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Pratik Pathak
Pratik Pathak

Posted on • Originally published at pratikpathak.com

Regret not learning this in Python

#python #pythonbokeh #pythondata #pythonprogramming

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
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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 😄!

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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.

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