Customizing glyph settings

Interactive Data Visualization with Bokeh

George Boorman

Core Curriculum Manager, DataCamp

Glyph size

fig = figure(x_axis_label="Rebounds", 
             y_axis_label="Points")
fig.circle(x="rebounds", y="points",

source=source, size=12)
output_file(filename="size_12_scatter.html") show(fig)

size_12_scatter

Interactive Data Visualization with Bokeh

Glyph outline color

fig = figure(x_axis_label="Blocks", 
             y_axis_label="Points")
fig.circle(x="blocks", y="points", 
           source=source, size=10,

line_color="red")
output_file(filename="red_lines.html") show(fig)

line_color_scatter

Interactive Data Visualization with Bokeh

Glyph fill color

fig = figure(x_axis_label="Assists", 
             y_axis_label="Blocks")
fig.circle(x="blocks", y="points", 
           source=source, size=12,

fill_color="red")
output_file(filename="red_circles.html") show(fig)

red_fill_color

Interactive Data Visualization with Bokeh

Glyph transparency

fig = figure(x_axis_label="Free Throw %", 
             y_axis_label="Field Goal %")
fig.circle(x="free_throw_perc", 
           y="field_goal_perc", 
           source=east, size=10,

fill_alpha=0.2, legend_label="East")
fig.circle(x="free_throw_perc", y="field_goal_perc", source=west, size=10, fill_alpha=0.2, fill_color="red", legend_label="West")
output_file(filename="transparent.html") show(fig)

fill_alpha_scatter

Interactive Data Visualization with Bokeh

Updating glyphs

fig = figure(x_axis_label="Steals", 
             y_axis_label="Points")

circle = fig.circle(x="steals", y="assists", source=source, size=10, fill_color="green")
output_file(filename="original.html") show(fig)
circle.glyph.size = 20

circle.glyph.fill_color = "orange"
output_file(filename="updated.html") show(fig)

original_scatter

updated_scatter

Interactive Data Visualization with Bokeh

Line glyphs

Scatter argument Line plot equivalent
size line_width
fill_alpha alpha
color line_color
fill_color Not applicable
line_color Not applicable
Interactive Data Visualization with Bokeh

The dataset

print(nba.iloc[:3, :6])
     player            position    minutes    field_goal_perc    three_point_perc    free_throw_perc
0    Russell Westbrook PG          34.6       0.425              0.343               0.845
1    James Harden      PG          36.4       0.440              0.347               0.847
2    Isaiah Thomas     PG          33.8       0.463              0.379               0.909
print(nba.iloc[:3, 6:])
     rebounds    assists    steals    blocks    points    team    conference    scorer_category
0    10.7        10.4       1.6       0.4       31.6      OKC     West          High Scorer
1    8.1         11.2       1.5       0.5       29.1      HOU     West          High Scorer
2    2.7         5.9        0.9       0.2       28.9      BOS     East          High Scorer
Interactive Data Visualization with Bokeh

Let's practice!

Interactive Data Visualization with Bokeh

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