unemployment.py

# -*- coding: utf-8 -*-
"""
Created on Sun Mar 09 13:34:28 2014

@author: Eric

Reads in uneployment data from http://www.bls.gov/lau/tables.htm

Suffixes at the end of variable names:
A: numpy array
B: boolean
D: dictionary
DF: pandas DataFrame
L: list
S: string
SR: pandas Series
T: tuple
Underscores indicate chaining: for instance, "fooT_T" is a tuple of tuples
"""

import os
import pandas as pd

import config
reload(config)



def main(fileNameS, year):
    pathS = os.path.join(config.rawDataPathS, 'unemployment_statistics')
    conversionD = {'state_fips_code': (lambda x: str(x)),
                   'county_fips_code': (lambda x: str(x)),
                   'year': (lambda x: int(x)),
                   'labor_force': (lambda x: int(str(x).translate(None, ','))),
                   'employed': (lambda x: int(str(x).translate(None, ','))),
                   'unemployed_level': (lambda x: int(str(x).translate(None, ',')))}
    tableDF = pd.read_fwf(os.path.join(pathS, fileNameS),
                          converters=conversionD,                          
                          names=['laus_code', 'state_fips_code',
                                 'county_fips_code', 'county_and_state',
                                 'year', 'labor_force', 'employed',
                                 'unemployed_level', 'unemployed_rate'],
                          skipfooter=3,
                          skiprows=6,
                          widths=[18, 7, 6, 50, 4, 14, 13, 11, 9])
    tableDF.loc[:, 'fips_code'] = (tableDF.state_fips_code + 
                                   tableDF.county_fips_code).astype(int)
    
    # Select relevant columns and set index
    finalDF = tableDF.loc[:, ['fips_code', 'unemployed_rate']]
    finalDF.columns = ['FIPS', 'URate' + str(year)]
    finalDF = finalDF.sort(columns='FIPS')
    finalDF = finalDF.set_index('FIPS')
    
    return finalDF