#BOKEH PLOT CODE#
#BOKEH PLOT SERIES#

The vbar() method has following parameters − Sr.No The bars are shown vertically across plot height.

#BOKEH PLOT CODE#

The y coordinates of the centers of the horizontal bars.įollowing code is an example of horizontal bar using Bokeh.įig = figure(plot_width = 400, plot_height = 200)įig.hbar(y =, height = 1, left = 0, right =, color = 'Cyan') The hbar() method has the following parameters − Sr.No The bars are shown horizontally across plot width. The figure object has two different methods for constructing bar plot hbar()

It needs x and y parameters as data arrays for showing their linear relationship.įollowing code renders a simple line plot between two sets of values in the form Python list objects −įrom otting import figure, output_file, showįig = figure(title = 'Line Plot example', x_axis_label = 'x', y_axis_label = 'y') The line() method of Figure object adds a line glyph to the Bokeh figure. The Figure object can be customised by various keyword arguments. The Figure object is obtained by following constructor − This type of plot is used to visualize relationship between two variables and to indicate the strength of correlation between them.ĭifferent glyph plots are formed by calling appropriate method of Figure class. This type of plot is used to distinguish different groups within the same dataset. This plot indicates a region of points in a particular shade of color. This is typically useful for indicating the count of each category of a particular column or field in your dataset.

#BOKEH PLOT SERIES#

It is used to perform time series analytics. This type of plot is useful for visualizing the movements of points along the x-and y-axes in the form of a line. Types of Plotsĭifferent types of plots created using glyphs are as given below − Line plot However, it is possible to customize the styles using available plotting tools. Bokeh plots constructed using otting interface use a default set of tools and styles. In Bokeh terminology, these geometrical shapes are called gylphs.

These shapes have visual information about the corresponding set of data. Any plot is usually made up of one or many geometrical shapes such as line, circle, rectangle, etc.