# The clinic names and addresses are mixed
clinic_col = ("PERIOD,PRACTICE,CLINIC NAME ONE,CLINIC NAME TWO,ROAD NAME,"
              "TOWN,COUNTY,UNKNOWN").split(",")
clinic = pd.read_csv("uk_drug_prescription/T201611ADDR+BNFT.CSV",
                     names = clinic_col)

# Remove whitespace from all the columns
rm_ws_col = ("CLINIC NAME ONE,CLINIC NAME TWO,ROAD NAME,TOWN,COUNTY,"
             "UNKNOWN").split(",")
for i in rm_ws_col:
    clinic[i] = list(map(rm_ws, clinic[i]))

# Arrange the clinic names and road names into correct columns
a = clinic.loc[:, "CLINIC NAME TWO"]
b = clinic.loc[:, "ROAD NAME"]
tf = clinic.loc[:, "ROAD NAME"] == ""
for key, value in enumerate(tf):
    if value == True:
        a.iloc[key], b.iloc[key] = b.iloc[key], a.iloc[key] # swapping values
                                                            # shallow.copy

# Remove all dashes in TOWN and COUNTY column
def remove_dashes(row, column):
    t = row[column]
    return re.sub(r"-", " ", t)

town_dashes = partial(remove_dashes, column = "TOWN")
clinic["TOWN"] = clinic.apply(town_dashes, axis = 1)
county_dashes = partial(remove_dashes, column = "COUNTY")
clinic["COUNTY"] = clinic.apply(county_dashes, axis = 1)