random_data_df() style = {'padding': '5px', 'fontSize': '16px'} return [ total_power_df["Total Power"].iloc[-1] ]# Multiple components can update everytime interval gets fired.@app.callback(Output('live-update-graph', 'figure'), Input('interval-component', 'n_intervals'))def update_graph_live(n): satellite = Orbital('TERRA') data = { 'time': [], 'Latitude': [], 'Longitude': [], 'Altitude': [] } # Collect some data for i in range(180): time = datetime.datetime.now() - datetime.timedelta(seconds=i*20) lon, lat, alt = satellite.get_lonlatalt( time ) data['Longitude'].append(lon) data['Latitude'].append(lat) data['Altitude'].append(alt) data['time'].append(time) # Create the graph with subplots fig = plotly.tools.make_subplots(rows=2, cols=1, vertical_spacing=0.2) fig['layout']['margin'] = { 'l': 30, 'r': 10, 'b': 30, 't': 10 } fig['layout']['legend'] = {'x': 0, 'y': 1, 'xanchor': 'left'} fig.append_trace({ 'x': data['time'], 'y': data['Altitude'], 'name': 'Altitude', 'mode': 'lines+markers', 'type': 'scatter' }, 1, 1) fig.append_trace({ 'x': data['Longitude'], 'y': data['Latitude'], 'text': data['time'], 'name': 'Longitude vs Latitude', 'mode': 'lines+markers', 'type': 'scatter' }, 2, 1)if __name__ == '__main__': app.run_server(debug=True)

Second based updated table Put the shuffled data

done Put the data in the table header

MANUFACTURING SPC DASHBOARD - PROCESS ConTROL AND EXCEPTION REPORTING what to write here?