Posted on • Originally published atpratikpathak.com
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 usedp.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?
PythonBokeh 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 bokehNow everything is ready let’s go through the examples 🏃♂️…
1. LinePlot
from bokeh.plotting import figure, show, output_notebookx = [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)Live Preview |Source Code |🌿 Contribute
2.Scatter Plot
from bokeh.plotting import figure, show, output_notebookx = [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)3.Bar Chart
from bokeh.plotting import figure, show, output_notebookcategories = ["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)4.Histogram
from bokeh.plotting import figure, show, output_notebookimport numpy as npdata = 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)5.Pie Chart
from bokeh.plotting import figure, show, output_notebooklabels = ["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)Live Preview |Source Code |🌿 Contribute
6.Time Series Plot
from bokeh.plotting import figure, show, output_notebookfrom datetime import datetime, timedeltastart = 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)7.Linked Brushing
from bokeh.plotting import figure, show, output_notebookfrom bokeh.models import ColumnDataSourcex1 = [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)8.Hover Tooltips
from bokeh.plotting import figure, show, output_notebookfrom bokeh.models import HoverToolx = [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)9.Annotations
from bokeh.plotting import figure, show, output_notebookfrom bokeh.models import Arrow, VectorRenderer, Labelx = [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)10.Custom Glyphs
from bokeh.plotting import figure, show, output_notebookfrom bokeh.models.glyphs import Asteriskx = [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)Live Preview |Source Code |🌿 Contribute
11.Gridlines and Axes
from bokeh.plotting import figure, show, output_notebookx = [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)12.Legend
from bokeh.plotting import figure, show, output_notebookx1 = [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)13.Categorical Plots
from bokeh.plotting import figure, show, output_notebookfruits = ["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)14.Subplots
from bokeh.plotting import figure, show, output_notebookfrom bokeh.layouts import gridplotx1 = [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)15.Interactive Plots
from bokeh.plotting import figure, show, output_notebookfrom bokeh.models import ColumnDataSource, HoverTool, BoxSelectToolimport numpy as npx = 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)Live Preview |Source Code |🌿 Contribute
16.Linked Panning and Zooming
from bokeh.plotting import figure, show, output_notebookfrom bokeh.models import Range1dx1 = [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)More Important examples are here at25+ Python Bokeh Example
How to Contribute?
Feel free to open a PR request on our GitHub repo.
Steps to contribute:
- Fork the repo
- Make changes in the Forked repo and save
- Open a Pull Request
- That’s it 😄!
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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