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demo_analyze.py
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demo_analyze.py
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"""Test scripts to demonstrate analyze module.
Everything in here will be in the notebook. This
is just in case there is a problem running the notebook
"""
import pandas as pd
from faers_lib.analyze import load_one_quarter, display_frame
from faers_lib.analyze import drug_used_together, gen_drug_demo_react_agg
from faers_lib.common import data_dir_template
def analyze_pairs(pairs):
from faers_lib.analyze import check_drug_pairs, companion_drug
from faers_lib.analyze import display_frame
pairs.set_index(['drugname_x', 'drugname_y'], inplace=True)
print(pairs.head(20))
print(pairs.loc['PRILOSEC', 'NEXIUM'])
print(check_drug_pairs(all_frames, 'PRILOSEC', 'NEXIUM'))
print(check_drug_pairs(all_frames, 'PREVACID', 'NEXIUM'))
display_frame(companion_drug(all_frames, 'NEXIUM').head(10))
def get_drugs_with_many_AE(all_frames):
"""Misc test, showing drugs with many AE
Showing AE on different countries
"""
dr = all_frames['drug']
e_by_drug = dr[['drugname', 'primaryid']].groupby(
'drugname').count()
e_by_drug.rename(columns={'primaryid': 'prim_cnt'}, inplace=True)
display_frame(e_by_drug.describe())
esort = e_by_drug.sort_values(by='prim_cnt', ascending=False)
return esort
def analyze_by_disease_area(all_frames, drug_demo_react_agg):
""" test script to find a list of drugs used to
treat many diseases. Then break down AE by disease
for one example
"""
indication = all_frames['indication']
dr = all_frames['drug']
dr_de_indication_fr = pd.merge(
drug_demo_react_agg, indication,
how='inner', left_on=('primaryid', 'drug_seq'),
right_on=('primaryid', 'indi_drug_seq'))
# look for some drug use for treatment of several diseases:
i_drug_name = pd.merge(
dr[['primaryid', 'drug_seq', 'drugname']],
indication[['primaryid', 'indi_drug_seq', 'indi_pt']],
how='inner', left_on=['primaryid', 'drug_seq'],
right_on=['primaryid', 'indi_drug_seq'])
disct_drug_name = i_drug_name[['drugname', 'indi_pt']].groupby(
by=['drugname', 'indi_pt']).count().reset_index()
drug_disease = disct_drug_name.groupby(
by=['drugname']).count().sort_values(
by='indi_pt', ascending=False)
drug_disease.rename(columns={'primaryid': 'cnt'}, inplace=True)
# display_frame(drug_disease)
a_drug = drug_disease.index[0]
analyze_by_disease_area_by_drug(a_drug, dr_de_indication_fr)
def adverse_by_country(all_frames, one_drug):
"""Showing adverse events by country for a particular drug
"""
dr_de_react_fr = gen_drug_demo_react_agg(all_frames)
analyze_one_drug_by_country(dr_de_react_fr, one_drug,
cntry_field='occr_country')
analyze_one_drug_by_country(dr_de_react_fr, one_drug,
cntry_field='reporter_country')
def analyze_one_drug_by_country(
drug_demo_react_agg, one_drug, cntry_field='occr_country',
show_top=10):
"""Summarizing AE data on one drug by country.
We can choose eiither occr_country or reporter_country
"""
print('reporting on %s for %s by country and reaction' % (
cntry_field, one_drug))
data = drug_demo_react_agg.loc[
drug_demo_react_agg.drugname == one_drug]
by_cntry_tbl = data[['primaryid', cntry_field]].groupby(
by=[cntry_field]).count().sort_values(
by='primaryid', ascending=False)
by_cntry_tbl.rename(columns={'primaryid': 'cnt'}, inplace=True)
display_frame(by_cntry_tbl.head(show_top))
print("---------------------")
print("TOP EVENTS BY COUNTRY:")
for c in by_cntry_tbl.index[:5]:
react_by_cntry = data.loc[data[cntry_field] == c][
[cntry_field, 'pt', 'primaryid']].groupby(
[cntry_field, 'pt']).count().sort_values(
by=['primaryid'], ascending=False)
react_by_cntry.rename(columns={'primaryid': 'cnt'}, inplace=True)
display_frame(react_by_cntry.head(show_top))
def analyze_by_disease_area_by_drug(a_drug, dr_de_indication_fr, show_top=10):
""" analyze AE by disease area
"""
data_by_drug = dr_de_indication_fr.loc[
dr_de_indication_fr.drugname == a_drug]
by_disease = data_by_drug[['indi_pt', 'primaryid']].groupby(
by=['indi_pt']).count().sort_values(by=['primaryid'], ascending=False)
# print(by_disease.head())
print("---------------------")
print("TOP EVENTS BY INDICATION:")
for ipt in by_disease.index[:show_top].values:
data = data_by_drug.loc[data_by_drug.indi_pt == ipt]
ipt_report = data[['indi_pt', 'primaryid', 'drugname', 'pt']].groupby(
by=['indi_pt', 'drugname', 'pt']).count().sort_values(
by='primaryid', ascending=False)
ipt_report.rename(columns={'primaryid': 'cnt'}, inplace=True)
display_frame(ipt_report.head(show_top))
def analyze_disease(all_frames):
import pandas as pd
dr = all_frames['drug']
de = all_frames['demographic']
react = all_frames['reaction']
dr_de_fr = pd.merge(
dr[['primaryid', 'drug_seq', 'drugname']],
de[['primaryid', 'reporter_country', 'occr_country']], how='left',
left_on='primaryid', right_on='primaryid')
dr_de_react_fr = pd.merge(
dr_de_fr, react, how='left',
left_on='primaryid', right_on='primaryid')
analyze_by_disease_area(all_frames, dr_de_react_fr)
def test_summarize_data(all_frames):
""" check that all_frames has been loaded correctly
"""
for kk in all_frames:
print(kk)
afile = all_frames[kk]
print(afile.shape)
print(afile.columns)
print(data_dir_template)
if __name__ == '__main__':
all_frames = load_one_quarter(2019, 4)
test_summarize_data(all_frames)
pairs = drug_used_together(all_frames)
analyze_pairs(pairs)
esort = get_drugs_with_many_AE(all_frames)
display_frame(esort.head(10))
# try one drug
drug_idx = 690
display_frame(esort.iloc[690:790])
# try a middle of the pack
one_drug = esort.iloc[drug_idx, :].name
adverse_by_country(all_frames, one_drug)
analyze_disease(all_frames)
pass