With color mapping, you can encode values from a sequence of data intoīokeh provides two functions to perform color mapping directly in the This section provides an overview of the different transform objects that are If the necessary calculations for color mapping happenĭirectly in the browser, you will also need to send less data. However, you can also perform some data operations directly in the browser.ĭynamically calculating color maps in the browser, for example, can reduce theĪmount of Python code. So far, you have added data to a ColumnDataSource to control Bokeh plots. ( index, new_value ) # replace a single column value # or ( slice, new_values ) # replace several column valuesįor a full example, see examples/howto/patch_app.py. Of values, such as lists or arrays (including NumPy arrays and pandas Series): The data you pass as part of your dict can be any non-string ordered sequences The dictionary’s values are used as the data values for your ColumnDataSource. To create a basic ColumnDataSource object, you need a Python dictionary toīokeh uses the dictionary’s keys as column names. Think of a ColumnDataSource as a collection of sequences of data that each have Together with multiple renderers, those renderers also share information aboutĭata you select with a select tool from Bokeh’s toolbar (see However,Ĭreating a ColumnDataSource yourself gives you access to more advanced options.įor example: Creating your own ColumnDataSource allows you to share dataīetween multiple plots and widgets. When you pass sequences like Python lists or NumPy arrays to a Bokeh renderer,īokeh automatically creates a ColumnDataSource with this data for you. The ColumnDataSource (CDS) is the core of most Bokeh plots. line ( x = x, y = cosine ) Providing data as a ColumnDataSource # Import numpy as np from otting import figure x = random = np.
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