Python: Add a complex conditional column without for loop

Question

I'm trying to add a "conditional" column to my dataframe. I can do it with a for loop but I understand this is not efficient. Can my code be simplified and made more efficient? (I've tried masks but I can't get my head around the syntax as I'm a relative newbie to python).

import pandas as pd

path = (r"C:\Users\chris\Documents\UKHR\PythonSand\PY_Scripts\CleanModules\Racecards")
hist_file = r"\x3RC_trnhist.xlsx"

racecard_path = path + hist_file
df = pd.read_excel(racecard_path)

df["Mask"] = df["HxFPos"].copy
df["Total"] = df["HxFPos"].copy
cnt = -1
for trn in df["HxRun"]:

cnt = cnt + 1
if df.loc[cnt,"HxFPos"] > 6 or df.loc[cnt,"HxTotalBtn"] > 30:
    df.loc[cnt,"Mask"] = 0
elif df.loc[cnt,"HxFPos"] < 2 and df.loc[cnt,"HxRun"] < 4 and df.loc[cnt,"HxTotalBtn"] < 10:
    df.loc[cnt,"Mask"] = 1
elif df.loc[cnt,"HxFPos"] < 4 and df.loc[cnt,"HxRun"] < 9 and df.loc[cnt,"HxTotalBtn"] < 10:
    df.loc[cnt,"Mask"] = 1
elif df.loc[cnt,"HxFPos"] < 5 and df.loc[cnt,"HxRun"] < 20 and df.loc[cnt,"HxTotalBtn"] < 20:
    df.loc[cnt,"Mask"] = 1
else: 
    df.loc[cnt,"Mask"] = 0
df.loc[cnt,"Total"] = df.loc[cnt,"Mask"] * df.loc[cnt,"HxFPos"]

df.to_excel(r'C:\Users\chris\Documents\UKHR\PythonSand\PY_Scripts\CleanModules\Racecards\cond_col.xlsx', index = False)

Sample data/output:

HxRun   HxFPos  HxTotalBtn  Mask    Total
7   5   8   0   0
13  3   2.75    1   3
12  5   3.75    0   0
11  5   5.75    0   0
11  7   9.25    0   0
11  9   14.5    0   0
10  10  26.75   0   0
8   4   19.5    1   4
8   8   67  0   0

Answer 1

Edit - this is where I found an answer: Pandas conditional creation of a series/dataframe column

by @Hossein-Kalbasi

I've just found an answer - please comment if this is not the most efficient.

df.loc[(((df['HxFPos']<3)&(df['HxRun']<5)|(df['HxRun']>4)&(df['HxFPos']<5)&(df['HxRun']<9)|(df['HxRun']>8)&(df['HxFPos']<6)&(df['HxRun']<30))&(df['HxTotalBtn']<30)), 'Mask'] = 1