```
data = '''5.639792 1.36
4.844813 1.89
4.809105 2.33
3.954150 2.69
2.924234 3.42
1.532669 4.50
0.000000 5.63
'''
# use the integer part of second value to categorize the first value and add it to that bin
freq = dict()
for d in data.splitlines():
energy, pos = map(float, d.split())
freq[int(pos)] = freq.setdefault(int(pos),0) + float(energy)
print('Categorized by integer part')
print(sorted(freq.items()))
# using numpy.histogram
import numpy
data = [d.split() for d in data.splitlines() if d != '\n']
weights = [float(a) for a,b in data]
pos = [int(float(b)) for a,b in data]
# numpy organizes by itself the limits for bins
print('5 bins by numpy histogram')
print(numpy.histogram(pos,bins=5, weights=weights))
```

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