In [1]:

    

from scatter import *
%matplotlib inline


    

In [2]:

    

from __future__ import print_function

import sys
import numpy as np
import math

import brfss
import thinkplot
import thinkstats2


    

In [3]:

    

df = brfss.ReadBrfss(nrows=None)


    

In [46]:

    

sample = thinkstats2.SampleRows(df, 5000)
heights, weights = sample.htm3, sample.wtkg2


    

In [4]:

    

thinkplot.Scatter(heights, weights)
thinkplot.Show(xlabel='Heights (cm)', ylabel='Weights (kg)', axis=[140, 210, 20, 200])


    

    




/Users/nathankiner/anaconda/lib/python2.7/site-packages/matplotlib/axes/_axes.py:475: UserWarning: No labelled objects found. Use label='...' kwarg on individual plots.
  warnings.warn("No labelled objects found. "
/Users/nathankiner/anaconda/lib/python2.7/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):






    













    






<matplotlib.figure.Figure at 0x108a18dd0>

In [9]:

    

heights = thinkstats2.Jitter(heights, 1.3)
weights = thinkstats2.Jitter(weights, 0.5)


    

In [15]:

    

thinkplot.Scatter(heights, weights, alpha=0.2)
thinkplot.Show(xlabel='Heights (cm)', ylabel='Weights (kg)', axis=[140, 210, 20, 200])


    

    













    






<matplotlib.figure.Figure at 0x10c9bb210>

In [16]:

    

thinkplot.Scatter(heights, weights, alpha=0.1)
thinkplot.Show(xlabel='Heights (cm)', ylabel='Weights (kg)', axis=[140, 210, 20, 200])


    

    













    






<matplotlib.figure.Figure at 0x10cb09950>

In [19]:

    

thinkplot.HexBin(heights, weights)
thinkplot.Show(xlabel='Heights (cm)', ylabel='Weights (kg)', axis=[140, 210, 20, 200])


    

    













    






<matplotlib.figure.Figure at 0x10ce32d10>

In [38]:

    

df = df.dropna(subset=['htm3', 'wtkg2'])
df.describe()


    

    
Out[38]:






  

    

      

      
age
      
sex
      
wtyrago
      
finalwt
      
wtkg2
      
htm3
    
  
  

    

      
count
      
393518.000000
      
395832.000000
      
388137.000000
      
395832.000000
      
395832.000000
      
395832.000000
    
    

      
mean
      
54.891207
      
1.612730
      
79.766921
      
562.527274
      
79.044413
      
168.956188
    
    

      
std
      
16.742237
      
0.487127
      
20.574880
      
1076.206594
      
19.547890
      
10.390752
    
    

      
min
      
18.000000
      
1.000000
      
22.727273
      
1.695143
      
20.000000
      
61.000000
    
    

      
25%
      
43.000000
      
1.000000
      
64.545455
      
97.241254
      
64.550000
      
163.000000
    
    

      
50%
      
55.000000
      
2.000000
      
77.272727
      
234.914579
      
77.270000
      
168.000000
    
    

      
75%
      
67.000000
      
2.000000
      
90.909091
      
593.585278
      
90.910000
      
178.000000
    
    

      
max
      
99.000000
      
2.000000
      
342.272727
      
60995.111700
      
300.000000
      
236.000000
    
  

In [53]:

    

bins = np.arange(135, 210, 5)
indices = np.digitize(df.htm3, bins)
groups = df.groupby(indices)


    

In [54]:

    

for i, group in groups:
    print(i, len(group))


    

    




0 305
1 228
2 477
3 2162
4 18759
5 45761
6 70610
7 72138
8 61725
9 49938
10 43555
11 20077
12 7784
13 1777
14 405
15 131

In [55]:

    

heights = [group.htm3.mean() for i, group in groups]
cdfs = [thinkstats2.Cdf(group.wtkg2) for i, group in groups]


    

In [49]:

    

for percent in [75, 50, 25]:
    weights = [cdf.Percentile(percent) for cdf in cdfs]
    label = '%dth percent' % percent
    thinkplot.Plot(heights, weights, label=label)


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-49-d50573c058b2> in <module>()
      2     weights = [cdf.Percentile(percent) for cdf in cdfs]
      3     label = '%dth percent' % percent
----> 4     thinkplot.Plot(heights, weights, label=label)

/Users/nathankiner/Documents/Data Science/ThinkStats2/code/thinkplot.pyc in Plot(obj, ys, style, **options)
    221         pyplot.plot(xs, style, **options)
    222     else:
--> 223         pyplot.plot(xs, ys, style, **options)
    224 
    225 

/Users/nathankiner/anaconda/lib/python2.7/site-packages/matplotlib/pyplot.pyc in plot(*args, **kwargs)
   3097         ax.hold(hold)
   3098     try:
-> 3099         ret = ax.plot(*args, **kwargs)
   3100         draw_if_interactive()
   3101     finally:

/Users/nathankiner/anaconda/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in plot(self, *args, **kwargs)
   1371         lines = []
   1372 
-> 1373         for line in self._get_lines(*args, **kwargs):
   1374             self.add_line(line)
   1375             lines.append(line)

/Users/nathankiner/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.pyc in _grab_next_args(self, *args, **kwargs)
    302                 return
    303             if len(remaining) <= 3:
--> 304                 for seg in self._plot_args(remaining, kwargs):
    305                     yield seg
    306                 return

/Users/nathankiner/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.pyc in _plot_args(self, tup, kwargs)
    280             x = np.arange(y.shape[0], dtype=float)
    281 
--> 282         x, y = self._xy_from_xy(x, y)
    283 
    284         if self.command == 'plot':

/Users/nathankiner/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.pyc in _xy_from_xy(self, x, y)
    221         y = np.atleast_1d(y)
    222         if x.shape[0] != y.shape[0]:
--> 223             raise ValueError("x and y must have same first dimension")
    224         if x.ndim > 2 or y.ndim > 2:
    225             raise ValueError("x and y can be no greater than 2-D")

ValueError: x and y must have same first dimension





    

In [47]:

    

thinkstats2.Cov(heights, weights)


    

    
Out[47]:





105.82155294999997

In [48]:

    

thinkstats2.Corr(heights, weights)


    

    
Out[48]:





0.51763333445295123

In [ ]: