
- Bokeh Tutorial
- Bokeh - Home
- Bokeh - Introduction
- Bokeh - Environment Setup
- Bokeh - Getting Started
- Bokeh - Jupyter Notebook
- Bokeh - Basic Concepts
- Bokeh - Plots with Glyphs
- Bokeh - Area Plots
- Bokeh - Circle Glyphs
- Bokeh - Rectangle, Oval and Polygon
- Bokeh - Wedges and Arcs
- Bokeh - Specialized Curves
- Bokeh - Setting Ranges
- Bokeh - Axes
- Bokeh - Annotations and Legends
- Bokeh - Pandas
- Bokeh - ColumnDataSource
- Bokeh - Filtering Data
- Bokeh - Layouts
- Bokeh - Plot Tools
- Bokeh - Styling Visual Attributes
- Bokeh - Customising legends
- Bokeh - Adding Widgets
- Bokeh - Server
- Bokeh - Using Bokeh Subcommands
- Bokeh - Exporting Plots
- Bokeh - Embedding Plots and Apps
- Bokeh - Extending Bokeh
- Bokeh - WebGL
- Bokeh - Developing with JavaScript
- Bokeh Useful Resources
- Bokeh - Quick Guide
- Bokeh - Useful Resources
- Bokeh - Discussion
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Bokeh - Getting Started
Creating a simple line plot between two numpy arrays is very simple. To begin with, import following functions from bokeh.plotting modules −
from bokeh.plotting import figure, output_file, show
The figure() function creates a new figure for plotting.
The output_file() function is used to specify a HTML file to store output.
The show() function displays the Bokeh figure in browser on in notebook.
Next, set up two numpy arrays where second array is sine value of first.
import numpy as np import math x = np.arange(0, math.pi*2, 0.05) y = np.sin(x)
To obtain a Bokeh Figure object, specify the title and x and y axis labels as below −
p = figure(title = "sine wave example", x_axis_label = 'x', y_axis_label = 'y')
The Figure object contains a line() method that adds a line glyph to the figure. It needs data series for x and y axes.
p.line(x, y, legend = "sine", line_width = 2)
Finally, set the output file and call show() function.
output_file("sine.html") show(p)
This will render the line plot in ‘sine.html’ and will be displayed in browser.
Complete code and its output is as follows
from bokeh.plotting import figure, output_file, show import numpy as np import math x = np.arange(0, math.pi*2, 0.05) y = np.sin(x) output_file("sine.html") p = figure(title = "sine wave example", x_axis_label = 'x', y_axis_label = 'y') p.line(x, y, legend = "sine", line_width = 2) show(p)
Output on browser
