Create new column with conditional operations on existing columns

Question

I'm extracting data within certain ranges and coming up with new columns that represent 1 when the values in a column fall within that range and 0 when they don't.

I tried using boolean conditions with no luck.

data["normal"]=np.where((data["sysBP"]<80) & (data["diaBP"]<120),1,0)

data["prehyper"]=np.where(((data["sysBP"]<90) & (data["sysBP"]>=80)) & 
                          ((data["diaBP"]<140) & (data["diaBP"]>=120)),1,0)

I expect the new column show 1 for that data that lies within the range and 0 for those that don't. I got a column with all 0s with my above code.

Answer 1

You can use the astype(int) to convert True to 1 and False to 0:

data["normal"] = ((data["sysBP"]<80) & (data["diaBP"]<120)).astype(int)

data["prehyper"] = ((data["sysBP"]<90) & (data["sysBP"]>=80) & (data["diaBP"]<140) & (data["diaBP"]>=120)).astype(int)