Regret not learning this in Python
Tags: python, pythonbokeh, pythondata, pythonprogramming
Published: 2024-04-14 06:09:18

---
canonical_url: https://pratikpathak.com/25-python-bokeh-example-learn-bokeh-from-examples/?utm_source=rss&utm_medium=rss&utm_campaign=25-python-bokeh-example-learn-bokeh-from-examples
---
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](https://bokeh.org/) 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
```

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)
```

[Live Preview](https://colab.research.google.com/drive/1hQD7qMu5rbhV8JQ6gZ61drGiTQfUOyTE?usp=sharing) | [Source Code](https://github.com/zpratikpathak/25-Python-Bokeh-Example) | [🌿 Contribute](https://github.com/zpratikpathak/25-Python-Bokeh-Example)

## 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)
```

## 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)
```

## 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)
```

## 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)
```

[Live Preview](https://colab.research.google.com/drive/1hQD7qMu5rbhV8JQ6gZ61drGiTQfUOyTE?usp=sharing) | [Source Code](https://github.com/zpratikpathak/25-Python-Bokeh-Example) | [🌿 Contribute](https://github.com/zpratikpathak/25-Python-Bokeh-Example)

## 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)
```

## 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)
```

## 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)
```

## 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)
```

## 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)
```

[Live Preview](https://colab.research.google.com/drive/1hQD7qMu5rbhV8JQ6gZ61drGiTQfUOyTE?usp=sharing) | [Source Code](https://github.com/zpratikpathak/25-Python-Bokeh-Example) | [🌿 Contribute](https://github.com/zpratikpathak/25-Python-Bokeh-Example)

## 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)
```

## 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)
```

## 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)
```

## 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)
```

## 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)
```

[Live Preview](https://colab.research.google.com/drive/1hQD7qMu5rbhV8JQ6gZ61drGiTQfUOyTE?usp=sharing) | [Source Code](https://github.com/zpratikpathak/25-Python-Bokeh-Example) | [🌿 Contribute](https://github.com/zpratikpathak/25-Python-Bokeh-Example)

## 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)
```

More Important examples are here at [25+ Python Bokeh Example](https://pratikpathak.com/25-python-bokeh-example-learn-bokeh-from-examples/)

## 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](https://github.com/zpratikpathak/25-Python-Bokeh-Example)

## 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.