CODEWITHSUNDEEP
pythonmatplotlibhistogram
Angel
Angel

Reputation: 145

How to plot histogram of counts per range that each bin is labeled with a interval range?

I have a python directory, the keys of which stores the percentage range: 0_5, 5_10, 10_15,....80_85, 85_90, 90_95, 95_100. The value for each key is the count number in the whole data. I want to use matplotlib to plot a histogram to see its distribution and there will be 20 bins and each bin should be labeled with its percentage range and there will be a little spacing between each bin so that they are seperated.

I've tried this code and it gives me histogram that has 20 bins. But it's not what I need.

commutes = pd.Series(counts)
commutes.plot.hist(grid = False, bins = 20, rwidth = 0.8, color = 'tomato', edgecolor='gray', label = 'Type 1')

Also, I tried this and it shows the error: ValueError: weights should have the same shape as x

pylab.hist(ratio.keys(), weights = ratio.values(), bins=range(20))

This is how I created the directory. The variable counts stores a list of 700 percentage values. 

for i in range(0,100,5):
    start = i
    end = i+5
    key = str(start)+"_"+str(end)
    number = 0
    for count in counts:
        if((count >= start) and (count < end)):
            number = number + 1
    ratio[key] = number

Upvotes: 2

Views: 959

Answers (1)

Martin Valgur
Martin Valgur

Reputation: 6322

ratio.keys() and ratio.values() are of type dict_keys and dict_values. I'm guessing that matplotlib is trying to apply np.array() or np.asarray() to them, which does not work as intended, i.e. it gets converted to array(dict_keys([...]), dtype=object) rather than an array of numbers.

A simple fix is to convert the dictionary keys and values to lists first.

pylab.hist(list(ratio.keys()), weights=list(ratio.values()), bins=range(len(ratio)))

Upvotes: 0

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