Get Interactive Plots Directly With Pandas - Jun 14, 2021.
Telling a story with data is a core function for any Data Scientist, and creating data visualizations that are simultaneously illuminating and appealing can be challenging. This tutorial reviews how to create Plotly and Bokeh plots directly through Pandas plotting syntax, which will help you convert static visualizations into interactive counterparts -- and take your analysis to the next level.
Bokeh, Data Visualization, Pandas, Plotly, Python
Top 20 Python Libraries for Data Science in 2018 - Jun 27, 2018.
Our selection actually contains more than 20 libraries, as some of them are alternatives to each other and solve the same problem. Therefore we have grouped them as it's difficult to distinguish one particular leader at the moment.
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Bokeh, Data Science, Keras, Matplotlib, NLTK, numpy, Pandas, Plotly, Python, PyTorch, scikit-learn, SciPy, Seaborn, TensorFlow, XGBoost
- Beautiful Python Visualizations: An Interview with Bryan Van de Ven, Bokeh Core Developer - Aug 1, 2017.
Read this insightful interview with Bokeh's core developer, Bryan Van de Ven, and gain an understanding of what Bokeh is, when and why you should use it, and what makes Bryan a great fit for helming this project.
Bokeh, Continuum Analytics, Data Visualization, Visualization
- Bokeh Cheat Sheet: Data Visualization in Python - Mar 3, 2017.
Bokeh is the Python data visualization library that enables high-performance visual presentation of large datasets in modern web browsers. The package is flexible and offers lots of possibilities to visualize your data in a compelling way, but can be overwhelming.
Bokeh, Cheat Sheet, Data Visualization, DataCamp, Python
- Make Beautiful Interactive Data Visualizations Easily, Dec 15 Webinar - Dec 7, 2015.
Learn how to use Bokeh interactive visualization framework for open data science to create rich, interactive visualizations in the browser, without writing a line of JavaScript, HTML, or CSS.
Anaconda, Bokeh, Continuum Analytics, Data Visualization, scikit-learn
