<｜begin▁of▁sentence｜>### Instruction:
As a costume designer, imagine you are preparing costumes for an upcoming theater production. In order to ensure you have the right amount of materials for each costume, you need to categorize the measurements of the actors into bins representing various size intervals. 

To achieve this, you could create a generator to return the bins of a bare-bones histogram in increasing order. Each bin would include the left bound, right bound, and the number of actors falling within that particular size range. This would help you accurately plan and allocate resources for creating the costumes.
### Response:
from random import gauss
from collections import Counter

# Simulating data generation using Gaussian distribution
sample_data = [gauss(0, 1) for _ in range(1000)]

# Create a histogram using the Counter from the collections library
histogram = Counter(int(x) for x in sample_data)

# Generator function to return histogram bins
def get_bins(histogram):
    sorted_bins = sorted(histogram.items())
    for left_bound, count in sorted_bins:
        yield (left_bound, left_bound+1, count)

# Get bins information
for bin_info in get_bins(histogram):
    print(bin_info)
<|EOT|>
