In [1]:

    

from datetime import datetime
import matplotlib.pyplot as plt
import numpy as np
import warnings
import matplotlib
import pandas as pd
import scipy.stats as stats
import data_dictionary as dd

warnings.filterwarnings('ignore')

#%load_ext autoreload
#%autoreload 2
%matplotlib inline
%config InlineBackend.figure_format = 'retina'


    

In [2]:

    

pwd


    

    
Out[2]:





'C:\\Users\\gary\\Documents\\aaaRepos\\machine_learning\\co-presence'

In [3]:

    

DATA_DIRECTORY = "C:\\Users\\gary\\Documents\\data"


    

In [4]:

    

ls $DATA_DIRECTORY


    

    




 Volume in drive C is OS
 Volume Serial Number is F8CA-7CC7

 Directory of C:\Users\gary\Documents\data

07/03/2017  08:42 AM    <DIR>          .
07/03/2017  08:42 AM    <DIR>          ..
07/02/2017  08:15 AM    <DIR>          atusact_2016
07/01/2017  09:25 AM         3,684,229 atusact_2016.zip
07/02/2017  08:15 AM    <DIR>          atuscps_2016
07/01/2017  09:26 AM         6,860,353 atuscps_2016.zip
07/02/2017  09:28 AM           864,474 atuscpscodebk16.pdf
07/02/2017  09:29 AM           570,216 atusintcodebk16.pdf
07/01/2017  09:35 AM    <DIR>          atusresp_2016
07/01/2017  09:25 AM           841,679 atusresp_2016.zip
07/02/2017  08:15 AM    <DIR>          atusrost_2016
07/01/2017  09:25 AM           144,334 atusrost_2016.zip
07/02/2017  08:17 AM    <DIR>          atusrostec_2016
07/01/2017  09:26 AM            23,198 atusrostec_2016.zip
07/02/2017  08:17 AM    <DIR>          atussum_2016
07/01/2017  09:25 AM           713,076 atussum_2016.zip
07/02/2017  08:17 AM    <DIR>          atuswho_2016
07/01/2017  09:25 AM           841,409 atuswho_2016.zip
07/02/2017  04:16 PM    <DIR>          cps_00001.csv
07/02/2017  04:15 PM         1,215,296 cps_00001.csv.gz
07/02/2017  06:44 PM            98,267 freqvariables.pdf
07/02/2017  09:26 AM            70,656 hinc01_1.xls
07/03/2017  08:41 AM           285,378 lexiconnoex2016.pdf
07/03/2017  08:42 AM           797,090 lexiconwex2016.pdf
07/02/2017  08:00 PM           352,873 tu2016coderules.pdf
07/02/2017  06:44 PM           833,607 tuquestionnaire.pdf
              16 File(s)     18,196,135 bytes
              10 Dir(s)  668,077,223,936 bytes free

In [5]:

    

filename = DATA_DIRECTORY + '/atusact_2016/atusact_2016.dat'
resp = pd.read_csv(filename, usecols=dd.ACTIVITY_FIELDS)
resp.describe()


    

    
Out[5]:







  

    

      

      
TUCASEID
      
TUACTIVITY_N
      
TEWHERE
      
TUACTDUR
      
TUTIER1CODE
      
TUTIER2CODE
      
TUTIER3CODE
    
  
  

    

      
count
      
2.072130e+05
      
207213.000000
      
207213.000000
      
207213.000000
      
207213.000000
      
207213.000000
      
207213.000000
    
    

      
mean
      
2.016063e+13
      
12.085646
      
4.095235
      
81.298866
      
8.797860
      
3.514997
      
3.517762
    
    

      
std
      
3.473787e+08
      
8.580891
      
7.449853
      
125.492770
      
7.677521
      
7.291834
      
10.728536
    
    

      
min
      
2.016010e+13
      
1.000000
      
-1.000000
      
1.000000
      
1.000000
      
1.000000
      
1.000000
    
    

      
25%
      
2.016030e+13
      
5.000000
      
1.000000
      
15.000000
      
2.000000
      
1.000000
      
1.000000
    
    

      
50%
      
2.016061e+13
      
11.000000
      
1.000000
      
30.000000
      
11.000000
      
2.000000
      
1.000000
    
    

      
75%
      
2.016091e+13
      
17.000000
      
8.000000
      
90.000000
      
12.000000
      
3.000000
      
3.000000
    
    

      
max
      
2.016121e+13
      
81.000000
      
89.000000
      
1440.000000
      
50.000000
      
99.000000
      
99.000000
    
  

In [6]:

    

resp.info()


    

    




<class 'pandas.core.frame.DataFrame'>
RangeIndex: 207213 entries, 0 to 207212
Data columns (total 9 columns):
TUCASEID        207213 non-null int64
TUACTIVITY_N    207213 non-null int64
TEWHERE         207213 non-null int64
TUACTDUR        207213 non-null int64
TUSTARTTIM      207213 non-null object
TUSTOPTIME      207213 non-null object
TUTIER1CODE     207213 non-null int64
TUTIER2CODE     207213 non-null int64
TUTIER3CODE     207213 non-null int64
dtypes: int64(7), object(2)
memory usage: 14.2+ MB

In [7]:

    

list(resp)


    

    
Out[7]:





['TUCASEID',
 'TUACTIVITY_N',
 'TEWHERE',
 'TUACTDUR',
 'TUSTARTTIM',
 'TUSTOPTIME',
 'TUTIER1CODE',
 'TUTIER2CODE',
 'TUTIER3CODE']

In [13]:

    

resp.TUACTDUR.max()


    

    
Out[13]:





1440

In [22]:

    

resp222 = resp.loc[(resp['TUTIER1CODE'] == 2) & (resp['TUTIER2CODE'] == 2) & (resp['TUTIER3CODE'] == 2)]


    

In [23]:

    

len(resp222)


    

    
Out[23]:





307

In [24]:

    

resp222.describe()


    

    
Out[24]:







  

    

      

      
TUCASEID
      
TUACTIVITY_N
      
TEWHERE
      
TUACTDUR
      
TUTIER1CODE
      
TUTIER2CODE
      
TUTIER3CODE
    
  
  

    

      
count
      
3.070000e+02
      
307.000000
      
307.000000
      
307.000000
      
307.0
      
307.0
      
307.0
    
    

      
mean
      
2.016061e+13
      
16.332248
      
1.296417
      
15.381107
      
2.0
      
2.0
      
2.0
    
    

      
std
      
3.577121e+08
      
9.588274
      
1.452996
      
20.665592
      
0.0
      
0.0
      
0.0
    
    

      
min
      
2.016010e+13
      
2.000000
      
1.000000
      
1.000000
      
2.0
      
2.0
      
2.0
    
    

      
25%
      
2.016030e+13
      
8.500000
      
1.000000
      
5.000000
      
2.0
      
2.0
      
2.0
    
    

      
50%
      
2.016060e+13
      
16.000000
      
1.000000
      
10.000000
      
2.0
      
2.0
      
2.0
    
    

      
75%
      
2.016091e+13
      
22.000000
      
1.000000
      
15.000000
      
2.0
      
2.0
      
2.0
    
    

      
max
      
2.016121e+13
      
46.000000
      
12.000000
      
225.000000
      
2.0
      
2.0
      
2.0
    
  

In [ ]:

    

for code1, dict1 in dd.ACTIVITY_CODE.items():
    for name1, dict2 in dict1.items():
        print(code1, name1)
        for code2, dict3 in dict2.items():
            for name2, dict4 in dict3.items():
                print( '\t', code2, name2)
                for code3, name3 in dict4.items():
                    print('\t\t', code3, name3)


    

In [ ]:

    

for code1, name1 in dd.ACTIVITY_WHERE.items():
        print(code1, name1)


    

In [ ]:

    

for code1, name1 in dd.ACTIVITY_WHO.items():
        print(code1, name1)


    

In [ ]: