With krisk, you also can customize color and themes.
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import krisk.plot as kk
import pandas as pd
# Use this when you want to nbconvert the notebook (used by nbviewer)
from krisk import init_notebook; init_notebook()
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df = pd.read_csv('../krisk/tests/data/gapminderDataFiveYear.txt', sep='\t').sample(50)
There are currently six possible themes in krisk, as supported by Echarts. Here I will show you simple chart using each of theme.
For more intutitive about them, please visit http://echarts.baidu.com/download-theme.html
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p = kk.bar(df,'year',c='continent',stacked=True)
p
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p.set_theme('vintage')
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p.set_theme('dark')
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p.set_theme('macarons')
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p.set_theme('infographic')
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p.set_theme('roma')
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p.set_theme('shine')
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Krisk doesn't have existing based colormap. But you can feed CSS Color Codes, hex, or RGB colors manually.
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pallete = ['Navy','#FF0000','rgb(205,92,92)', '#65c3bf','hsl(60, 100%, 87%)']
p.set_color(background='Aqua', palette=pallete)
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You also can using existing palettes provided by visualization libraries you already know. Here I will use libraries like Seaborn, Colorlover, and Bokeh.
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import seaborn as sns
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palette_sns1 = sns.color_palette('muted').as_hex()
p.set_color(palette=palette_sns1)
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Seaborn also nicely integrate colormap from matplotlib
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palette_sns2 = sns.color_palette('YlGnBu').as_hex()
p.set_color(palette=palette_sns2)
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import colorlover as cl
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cl2 = cl.to_hsl( cl.scales['3']['div']['RdYlBu'] )
p.set_color(palette=cl2)
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import bokeh.palettes as bp
import bokeh.colors as bc
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p.set_color(background=bc.aliceblue.to_hex(),palette=bp.PuBuGn6)
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