Convert numpy bins to a string format ideal for creating frequency charts in the numpy-pandas ecosystem. Ex. [0, 2, 4, 6, 8, 10] -> ['0-2', '2-4', '4-6', '6-8', '8-10']
Project description
compress-bins
This package provides the compress_bins() function, a quality-of-life function for creating frequency charts in the numpy-pandas ecosystem.
Usage:
import compressbins.compressbins as cb
compressed_bins = cb.compress_bins([0,2,4,6])
print(compressed_bins) # ['0-2','2-4','4-6']
We can then use these compressed bins in creating frequency charts:
import pandas as pd
import numpy as np
counts, bins = np.histogram(df, bins=np.arange(10.00, 20.00, 1.00))
cbins = compress_bins(bins)
freqChart = pd.DataFrame({"Cost":cbins, "Count":counts})
print(freqChart)
Cost Count
0 10.0-11.0 1
1 11.0-12.0 8
2 12.0-13.0 16
3 13.0-14.0 9
4 14.0-15.0 6
5 15.0-16.0 4
6 16.0-17.0 3
7 17.0-18.0 2
8 18.0-19.0 1
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