show(row(box1, box2)) # In[6]: # 弦图 Chord chord1 = Chord(data=exercise, source="id", target="kind") chord2 = Chord(data=exercise, source="id", target="kind", value="pulse") show(row(chord1, chord2)) # * bokeh.plotting # In[7]: from bokeh.plotting import figure import numpy as np p = figure(plot_width=400, plot_height=400) # 方框 p.square(np.random.randint(1, 10, 5), np.random.randint(1, 10, 5), size=20, color="navy") # 圆形 p.circle(np.random.randint(1, 10, 5), np.random.randint(1, 10, 5), size=10, color="green") show(p)
#!/usr/local/opt/python3/bin/python3 import pandas from bokeh.charts import Scatter from bokeh.plotting import figure, output_file, show df = pandas.DataFrame(columns=["X-Axis", "Y-Axis"]) df["X-Axis"] = [1, 2, 3, 4, 5] df["Y-Axis"] = [5, 6, 4, 5, 3] p = Scatter(df, x="X-Axis", y="Y-Axis", title="Temperature Observations", xlabel="Day of Observations", ylabel="Temperature") output_file("Scatter_charts.html") show(p) p = figure(plot_width=500, plot_height=500, title="Earthquakes") # p.circle([1,2,3,4,5],[3,4,6,1,7],size=12,color="red",alpha=0.5) # p.triangle([1,2,3,4,5],[3,4,6,1,7],size=12,color="red",alpha=0.5) # p.circle([1,2,3,4,5],[3,4,6,1,7],size=[8,12,14,16,18],color="red",alpha=0.5) p.circle([1, 2, 3, 4, 5], [3, 4, 6, 1, 7], size=[i * 2 for i in [8, 12, 14, 16, 18]], color="red", alpha=0.5) show(p) output_file("Scatter_plotting.html")
inner="stick") output_file("Bokeh-ViolinPlot.html") show(mpl.to_bokeh()) # Gráficos de Linha from bokeh.plotting import figure, output_file, show # Outuput output_file("Bokeh-Grafico-Linha.html") p = figure(plot_width=400, plot_height=400) # Adicionando círculos ao gráfico p.circle([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], size=20, color="navy", alpha=0.5) # Mostrando o resultado show(p) # Geojson from bokeh.io import output_file, show from bokeh.models import GeoJSONDataSource from bokeh.plotting import figure from bokeh.sampledata.sample_geojson import geojson geo_source = GeoJSONDataSource(geojson=geojson) p = figure() p.circle(x='x', y='y', alpha=0.9, source=geo_source) output_file("Bokeh-GeoJSON.html")
# ----- (2) Test using bokeh.plotting (recommended for more customization) ----- # p = figure(plot_width=500, plot_height=400, title='Earthquake') p = figure(plot_width=500, plot_height=400) # help(p) p.title = 'Earthquake' p.title_text_color = 'Orange' p.title_text_font = 'Times' p.title_text_font_style = 'italic' p.yaxis.minor_tick_line_color = None p.xaxis.axis_label = 'Times' p.yaxis.axis_label = 'Value' # quad may also be used p.circle([4, 8, 12], [7, 14, 21], size=17, color='orange', alpha=0.5) # p.triangle(df['X'], df['Y'], size=10, color='red', alpha=0.5) p.triangle(df['X'], df['Y'], size=[5, 10, 15, 20, 25], color='red', alpha=0.5) output_file('Scatter_plotting.html') # show(p) # ----- (3) Exercise: Reading from excel ----- df = pandas.read_excel("verlegenhuken.xlsx", sheetname=0) 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"