show(p)
# Plots de Séries Temporais com Pandas
import pandas as pd
from bokeh.plotting import figure, output_file, show
AAPL = pd.read_csv(
"http://ichart.yahoo.com/table.csv?s=AAPL&a=0&b=1&c=2000&d=0&e=1&f=2010",
parse_dates=['Date'])
output_file("Bokeh-Datetime.html")
# create a new plot with a datetime axis type
p = figure(width=800, height=250, x_axis_type="datetime")
p.line(AAPL['Date'], AAPL['Close'], color='navy', alpha=0.5)
show(p)
# Google Maps
from bokeh.io import output_file, show
from bokeh.models import (GMapPlot, GMapOptions, ColumnDataSource, Circle,
DataRange1d, PanTool, WheelZoomTool, BoxSelectTool)
map_options = GMapOptions(lat=-23.5431786,
lng=-46.62918450000001,
map_type="roadmap",
zoom=11)
plot = GMapPlot(x_range=DataRange1d(),
y_range=DataRange1d(),
df["Temperature"] = df["Temperature"]/10
df["Pressure"] = df["Pressure"]/10
p = figure(plot_width=500, plot_height=400, tools='pan,resize', logo=None)
p.title = "Temperature and Air Pressure"
p.title_text_color = "Gray"
p.title_text_font = "arial"
p.title_text_font_style = "bold"
p.xaxis.minor_tick_line_color = None
p.yaxis.minor_tick_line_color = None
p.xaxis.axis_label = "Temperature (°C)"
p.yaxis.axis_label = "Pressure (hPa)"
p.circle(df["Temperature"],df["Pressure"], size=0.5)
output_file("Weather.html", mode='cdn')
# The JS and CSS will be fetched from CDN by default
# output_file("Weather.html", mode='inline')
# output_file("Weather.html", mode='relative')
# show(p)
# ----- (4) Time Date Plot -----
df = pandas.read_csv('http://ichart.yahoo.com/table.csv?s=AAPL&a=0&b=1&c=2000&d=0&e=1&f=2010',
parse_dates=["Date"])
p = figure(width=500, height=250, x_axis_type='datetime', responsive=True)
p.line(df['Date'], df['Close'], color='Orange', alpha=0.5)
output_file('Timeseries.html')
show(p)
