import asyncio

from io import StringIO

from js import fetch

import panel as pn

import param

import pandas as pd

from panel.io.pyodide import show

from pyodide.http import open_url

MAPBOX_KEY = "pk.eyJ1IjoicGFuZWxvcmciLCJhIjoiY2s1enA3ejhyMWhmZjNobjM1NXhtbWRrMyJ9.B_frQsAVepGIe-HiOJeqvQ"

class App(pn.viewable.Viewer):

data = param.DataFrame(precedence=-1)

view = param.DataFrame(precedence=-1)

arc_view = param.DataFrame(precedence=-1)

radius = param.Integer(default=50, bounds=(20, 1000))

elevation = param.Integer(default=10, bounds=(0, 50))

hour = param.Integer(default=0, bounds=(0, 23))

self.deck_gl = None

super().__init__(**params)

self.deck_gl = pn.pane.DeckGL(

dict(self.spec), mapbox_api_key=MAPBOX_KEY, throttle={'click': 10},

sizing_mode='stretch_both', margin=0)

dict(self.spec),

mapbox_api_key=MAPBOX_KEY,

throttle={'click': 10},

sizing_mode='stretch_both',

margin=0

)

self.deck_gl.param.watch(self._update_arc_view, 'click_state')

self._playing = False

self._cb = pn.state.add_periodic_callback(

(df.pickup_y<=float(lat+tol))

]

@param.depends('hour', watch=True)

@param.depends('hour', watch=True, on_init=True)

def _update_hourly_view(self):

self.view = self.data[self.data.hour==self.hour]

def update_spec(self):

self.deck_gl.object = dict(self.spec)

data = await fetch('https://s3.eu-west-1.amazonaws.com/assets.holoviews.org/data/nyc_taxi_wide.csv')

df = pd.read_csv(StringIO(await data.text()))

url = 'https://s3.eu-west-1.amazonaws.com/assets.holoviews.org/data/nyc_taxi_wide.csv'

df = pd.read_csv(open_url(url))

app = App(data=df)

controls = pn.Param(app.param, sizing_mode='stretch_width', show_name=False)

import asyncio

from io import StringIO

from js import fetch

import altair as alt

import panel as pn

import pandas as pd

from panel.io.pyodide import show

from sklearn.cluster import KMeans

from pyodide.http import open_url

pn.config.sizing_mode = 'stretch_width'

data =await fetch('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-28/penguins.csv')

penguins = pd.read_csv(StringIO(await data.text())).dropna()

url = 'https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-28/penguins.csv'

penguins = pd.read_csv(open_url(url)).dropna()

cols = list(penguins.columns)[2:6]

x = pn.widgets.Select(name='x', options=cols, value='bill_depth_mm')