Breathtaking Bokeh Line Chart

Bokeh is a Python interactive visualization library that targets modern web browsers for presentation.

Bokeh line chart. The example below shows a sequence of simple 1-level categories. Lets create a vertical bar chart showing changes in measles occurrences in the US over the years 20002015 using the same UN world healthcare indicators database. It is pretty straight-forward to draw bar charts with Bokeh.

Bokeh is a Python interactive data visualization. An alternative output function to be aware of is output_notebook which is used to show plots in-line in a Jupyter Notebook. One for date and one for the values corresponding to that date.

Thats why nowadays it is used more often than its counterparts such as Maplotlib and Seaborn. The basic idea of Bokeh is a two-step process. It renders its plots using HTML and JavaScript.

Let us first import the required packages and take a look at the data. The dataset used here is the SF Monthly Property Crime Report. Time-Series Visualization using bokeh.

Time-Series Visualization using bokeh. First you select from Bokehs building blocks to create your visualization. Bokeh recommends that output_file to which we pass a file name be called at the start of your script immediately after imports.

It targets modern web browsers for presentation providing elegant concise construction of novel graphics with high-performance interactivity. Currently pandas_bokeh supports the following chart types. As usual we need to specify a type of chart or chose a glyph and pass the data to the plotting function.