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brfss.py
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brfss.py
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"""This file contains code for use with "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2010 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function, division
import math
import sys
import pandas
import numpy as np
import thinkstats2
import thinkplot
def Summarize(df, column, title):
"""Print summary statistics male, female and all."""
items = [
('all', df[column]),
('male', df[df.sex == 1][column]),
('female', df[df.sex == 2][column]),
]
print(title)
print('key\tn\tmean\tvar\tstd\tcv')
for key, series in items:
mean, var = series.mean(), series.var()
std = math.sqrt(var)
cv = std / mean
t = key, len(series), mean, var, std, cv
print('%s\t%d\t%4.2f\t%4.2f\t%4.2f\t%4.4f' % t)
def CleanBrfssFrame(df):
"""Recodes BRFSS variables.
df: DataFrame
"""
# clean age
df.age.replace([7, 9], float('NaN'), inplace=True)
# clean height
df.htm3.replace([999], float('NaN'), inplace=True)
# clean weight
df.wtkg2.replace([99999], float('NaN'), inplace=True)
df.wtkg2 /= 100.0
# clean weight a year ago
df.wtyrago.replace([7777, 9999], float('NaN'), inplace=True)
df['wtyrago'] = df.wtyrago.apply(lambda x: x/2.2 if x < 9000 else x-9000)
def ReadBrfss(filename='CDBRFS08.ASC.gz', compression='gzip', nrows=None):
"""Reads the BRFSS data.
filename: string
compression: string
nrows: int number of rows to read, or None for all
returns: DataFrame
"""
var_info = [
('age', 101, 102, int),
('sex', 143, 143, int),
('wtyrago', 127, 130, int),
('finalwt', 799, 808, int),
('wtkg2', 1254, 1258, int),
('htm3', 1251, 1253, int),
]
columns = ['name', 'start', 'end', 'type']
variables = pandas.DataFrame(var_info, columns=columns)
variables.end += 1
dct = thinkstats2.FixedWidthVariables(variables, index_base=1)
df = dct.ReadFixedWidth(filename, compression=compression, nrows=nrows)
CleanBrfssFrame(df)
return df
def MakeNormalModel(weights):
"""Plots a CDF with a Normal model.
weights: sequence
"""
cdf = thinkstats2.Cdf(weights, label='weights')
mean, var = thinkstats2.TrimmedMeanVar(weights)
std = math.sqrt(var)
print('n, mean, std', len(weights), mean, std)
xmin = mean - 4 * std
xmax = mean + 4 * std
xs, ps = thinkstats2.RenderNormalCdf(mean, std, xmin, xmax)
thinkplot.Plot(xs, ps, label='model', linewidth=4, color='0.8')
thinkplot.Cdf(cdf)
def MakeNormalPlot(weights):
"""Generates a normal probability plot of birth weights.
weights: sequence
"""
mean, var = thinkstats2.TrimmedMeanVar(weights, p=0.01)
std = math.sqrt(var)
xs = [-5, 5]
xs, ys = thinkstats2.FitLine(xs, mean, std)
thinkplot.Plot(xs, ys, color='0.8', label='model')
xs, ys = thinkstats2.NormalProbability(weights)
thinkplot.Plot(xs, ys, label='weights')
def MakeFigures(df):
"""Generates CDFs and normal prob plots for weights and log weights."""
weights = df.wtkg2.dropna()
log_weights = np.log10(weights)
# plot weights on linear and log scales
thinkplot.PrePlot(cols=2)
MakeNormalModel(weights)
thinkplot.Config(xlabel='adult weight (kg)', ylabel='CDF')
thinkplot.SubPlot(2)
MakeNormalModel(log_weights)
thinkplot.Config(xlabel='adult weight (log10 kg)')
thinkplot.Save(root='brfss_weight')
# make normal probability plots on linear and log scales
thinkplot.PrePlot(cols=2)
MakeNormalPlot(weights)
thinkplot.Config(xlabel='z', ylabel='weights (kg)')
thinkplot.SubPlot(2)
MakeNormalPlot(log_weights)
thinkplot.Config(xlabel='z', ylabel='weights (log10 kg)')
thinkplot.Save(root='brfss_weight_normal')
def main(script, nrows=1000):
"""Tests the functions in this module.
script: string script name
"""
thinkstats2.RandomSeed(17)
nrows = int(nrows)
df = ReadBrfss(nrows=nrows)
MakeFigures(df)
Summarize(df, 'htm3', 'Height (cm):')
Summarize(df, 'wtkg2', 'Weight (kg):')
Summarize(df, 'wtyrago', 'Weight year ago (kg):')
if nrows == 1000:
assert(df.age.value_counts()[40] == 28)
assert(df.sex.value_counts()[2] == 668)
assert(df.wtkg2.value_counts()[90.91] == 49)
assert(df.wtyrago.value_counts()[160/2.2] == 49)
assert(df.htm3.value_counts()[163] == 103)
assert(df.finalwt.value_counts()[185.870345] == 13)
print('%s: All tests passed.' % script)
if __name__ == '__main__':
main(*sys.argv)