I have
reset()
import scipy.stats
n = 2000
p = 0.2
binom_dist = scipy.stats.binom(n,p)
bar_chart([binom_dist.pmf(x) for x in range(n)], axes_labels=['$k$','$B(k,{},{})$'.format(n,float(p))])How could I create something nicer, like
You can add a list_plot:
reset()
import scipy.stats
n = 2000
p = 0.2
binom_dist = scipy.stats.binom(n,p)
data = [binom_dist.pmf(x) for x in range(n)]
Layout = {'frame': True, 'axes_labels': ['$k$', f'$B(k,{n},{float(p)})$']}
BarChart = bar_chart([binom_dist.pmf(x) for x in range(n)], **Layout)
ListPlot = list_plot(data, plotjoined=True)
show(BarChart + ListPlot)You will note that I reuse code from your other question.
oups, your answer appeared while I was writing mine
Very good. And yes, I note that as well. ;)
I suggest to use list_plot instead of bar_chart
sage: import scipy.stats
sage: n = 2000
sage: p = 0.2
sage: binom_dist = scipy.stats.binom(n, p)
sage: L = [binom_dist.pmf(k) for k in range(n)]
sage: kwds = dict(axes_labels=['$k$',''])
sage: kwds.update(legend_label='$B(k,{},{})$'.format(n, float(p)))
sage: kwds.update(title='Binomial distribution')
sage: m = n*p
sage: v = n*p*(1-p)
sage: list_plot(L, plotjoined=True, xmin=m-v, xmax=m+v, **kwds)
To add the bars to the plot, you may do:
sage: list_plot(L, plotjoined=True, xmin=m-v, xmax=m+v, **kwds) + bar_chart(L)Very good, too. :()
Asked: 4 years ago
Seen: 510 times
Last updated: Apr 06 '20
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