convert TB to GB on specific index - pandas

Question

I wrote such an code. Here i wanted to change all column that constitute TB and GB to single integer. for example if column has 2 TB, this code will delete TB and will keep it as 2. The program works good. What now i want to do is to convert 2TB to 2048 GB so that i can sum all column values. Is there any way to remove TB and make calculation on specific row at the same time?
def removeend():
df= pd.read_csv('ExportList.csv')
if df["Used Space"].str.contains("GB | TB").any() or df["Memory Size"].str.contains("GB | TB").any() or df["Host CPU"].str.contains("Hz|MHz|GHz").any():
df['Used Space'] = df['Used Space'].str.replace(r'GB|TB', '', regex=True)
df["Memory Size"] = df["Memory Size"].str.replace(r'GB|TB', '', regex=True)
df['Host CPU'] = df['Host CPU'].str.replace(r'MHz|Hz|GHz', '', regex=True)
df = df.convert_dtypes()
df["Used Space"] = pd.to_numeric(df["Used Space"])
df["Memory Size"] = pd.to_numeric(df["Memory Size"])
df["Host CPU"] = pd.to_numeric(df["Host CPU"])
else:
print("Error occured!!!")
return df

Answer 1

define\create a custom function:
def converter(x):
try:
return pd.eval(x)
except:
return x
Finally:
cols=["Used Space","Memory Size"]
df[cols]=df[cols].replace({'GB':'','TB':'*1024'},regex=True).applymap(converter)
df["Host CPU"]=df["Host CPU"].replace({'MHz':'','GHz':'*0.001','Hz':'*0.000001'},regex=True).map(converter)