def get_mapbox_graph(sbb, hovertext_cols, options_list, option_dropdown, colorbar, travel_time_cols,
dropdown_locations=None):
cmin = min(colorbar[option_dropdown]['intervals'])*3600
cmax = max(colorbar[option_dropdown]['intervals'])*3600
mapbox_graph = [Scattermapbox(
lat=sbb["lat"],
lon=sbb["lon"],
mode="markers",
hoverinfo='text',
hovertext=sbb[hovertext_cols[options_list[option_dropdown]]],
text=sbb[hovertext_cols[options_list[option_dropdown]]],
marker=dict(
showscale=True,
color=sbb[travel_time_cols[options_list[option_dropdown]]],
opacity=0.85,
size=7.5,
colorscale=colorbar[option_dropdown]['input'],
cmax=cmax,
cmin=cmin,
colorbar=dict(
title=colorbar[option_dropdown]['title'],
x=0.035,
xpad=0,
tickvals=colorbar[option_dropdown]['tickvals'],
ticktext=colorbar[option_dropdown]['ticktext'],
tickfont=dict(color="#000000",
size=14),
titlefont=dict(color="#000000",
size=16),
ticksuffix=" hours",
showticksuffix="all",
thicknessmode="pixels",
),
),
)]
if dropdown_locations:
mapbox_graph.append(
# Plot of important locations on the map
Scattermapbox(
lat=[dropdown_locations[i]["lat"] for i in dropdown_locations],
lon=[dropdown_locations[i]["lon"] for i in dropdown_locations],
mode="markers",
hoverinfo="text",
text=[i for i in dropdown_locations],
marker=dict(size=8, color="#000000"),
)
)
return mapbox_graph
def plotly_map(locations):
mapbox_access_token = 'pk.eyJ1Ijoic3VodHdpbnMiLCJhIjoi' +\
'Y2pnNGJvbXRhMGpoNDJwcWRva3JieWgwcCJ9' +\
'.cmsuwG65XkGUh2pv07nIVg'
data = [
Scattermapbox(
lat=[location.latitude for location in locations],
lon=[location.longitude for location in locations],
text=[location.name for location in locations],
mode='markers',
)
]
layout = Layout(
autosize=True,
hovermode='closest',
mapbox=dict(
accesstoken=mapbox_access_token,
bearing=0,
center=dict(
lat=mean([location.latitude for location in locations]),
lon=mean([location.longitude for location in locations])),
pitch=100,
zoom=10),
)
fig = dict(data=data, layout=layout)
output = plotly.offline.plot(fig,
include_plotlyjs=False,
output_type='div')
return (output)
def plot_map(restos, cuisine_type='Thai'):
""" Visualise restaurants on a map of NYC
Parameters
----------
restos: DataFrame
contains NYC restaurant inspection results
cuisine_type: str
type of cuisine to search for
Returns
-------
fig : plotly.Figure
"""
top_ten = get_top_N(restos, cuisine_type=cuisine_type)
lat_lons = find_lat_lon(top_ten)
nyc_central_lat = 40.7128
nyc_central_lon = -73.9
data = [
Scattermapbox(
lon=[lat_lon['lon'] for lat_lon in lat_lons.values],
lat=[lat_lon['lat'] for lat_lon in lat_lons.values],
text=[lat_lon['name'] for lat_lon in lat_lons.values],
mode='markers+text',
showlegend=False,
hoverinfo='text',
textposition='top center',
marker=dict(symbol='star', size=10),
)
]
layers = [
dict(sourcetype='geojson', type='fill', color='rgba(163,22,19,0.8)')
]
layout = Layout(
title='',
height=800,
width=600,
autosize=True,
hovermode='closest',
mapbox=dict(layers=layers,
accesstoken=MAPBOX_ACCESS_TOKEN,
bearing=0,
center=dict(lat=nyc_central_lat, lon=nyc_central_lon),
pitch=0,
zoom=10,
style='light'),
)
fig = Figure(layout=layout, data=data)
iplot(fig, validate=False)
return fig
def update_graph_user(user):
zoom = 12.0
latInitial = 37.766083
lonInitial = -122.448649
bearing = 0
venue_list = session.execute("select venue_id, user_id, lat, log, rating from friendratingloc WHERE user_id = \'{}\'".format(user))
venue_name = []
venue_lat = []
venue_lon = []
venue_rating = []
for venue in venue_list:
venue_name.append(venue.venue_id)
venue_lat.append(venue.lat)
venue_lon.append(venue.log)
venue_rating.append(venue.rating)
return go.Figure(
data=[
Scattermapbox(
#lat=["37.752443", "37.807771", "37.810088", "37.769361", "37.802067"],
#lon=["-122.447543", "-122.473899", "-122.410428", "-122.485742",
# "-122.418840"],
lat = venue_lat,
lon = venue_lon,
mode='markers',
hoverinfo="text",
text = venue_rating,
#text=["1", "2", "3", "4", "5"],
# opacity=0.5,
marker=dict(
size=12,
color=venue_rating
),
),
],
layout=Layout(
autosize=True,
height=750,
margin=Margin(l=0, r=0, t=0, b=0),
showlegend=False,
mapbox=dict(
accesstoken=mapbox_access_token,
center=dict(
lat=latInitial, # 40.7272
lon=lonInitial # -73.991251
),
style='dark',
bearing=bearing,
zoom=zoom
)
)
)
def makeborder3(name, lats, lons, color, shape, group, showlegend):
return Scattermapbox(
name=name,
mode="markers",
lon=lats,
lat=lons,
# SPECS
marker=dict(
size=15,
color=color,
symbol=shape,
opacity=0.8,
),
legendgroup=group,
showlegend=showlegend,
)
def maketrace(name, lats, lons, dataframe, color, shape, group, showlegend,
sd):
return Scattermapbox(
name=name,
mode="markers",
lon=lats,
lat=lons,
text="ID: " + dataframe['ID'].astype(str) +
"<br>Mask/Social Distance Compliance: " + sd,
hoverinfo="lon+lat+text",
# SPECS
marker=dict(
size=12,
color=color,
symbol=shape,
opacity=0.8,
),
legendgroup=group,
showlegend=showlegend,
)
def plot_cluster(days, param="End", peak="AM", marker_size_scale=30):
config_plotly()
color_scale = colorlover.scales['5']['qual']['Set1']
data = list()
top_size = days['7'].max()
for cluster in days.cluster_id.unique():
data.append(
Scattermapbox(
lat=days[days.cluster_id == cluster][param + "_Lat_mean" +
peak],
lon=days[days.cluster_id == cluster][param + "_Lon_mean" +
peak],
mode='markers',
marker=Marker(size=days[days.cluster_id == cluster]['7'] /
top_size * marker_size_scale,
color=color_scale[cluster]),
text="CL: " + str(cluster),
hoverinfo='text'))
data = Data(data)
layout = Layout(
title='Clusters centres of gravity:' + param + peak,
autosize=True,
hovermode='closest',
showlegend=False,
mapbox=dict(accesstoken=PLOTLY_API_KEY,
bearing=0,
center=dict(lat=40, lon=-73),
pitch=0,
zoom=7,
style='light'),
)
fig = dict(data=data, layout=layout)
py.plot(fig, filename='Clusters:' + param + peak)
def plot_vectors(days, peak="PM"):
_scaler = 6
config_plotly()
color_scale = colorlover.scales['5']['qual']['Dark2']
data = list()
top_size = days['7'].max()
for index, row in days.iterrows():
desc = str(index) + " cluster_id" + str(row['cluster_id'])
data.append(
Scattermapbox(
lat=[row["Start_Lat_mean" + peak], row["End_Lat_mean" + peak]],
lon=[row["Start_Lon_mean" + peak], row["End_Lon_mean" + peak]],
mode='lines',
text=desc,
name=desc,
opacity=0.7,
line=Line(width=int(_scaler * row['7'] / top_size),
color=color_scale[int(row['cluster_id'])])))
data = Data(data)
layout = Layout(
showlegend=False,
autosize=True,
hovermode='closest',
mapbox=dict(accesstoken=PLOTLY_API_KEY,
bearing=0,
center=dict(lat=row["Start_Lat_mean" + peak],
lon=row["Start_Lon_mean" + peak]),
pitch=0,
zoom=11),
)
fig = dict(data=data, layout=layout)
py.plot(fig, filename='Vectors ' + peak)
def update_graph(interval):
zoom = 12.0
latInitial = 37.766083
lonInitial = -122.448649
bearing = 0
venue_list = session.execute(
'select venue_id, latitude, longitude,SUM(visit) AS totalvisit from venuevisitloc GROUP BY venue_id LIMIT 500'
)
venue_name = []
venue_visit = []
venue_lat = []
venue_lon = []
for venue in venue_list:
venue_name.append(venue.venue_id)
venue_visit.append(venue.totalvisit)
venue_lat.append(venue.latitude)
venue_lon.append(venue.longitude)
# to get fixed color range:
y = np.array(venue_visit)
color = np.array(['rgb(255,255,255)'] * y.shape[0])
for i in range(y.shape[0]):
if y[i] < 10: color[i] = 'rgb(166,206,227)'
elif y[i] >= 10 and y[i] < 100: color[i] = 'rgb(31,120,180)'
elif y[i] >= 100 and y[i] < 200: color[i] = 'rgb(178,223,138)'
elif y[i] >= 200 and y[i] < 400: color[i] = 'rgb(51,160,44)'
elif y[i] >= 400 and y[i] < 800: color[i] = 'rgb(251,154,153)'
else: color[i] = 'rgb(227,26,28)'
return go.Figure(
data=[
Scattermapbox(
# lat=["37.752443", "37.807771", "37.810088", "37.769361", "37.802067",
# "40.7127", "40.7589", "40.8075", "40.7489"],
# lon=["-122.447543", "-122.473899", "-122.410428", "-122.485742",
# "-122.418840", "-74.0134", "-73.9851", "-73.9626",
# "-73.9680"],
lat=venue_lat,
lon=venue_lon,
mode='markers',
hoverinfo="text",
text=venue_visit,
#text=["Twin Peaks", "Golden Gate Bridge",
# "Pier 39", "Golden Gate Park",
# "Lombard Street", "One World Trade Center",
# "Times Square", "Columbia University",
# "United Nations HQ"],
# opacity=0.5,
marker=dict(
size=8,
#color="#ffa0a0"
# color = venue_visit,
color=color.tolist(),
# colorbar=dict(
# title='Colorbar'
# ),
# colorscale = [[0, 'rgb(166,206,227)'], [0.25, 'rgb(31,120,180)'], [0.45, 'rgb(178,223,138)'], [0.65, 'rgb(51,160,44)'], [0.85, 'rgb(251,154,153)'], [1, 'rgb(227,26,28)']],
# colorscale='Jet',
),
),
],
layout=Layout(
autosize=True,
height=750,
margin=Margin(l=0, r=0, t=0, b=0),
showlegend=False,
mapbox=dict(
accesstoken=mapbox_access_token,
center=dict(
lat=latInitial, # 40.7272
lon=lonInitial # -73.991251
),
style='dark',
bearing=bearing,
zoom=zoom)))
def plotly_map():
mapbox_access_token = 'pk.eyJ1Ijoic3VodHdpbnMiLCJhIjoi' +\
'Y2pnNGJvbXRhMGpoNDJwcWRva3JieWgwcCJ9' +\
'.cmsuwG65XkGUh2pv07nIVg'
data = Data([
Scattermapbox(
lat=['37.7765', '37.791377'],
lon=['-122.4506', '-122.392609'],
mode='markers',
marker=Marker(size=15),
text=["University of San Francisco, Main Campus",
"University of San Francisco, Downtown Campus"])])
layout = Layout(
autosize=True,
hovermode='closest',
mapbox=dict(
accesstoken=mapbox_access_token,
bearing=0,
center=dict(
lat=37.773972,
lon=-122.431297
),
pitch=0,
zoom=11
),
)
fig = dict(data=data, layout=layout)
output = plotly.offline.plot(fig, include_plotlyjs=False,
output_type='div')
activities_grouped_df = activities_df.groupby(['date'], as_index=False)['miles'].sum()
activities_grouped_df['dow'] = activities_grouped_df.date.apply(lambda x: x.weekday())
activities_grouped_df['week_start'] = activities_grouped_df.date.apply(lambda x: x - timedelta(days=x.weekday()))
miles_per_week = activities_grouped_df.groupby(['week_start'], as_index=False).miles.sum()
by_week_df = pd.DataFrame(activities_grouped_df.week_start.unique(), columns=['week_start'])
for i in range(7):
by_week_df['{}'.format(i)] = i
for i in range(7):
by_week_df = pd.merge(by_week_df, activities_grouped_df, left_on=['week_start', '{}'.format(i)],
right_on=['week_start', 'dow'], how='left', suffixes=('', '_{}'.format(i)))
by_week_df = by_week_df[['week_start', 'miles', 'miles_1', 'miles_2', 'miles_3', 'miles_4', 'miles_5', 'miles_6']]
by_week_df.columns = ['week_start', 'miles_0', 'miles_1', 'miles_2', 'miles_3', 'miles_4', 'miles_5', 'miles_6']
by_week_df['year'] = by_week_df['week_start'].apply(lambda x: x.year)
by_week_df.fillna(0, inplace=True)
by_week_df = pd.merge(by_week_df, miles_per_week, how='left', on='week_start')
days_dict = {0: 'Monday', 1: 'Tuesday', 2: 'Wednesday', 3: 'Thursday', 4: 'Friday', 5: 'Saturday', 6: 'Sunday'}
dimensions = list()
for i in range(7):
dimensions.append(
dict(range=[0, 20],
constraintrange=[0, 20],
label='{}'.format(days_dict[i]), values=by_week_df['miles_{}'.format(i)]))
data = [
go.Parcoords(
line=dict(color=by_week_df['miles'],
colorscale='Hot',
showscale=True,
reversescale=True),
opacity=0.5,
dimensions=dimensions, hoverinfo='text')
]
layout = go.Layout(
plot_bgcolor='#E5E5E5',
paper_bgcolor='#E5E5E5',
title='Miles per week broken down by day'
)
fig = go.Figure(data=data, layout=layout)
output2 = plotly.offline.plot(fig, include_plotlyjs=False,
output_type='div')
activities_df['week_start'] = activities_df.date.apply(lambda x: x - timedelta(days=x.weekday()))
activities_grouped_df_2 = activities_df.groupby(['workout_type', 'week_start'], as_index=False)['miles'].sum()
by_week_activity_df = pd.DataFrame(activities_grouped_df_2.week_start.unique(), columns=['week_start'])
for i in activities_df.workout_type.unique():
by_week_activity_df['{}'.format(i)] = i
for i in range(4):
by_week_activity_df = pd.merge(by_week_activity_df, activities_grouped_df_2,
left_on=['week_start', '{}'.format(activities_df.workout_type.unique()[i])],
right_on=['week_start', 'workout_type'], how='left',
suffixes=('', '_{}'.format(activities_df.workout_type.unique()[i])))
by_week_activity_df = by_week_activity_df[['week_start', 'miles', 'miles_Workout', 'miles_Long Run', 'miles_Race']]
by_week_activity_df.columns = ['week_start', 'miles_Run', 'miles_Workout', 'miles_Long Run', 'miles_Race']
by_week_activity_df.fillna(0, inplace=True)
by_week_activity_df['miles_Run'] = np.array(by_week_activity_df['miles_Run']) + np.array(
by_week_activity_df['miles_Long Run'])
by_week_activity_df['miles_Run'] = np.array(by_week_activity_df['miles_Run']) + np.array(
by_week_activity_df['miles_Long Run'])
data = []
custom_colours = ['blue', 'orange', 'red']
j = 0
for i in ['Run', 'Workout', 'Race']:
data.append(go.Bar(
x=by_week_activity_df['week_start'],
y=by_week_activity_df['miles_{}'.format(i)],
marker=dict(color=custom_colours[j]),
name=i))
j += 1
layout = dict(
barmode='stack',
hovermode='closest',
title='Miles per week',
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label='1m',
step='month',
stepmode='backward'),
dict(count=6,
label='6m',
step='month',
stepmode='backward'),
dict(count=1,
label='YTD',
step='year',
stepmode='todate'),
dict(count=1,
label='1y',
step='year',
stepmode='backward'),
dict(step='all')
])
),
rangeslider=dict(),
type='date'
)
)
fig = go.Figure(data=data, layout=layout)
output3 = plotly.offline.plot(fig, include_plotlyjs=False,
output_type='div')
return(output,output2,output3)
def st_map(self,
zoom=11,
style='mapbox://styles/rmetfc/ck1manozn0edb1dpmvtzle2cp',
build_order=None):
if self.dataset.node_station_info is None or len(
self.dataset.node_station_info) == 0:
raise ValueError('No station information found in dataset')
import numpy as np
import plotly
from plotly.graph_objs import Scattermapbox, Layout
mapboxAccessToken = "pk.eyJ1Ijoicm1ldGZjIiwiYSI6ImNrMW02YmwxbjAxN24zam9kNGVtMm5raWIifQ.FXKqZCxsFK-dGLLNdeRJHw"
# os.environ['MAPBOX_API_KEY'] = mapboxAccessToken
# lat_lng_name_list = [e[2:] for e in self.dataset.node_station_info]
build_order = build_order or list(
range(len(self.dataset.node_station_info)))
color = ['rgb(255, 0, 0)' for _ in build_order]
lat = np.array([float(e[2]) for e in self.dataset.node_station_info
])[self.traffic_data_index]
lng = np.array([float(e[3]) for e in self.dataset.node_station_info
])[self.traffic_data_index]
text = [str(e) for e in range(len(build_order))]
file_name = self.dataset.dataset + '-' + self.dataset.city + '.html'
bikeStations = [
Scattermapbox(
lon=lng,
lat=lat,
text=text,
mode='markers',
marker=dict(
size=6,
# color=['rgb(%s, %s, %s)' % (255,
# 195 - e * 195 / max(build_order),
# 195 - e * 195 / max(build_order)) for e in build_order],
color=color,
opacity=1,
))
]
layout = Layout(
title=
'Bike Station Location & The latest built stations with deeper color',
autosize=True,
hovermode='closest',
showlegend=False,
mapbox=dict(accesstoken=mapboxAccessToken,
bearing=0,
center=dict(lat=np.median(lat), lon=np.median(lng)),
pitch=0,
zoom=zoom,
style=style),
)
fig = dict(data=bikeStations, layout=layout)
plotly.offline.plot(fig, filename=file_name)
# Dataset: Starbucks Locations in USA
# Data Source: https://gist.github.com/dankohn/09e5446feb4a8faea24f
df = pd.read_csv('/home/local/ALGOANALYTICS/sayali/Desktop/Data Visualisation/Satellite map/starbucks_us_locations.csv')
df.columns = ['Longitude','Latitude','ADR_Line_1','ADR_Line_2']
# Open mapbox account and pass your access token over here
# Mapbox account sign up and access token is free.
# Mapbox information: https://www.mapbox.com/help/how-access-tokens-work/#rotating-tokens
mapbox_access_token = 'Enter_your_access_token'
# Use Scattermap box for satellite maps
data = Data([Scattermapbox(
lat= df['Latitude'],
lon= df['Longitude'],
#color = df['MAPE_scaled'],
text = [str(n) for n in df['ADR_Line_2']],
mode='markers',
marker = dict(color = 'rgb(139, 0, 139)',size=11),
hoverinfo='skip'
) ])
# Declare Layout
layout = Layout(
title = "STARBUCKS LOCATIONS IN USA",
font=dict(family='Courier New, monospace', size=18, color='rgb(0,0,0)'),
autosize=False,
hovermode='closest',
showlegend=False,
width=1800,
height=1000,
ids.append(pf['id'][i])
if pf["Masksd"][i] == 1:
masklon.append(pf['LON'][i])
masklat.append(pf['LAT'][i])
elif pf["Masksd"][i] == 0:
nomasklon.append(pf['LON'][i])
nomasklat.append(pf['LAT'][i])
else:
unknownlon.append(pf['LON'][i])
unknownlat.append(pf['LAT'][i])
trace1 = Scattermapbox(
name="Buildings",
mode="markers",
lon=df['LAT'],
lat=df['LON'],
text=df['Location'],
hoverinfo="lon+lat+text",
marker=dict(symbol='square-stroked', size=12, color='black', opacity=1),
legendgroup="Buildings",
)
def maketrace(name, lats, lons, dataframe, color, shape, group, showlegend,
sd):
return Scattermapbox(
name=name,
mode="markers",
lon=lats,
lat=lons,
text="ID: " + dataframe['ID'].astype(str) +
"<br>Mask/Social Distance Compliance: " + sd,
def update_graph(value, slider_value, selectedData, prevLayout, mapControls):
zoom = 12.0
latInitial = 40.7272
lonInitial = -73.991251
bearing = 0
listStr = get_lat_lon_color(selectedData, value, slider_value)
if (prevLayout is not None and mapControls is not None
and 'lock' in mapControls):
zoom = float(prevLayout['mapbox']['zoom'])
latInitial = float(prevLayout['mapbox']['center']['lat'])
lonInitial = float(prevLayout['mapbox']['center']['lon'])
bearing = float(prevLayout['mapbox']['bearing'])
return go.Figure(
data=Data([
Scattermapbox(
lat=eval(listStr)['Lat'],
lon=eval(listStr)['Lon'],
mode='markers',
hoverinfo="lat+lon+text",
text=eval(listStr).index.hour,
marker=go.Marker(color=np.append(
np.insert(eval(listStr).index.hour, 0, 0), 23),
colorscale=[[0, 'rgb(153,236,21)'],
[0.04167, 'rgb(218,240,23)'],
[0.0833, 'rgb(187,236,25)'],
[0.125, 'rgb(157,232,27)'],
[0.1667, 'rgb(128,228,29)'],
[0.2083, 'rgb(102,224,31)'],
[0.25, 'rgb(76,220,32)'],
[0.292, 'rgb(52,216,34)'],
[0.333, 'rgb(36,210,73)'],
[0.375, 'rgb(37,208,66)'],
[0.4167, 'rgb(38,204,88)'],
[0.4583, 'rgb(40,200,109)'],
[0.50, 'rgb(41,196,129)'],
[0.54167, 'rgb(42,192,147)'],
[0.5833, 'rgb(43,188,164)'],
[1.0, 'rgb(97,48,153)']],
opacity=0.5,
size=5,
colorbar=dict(thicknessmode="fraction",
title="Time of<br>Day",
x=0.935,
xpad=0,
nticks=24,
tickfont=dict(color='white'),
titlefont=dict(color='white'),
titleside='right')),
),
Scattermapbox(
lat=[
"40.7505", "40.8296", "40.7484", "40.7069", "40.7527",
"40.7127", "40.7589", "40.8075", "40.7489"
],
lon=[
"-73.9934", "-73.9262", "-73.9857", "-74.0113", "-73.9772",
"-74.0134", "-73.9851", "-73.9626", "-73.9680"
],
mode='markers',
hoverinfo="text",
text=[
"Madison Square Garden", "Yankee Stadium",
"Empire State Building", "New York Stock Exchange",
"Grand Central Station", "One World Trade Center",
"Times Square", "Columbia University", "United Nations HQ"
],
# opacity=0.5,
marker=go.Marker(size=6, color="#ffa0a0"),
),
]),
layout=Layout(
autosize=True,
height=750,
margin=Margin(l=0, r=0, t=0, b=0),
showlegend=False,
mapbox=dict(
accesstoken=mapbox_access_token,
center=dict(
lat=latInitial, # 40.7272
lon=lonInitial # -73.991251
),
style='dark',
bearing=bearing,
zoom=zoom),
updatemenus=[
dict(buttons=([
dict(args=[{
'mapbox.zoom': 12,
'mapbox.center.lon': '-73.991251',
'mapbox.center.lat': '40.7272',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='Reset Zoom',
method='relayout')
]),
direction='left',
pad={
'r': 0,
't': 0,
'b': 0,
'l': 0
},
showactive=False,
type='buttons',
x=0.45,
xanchor='left',
yanchor='bottom',
bgcolor='#323130',
borderwidth=1,
bordercolor="#6d6d6d",
font=dict(color="#FFFFFF"),
y=0.02),
dict(buttons=([
dict(args=[{
'mapbox.zoom': 15,
'mapbox.center.lon': '-73.9934',
'mapbox.center.lat': '40.7505',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='Madison Square Garden',
method='relayout'),
dict(args=[{
'mapbox.zoom': 15,
'mapbox.center.lon': '-73.9262',
'mapbox.center.lat': '40.8296',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='Yankee Stadium',
method='relayout'),
dict(args=[{
'mapbox.zoom': 15,
'mapbox.center.lon': '-73.9857',
'mapbox.center.lat': '40.7484',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='Empire State Building',
method='relayout'),
dict(args=[{
'mapbox.zoom': 15,
'mapbox.center.lon': '-74.0113',
'mapbox.center.lat': '40.7069',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='New York Stock Exchange',
method='relayout'),
dict(args=[{
'mapbox.zoom': 15,
'mapbox.center.lon': '-73.785607',
'mapbox.center.lat': '40.644987',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='JFK Airport',
method='relayout'),
dict(args=[{
'mapbox.zoom': 15,
'mapbox.center.lon': '-73.9772',
'mapbox.center.lat': '40.7527',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='Grand Central Station',
method='relayout'),
dict(args=[{
'mapbox.zoom': 15,
'mapbox.center.lon': '-73.9851',
'mapbox.center.lat': '40.7589',
'mapbox.bearing': 0,
'mapbox.style': 'dark'
}],
label='Times Square',
method='relayout')
]),
direction="down",
pad={
'r': 0,
't': 0,
'b': 0,
'l': 0
},
showactive=False,
bgcolor="rgb(50, 49, 48, 0)",
type='buttons',
yanchor='bottom',
xanchor='left',
font=dict(color="#FFFFFF"),
x=0,
y=0.05)
]))