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bokehholoviewshvplotholoviz

How does one show the cdf from histogram data using holoviews?

I'm using holoviews with bokeh backend for interactive visualizations. I have a histogram with edges and frequency data. What is an elegant way of overlaying my histogram with the cumulative distribution (cdf) curve?

I tried using the cumsum option in hv.dim but don't think i'm doing it right. The help simply says,

Help on function cumsum in module holoviews.util.transform:
cumsum(self, **kwargs)

My code looks something like,

df_hist = pd.DataFrame(columns=['edges', 'freq'])
df_hist['edges'] = [-2, -1, 0, 1, 2]
df_hist['freq'] = [1, 3, 5, 3, 1]

hv.Histogram((df_hist.edges, df_hist.freq))

The result is a histogram plot.

Is there something like a...

hv.Histogram((df_hist.edges, df_hist.freq), type='cdf') ... to show the cumulative distribution?

Solution

  • One possible solution is by using histogram(cumulative=True) as follows:

    from holoviews.operation import histogram

histogram(hv.Histogram((df_hist.edges, df_hist.freq)), cumulative=True)

    More info on transforming elements here:
    http://holoviews.org/user_guide/Transforming_Elements.html


    Or a more general solution by turning the original data into a hv.Dataset():

    import holoviews as hv
import seaborn as sns
hv.extension('bokeh')

iris = sns.load_dataset('iris')

hv_data = hv.Dataset(iris['petal_width'])

histogram(hv_data, cumulative=True)


    But I like using library hvplot, which is built on top of Holoviews, even more:

    import hvplot
import hvplot.pandas

iris['petal_width'].hvplot.hist(cumulative=True)

    hvplot cumulative histogram