def _data_fetch():
# df = acs(['B24092_004E', 'B24092_013E'])
# todo: test this against what I'm seeing in kauffman_indicators
# df = qwi(indicator_lst=['Emp', 'HirA'], obs_level='us', annualize=None, strata=['sex', 'industry'])
df = qwi(obs_level='msa', state_list=['CO', 'UT'], strata=['firmsize'])
df = qwi(obs_level='state')
df = qwi(obs_level='msa')
df = qwi(obs_level='county')
# df = bed('firm size', 1)
# df = bed('firm size', 2)
# df = bed('firm size', 3)
# df = bed('firm size', 4)
# df = bed('1bf', obs_level=['AL', 'US', 'MO'])
# df = bfs(['BA_BA', 'BF_SBF8Q'], obs_level=['AZ'])
# df = bfs(['BA_BA', 'BF_SBF8Q'], obs_level='state')
# df = bfs(['BA_BA', 'BF_SBF8Q', 'BF_DUR8Q'], obs_level=['AZ'], annualize=True)
# df = bfs(['BA_BA', 'BF_SBF8Q', 'BF_DUR8Q'], obs_level=['US', 'AK'], march_shift=True)
# df = bds(['FIRM', 'ESTAB'], obs_level='all')
# df = pep(obs_level='us')
# df = pep(obs_level='state')
df = pep(obs_level='msa')
# df = pep(obs_level='county')
print(df.head())
print(df.tail())
print(df.info())
def mpj_data_fetch():
## setting private=False results in zero rows returned
# qwi(['EarnBeg'], obs_level='us', private=True, annualize=True) \
# [['time', 'EarnBeg']]. \
# rename(columns={'EarnBeg': 'EarnBeg_us'}). \
# apply(pd.to_numeric). \
# to_csv(c.filenamer('../tests/data/earnbeg_us.csv'), index=False)
# for region in ['us', 'state', 'msa', 'county']:
for region in ['us', 'state']:
qwi(['Emp', 'EmpEnd', 'EarnBeg', 'EmpS', 'EmpTotal', 'FrmJbC'], obs_level=region, private=True, strata=['firmage', 'industry'], annualize=True).\
to_csv(c.filenamer(f'../tests/data/qwi_{region}.csv'), index=False)
pep(region).\
rename(columns={'POP': 'population'}). \
to_csv(c.filenamer(f'../tests/data/pep_{region}.csv'), index=False)
def qwi_test():
# strata, msa
df = qwi(['Emp', 'EmpEnd', 'EarnBeg', 'EmpS', 'EmpTotal', 'FrmJbC'],
obs_level='msa',
state_list=['06'],
private=True,
strata=['firmage'],
annualize=True)
print(df)
def county_msa_cw():
df = qwi(['Emp'], obs_level='county', state_list=['MO'], annualize=False).\
pipe(county_msa_cross_walk, 'fips')
print(df.head(10))
def _etl_tests():
df = qwi(['Emp'], obs_level='county', annualize=False).\
pipe(county_msa_cross_walk, 'fips')
print(df.head(10))