In this chapter, we will discuss Bokeh ColumnDataSource. Most of the plotting methods in API are able to receive data source parameters through the columnDatasource object. It makes sharing data between plots and ‘DataTables’.
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Example’s Bokeh ColumnDataSource
Below is the example
from bokeh.models import ColumnDataSource
data = {'x':[1, 4, 3, 2, 5],
'y':[6, 5, 2, 4, 7]}
cds = ColumnDataSource(data = data)
The following code generates a scatter plot using ColumnDataSource.
from bokeh.plotting import figure, output_file, show
from bokeh.models import ColumnDataSource
data = {'x':[1, 4, 3, 2, 5],
'y':[6, 5, 2, 4, 7]}
cds = ColumnDataSource(data = data)
fig = figure()
fig.scatter(x = 'x', y = 'y',source = cds, marker = "circle", size = 20, fill_color = "grey")
show(fig)
Output
Instead of assigning a Python dictionary to ColumnDataSource, we can use a Pandas DataFrame for it.
Let us use ‘test.csv’ (used earlier in this section) to obtain a DataFrame and use it for getting ColumnDataSource and rendering line plot.
from bokeh.plotting import figure, output_file, show
import pandas as pd
from bokeh.models import ColumnDataSource
df = pd.read_csv('test.csv')
cds = ColumnDataSource(df)
fig = figure(y_axis_type = 'log')
fig.line(x = 'x', y = 'pow',source = cds, line_color = "grey")
show(fig)
Output
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