CODEWITHSUNDEEP
pythonpandasbokeh
PEREZje
PEREZje

Reputation: 2492

Color based on year in bokeh

So I've basically got this snippet of code:

import pandas as pd
from bokeh.plotting import figure, ColumnDataSource
from bokeh.io import show, output_file
import bokeh.models as bmo

data = {
        'ranking': df['ranking'],
        'pct_intl_student' : df['pct_intl_student'],
        'years': year_list,
        'color': colors,
        'university':df['university_name']
}

source = ColumnDataSource(data)
hover = bmo.HoverTool(
            tooltips=[('year', '@years'),
                      ('ranking', '@ranking'),
                      ('% Int. Stu.', '@pct_intl_student'),
                      ('University', '@university')])



p = figure(tools=[hover], title="Scatterplot: International Students")
p.xaxis.axis_label = 'International Ranking'
p.yaxis.axis_label = 'Pct. International Students'

p.scatter('ranking', 'pct_intl_student', source=source)

show(p)

Where color is basically a list that has a color that corresponds to every datapoint in ranking and pct_intl_student. Basically, they're the same length. Would it be possible to make sure that every datapoint that I plot in the scatterplot has the color as specified in the colors list? I figured it would just be some attribute of the figure, but can't find it easiliy in the documentation. All data is retrieved from a dataframe and I created the color mapping as such:

colormap = {2016: 'red',
            2017: 'green',
            2018: 'blue'}
colors = [colormap[x] for x in df['year']]

Upvotes: 0

Views: 1560

Answers (1)

PEREZje
PEREZje

Reputation: 2492

Okay so I just posed the question but I figured it out in the line:

p.scatter('ranking', 'pct_intl_student', source=source)

You should add: color='color'.

So it looks like this:

p.scatter('ranking', 'pct_intl_student', source=source, color='color')

For sake of completion here's entire code snippet with edits:

colormap = {2016: 'red',
            2017: 'green',
            2018: 'blue'}
colors = [colormap[x] for x in df['year']]

data = {
        'ranking': df['ranking'],
        'pct_intl_student' : df['pct_intl_student'],
        'years': year_list,
        'color': colors,
        'university':df['university_name']
}

source = ColumnDataSource(data)
hover = bmo.HoverTool(
            tooltips=[('year', '@years'),
                      ('ranking', '@ranking'),
                      ('% Int. Stu.', '@pct_intl_student'),
                      ('University', '@university')])



p = figure(tools=[hover], title="Scatterplot: International Students")
p.xaxis.axis_label = 'International Ranking'
p.yaxis.axis_label = 'Pct. International Students'

p.scatter('ranking', 'pct_intl_student', source=source, color='color')

show(p)

Upvotes: 2

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