Regret not learning this in Python

Representing your data in Python is one of the crucial steps, usually whenever I deal with data I just simply use dp.head() (as we do in pandas) and that’s it, but it has many disadvantages. Later I found out about the python bokeh which can create interactive graphs. Here I will show you a list of 25+ Python Bokeh examples to learn Python Bokeh.

Python Bokeh is one of the best Python packages for data visualization. Today we are going to see some Python Bokeh Examples. I have also provided the Python Bokeh project source code GitHub. Learn this easy visualization tool and add it to your Python stack.

What is Python Bokeh?

Python Bokeh is a data visualization tool or we can also say Python Bokeh is used to plot various types of graphs. There are various other graph plotting libraries like matplotlib but Python Bokeh graphs are dynamic in nature means you can interact with the generated graph. See the below examples…

Installation :

Python Bokeh can be easily installed using PIP. You can install the Python Bokeh easily by running the command:

pip install bokeh
pip install bokeh
pip install bokeh

Enter fullscreen mode Exit fullscreen mode

Now everything is ready let’s go through the examples ‍️…

1. LinePlot

from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="{LinePlot Python Bokeh Example")
p.line(x, y, line_width=2)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="{LinePlot Python Bokeh Example")
p.line(x, y, line_width=2)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook x = [1, 2, 3, 4, 5] y = [4, 5, 5, 7, 3] p = figure(title="{LinePlot Python Bokeh Example") p.line(x, y, line_width=2) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

Live Preview | Source Code | Contribute

2. Scatter Plot

from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Scatter Plot Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=10, color="navy", alpha=0.5)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Scatter Plot Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=10, color="navy", alpha=0.5)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook x = [1, 2, 3, 4, 5] y = [4, 5, 5, 7, 3] p = figure(title="Scatter Plot Python Bokeh Example by PratikPathak.com") p.circle(x, y, size=10, color="navy", alpha=0.5) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

3. Bar Chart

from bokeh.plotting import figure, show, output_notebook
categories = ["A", "B", "C", "D", "E"]
values = [10, 15, 8, 12, 6]
p = figure(x_range=categories, title="Bar Chart Python Bokeh Example by PratikPathak.com")
p.vbar(x=categories, top=values, width=0.9)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
categories = ["A", "B", "C", "D", "E"]
values = [10, 15, 8, 12, 6]
p = figure(x_range=categories, title="Bar Chart Python Bokeh Example by PratikPathak.com")
p.vbar(x=categories, top=values, width=0.9)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook categories = ["A", "B", "C", "D", "E"] values = [10, 15, 8, 12, 6] p = figure(x_range=categories, title="Bar Chart Python Bokeh Example by PratikPathak.com") p.vbar(x=categories, top=values, width=0.9) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

4. Histogram

from bokeh.plotting import figure, show, output_notebook
import numpy as np
data = np.random.normal(0, 1, 1000)
p = figure(title="Histogram Python Bokeh Example by PratikPathak.com")
p.hist(data, bins=30, color="navy", alpha=0.5)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
import numpy as np
data = np.random.normal(0, 1, 1000)
p = figure(title="Histogram Python Bokeh Example by PratikPathak.com")
p.hist(data, bins=30, color="navy", alpha=0.5)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook import numpy as np data = np.random.normal(0, 1, 1000) p = figure(title="Histogram Python Bokeh Example by PratikPathak.com") p.hist(data, bins=30, color="navy", alpha=0.5) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

5. Pie Chart

from bokeh.plotting import figure, show, output_notebook
labels = ["A", "B", "C", "D"]
values = [10, 15, 8, 12]
p = figure(title="Pie Chart Python Bokeh Example by PratikPathak.com")
p.wedge(x=0, y=0, radius=0.4, start_angle=0.6, end_angle=2.6, color=["red", "green", "blue", "yellow"], legend_label=labels)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
labels = ["A", "B", "C", "D"]
values = [10, 15, 8, 12]
p = figure(title="Pie Chart Python Bokeh Example by PratikPathak.com")
p.wedge(x=0, y=0, radius=0.4, start_angle=0.6, end_angle=2.6, color=["red", "green", "blue", "yellow"], legend_label=labels)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook labels = ["A", "B", "C", "D"] values = [10, 15, 8, 12] p = figure(title="Pie Chart Python Bokeh Example by PratikPathak.com") p.wedge(x=0, y=0, radius=0.4, start_angle=0.6, end_angle=2.6, color=["red", "green", "blue", "yellow"], legend_label=labels) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

Live Preview | Source Code | Contribute

6. Time Series Plot

from bokeh.plotting import figure, show, output_notebook
from datetime import datetime, timedelta
start = datetime(2023, 1, 1)
end = start + timedelta(days=30)
x = [start + timedelta(days=i) for i in range((end-start).days)]
y = [10, 15, 8, 12, 6, 18, 9, 14, 7, 11, 5, 16, 8, 13, 6]
p = figure(x_axis_type="datetime", title="Time Series Plot Python Bokeh Example by PratikPathak.com")
p.line(x, y, line_width=2)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
from datetime import datetime, timedelta
start = datetime(2023, 1, 1)
end = start + timedelta(days=30)
x = [start + timedelta(days=i) for i in range((end-start).days)]
y = [10, 15, 8, 12, 6, 18, 9, 14, 7, 11, 5, 16, 8, 13, 6]
p = figure(x_axis_type="datetime", title="Time Series Plot Python Bokeh Example by PratikPathak.com")
p.line(x, y, line_width=2)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook from datetime import datetime, timedelta start = datetime(2023, 1, 1) end = start + timedelta(days=30) x = [start + timedelta(days=i) for i in range((end-start).days)] y = [10, 15, 8, 12, 6, 18, 9, 14, 7, 11, 5, 16, 8, 13, 6] p = figure(x_axis_type="datetime", title="Time Series Plot Python Bokeh Example by PratikPathak.com") p.line(x, y, line_width=2) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

7. Linked Brushing

from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
source = ColumnDataSource(data=dict(x1=x1, y1=y1, x2=x2, y2=y2))
p1 = figure(title="Scatter Plot 1")
p1.circle('x1', 'y1', source=source)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle('x2', 'y2', source=source)
output_notebook()
show(p1, p2)
from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
source = ColumnDataSource(data=dict(x1=x1, y1=y1, x2=x2, y2=y2))
p1 = figure(title="Scatter Plot 1")
p1.circle('x1', 'y1', source=source)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle('x2', 'y2', source=source)
output_notebook()
show(p1, p2)
from bokeh.plotting import figure, show, output_notebook from bokeh.models import ColumnDataSource x1 = [1, 2, 3, 4, 5] y1 = [4, 5, 5, 7, 3] x2 = [2, 3, 4, 5, 6] y2 = [2, 4, 6, 8, 4] source = ColumnDataSource(data=dict(x1=x1, y1=y1, x2=x2, y2=y2)) p1 = figure(title="Scatter Plot 1") p1.circle('x1', 'y1', source=source) p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com") p2.circle('x2', 'y2', source=source) output_notebook() show(p1, p2)

Enter fullscreen mode Exit fullscreen mode

8. Hover Tooltips

from bokeh.plotting import figure, show, output_notebook
from bokeh.models import HoverTool
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Hover Tooltips Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
from bokeh.models import HoverTool
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Hover Tooltips Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook from bokeh.models import HoverTool x = [1, 2, 3, 4, 5] y = [4, 5, 5, 7, 3] p = figure(title="Hover Tooltips Python Bokeh Example by PratikPathak.com") p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5) hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")]) p.add_tools(hover) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

9. Annotations

from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Arrow, VectorRenderer, Label
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Annotations Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
arrow = Arrow(x_start=2, y_start=4, x_end=3, y_end=5, line_width=2, line_color="red")
label = Label(x=3, y=6, text="This is a label", render_mode='css', border_line_color='black', border_line_alpha=1.0, background_fill_color='white', background_fill_alpha=0.5)
p.add_layout(arrow)
p.add_layout(label)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Arrow, VectorRenderer, Label
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Annotations Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
arrow = Arrow(x_start=2, y_start=4, x_end=3, y_end=5, line_width=2, line_color="red")
label = Label(x=3, y=6, text="This is a label", render_mode='css', border_line_color='black', border_line_alpha=1.0, background_fill_color='white', background_fill_alpha=0.5)
p.add_layout(arrow)
p.add_layout(label)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook from bokeh.models import Arrow, VectorRenderer, Label x = [1, 2, 3, 4, 5] y = [4, 5, 5, 7, 3] p = figure(title="Annotations Python Bokeh Example by PratikPathak.com") p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5) arrow = Arrow(x_start=2, y_start=4, x_end=3, y_end=5, line_width=2, line_color="red") label = Label(x=3, y=6, text="This is a label", render_mode='css', border_line_color='black', border_line_alpha=1.0, background_fill_color='white', background_fill_alpha=0.5) p.add_layout(arrow) p.add_layout(label) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

10. Custom Glyphs

from bokeh.plotting import figure, show, output_notebook
from bokeh.models.glyphs import Asterisk
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Custom Glyphs Python Bokeh Example by PratikPathak.com")
p.add_glyph(x, y, Asterisk(size=20, line_color="red", fill_color="yellow"))
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
from bokeh.models.glyphs import Asterisk
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Custom Glyphs Python Bokeh Example by PratikPathak.com")
p.add_glyph(x, y, Asterisk(size=20, line_color="red", fill_color="yellow"))
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook from bokeh.models.glyphs import Asterisk x = [1, 2, 3, 4, 5] y = [4, 5, 5, 7, 3] p = figure(title="Custom Glyphs Python Bokeh Example by PratikPathak.com") p.add_glyph(x, y, Asterisk(size=20, line_color="red", fill_color="yellow")) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

Live Preview | Source Code | Contribute

11. Gridlines and Axes

from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Gridlines and Axes Python Bokeh Example by PratikPathak.com", x_range=(0, 6), y_range=(0, 8))
p.grid.grid_line_color = "grey"
p.grid.grid_line_dash = [6, 4]
p.xaxis.axis_label = "X-axis"
p.yaxis.axis_label = "Y-axis"
p.line(x, y, line_width=2)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Gridlines and Axes Python Bokeh Example by PratikPathak.com", x_range=(0, 6), y_range=(0, 8))
p.grid.grid_line_color = "grey"
p.grid.grid_line_dash = [6, 4]
p.xaxis.axis_label = "X-axis"
p.yaxis.axis_label = "Y-axis"
p.line(x, y, line_width=2)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook x = [1, 2, 3, 4, 5] y = [4, 5, 5, 7, 3] p = figure(title="Gridlines and Axes Python Bokeh Example by PratikPathak.com", x_range=(0, 6), y_range=(0, 8)) p.grid.grid_line_color = "grey" p.grid.grid_line_dash = [6, 4] p.xaxis.axis_label = "X-axis" p.yaxis.axis_label = "Y-axis" p.line(x, y, line_width=2) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

12. Legend

from bokeh.plotting import figure, show, output_notebook
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p = figure(title="Legend Python Bokeh Example by PratikPathak.com")
p.line(x1, y1, line_width=2, color="red", legend_label="Line 1")
p.line(x2, y2, line_width=2, color="blue", legend_label="Line 2")
p.legend.location = "top_left"
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p = figure(title="Legend Python Bokeh Example by PratikPathak.com")
p.line(x1, y1, line_width=2, color="red", legend_label="Line 1")
p.line(x2, y2, line_width=2, color="blue", legend_label="Line 2")
p.legend.location = "top_left"
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook x1 = [1, 2, 3, 4, 5] y1 = [4, 5, 5, 7, 3] x2 = [2, 3, 4, 5, 6] y2 = [2, 4, 6, 8, 4] p = figure(title="Legend Python Bokeh Example by PratikPathak.com") p.line(x1, y1, line_width=2, color="red", legend_label="Line 1") p.line(x2, y2, line_width=2, color="blue", legend_label="Line 2") p.legend.location = "top_left" output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

13. Categorical Plots

from bokeh.plotting import figure, show, output_notebook
fruits = ["Apples", "Pears", "Nectarines", "Plums", "Grapes", "Strawberries"]
counts = [5, 3, 4, 2, 4, 6]
p = figure(x_range=fruits, title="Categorical Plots Python Bokeh Example by PratikPathak.com")
p.vbar(x=fruits, top=counts, width=0.9)
p.xaxis.axis_label = "Fruit"
p.yaxis.axis_label = "Count"
p.xaxis.axis_label_text_font_size = "12pt"
p.yaxis.axis_label_text_font_size = "12pt"
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
fruits = ["Apples", "Pears", "Nectarines", "Plums", "Grapes", "Strawberries"]
counts = [5, 3, 4, 2, 4, 6]
p = figure(x_range=fruits, title="Categorical Plots Python Bokeh Example by PratikPathak.com")
p.vbar(x=fruits, top=counts, width=0.9)
p.xaxis.axis_label = "Fruit"
p.yaxis.axis_label = "Count"
p.xaxis.axis_label_text_font_size = "12pt"
p.yaxis.axis_label_text_font_size = "12pt"
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook fruits = ["Apples", "Pears", "Nectarines", "Plums", "Grapes", "Strawberries"] counts = [5, 3, 4, 2, 4, 6] p = figure(x_range=fruits, title="Categorical Plots Python Bokeh Example by PratikPathak.com") p.vbar(x=fruits, top=counts, width=0.9) p.xaxis.axis_label = "Fruit" p.yaxis.axis_label = "Count" p.xaxis.axis_label_text_font_size = "12pt" p.yaxis.axis_label_text_font_size = "12pt" output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

14. Subplots

from bokeh.plotting import figure, show, output_notebook
from bokeh.layouts import gridplot
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com")
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
grid = gridplot([[p1, p2]], plot_width=400, plot_height=400)
output_notebook()
show(grid)
from bokeh.plotting import figure, show, output_notebook
from bokeh.layouts import gridplot
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com")
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
grid = gridplot([[p1, p2]], plot_width=400, plot_height=400)
output_notebook()
show(grid)
from bokeh.plotting import figure, show, output_notebook from bokeh.layouts import gridplot x1 = [1, 2, 3, 4, 5] y1 = [4, 5, 5, 7, 3] x2 = [2, 3, 4, 5, 6] y2 = [2, 4, 6, 8, 4] p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com") p1.circle(x1, y1, size=10, color="navy", alpha=0.5) p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com") p2.circle(x2, y2, size=10, color="red", alpha=0.5) grid = gridplot([[p1, p2]], plot_width=400, plot_height=400) output_notebook() show(grid)

Enter fullscreen mode Exit fullscreen mode

15. Interactive Plots

from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, HoverTool, BoxSelectTool
import numpy as np
x = np.random.random(1000)
y = np.random.random(1000)
source = ColumnDataSource(data=dict(x=x, y=y))
p = figure(title="Interactive Plots Python Bokeh Example by PratikPathak.com", tools="hover,box_select")
p.circle('x', 'y', source=source, size=3, color="navy", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, HoverTool, BoxSelectTool
import numpy as np
x = np.random.random(1000)
y = np.random.random(1000)
source = ColumnDataSource(data=dict(x=x, y=y))
p = figure(title="Interactive Plots Python Bokeh Example by PratikPathak.com", tools="hover,box_select")
p.circle('x', 'y', source=source, size=3, color="navy", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p)
from bokeh.plotting import figure, show, output_notebook from bokeh.models import ColumnDataSource, HoverTool, BoxSelectTool import numpy as np x = np.random.random(1000) y = np.random.random(1000) source = ColumnDataSource(data=dict(x=x, y=y)) p = figure(title="Interactive Plots Python Bokeh Example by PratikPathak.com", tools="hover,box_select") p.circle('x', 'y', source=source, size=3, color="navy", alpha=0.5) hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")]) p.add_tools(hover) output_notebook() show(p)

Enter fullscreen mode Exit fullscreen mode

Live Preview | Source Code | Contribute

16. Linked Panning and Zooming

from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Range1d
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com", x_range=Range1d(0, 6), y_range=Range1d(0, 8))
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com", x_range=p1.x_range, y_range=p1.y_range)
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
output_notebook()
show(p1, p2)
from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Range1d
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com", x_range=Range1d(0, 6), y_range=Range1d(0, 8))
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com", x_range=p1.x_range, y_range=p1.y_range)
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
output_notebook()
show(p1, p2)
from bokeh.plotting import figure, show, output_notebook from bokeh.models import Range1d x1 = [1, 2, 3, 4, 5] y1 = [4, 5, 5, 7, 3] x2 = [2, 3, 4, 5, 6] y2 = [2, 4, 6, 8, 4] p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com", x_range=Range1d(0, 6), y_range=Range1d(0, 8)) p1.circle(x1, y1, size=10, color="navy", alpha=0.5) p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com", x_range=p1.x_range, y_range=p1.y_range) p2.circle(x2, y2, size=10, color="red", alpha=0.5) output_notebook() show(p1, p2)

Enter fullscreen mode Exit fullscreen mode

More Important examples are here at 25+ Python Bokeh Example

How to Contribute?

Feel free to open a PR request on our GitHub repo.

Steps to contribute:

  1. Fork the repo
  2. Make changes in the Forked repo and save
  3. Open a Pull Request
  4. That’s it !

Contribute

Conclusion

In this article I have shared you 25+ Python Bokeh examples which can help you to learn python bokeh. Feel free to contribute to our github repo and keep it updated.

原文链接:Regret not learning this in Python

© 版权声明
THE END
喜欢就支持一下吧
点赞10 分享
Flat rich prosperous time in vain to develop a group of coward, hardship is the mother of strong forever.
平富足的盛世徒然养成一批懦夫,困苦永远是坚强之母
评论 抢沙发

请登录后发表评论

    暂无评论内容