Basic Plotting Using Bokeh Python Pandas Library – Scatter, Line Visualizations

 

Bokeh is a powerful framework for data visualization in Python. Here I take a look at straightforward plotting and visualization using this powerful library.

Credit to PythonHow. You can check him out on Youtube

bokeh.models #It is a low level interface which involves a lot of work

bokeh.plotting # It is a middle level interface

bokeh.chart # It is a  high level interface

Lets try to create scatter plot

In [130]:

 

lets create a dataframe and add some values to it for our plot

In [131]:

 

lets add some values to the X and Y axis

In [132]:

 

lets store the scatterplot in a variable

In [133]:

 

we can save our file as html using the output_file method and we can also show our plot using the show method

In [134]:

 

In [135]:

 

In [ ]:

lets now plot using the bokeh.plotting interface

lets import the figure object from the plotting interface as that is the main object we will be using to plot. the idea is that you make an empty figure and you add objects to it

In [136]:

 

lets store the figure object in a variable. we can set the with and height of the figure or we can leave it blank to use defaut with
and height

In [137]:

 

you can also customise the plot

In [138]:

 

let’s use the circle method to plot our scatter plots. the circle method takes array of X and Y values. You can also set the size of the scatter circles

In [139]:

 

Out[139]:

You can use a list to determine the size each X,Y pair of plot

In [140]:

 

you can get a full HELP with the p variable by typing help(p)

In [141]:

 

lets plot some time series data

In [142]:

 

In [143]:

 

responsive = True enlarges the whole graph to cover the screen

In [ ]:

lets plot with a line graph

In [128]:

 

Out[128]:

lets save the file and also show it

In [129]:

 

 

Want more information like this?

Similar Posts

Leave a Reply

Your email address will not be published. Required fields are marked *