# How to use the census.math.log function in census

## To help you get started, we’ve selected a few census examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately. datamade / census / census / math.py View on Github """
Interpolates a percentile value assuming that the data is drawn
from a Pareto distribution. Good for income and other highly
skewed distributions.
"""
i, bin, counts = _bin_select(data_list, percentile)

lower_bound, upper_bound = bin

ratio_proportion = (percentile * sum(counts))/sum(counts[i:])
ratio_overall = sum(counts[(i + 1):])/sum(counts[i:])
ratio_bounds = upper_bound/lower_bound

return lower_bound * math.exp((math.log(ratio_proportion) /
math.log(ratio_overall)) *
math.log(ratio_bounds)) datamade / census / census / math.py View on Github def pareto_percentile(data_list, percentile=0.5):
"""
Interpolates a percentile value assuming that the data is drawn
from a Pareto distribution. Good for income and other highly
skewed distributions.
"""
i, bin, counts = _bin_select(data_list, percentile)

lower_bound, upper_bound = bin

ratio_proportion = (percentile * sum(counts))/sum(counts[i:])
ratio_overall = sum(counts[(i + 1):])/sum(counts[i:])
ratio_bounds = upper_bound/lower_bound

return lower_bound * math.exp((math.log(ratio_proportion) /
math.log(ratio_overall)) *
math.log(ratio_bounds))

## census

A wrapper for the US Census Bureau's API GitHub BSD-3-Clause Latest version published 5 months ago

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