File size: 1,408 Bytes
fee6d7b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | import pandas as pd
from pathlib import Path
# Directory of this file: .../thicc/data
BASE_DIR = Path(__file__).resolve().parent
HOSPITALS = {
"Mayo Clinic": BASE_DIR / "hospitals" / "mayo_clinic_data.csv",
"Cleveland Clinic": BASE_DIR / "hospitals" / "cleveland_clinic_data.csv",
"Johns Hopkins Hospital": BASE_DIR / "hospitals" / "johns_hopkins_hospital_data.csv",
"Massachusetts General Hospital": BASE_DIR / "hospitals" / "massachusetts_general_hospital_data.csv",
"UCLA Medical Center": BASE_DIR / "hospitals" / "ucla_medical_center_data.csv",
"Cedars-Sinai Medical Center": BASE_DIR / "hospitals" / "cedars_sinai_medical_center_data.csv",
"NewYork-Presbyterian Hospital": BASE_DIR / "hospitals" / "newyork_presbyterian_hospital_data.csv",
"Northwestern Memorial Hospital": BASE_DIR / "hospitals" / "northwestern_memorial_hospital_data.csv",
"UCSF Medical Center": BASE_DIR / "hospitals" / "ucsf_medical_center_data.csv",
"Houston Methodist Hospital": BASE_DIR / "hospitals" / "houston_methodist_hospital_data.csv",
}
def load_services_data(path) -> pd.DataFrame:
"""Load price data from a CSV file."""
df = pd.read_csv(path)
return df[[
"intent",
"description",
"gross_charge",
"negotiated_rate",
]]
def list_services(services_data: pd.DataFrame) -> list[str]:
return services_data["description"].tolist()
|