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Hands-on Data Visualization with Bokeh | 3. Plotting with different Data Structures
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This is the “Code in Action” video for chapter 3 of Hands-on Data Visualization with Bokeh by Kevin Jolly, published by Packt. It includes the following topics:
00:00 Creating line plots using NumPy arrays
00:09 Creating scatter plots using NumPy arrays
00:25 Creating a time series plot using a pandas DataFrame
00:40 Creating scatter plots using a pandas DataFrame
00:58 Creating a time series plot using the ColumnDataSource
01:17 Creating a scatter plot using the ColumnDataSource
Hands-on Data Visualization is available from:
Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free.
Connect with Packt:
Video created by Kevin Jolly
00:00 Creating line plots using NumPy arrays
00:09 Creating scatter plots using NumPy arrays
00:25 Creating a time series plot using a pandas DataFrame
00:40 Creating scatter plots using a pandas DataFrame
00:58 Creating a time series plot using the ColumnDataSource
01:17 Creating a scatter plot using the ColumnDataSource
Hands-on Data Visualization is available from:
Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free.
Connect with Packt:
Video created by Kevin Jolly