#Bokeh python vs panda how to#
Portable: The output of the Bokeh charts can be rendered on any web framework such as Django and Python and also on Jupyter Notebooks. In this lesson you will learn how to visually explore and present data in Python by using the Bokeh and Pandas libraries.Powerful: Bokeh is a powerful library because it allows the addition of JavaScript for use-cases.Interactive: Bokeh is a very interactive library that provides the functionality of interactivity to the graphs in addition to static plots.If you’re using Python to analyze data, there are several libraries to choose from.
#Bokeh python vs panda code#
The code here is not crucial for understanding Bokeh, but it’s useful nonetheless because of the prevalence of numpy and pandas in data science '''Bins will be five minutes in width, so the number of bins is (length of interval / 5). Visualizations can help you and your stakeholders gain a better understanding of the data you’re dealing with. After generating the data, we put it in a pandas dataframe to keep all the data in one object. Keep reading this article to get some insights on the usage of Bokeh Features of Python Bokeh Decem14 min read 3976 If you’re a data scientist or analyst, visualizing data can be the most interesting part of your job. If you use a pandas DataFrame, the resulting ColumnDataSource in Bokeh will have columns that correspond to the columns of the DataFrame.The naming of the columns follows these rules: If the DataFrame has a named index column, the ColumnDataSource will also have a column with this name. For example, if you select the zoom button you can draw a box around any area of the chart you want to focus on. By default you get tools on the right of a chart that lets you do a bunch of things out of the box. It is widely used for stock market analysis in the industry because it is very easy to integrate this library with different web frameworks as well such as JS, Django, and HTML. A really nice feature of Bokeh is how easy it is to add interactivity to our charts. We can create scatter plots, line charts, etc using this library. In this article, we will be looking into data visualization using Python Bokeh.īokeh allows users to take in data in any format such as CSV, JSON, hard-coded data, or databases.
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