plot thousand markers on python bokeh maps

Source = ColumnDataSource(dict(x=x, y=y, z=z)) Should I just add a 'color' column to the data frame? I feel there is an easier/more convenient way to do that.ĮDIT: Here is a minimal working example using the answer by bigreddot: from bokeh.io import curdocįrom bokeh.models import Button, ColumnDataSource, ColorBar, HoverTool See picture below (given that quantity I would expect green, but it is blue as it still seen as < 4000 as in the map of the first plot before the callback). The color map is updated with new values, but it seems that the colors of the marker still follow the original pattern. Mapper = linear_cmap(field_name='quantity', palette=palettes.Spectral6 ,low=min_q, high=max_q)Ĭolor_bar.color_mapper=mapper # I think I should not create a new mapper but doing so I get closer # get new df (according to new date/select) Then I have a callback function update() triggered upon changing value in some widget (a select or a time picker). Below is the plot I get upon starting the bokeh server. P.scatter(x='date_column', y='value', marker='triangle', fill_color=mapper, line_color=None, source=source)Ĭolor_bar = ColorBar(color_mapper=mapper, width=8, location=(0,0)) Source = ColumnDataSource(data=get_data(df)) Mapper = linear_cmap(field_name='quantity', palette=palettes.Spectral6, low=min_q, high=max_q) I have a scatter plot in which I would like to color each marker according to a certain third property (say a quantity, while the x-axis is a date and the y-axis is a given value at that point in time).Īssuming my data is in a data frame, I managed to do this using a linear color map as follows: min_q = df.quantity.min()

Plot thousand markers on python bokeh maps