Plotting a histogram from pre-counted data in Matplotlib

You can use the weights keyword argument to np.histgram (which plt.hist calls underneath)

val, weight = zip(*[(k, v) for k,v in counted_data.items()])
plt.hist(val, weights=weight)

Assuming you only have integers as the keys, you can also use bar directly:

min_bin = np.min(counted_data.keys())
max_bin = np.max(counted_data.keys())

bins = np.arange(min_bin, max_bin + 1)
vals = np.zeros(max_bin - min_bin + 1)

for k,v in counted_data.items():
    vals[k - min_bin] = v

plt.bar(bins, vals, ...)

where … is what ever arguments you want to pass to bar (doc)

If you want to re-bin your data see Histogram with separate list denoting frequency