Temperature against space use#
It’s useful to be able to see when users are in the building against what temperature it is. We’re experimenting with this feature. To see what it might look like, choose venue 99a in the dropdown. The data doesn’t always show automatically.
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# Imports
import ipywidgets as widgets
import pandas as pd
#import plotly.express as px
import plotly.graph_objects as go
import os
#from IPython.display import display
# Get the possible data venues
venuekeysfile = "diary-venue-keys.csv"
dfVenueKeys = pd.read_csv(venuekeysfile)
dfVenueKeys = dfVenueKeys.dropna(subset=['channel_id'])
#Retrieve the venue and begin graphing
dfCollatedDataSet = pd.DataFrame() # columns=['timestamp', 'entry_id', 'temperature', 'rh', 'voltage', 'awake_time', 'original_timestamp', 'location', 'venue_id']
dfCollatedUseDiaries = pd.DataFrame(columns=['start', 'end', 'entry_id', 'venue_id'])
for index, venueSensorDetails in dfVenueKeys.iterrows():
# sensorMacOfSelection = venueSensorDetails['sensor_MAC']
venueOfSelection = str(venueSensorDetails['venue_id'])
#print(venueOfSelection)
dfTempDataSet = pd.read_csv('deviceData/before_2023_07/'+ "venue_" + venueOfSelection + '.csv' )
dfTempDataSet.sample(6)
dfTempDataSet = dfTempDataSet.dropna()
dfTempDataSet['timestamp'] = pd.to_datetime(dfTempDataSet['timestamp'])
dfTempDataSet['venue_id'] = venueSensorDetails['venue_id']
#display(dfTempDataSet)
#dfCollatedDataSet = dfCollatedDataSet.append(dfTempDataSet, ignore_index=True)
dfCollatedDataSet = pd.concat([dfCollatedDataSet, dfTempDataSet])
#should already be datetimes - why is this here?
dfCollatedDataSet['timestamp'] = pd.to_datetime(dfCollatedDataSet['timestamp'])
if os.path.exists('useDiaries/'+ "venue_" + venueOfSelection + "_diary" + '.csv'):
dfUseDiary = pd.read_csv('useDiaries/'+ "venue_" + venueOfSelection + "_diary" + '.csv' )
dfUseDiary = dfUseDiary.fillna('')
dfUseDiary['start'] = pd.to_datetime(dfUseDiary['startUse'])
dfUseDiary['end'] = pd.to_datetime(dfUseDiary['endUse'])
dfUseDiary['venue_id'] = venueSensorDetails['venue_id']
#display(dfUseDiary)
#dfCollatedUseDiaries = dfCollatedUseDiaries.append(dfUseDiary, ignore_index=True)
dfCollatedUseDiaries = pd.concat([dfCollatedUseDiaries, dfUseDiary])
#should already be datetimes - why is this here?
dfCollatedUseDiaries['start'] = pd.to_datetime(dfUseDiary['start'])
dfCollatedUseDiaries['end'] = pd.to_datetime(dfUseDiary['end'])
#print('Loading data for venue: ', venueSensorDetails['venue_id'])
#print('Check')
#dfCollatedDataSet.sample(6)
row=dfVenueKeys.iloc(0)[0]
value=row[0]
#give user option to select their venue
venueDropdown = widgets.Dropdown(
options=dfVenueKeys['venue_id'],
value=dfVenueKeys['venue_id'][0],
description='Venue ID:',
disabled=False,
)
container = widgets.HBox(children=[venueDropdown])
# Assign an empty figure widget with two traces
trace0 = go.Scatter(customdata=dfCollatedDataSet[dfCollatedDataSet['venue_id'] == 0],
y=dfCollatedDataSet['temperature'],
x = dfCollatedDataSet['timestamp'],
mode='lines',
hoverinfo='all',
name='Temperature',
)
# trace1 = go.Scatter(customdata=dfCollatedDataSet[dfCollatedDataSet['venue_id'] == 0],
# y=dfCollatedDataSet['rh'],
# x = dfCollatedDataSet['timestamp'],
# mode='lines',
# hoverinfo='all',
# name='Relative Humidity',
#)
g = go.FigureWidget(data=[trace0], #, trace1],
layout = go.Layout(
yaxis=dict(range=[0,0])
))
#print("Job Done")
/tmp/ipykernel_2399/3983342851.py:45: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
dfCollatedUseDiaries = pd.concat([dfCollatedUseDiaries, dfUseDiary])
/tmp/ipykernel_2399/3983342851.py:57: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
value=row[0]
Show code cell source
updatemenu = []
buttons = []
# button with one option for each dataframe
for index, venue in dfVenueKeys.iterrows():
buttons.append(dict(method='update',
label='Venue ' + str(venue['venue_id']),
visible=True,
args=[{'y':[dfCollatedDataSet[dfCollatedDataSet['venue_id']==venue['venue_id']]['temperature'].values], #,
#dfCollatedDataSet[dfCollatedDataSet['venue_id']==venue['venue_id']]['rh'].values],
'x':[dfCollatedDataSet[dfCollatedDataSet['venue_id']==venue['venue_id']]['timestamp'].values],
'type':'scatter',
# 'name': 'Temperature',
},
{
'title.text': 'Temperature for Venue = ' + str(venue['venue_id']),
'title.font.color': 'green',
#'yaxis.range': [-5,dfCollatedDataSet[dfCollatedDataSet['venue_id']==venue['venue_id']][['temperature', 'rh']].max().max()+5],
'yaxis.range': [dfCollatedDataSet[dfCollatedDataSet['venue_id']==venue['venue_id']]['temperature'].min()-10,dfCollatedDataSet[dfCollatedDataSet['venue_id']==venue['venue_id']]['temperature'].max()+5],
'yaxis.title.text': 'Temperature',
'xaxis.title.text': 'Timestamp'
},
],
)
)
# some adjustments to the updatemenus
updatemenu = []
your_menu = dict()
updatemenu.append(your_menu)
updatemenu[0]['buttons'] = buttons
updatemenu[0]['direction'] = 'down'
updatemenu[0]['showactive'] = True
# updatemenu[0]['active'] = 0
fig = go.Figure(g)
# add dropdown menus to the figure
fig.update_layout(showlegend=True,
updatemenus=updatemenu,
autosize = True,
title= "Please select a venue to see your data.",
width=1000,
height=500,
)
fig.update_layout(
hovermode='x unified',
hoverlabel=dict(
bgcolor="white",
# font_size=16,
font_family="Rockwell"
)
)
# Add range slider
fig.update_layout(
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(
label="All",
step="all"
),
dict(count=1,
label="Hour",
step="hour",
stepmode="todate"),
dict(count=1,
label="Day",
step="day",
stepmode="backward"),
dict(count=7,
label="Week",
step="day",
stepmode="backward"),
dict(count=1,
label="Year",
step="year",
stepmode="backward")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
#fig.update_yaxes(range=[50, 60])
#fig.add_hline(y=16, annotation_text='16C - usual minimum for children', annotation_font_color="blue", line_color='red', layer='above', line_dash='dash')
# fig.update_yaxes(range = [-5, dfCollatedDataSet['temperature'].max()+5])
for ind in dfCollatedUseDiaries.index:
#print(dfCollatedUseDiaries['start'][ind])
#print(dfCollatedUseDiaries['end'][ind])
fig.add_vrect(x0=dfCollatedUseDiaries['start'][ind], x1=dfCollatedUseDiaries['end'][ind],
annotation_text=dfCollatedUseDiaries['label'][ind],
annotation_position="top left",
annotation=dict(font_size=14,
font_family="Times New Roman"),
fillcolor="green",
opacity=0.25,
line_width=0)
fig.show()