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Erschienen in:
2018 | OriginalPaper | Buchkapitel
7. Data Visualization
verfasst von : Dr. Ossama Embarak
Erschienen in: Data Analysis and Visualization Using Python
Verlag: Apress
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Abstract
This chapter demonstrates various plottings for data visualization. Various Python libraries can be used for data visualization, such as Pandas, Seaborn, Bokeh, Pygal, and Ploty. Python Pandas is the simplest method for basic plotting. Python Seaborn is great for creating visually appealing statistical charts that include color. Python Bokeh works great for more complicated visualizations, especially for web-based interactive presentations. Python Pygal works well for generating vector and interactive files. However, it does not have the flexibility that other methods do. Python Plotly is the most useful and easiest option for creating highly interactive web-based visualizations.