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)